system

Abstract

Provide a system. [Solution] means for receiving a sentence generation request from a user; means for maintaining a database containing elements for sentence generation; means for randomly selecting elements from said database; means for combining the selected elements to generate a sentence; means for presenting the generated sentence to a user; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In traditional creative activities, artists and creators often struggle with inspiration. This has led to a demand for tools that can provide new ideas and perspectives. However, existing tools are limited to simple document generation and melody generation, and are therefore limited in their ability to effectively support creative activities. Therefore, a system that can broaden the scope of creativity and efficiently provide new inspiration is needed. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes: means for receiving a sentence generation request from a user, maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for combining the selected elements to generate a sentence, and means for presenting the generated sentence to the user. This system allows users to easily come up with new ideas and effectively supports creative activities.

[0006] "User" refers to an individual or group of artists, creators, etc. who use the system.

[0007] "Means for receiving requests" refers to the interface and communication technology used to sense instructions from a user and communicate that information to other parts of the system.

[0008] A "database" refers to a structured information management system for temporary or long-term storage of elements necessary for sentence generation (subjects, verbs, actions, etc.).

[0009] "Means for randomly selecting elements" refers to algorithms or programs that statistically randomly select any subject, verb, action, etc. from a database.

[0010] "Means for generating sentences" refers to logic or programs that combine selected elements to construct grammatical sentences.

[0011] The "means for presenting the generated text" refers to a display device or software for displaying the constructed text in a form that can be visually recognized by the user.

[0012] "Terminal" refers to an electronic device such as a computer, smartphone, or tablet that allows a user to access and operate the system. [Brief explanation of the drawings]

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

[0014] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

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

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

[0019] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0021] [First embodiment]

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

[0023] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0026] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0030] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0033] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0034] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain inspiration.

[0035] System configuration

[0036] The system consists of the following main components:

[0037] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[0038] 2. Server: A central computer that holds the database for text generation and processes requests.

[0039] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0040] System Operation

[0041] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[0042] 1. User Action:

[0043] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0044] 2. Submit your request:

[0045] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[0046] 3. Receiving and Processing Requests:

[0047] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[0048] 4. Random selection of elements:

[0049] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0050] 5. Sentence generation:

[0051] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[0052] 6. Sending the generated text:

[0053] The server sends the generated text to the user's terminal, formatting the data so that it can be immediately understood by the user.

[0054] 7. Display of text:

[0055] The user terminal displays the received text on the user interface, allowing the user to engage in creative activities based on the displayed text.

[0056] Specific examples

[0057] As a concrete example, the following spear-like action is envisioned:

[0058] 1. User Action:

[0059] A user is looking for new story ideas and clicks the "Generate New Text" button.

[0060] 2. Submit your request:

[0061] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[0062] 3. Receiving and Processing Requests:

[0063] The server receives the HTTP request and initiates access to the database.

[0064] 4. Random selection of elements:

[0065] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0066] 5. Sentence generation:

[0067] The server generates the sentence "The cat walks."

[0068] 6. Sending the generated text:

[0069] The server sends the generated text to the user's smartphone.

[0070] 7. Display of text:

[0071] The user's device displays the sentence "A cat walks" on the screen, and the user begins writing a new story based on that sentence.

[0072] In this way, the system helps the user find inspiration and supports creative activities.

[0073] The processing flow will be explained below.

[0074] Step 1:

[0075] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[0076] Step 2:

[0077] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[0078] Step 3:

[0079] The server receives a request from the terminal, which includes instructions for generating a sentence.

[0080] Step 4:

[0081] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[0082] Step 5:

[0083] The server accesses the database and reads the list of elements (subject, verb, action) for sentence generation.

[0084] Step 6:

[0085] The server randomly selects a subject from the subject list using a random number generation algorithm that ensures statistical randomness.

[0086] Step 7:

[0087] The server randomly selects a verb from the verb list, again using an algorithm that ensures statistical randomness.

[0088] Step 8:

[0089] The server randomly selects an action from the list of actions, again based on a random number generation algorithm.

[0090] Step 9:

[0091] The server combines the selected subject, verb, and action to generate a sentence. For example, the sentence "The cat walks."

[0092] Step 10:

[0093] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0094] Step 11:

[0095] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0096] Step 12:

[0097] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0098] Step 13:

[0099] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[0100] Through the above steps, this system provides users with new inspiration and supports their creative activities.

[0101] Example 1

[0102] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0103] Conventional text generation systems have not provided users with an efficient way to gain new inspiration. Specifically, they often lack an interface that allows users to easily generate text, or a function to instantly receive and display the generated text. A new system is needed to resolve these issues and support users' creative activities.

[0104] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0105] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for transmitting the generated sentences to the user's terminal, and means for displaying the generated sentences on the user's terminal, thereby enabling the user to quickly and easily generate inspirational sentences and start creative activities based on them.

[0106] A "user" is an individual or group who wishes to generate text and operates the system.

[0107] The "means for receiving a request" is a mechanism for transmitting a request from a user to a server and starting processing.

[0108] The "means for maintaining the database" is a system component that has the function of storing and managing elements necessary for sentence generation (subject, verb, action, etc.).

[0109] The "means for randomly selecting elements" is a mechanism for randomly extracting elements from the database.

[0110] The "means for generating a sentence" is a program that has the function of combining selected elements to construct a single sentence.

[0111] "Means for transmitting the generated text to the user's terminal" refers to a mechanism by which the server transmits the generated text to the user's device via a network.

[0112] The "means for displaying the generated text on the user's terminal" is a component that has the function of visually displaying the received text on the user interface.

[0113] A "subject" is a noun or pronoun that is the subject of an action in a sentence.

[0114] A "verb" is a word that expresses the action or state that the subject of a sentence performs.

[0115] An "action" is a specific action in a sentence in which a verb is performed by the subject.

[0116] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain new inspiration.

[0117] System configuration

[0118] The system consists of the following main components:

[0119] 1. User terminal: A device used by a user to perform operations, including computers, smartphones, tablets, etc.

[0120] 2. Server: This is the central system that holds the database for text generation and processes requests.

[0121] 3. Database: This is where the elements necessary for sentence generation (subject, verb, action) are stored.

[0122] System Operation

[0123] In this system, when a user wishes to create a new sentence, the following process is carried out:

[0124] User operations

[0125] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0126] Submitting a Request

[0127] In response to a user's operation, the device sends an HTTP POST request to the server, which includes information such as the user ID and the request type.

[0128] Receiving and processing requests

[0129] The server receives the request, analyzes it, and prepares the necessary data based on the information contained in the request.

[0130] Random selection of elements

[0131] The server accesses the database and uses a random number generation algorithm to randomly select elements from the subject list, verb list, and action list.

[0132] Sentence generation

[0133] The server combines the selected elements to generate a sentence. For example, if the elements "cat," "ga," and "aruku" are selected, the sentence "The cat walks" is generated.

[0134] Sending generated text

[0135] The server sends the generated text to the user's device, often in JSON format.

[0136] Displaying text

[0137] The device displays the received text on the user interface, allowing users to create new stories and engage in creative activities based on the displayed text.

[0138] Specific examples

[0139] As a specific example, the following exchange is envisioned.

[0140] 1. User action: A user is looking for a new story idea and clicks the "Generate new text" button on their smartphone UI.

[0141] 2. Sending a request: The device catches the button click event and sends an HTTP POST request to the server.

[0142] 3. Receiving and processing the request: The server receives the request and parses it.

[0143] 4. Random selection of elements: The server obtains the subject "dog", the verb "ga", and the action "bark" randomly selected from the database.

[0144] 5. Sentence generation: The server generates the sentence "The dog is barking."

[0145] 6. Sending the generated text: The server sends the generated text to the terminal in JSON format.

[0146] 7. Displaying the text: The device displays the received text on the UI, and the user uses it as a reference to create a new story.

[0147] Prompt Sentence Examples

[0148] For example, if a user wants to generate text on a specific topic or setting, they might input the following prompt into a generative AI model:

[0149] "Generate the opening phrase of a new adventure story."

[0150] This system functions as a tool that allows users to easily obtain creative ideas and promotes inspiration.

[0151] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0152] Step 1:

[0153] The user clicks the "Generate new text" button on the user device interface. This operation initiates a request to generate text. The input is the user's click operation, and the output is the generation of the request. Specifically, the event listener of the user interface catches the click event.

[0154] Step 2:

[0155] The device catches the user's click event and creates an HTTP POST request. The request includes the user ID and request type. The input is the user's click operation, and the output is the request sent to the server. Specifically, the device program generates data in JSON format and prepares the HTTP request.

[0156] Step 3:

[0157] The server receives a request from the device. The server analyzes the request data and obtains the user ID and request type. The input is the HTTP request, and the output is the analyzed user ID and request type. Specifically, the server receives the request at an API endpoint using a framework such as Flask.

[0158] Step 4:

[0159] The server accesses the database and obtains a list of elements (subject, verb, action) required for sentence generation. The input is the parsed request information, and the output is a list of elements. Specifically, the server executes SQL queries or NoSQL read operations.

[0160] Step 5:

[0161] The server uses a random number generation algorithm to randomly select a subject, verb, and action from a database. The input is a list of elements, and the output is a randomly selected element. Specifically, the server selects a random element using a Python module such as the random module.

[0162] Step 6:

[0163] The server combines the selected elements to generate a sentence. The input is the randomly selected elements, and the output is the generated sentence. Specifically, the server combines the selected elements as a string to build a complete sentence.

[0164] Step 7:

[0165] The server sends the generated text in JSON format to the user's device. The input is the generated text, and the output is the transmitted data. Specifically, the server constructs an HTTP response and transmits it along with the data.

[0166] Step 8:

[0167] The terminal receives the response from the server and displays the generated text on the UI. The input is JSON format data sent from the server, and the output is the display on the UI. Specifically, the terminal analyzes the response data and displays the text on the user interface.

[0168] Through these steps, users can quickly and efficiently generate new inspirational writing.

[0169] (Application example 1)

[0170] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0171] In virtual stores, the product descriptions are fixed, which means that users are unable to get a fresh perspective when considering purchasing a product, making it difficult to stimulate their purchasing motivation. Furthermore, conventional systems lack a means to stimulate purchasing motivation by presenting randomly generated text to users.

[0172] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0173] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, and means for generating product descriptions and presenting them to the user in the virtual store. This makes it possible to provide fresh product information to users in the virtual store and increase their desire to purchase.

[0174] "Means for receiving a sentence generation request from a user" refers to an interface used to send a request to generate a new sentence to the server from a terminal operated by the user.

[0175] "Means for maintaining a database containing elements for sentence generation" refers to a system for saving a database for storing and managing elements such as subjects, verbs, and adjectives necessary for sentence generation.

[0176] The "means for randomly selecting an element from the database" refers to a processing mechanism for randomly selecting an element from among a plurality of elements stored in the database using a random number generation algorithm.

[0177] "Means for combining selected elements to generate a sentence" refers to an algorithm for combining randomly selected elements to generate a single meaningful sentence.

[0178] "Means for presenting the generated text to the user" refers to a system that displays the generated text on the screen or interface of the user's terminal.

[0179] "Means for generating product descriptions and presenting them to users in a virtual store" refers to a function for generating descriptions about products in a virtual store using random elements and displaying the descriptions to users.

[0180] "Subject, verb, and adjective" are the basic elements that make up a sentence. A subject refers to the subject of an action or state, a verb refers to that action or state, and an adjective refers to the word that modifies them.

[0181] "Means for transmitting to the user's terminal" refers to a communication system for transmitting the generated text via a network to a terminal such as a smartphone or tablet operated by the user.

[0182] The configuration and operation of a product description generation system for a virtual store will be described in detail below as an embodiment of the present invention. The system is composed of the following main components.

[0183] 1. User Device:

[0184] The user uses devices such as smartphones, tablets, and head-mounted displays as interfaces for operation. These devices communicate with a server via the Internet.

[0185] 2. Server:

[0186] This is the central computer that holds the database necessary for sentence generation and processes user requests. The sentence generation program is installed on the server, which is built using Python and the Flask framework.

[0187] 3. Database:

[0188] This is where the elements necessary for sentence generation (subject, verb, adjective) are stored. For example, a database such as SQLite is used.

[0189] System Operation

[0190] 1. User Action:

[0191] The user uses the virtual store interface to send a request to generate a new product description, for example by clicking a "Generate New Description" button.

[0192] 2. Submit your request:

[0193] The user device receives the button click event and sends an HTTP request to the server using HTTP / HTTPS as the communication protocol.

[0194] 3. Receiving and Processing Requests:

[0195] The server receives and analyzes the HTTP request, and prepares the necessary data based on the user information and request type included in the request.

[0196] 4. Random selection of elements:

[0197] The server accesses the database and randomly selects elements from the subject list, verb list, and adjective list using a random number generation algorithm.

[0198] 5. Sentence generation:

[0199] By combining the selected elements, the server generates a sentence, such as "This product is of the highest quality and will change your life."

[0200] 6. Sending the generated text:

[0201] The server sends the generated text to the user's terminal, where it is formatted so that the user can immediately understand it.

[0202] 7. Display of text:

[0203] The user terminal displays the received text on the user interface, allowing the user to gain a new perspective on the product based on the displayed text.

[0204] This makes it possible to provide users with fresh product information in the virtual store, thereby increasing their desire to purchase.

[0205] Use of concrete examples and prompts

[0206] For example, when a user clicks the "Generate new description" button in a virtual store, the server randomly selects elements from a database and generates a sentence like this:

[0207] "This product is of the highest quality and will change your life."

[0208] "Get this item now with your own unique design"

[0209] Example prompts to input to a generative AI model:

[0210] Please generate a new product description. Please randomly select and combine product-related elements (subject, adjective, verb) from the list below. The target product is a "smartphone."

[0211] Subject: "This product," "This item," "This product"

[0212] Adjectives: "Top quality," "Convenient," "Unique design"

[0213] Verbs: "is amazing," "will change your life," "get it now"

[0214] In this way, the system helps make the shopping experience in virtual stores more engaging and creative.

[0215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0216] Step 1:

[0217] The user terminal clicks the "Generate new description" button through the virtual store interface.

[0218] Input: User clicks.

[0219] Data processing: Catching click events.

[0220] Output: HTTP request ready to send.

[0221] Specific operation: By clicking a button on the interface of the user terminal, a click event occurs, and the system is ready to request the server to generate a new sentence.

[0222] Step 2:

[0223] The user terminal sends an HTTP request to the server.

[0224] Input: The HTTP request to the server.

[0225] Data processing: Formatting the request data.

[0226] Output: Sending a request to the server.

[0227] Specific operation: Request data is formatted from the user terminal and sent to the server using the HTTP protocol.

[0228] Step 3:

[0229] The server receives an HTTP request from the user terminal.

[0230] Input: HTTP request from the user's device.

[0231] Data processing: Parsing the request.

[0232] Output: Confirm the request content and prepare to access the database.

[0233] Specific operation: The server analyzes the request data received, checks the required information and type of request, and prepares to access the database.

[0234] Step 4:

[0235] The server randomly selects elements necessary for sentence generation from the database.

[0236] Input: A request to access the database.

[0237] Data processing: selection of random elements.

[0238] Output: Random selection of subject, verb, and adjective.

[0239] What it does: The server accesses a database and uses a random number generation algorithm to randomly select a subject, verb, and adjective.

[0240] Step 5:

[0241] The server combines the selected elements to generate a sentence.

[0242] Input: Randomly selected elements (subject, verb, adjective).

[0243] Data processing: Combining elements and generating sentences.

[0244] Output: The generated sentence.

[0245] What it does: The server combines the selected elements to generate natural-sounding sentences, such as "This product is of the highest quality and will change your life."

[0246] Step 6:

[0247] The server transmits the generated text to the user terminal.

[0248] Input: The generated sentence.

[0249] Data processing: data formatting.

[0250] Output: Ready to send to user terminal.

[0251] Specific operation: The generated text is formatted and prepared for sending to the user's terminal as an HTTP response.

[0252] Step 7:

[0253] The user terminal displays the text received from the server.

[0254] Input: HTTP response from the server (generated text).

[0255] Data processing: Displaying text on the interface.

[0256] Output: The text displayed on the user interface.

[0257] Specific operation: The user device analyzes the text received from the server and displays it on the user interface. Using the displayed text, the user can gain a new perspective on the product.

[0258] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0259] The following describes in detail the configuration and operation of a system for implementing the present invention. The system supports a user in writing sentences to gain inspiration, recognizes the user's emotions, and adjusts the writing based on the emotions.

[0260] System configuration

[0261] The system consists of the following main components:

[0262] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[0263] 2. Server: A central computer that holds the database for text generation and processes requests.

[0264] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0265] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly.

[0266] System Operation

[0267] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[0268] 1. User Action:

[0269] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0270] 2. Submit your request:

[0271] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[0272] 3. Receiving and Processing Requests:

[0273] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[0274] 4. Emotion Recognition with Emotion Engine:

[0275] The server uses an emotion engine to recognize the user's emotional state, using technologies such as voice input and facial expression analysis.

[0276] 5. Random selection of elements:

[0277] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0278] 6. Adjusting emotional factors:

[0279] The server adjusts the selected elements based on the emotional information obtained from the emotion engine, for example, choosing a positive action if the user is happy, or adjusting the tone appropriately if the user is sad.

[0280] 7. Sentence Generation:

[0281] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[0282] 8. Sending the generated text:

[0283] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0284] 9. Sending generated text:

[0285] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0286] 10. Display of text:

[0287] The user terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0288] 11. User Verification:

[0289] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[0290] Specific examples

[0291] As a concrete example, the following exchange can be envisioned:

[0292] 1. User Action:

[0293] A user is looking for new story ideas and clicks the "Generate New Text" button.

[0294] 2. Submit your request:

[0295] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[0296] 3. Receiving and Processing Requests:

[0297] The server receives the HTTP request and initiates access to the database.

[0298] 4. Emotion Recognition with Emotion Engine:

[0299] The server uses an emotion engine to recognize the user's emotions from their voice and facial expressions. For example, it determines that the user is happy.

[0300] 5. Random selection of elements:

[0301] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0302] 6. Adjusting emotional factors:

[0303] The server adjusts the tone of the generated text to be more positive based on the emotional information.

[0304] 7. Sentence Generation:

[0305] The server generates the sentence "The cat is walking happily."

[0306] 8. Sending the generated text:

[0307] The server sends the generated text to the user's smartphone.

[0308] 9. Display of text:

[0309] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[0310] In this way, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[0311] The processing flow will be explained below.

[0312] Step 1:

[0313] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[0314] Step 2:

[0315] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[0316] Step 3:

[0317] The server receives a request from the terminal, which includes instructions for generating a sentence.

[0318] Step 4:

[0319] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[0320] Step 5:

[0321] The server launches an emotion engine to analyze the user's emotions, which uses voice input and facial expression data to determine the user's emotional state.

[0322] Step 6:

[0323] The emotion engine passes the obtained emotion information to the server. For example, the emotion information passed may indicate whether the user is "happy" or "sad."

[0324] Step 7:

[0325] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0326] Step 8:

[0327] The server adjusts the selected elements based on the emotional information, for example, choosing positive actions if the user is happy, or generating text that matches the tone if the user is sad.

[0328] Step 9:

[0329] The server combines the selected elements to generate a sentence, such as "The cat is walking happily."

[0330] Step 10:

[0331] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0332] Step 11:

[0333] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0334] Step 12:

[0335] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0336] Step 13:

[0337] The user checks the text displayed on the device screen and can then engage in creative activities based on the displayed text.

[0338] Through the above steps, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[0339] Example 2

[0340] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0341] Conventional text generation systems simply combine randomly selected elements without considering the user's emotions, making it difficult to obtain inspiration appropriate to the user's emotional state. Furthermore, the generated text is not adjusted to reflect the user's current emotions, resulting in insufficient support for creative activities.

[0342] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0343] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for recognizing the user's emotion, means for adjusting the selected elements based on the recognized emotion, means for generating a sentence by combining the selected elements, and means for presenting the generated sentence to the user. This enables the generation of sentences suited to the user's emotional state, thereby more effectively supporting creative activities.

[0344] The "means for receiving a sentence generation request from a user" refers to the interface through which a user requests the generation of a new sentence and the method by which the system receives the request.

[0345] "Means for maintaining a database containing elements for sentence generation" refers to a database for storing and managing elements necessary for sentence generation, such as subjects, verbs, and actions, and a method for operating the database.

[0346] The "means for randomly selecting elements from said database" refers to algorithms and methods for randomly selecting from among elements stored in the database.

[0347] "Means for recognizing user emotions" refers to a system or technology that detects the user's emotional state from their voice, facial expressions, etc., and analyzes that information.

[0348] The "means for adjusting selected elements based on recognized emotions" are algorithms and methods for optimizing selected elements depending on the emotional state of the user.

[0349] The "means for generating a sentence by combining selected elements" refers to an algorithm and method for generating a sentence by combining randomly selected elements.

[0350] The "means for presenting the generated text to the user" refers to a method and system for transmitting the generated text to the user's terminal and displaying it.

[0351] The present invention provides a system for generating sentences based on the user's emotions and presenting the generated sentences to the user.

[0352] System configuration

[0353] The system consists of the following major hardware and software components:

[0354] 1. User terminal: Computer, smartphone, tablet, etc. A device that provides an interface for users to perform operations.

[0355] 2. Server: A central computer that processes requests for text generation and manages the database and emotion engine.

[0356] 3. Database: Stores the elements necessary for sentence generation (subject, verb, action).

[0357] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text based on those emotions. It can use Microsoft® Azure® Emotion API or IBM Watson® Emotion Analysis API.

[0358] System Operation

[0359] The operation of the system is explained in the following sequence.

[0360] User operations

[0361] When a user wants to generate a new sentence, they click the "Generate New Sentence" button on the user device interface. This operation is performed by a button element on a web browser or a touch operation on a mobile app.

[0362] Submitting a Request

[0363] The user device catches the user's click event and sends an HTTP request to the server, which includes information such as the user ID and the request type.

[0364] Receiving and processing requests

[0365] The server analyzes the received HTTP request and prepares the necessary database operations and emotion recognition processes.

[0366] Emotion recognition by emotion engine

[0367] The server uses an emotion engine to recognize the user's emotional state, using voice input (microphone) and facial expression analysis (camera) technologies.

[0368] Random selection of elements

[0369] The server accesses a database and randomly selects an element from the subject, verb, and action list using a random number generation algorithm.

[0370] Adjusting elements based on emotions

[0371] The server adjusts randomly selected elements based on the emotion recognition results, for example, choosing a positive expression if the user is happy, or adjusting the appropriate tone if the user is sad.

[0372] Sentence generation

[0373] The server combines the selected and adjusted elements to generate a sentence, which is concisely expressed, for example, "The cat is walking happily."

[0374] Sending generated text

[0375] The server converts the generated text into JSON format and sends it to the user's terminal.

[0376] Displaying text

[0377] The user terminal analyzes the received data and displays the generated text on the user interface.

[0378] User Verification

[0379] The user checks the displayed text and starts a new creative activity based on that text.

[0380] Specific examples

[0381] As a concrete example, the following exchange can be envisioned:

[0382] 1. User operations

[0383] A user clicks the "Generate New Text" button for new story ideas.

[0384] 2. Submitting a Request

[0385] The user device catches the button click event and sends an HTTP request to the server, for example, sending a prompt such as "Please create a new sentence."

[0386] 3. Receiving and Processing Requests

[0387] The server receives the HTTP request and prepares to access the database.

[0388] 4. Emotion Recognition by Emotion Engine

[0389] The server uses an emotion engine to recognize emotions from the user's voice and facial expressions. For example, it determines that the user is happy.

[0390] 5. Random selection of elements

[0391] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0392] 6. Adjusting emotional elements

[0393] Based on the emotional information, the server adds modifiers such as "happily" to adjust the tone of the sentence to a more positive one.

[0394] 7. Sentence Generation

[0395] The server generates the sentence "The cat is walking happily."

[0396] 8. Sending the generated text

[0397] The server transmits the generated text to the user terminal.

[0398] 9. Display of text

[0399] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[0400] In this way, the system can provide new inspiration while taking into account the user's emotions and support creative activities.

[0401] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0402] Program processing flow

[0403] Step 1: User interaction

[0404] The user clicks the "Create a new document" button in the user device interface. This requests the creation of a new document. The input is a specific user action (the button click), and the output is this action being sent to the server as an HTTP request.

[0405] Step 2: Submitting the request

[0406] The device catches the user's click event and sends an HTTP request to the server based on that information. This request includes the user ID, request type, etc. The specific input is the user's click event, and the output is the HTTP request sent to the server.

[0407] Step 3: Receiving and Processing the Request

[0408] The server receives an HTTP request from the device and extracts the user ID and request type from the request body. Based on the analysis results of this request, it performs the necessary database operations and prepares for emotion recognition. The input is the content of the HTTP request, and the output is the analyzed user ID and request type.

[0409] Step 4: Emotion Recognition with the Emotion Engine

[0410] The server uses an emotion engine (e.g., emotion recognition API) to recognize the user's emotional state. At this time, voice data and facial photo data are used as input, and the user's emotional state (joy, anger, sadness, etc.) is output as a result. Specifically, this includes the operation of sending voice input data and image data taken by a camera to the emotion engine and receiving the results of the recognized emotion.

[0411] Step 5: Random selection of elements

[0412] The server accesses the database and randomly selects elements from the subject list, verb list, and action list. The input is each list in the database, and the output is the selected subject, verb, and action elements. The specific operation of randomly selecting elements using a random number generation algorithm is included.

[0413] Step 6: Adjusting emotional elements

[0414] The server adjusts randomly selected elements based on the emotional information obtained from the emotion engine. The input is the recognized emotional state and the randomly selected elements, and based on these, it adds positive or negative modifiers and obtains the adjusted elements as the output. For example, it performs a specific action to select a modifier such as "happy."

[0415] Step 7: Sentence generation

[0416] The server generates sentences by combining the selected and adjusted elements. The input is the adjusted subject, verb, and action elements, and the output is a sentence that combines them. For example, it performs operations including string manipulation to generate the sentence "The cat is walking happily."

[0417] Step 8: Sending the generated text

[0418] The server converts the generated text into JSON format and sends it to the user's terminal. The input is the generated text, and the output is JSON format data sent to the terminal. The specific operations of conversion and transmission are performed.

[0419] Step 9: Displaying the generated text

[0420] The user terminal analyzes the JSON data received from the server and displays the text at the specified position on the user interface. The input is the JSON data sent from the server, and the output is the text displayed on the user interface. For example, it performs the specific operation of displaying the text on the screen using HTML or JavaScript (registered trademark).

[0421] Step 10: Verify the user

[0422] The user checks the text displayed on the screen of the user device and begins creative activities such as creating a new story based on that text. The input is the displayed text, and the output is the user's confirmation of the text and new inspiration based on it. Specific actions taken by the user to confirm the text are included.

[0423] (Application example 2)

[0424] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0425] Conventional text generation systems present generated text without considering the user's emotions, making it impossible to provide text that is appropriate to the user's situation or emotions. As a result, the inspiration generated by the text generation system does not fully support the user's creative activities, and there are limitations to improving the interactive customer experience in physical stores. Furthermore, it is difficult to provide information that is in line with the user's emotions, making it difficult to maximize customer purchasing motivation.

[0426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0427] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, means for recognizing the user's emotions, and means for adjusting the generated sentences based on the recognized emotions. This allows optimal sentences to be generated based on the user's emotions, making it possible to significantly improve the customer experience in interactive environments such as brick-and-mortar stores.

[0428] The "means for receiving a request for sentence generation from a user" is a means for a user to send a request for generating a new sentence to a server via an interface.

[0429] The "means for maintaining a database containing elements for sentence generation" refers to a means for managing and maintaining a database that stores elements such as subjects, verbs, and actions required for sentence generation.

[0430] The "means for randomly selecting an element from the database" refers to a means including an algorithm for randomly selecting from among the stored elements.

[0431] The "means for generating a sentence by combining selected elements" is a means for constructing a sentence by combining randomly selected elements.

[0432] The "means for presenting the generated text to the user" refers to a means for displaying the generated text on a user interface or transmitting it to the user's device.

[0433] The "means for recognizing the user's emotions" refers to a means that uses technology to analyze the user's facial expressions and voice data and infer the user's emotional state.

[0434] The "means for adjusting the generated sentence based on the recognized emotion" is a means for appropriately changing the content and tone of the generated sentence based on the user's emotion data.

[0435] System configuration

[0436] A system for implementing the present invention comprises the following major components:

[0437] 1. User terminal: A device that provides an interface for users to operate. Examples include smart glasses and head-mounted displays (HMDs).

[0438] 2. Server: A central computer that holds the database for text generation and processes requests.

[0439] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0440] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated sentences accordingly.

[0441] System Operation

[0442] The system generates sentences based on the user's emotions as follows:

[0443] User operations

[0444] The user requests the generation of a new sentence, for example by clicking a button on the interface of the smart glasses or HMD.

[0445] emotion recognition

[0446] The camera and microphone of smart glasses or HMDs equipped with an emotion engine capture the user's facial expressions and voice and recognize their emotions. The emotion engine uses facial recognition software and voice analysis software to analyze emotion data in real time.

[0447] Submitting a Request

[0448] A request for sentence generation along with emotion data is sent to the server using HTTP or WebSocket as the communication protocol.

[0449] Random selection and adjustment of elements

[0450] The server accesses the database and randomly selects elements such as subjects, verbs, and actions. It then adjusts the selected elements based on the recognized emotional data. If the emotional information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one.

[0451] Text generation and display

[0452] The server uses a generative AI model to generate text from the adjusted elements, which is then converted into a data format and sent to the user's smart glasses or HMD for display.

[0453] Specific examples

[0454] For example, when a customer picks up a new product in a physical store, the emotion engine analyzes the customer's facial expressions and voice to recognize their emotional state. Based on the recognized emotion, the server receives a request such as "I'd like to know more about this product," selects appropriate elements from the database, and generates a tailored sentence.

[0455] Prompt Sentence Examples

[0456] "Please briefly describe the characteristics of this product. The emotion is 'joy'."

[0457] Such a highly interactive system is expected to enable users to obtain optimal information that matches their emotions, stimulating their purchasing desire.

[0458] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0459] Step 1:

[0460] The user requests the generation of a new sentence. The user clicks a button on the interface of smart glasses or a head-mounted display (HMD) to generate the request. This operation generates request data. The input is the user's operation, and the output is the request data.

[0461] Step 2:

[0462] The camera and microphone of smart glasses or HMD are used to capture the user's facial expressions and voice to obtain emotion data. The input is the user's real-time facial expressions and voice, and the output is emotion information (e.g., joy, sadness, etc.). The emotion engine processes this and generates emotion data.

[0463] Step 3:

[0464] The acquired emotion data and request data are sent to the server. The communication protocol is HTTP or WebSocket. The input is emotion data and request data, and the output is the data sent to the server.

[0465] Step 4:

[0466] The server analyzes the received emotion data and request data and accesses the database. The input is emotion data and request data, and the output is a database query. The server randomly selects elements such as subject, verb, and action.

[0467] Step 5:

[0468] The server adjusts the selected elements based on the emotion. If the emotion information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one. The input is the selected elements and the emotion information, and the output is the adjusted elements.

[0469] Step 6:

[0470] The server generates a sentence using a generative AI model based on the adjusted elements. The input is the adjusted elements, and the output is the generated sentence. The generative AI model constructs the optimal sentence based on the prompt sentence.

[0471] Step 7:

[0472] The generated text is converted into a data format (e.g., JSON, XML) and sent to the user's smart glasses or HMD. The input is the generated text, and the output is the transmitted data. The server sends the data using HTTPS or WebSocket.

[0473] Step 8:

[0474] The user's device analyzes the received data and displays the generated text on the interface. The input is the transmitted data, and the output is the text presented to the user. The user can visually check this text and get inspiration.

[0475] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0476] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0477] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0478] [Second embodiment]

[0479] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0480] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0481] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0482] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0483] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0484] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0485] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0486] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0487] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0488] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0489] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0490] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0491] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain inspiration.

[0492] System configuration

[0493] The system consists of the following main components:

[0494] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[0495] 2. Server: A central computer that holds the database for text generation and processes requests.

[0496] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0497] System Operation

[0498] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[0499] 1. User Action:

[0500] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0501] 2. Submit your request:

[0502] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[0503] 3. Receiving and Processing Requests:

[0504] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[0505] 4. Random selection of elements:

[0506] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0507] 5. Sentence generation:

[0508] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[0509] 6. Sending the generated text:

[0510] The server sends the generated text to the user's terminal, formatting the data so that it can be immediately understood by the user.

[0511] 7. Display of text:

[0512] The user terminal displays the received text on the user interface, allowing the user to engage in creative activities based on the displayed text.

[0513] Specific examples

[0514] As a concrete example, the following spear-like action is envisioned:

[0515] 1. User Action:

[0516] A user is looking for new story ideas and clicks the "Generate New Text" button.

[0517] 2. Submit your request:

[0518] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[0519] 3. Receiving and Processing Requests:

[0520] The server receives the HTTP request and initiates access to the database.

[0521] 4. Random selection of elements:

[0522] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0523] 5. Sentence generation:

[0524] The server generates the sentence "The cat walks."

[0525] 6. Sending the generated text:

[0526] The server sends the generated text to the user's smartphone.

[0527] 7. Display of text:

[0528] The user's device displays the sentence "A cat walks" on the screen, and the user begins writing a new story based on that sentence.

[0529] In this way, the system helps the user find inspiration and supports creative activities.

[0530] The processing flow will be explained below.

[0531] Step 1:

[0532] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[0533] Step 2:

[0534] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[0535] Step 3:

[0536] The server receives a request from the terminal, which includes instructions for generating a sentence.

[0537] Step 4:

[0538] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[0539] Step 5:

[0540] The server accesses the database and reads the list of elements (subject, verb, action) for sentence generation.

[0541] Step 6:

[0542] The server randomly selects a subject from the subject list using a random number generation algorithm that ensures statistical randomness.

[0543] Step 7:

[0544] The server randomly selects a verb from the verb list, again using an algorithm that ensures statistical randomness.

[0545] Step 8:

[0546] The server randomly selects an action from the list of actions, again based on a random number generation algorithm.

[0547] Step 9:

[0548] The server combines the selected subject, verb, and action to generate a sentence. For example, the sentence "The cat walks."

[0549] Step 10:

[0550] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0551] Step 11:

[0552] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0553] Step 12:

[0554] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0555] Step 13:

[0556] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[0557] Through the above steps, this system provides users with new inspiration and supports their creative activities.

[0558] Example 1

[0559] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0560] Conventional text generation systems have not provided users with an efficient way to gain new inspiration. Specifically, they often lack an interface that allows users to easily generate text, or a function to instantly receive and display the generated text. A new system is needed to resolve these issues and support users' creative activities.

[0561] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0562] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for transmitting the generated sentences to the user's terminal, and means for displaying the generated sentences on the user's terminal, thereby enabling the user to quickly and easily generate inspirational sentences and start creative activities based on them.

[0563] A "user" is an individual or group who wishes to generate text and operates the system.

[0564] The "means for receiving a request" is a mechanism for transmitting a request from a user to a server and starting processing.

[0565] The "means for maintaining the database" is a system component that has the function of storing and managing elements necessary for sentence generation (subject, verb, action, etc.).

[0566] The "means for randomly selecting elements" is a mechanism for randomly extracting elements from the database.

[0567] The "means for generating a sentence" is a program that has the function of combining selected elements to construct a single sentence.

[0568] "Means for transmitting the generated text to the user's terminal" refers to a mechanism by which the server transmits the generated text to the user's device via a network.

[0569] The "means for displaying the generated text on the user's terminal" is a component that has the function of visually displaying the received text on the user interface.

[0570] A "subject" is a noun or pronoun that is the subject of an action in a sentence.

[0571] A "verb" is a word that expresses the action or state that the subject of a sentence performs.

[0572] An "action" is a specific action in a sentence in which a verb is performed by the subject.

[0573] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain new inspiration.

[0574] System configuration

[0575] The system consists of the following main components:

[0576] 1. User terminal: A device used by a user to perform operations, including computers, smartphones, tablets, etc.

[0577] 2. Server: This is the central system that holds the database for text generation and processes requests.

[0578] 3. Database: This is where the elements necessary for sentence generation (subject, verb, action) are stored.

[0579] System Operation

[0580] In this system, when a user wishes to create a new sentence, the following process is carried out:

[0581] User operations

[0582] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0583] Submitting a Request

[0584] In response to a user's operation, the device sends an HTTP POST request to the server, which includes information such as the user ID and the request type.

[0585] Receiving and processing requests

[0586] The server receives the request, analyzes it, and prepares the necessary data based on the information contained in the request.

[0587] Random selection of elements

[0588] The server accesses the database and uses a random number generation algorithm to randomly select elements from the subject list, verb list, and action list.

[0589] Sentence generation

[0590] The server combines the selected elements to generate a sentence. For example, if the elements "cat," "ga," and "aruku" are selected, the sentence "The cat walks" is generated.

[0591] Sending generated text

[0592] The server sends the generated text to the user's device, often in JSON format.

[0593] Displaying text

[0594] The device displays the received text on the user interface, allowing users to create new stories and engage in creative activities based on the displayed text.

[0595] Specific examples

[0596] As a specific example, the following exchange is envisioned.

[0597] 1. User action: A user is looking for a new story idea and clicks the "Generate new text" button on their smartphone UI.

[0598] 2. Sending a request: The device catches the button click event and sends an HTTP POST request to the server.

[0599] 3. Receiving and processing the request: The server receives the request and parses it.

[0600] 4. Random selection of elements: The server obtains the subject "dog", the verb "ga", and the action "bark" randomly selected from the database.

[0601] 5. Sentence generation: The server generates the sentence "The dog is barking."

[0602] 6. Sending the generated text: The server sends the generated text to the terminal in JSON format.

[0603] 7. Displaying the text: The device displays the received text on the UI, and the user uses it as a reference to create a new story.

[0604] Prompt Sentence Examples

[0605] For example, if a user wants to generate text on a specific topic or setting, they might input the following prompt into a generative AI model:

[0606] "Generate the opening phrase of a new adventure story."

[0607] This system functions as a tool that allows users to easily obtain creative ideas and promotes inspiration.

[0608] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0609] Step 1:

[0610] The user clicks the "Generate new text" button on the user device interface. This operation initiates a request to generate text. The input is the user's click operation, and the output is the generation of the request. Specifically, the event listener of the user interface catches the click event.

[0611] Step 2:

[0612] The device catches the user's click event and creates an HTTP POST request. The request includes the user ID and request type. The input is the user's click operation, and the output is the request sent to the server. Specifically, the device program generates data in JSON format and prepares the HTTP request.

[0613] Step 3:

[0614] The server receives a request from the device. The server analyzes the request data and obtains the user ID and request type. The input is the HTTP request, and the output is the analyzed user ID and request type. Specifically, the server receives the request at an API endpoint using a framework such as Flask.

[0615] Step 4:

[0616] The server accesses the database and obtains a list of elements (subject, verb, action) required for sentence generation. The input is the parsed request information, and the output is a list of elements. Specifically, the server executes SQL queries or NoSQL read operations.

[0617] Step 5:

[0618] The server uses a random number generation algorithm to randomly select a subject, verb, and action from a database. The input is a list of elements, and the output is a randomly selected element. Specifically, the server selects a random element using a Python module such as the random module.

[0619] Step 6:

[0620] The server combines the selected elements to generate a sentence. The input is the randomly selected elements, and the output is the generated sentence. Specifically, the server combines the selected elements as a string to build a complete sentence.

[0621] Step 7:

[0622] The server sends the generated text in JSON format to the user's device. The input is the generated text, and the output is the transmitted data. Specifically, the server constructs an HTTP response and transmits it along with the data.

[0623] Step 8:

[0624] The terminal receives the response from the server and displays the generated text on the UI. The input is JSON format data sent from the server, and the output is the display on the UI. Specifically, the terminal analyzes the response data and displays the text on the user interface.

[0625] Through these steps, users can quickly and efficiently generate new inspirational writing.

[0626] (Application example 1)

[0627] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0628] In virtual stores, the product descriptions are fixed, which means that users are unable to get a fresh perspective when considering purchasing a product, making it difficult to stimulate their purchasing motivation. Furthermore, conventional systems lack a means to stimulate purchasing motivation by presenting randomly generated text to users.

[0629] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0630] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, and means for generating product descriptions and presenting them to the user in the virtual store. This makes it possible to provide fresh product information to users in the virtual store and increase their desire to purchase.

[0631] "Means for receiving a sentence generation request from a user" refers to an interface used to send a request to generate a new sentence to the server from a terminal operated by the user.

[0632] "Means for maintaining a database containing elements for sentence generation" refers to a system for saving a database for storing and managing elements such as subjects, verbs, and adjectives necessary for sentence generation.

[0633] The "means for randomly selecting an element from the database" refers to a processing mechanism for randomly selecting an element from among a plurality of elements stored in the database using a random number generation algorithm.

[0634] "Means for combining selected elements to generate a sentence" refers to an algorithm for combining randomly selected elements to generate a single meaningful sentence.

[0635] "Means for presenting the generated text to the user" refers to a system that displays the generated text on the screen or interface of the user's terminal.

[0636] "Means for generating product descriptions and presenting them to users in a virtual store" refers to a function for generating descriptions about products in a virtual store using random elements and displaying the descriptions to users.

[0637] "Subject, verb, and adjective" are the basic elements that make up a sentence. A subject refers to the subject of an action or state, a verb refers to that action or state, and an adjective refers to the word that modifies them.

[0638] "Means for transmitting to the user's terminal" refers to a communication system for transmitting the generated text via a network to a terminal such as a smartphone or tablet operated by the user.

[0639] The configuration and operation of a product description generation system for a virtual store will be described in detail below as an embodiment of the present invention. The system is composed of the following main components.

[0640] 1. User Device:

[0641] The user uses devices such as smartphones, tablets, and head-mounted displays as interfaces for operation. These devices communicate with a server via the Internet.

[0642] 2. Server:

[0643] This is the central computer that holds the database necessary for sentence generation and processes user requests. The sentence generation program is installed on the server, which is built using Python and the Flask framework.

[0644] 3. Database:

[0645] This is where the elements necessary for sentence generation (subject, verb, adjective) are stored. For example, a database such as SQLite is used.

[0646] System Operation

[0647] 1. User Action:

[0648] The user uses the virtual store interface to send a request to generate a new product description, for example by clicking a "Generate New Description" button.

[0649] 2. Submit your request:

[0650] The user device receives the button click event and sends an HTTP request to the server using HTTP / HTTPS as the communication protocol.

[0651] 3. Receiving and Processing Requests:

[0652] The server receives and analyzes the HTTP request, and prepares the necessary data based on the user information and request type included in the request.

[0653] 4. Random selection of elements:

[0654] The server accesses the database and randomly selects elements from the subject list, verb list, and adjective list using a random number generation algorithm.

[0655] 5. Sentence generation:

[0656] By combining the selected elements, the server generates a sentence, such as "This product is of the highest quality and will change your life."

[0657] 6. Sending the generated text:

[0658] The server sends the generated text to the user's terminal, where it is formatted so that the user can immediately understand it.

[0659] 7. Display of text:

[0660] The user terminal displays the received text on the user interface, allowing the user to gain a new perspective on the product based on the displayed text.

[0661] This makes it possible to provide users with fresh product information in the virtual store, thereby increasing their desire to purchase.

[0662] Use of concrete examples and prompts

[0663] For example, when a user clicks the "Generate new description" button in a virtual store, the server randomly selects elements from a database and generates a sentence like this:

[0664] "This product is of the highest quality and will change your life."

[0665] "Get this item now with your own unique design"

[0666] Example prompts to input to a generative AI model:

[0667] Please generate a new product description. Please randomly select and combine product-related elements (subject, adjective, verb) from the list below. The target product is a "smartphone."

[0668] Subject: "This product," "This item," "This product"

[0669] Adjectives: "Top quality," "Convenient," "Unique design"

[0670] Verbs: "is amazing," "will change your life," "get it now"

[0671] In this way, the system helps make the shopping experience in virtual stores more engaging and creative.

[0672] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0673] Step 1:

[0674] The user terminal clicks the "Generate new description" button through the virtual store interface.

[0675] Input: User clicks.

[0676] Data processing: Catching click events.

[0677] Output: HTTP request ready to send.

[0678] Specific operation: By clicking a button on the interface of the user terminal, a click event occurs, and the system is ready to request the server to generate a new sentence.

[0679] Step 2:

[0680] The user terminal sends an HTTP request to the server.

[0681] Input: The HTTP request to the server.

[0682] Data processing: Formatting the request data.

[0683] Output: Sending a request to the server.

[0684] Specific operation: Request data is formatted from the user terminal and sent to the server using the HTTP protocol.

[0685] Step 3:

[0686] The server receives an HTTP request from the user terminal.

[0687] Input: HTTP request from the user's device.

[0688] Data processing: Parsing the request.

[0689] Output: Confirm the request content and prepare to access the database.

[0690] Specific operation: The server analyzes the request data received, checks the required information and type of request, and prepares to access the database.

[0691] Step 4:

[0692] The server randomly selects elements necessary for sentence generation from the database.

[0693] Input: A request to access the database.

[0694] Data processing: selection of random elements.

[0695] Output: Random selection of subject, verb, and adjective.

[0696] What it does: The server accesses a database and uses a random number generation algorithm to randomly select a subject, verb, and adjective.

[0697] Step 5:

[0698] The server combines the selected elements to generate a sentence.

[0699] Input: Randomly selected elements (subject, verb, adjective).

[0700] Data processing: Combining elements and generating sentences.

[0701] Output: The generated sentence.

[0702] What it does: The server combines the selected elements to generate natural-sounding sentences, such as "This product is of the highest quality and will change your life."

[0703] Step 6:

[0704] The server transmits the generated text to the user terminal.

[0705] Input: The generated sentence.

[0706] Data processing: data formatting.

[0707] Output: Ready to send to user terminal.

[0708] Specific operation: The generated text is formatted and prepared for sending to the user's terminal as an HTTP response.

[0709] Step 7:

[0710] The user terminal displays the text received from the server.

[0711] Input: HTTP response from the server (generated text).

[0712] Data processing: Displaying text on the interface.

[0713] Output: The text displayed on the user interface.

[0714] Specific operation: The user device analyzes the text received from the server and displays it on the user interface. Using the displayed text, the user can gain a new perspective on the product.

[0715] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0716] The following describes in detail the configuration and operation of a system for implementing the present invention. The system supports a user in writing sentences to gain inspiration, recognizes the user's emotions, and adjusts the writing based on the emotions.

[0717] System configuration

[0718] The system consists of the following main components:

[0719] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[0720] 2. Server: A central computer that holds the database for text generation and processes requests.

[0721] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0722] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly.

[0723] System Operation

[0724] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[0725] 1. User Action:

[0726] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0727] 2. Submit your request:

[0728] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[0729] 3. Receiving and Processing Requests:

[0730] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[0731] 4. Emotion Recognition with Emotion Engine:

[0732] The server uses an emotion engine to recognize the user's emotional state, using technologies such as voice input and facial expression analysis.

[0733] 5. Random selection of elements:

[0734] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0735] 6. Adjusting emotional factors:

[0736] The server adjusts the selected elements based on the emotional information obtained from the emotion engine, for example, choosing a positive action if the user is happy, or adjusting the tone appropriately if the user is sad.

[0737] 7. Sentence Generation:

[0738] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[0739] 8. Sending the generated text:

[0740] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0741] 9. Sending generated text:

[0742] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0743] 10. Display of text:

[0744] The user terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0745] 11. User Verification:

[0746] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[0747] Specific examples

[0748] As a concrete example, the following exchange can be envisioned:

[0749] 1. User Action:

[0750] A user is looking for new story ideas and clicks the "Generate New Text" button.

[0751] 2. Submit your request:

[0752] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[0753] 3. Receiving and Processing Requests:

[0754] The server receives the HTTP request and initiates access to the database.

[0755] 4. Emotion Recognition with Emotion Engine:

[0756] The server uses an emotion engine to recognize the user's emotions from their voice and facial expressions. For example, it determines that the user is happy.

[0757] 5. Random selection of elements:

[0758] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0759] 6. Adjusting emotional factors:

[0760] The server adjusts the tone of the generated text to be more positive based on the emotional information.

[0761] 7. Sentence Generation:

[0762] The server generates the sentence "The cat is walking happily."

[0763] 8. Sending the generated text:

[0764] The server sends the generated text to the user's smartphone.

[0765] 9. Display of text:

[0766] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[0767] In this way, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[0768] The processing flow will be explained below.

[0769] Step 1:

[0770] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[0771] Step 2:

[0772] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[0773] Step 3:

[0774] The server receives a request from the terminal, which includes instructions for generating a sentence.

[0775] Step 4:

[0776] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[0777] Step 5:

[0778] The server launches an emotion engine to analyze the user's emotions, which uses voice input and facial expression data to determine the user's emotional state.

[0779] Step 6:

[0780] The emotion engine passes the obtained emotion information to the server. For example, the emotion information passed may indicate whether the user is "happy" or "sad."

[0781] Step 7:

[0782] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0783] Step 8:

[0784] The server adjusts the selected elements based on the emotional information, for example, choosing positive actions if the user is happy, or generating text that matches the tone if the user is sad.

[0785] Step 9:

[0786] The server combines the selected elements to generate a sentence, such as "The cat is walking happily."

[0787] Step 10:

[0788] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[0789] Step 11:

[0790] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[0791] Step 12:

[0792] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[0793] Step 13:

[0794] The user checks the text displayed on the device screen and can then engage in creative activities based on the displayed text.

[0795] Through the above steps, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[0796] Example 2

[0797] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0798] Conventional text generation systems simply combine randomly selected elements without considering the user's emotions, making it difficult to obtain inspiration appropriate to the user's emotional state. Furthermore, the generated text is not adjusted to reflect the user's current emotions, resulting in insufficient support for creative activities.

[0799] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0800] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for recognizing the user's emotion, means for adjusting the selected elements based on the recognized emotion, means for generating a sentence by combining the selected elements, and means for presenting the generated sentence to the user. This enables the generation of sentences suited to the user's emotional state, thereby more effectively supporting creative activities.

[0801] The "means for receiving a sentence generation request from a user" refers to the interface through which a user requests the generation of a new sentence and the method by which the system receives the request.

[0802] "Means for maintaining a database containing elements for sentence generation" refers to a database for storing and managing elements necessary for sentence generation, such as subjects, verbs, and actions, and a method for operating the database.

[0803] The "means for randomly selecting elements from said database" refers to algorithms and methods for randomly selecting from among elements stored in the database.

[0804] "Means for recognizing user emotions" refers to a system or technology that detects the user's emotional state from their voice, facial expressions, etc., and analyzes that information.

[0805] The "means for adjusting selected elements based on recognized emotions" are algorithms and methods for optimizing selected elements depending on the emotional state of the user.

[0806] The "means for generating a sentence by combining selected elements" refers to an algorithm and method for generating a sentence by combining randomly selected elements.

[0807] The "means for presenting the generated text to the user" refers to a method and system for transmitting the generated text to the user's terminal and displaying it.

[0808] The present invention provides a system for generating sentences based on the user's emotions and presenting the generated sentences to the user.

[0809] System configuration

[0810] The system consists of the following major hardware and software components:

[0811] 1. User terminal: Computer, smartphone, tablet, etc. A device that provides an interface for users to perform operations.

[0812] 2. Server: A central computer that processes requests for text generation and manages the database and emotion engine.

[0813] 3. Database: Stores the elements necessary for sentence generation (subject, verb, action).

[0814] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly. It can use Microsoft Azure's Emotion API or IBM Watson's Emotion Analysis API.

[0815] System Operation

[0816] The operation of the system is explained in the following sequence.

[0817] User operations

[0818] When a user wants to generate a new sentence, they click the "Generate New Sentence" button on the user device interface. This operation is performed by a button element on a web browser or a touch operation on a mobile app.

[0819] Submitting a Request

[0820] The user device catches the user's click event and sends an HTTP request to the server, which includes information such as the user ID and the request type.

[0821] Receiving and processing requests

[0822] The server analyzes the received HTTP request and prepares the necessary database operations and emotion recognition processes.

[0823] Emotion recognition by emotion engine

[0824] The server uses an emotion engine to recognize the user's emotional state, using voice input (microphone) and facial expression analysis (camera) technologies.

[0825] Random selection of elements

[0826] The server accesses a database and randomly selects an element from the subject, verb, and action list using a random number generation algorithm.

[0827] Adjusting elements based on emotions

[0828] The server adjusts randomly selected elements based on the emotion recognition results, for example, choosing a positive expression if the user is happy, or adjusting the appropriate tone if the user is sad.

[0829] Sentence generation

[0830] The server combines the selected and adjusted elements to generate a sentence, which is concisely expressed, for example, "The cat is walking happily."

[0831] Sending generated text

[0832] The server converts the generated text into JSON format and sends it to the user's terminal.

[0833] Displaying text

[0834] The user terminal analyzes the received data and displays the generated text on the user interface.

[0835] User Verification

[0836] The user checks the displayed text and starts a new creative activity based on that text.

[0837] Specific examples

[0838] As a concrete example, the following exchange can be envisioned:

[0839] 1. User operations

[0840] A user clicks the "Generate New Text" button for new story ideas.

[0841] 2. Submitting a Request

[0842] The user device catches the button click event and sends an HTTP request to the server, for example, sending a prompt such as "Please create a new sentence."

[0843] 3. Receiving and Processing Requests

[0844] The server receives the HTTP request and prepares to access the database.

[0845] 4. Emotion Recognition by Emotion Engine

[0846] The server uses an emotion engine to recognize emotions from the user's voice and facial expressions. For example, it determines that the user is happy.

[0847] 5. Random selection of elements

[0848] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0849] 6. Adjusting emotional elements

[0850] Based on the emotional information, the server adds modifiers such as "happily" to adjust the tone of the sentence to a more positive one.

[0851] 7. Sentence Generation

[0852] The server generates the sentence "The cat is walking happily."

[0853] 8. Sending the generated text

[0854] The server transmits the generated text to the user terminal.

[0855] 9. Display of text

[0856] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[0857] In this way, the system can provide new inspiration while taking into account the user's emotions and support creative activities.

[0858] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0859] Program processing flow

[0860] Step 1: User interaction

[0861] The user clicks the "Create a new document" button in the user device interface. This requests the creation of a new document. The input is a specific user action (the button click), and the output is this action being sent to the server as an HTTP request.

[0862] Step 2: Submitting the request

[0863] The device catches the user's click event and sends an HTTP request to the server based on that information. This request includes the user ID, request type, etc. The specific input is the user's click event, and the output is the HTTP request sent to the server.

[0864] Step 3: Receiving and Processing the Request

[0865] The server receives an HTTP request from the device and extracts the user ID and request type from the request body. Based on the analysis results of this request, it performs the necessary database operations and prepares for emotion recognition. The input is the content of the HTTP request, and the output is the analyzed user ID and request type.

[0866] Step 4: Emotion Recognition with the Emotion Engine

[0867] The server uses an emotion engine (e.g., emotion recognition API) to recognize the user's emotional state. At this time, voice data and facial photo data are used as input, and the user's emotional state (joy, anger, sadness, etc.) is output as a result. Specifically, this includes the operation of sending voice input data and image data taken by a camera to the emotion engine and receiving the results of the recognized emotion.

[0868] Step 5: Random selection of elements

[0869] The server accesses the database and randomly selects elements from the subject list, verb list, and action list. The input is each list in the database, and the output is the selected subject, verb, and action elements. The specific operation of randomly selecting elements using a random number generation algorithm is included.

[0870] Step 6: Adjusting emotional elements

[0871] The server adjusts randomly selected elements based on the emotional information obtained from the emotion engine. The input is the recognized emotional state and the randomly selected elements, and based on these, it adds positive or negative modifiers and obtains the adjusted elements as the output. For example, it performs a specific action to select a modifier such as "happy."

[0872] Step 7: Sentence generation

[0873] The server generates sentences by combining the selected and adjusted elements. The input is the adjusted subject, verb, and action elements, and the output is a sentence that combines them. For example, it performs operations including string manipulation to generate the sentence "The cat is walking happily."

[0874] Step 8: Sending the generated text

[0875] The server converts the generated text into JSON format and sends it to the user's terminal. The input is the generated text, and the output is JSON format data sent to the terminal. The specific operations of conversion and transmission are performed.

[0876] Step 9: Displaying the generated text

[0877] The user device analyzes the JSON data received from the server and displays the text at the specified location on the user interface. The input is the JSON data sent from the server, and the output is the text displayed on the user interface. For example, it performs specific operations to display on the screen using HTML or JavaScript.

[0878] Step 10: Verify the user

[0879] The user checks the text displayed on the screen of the user device and begins creative activities such as creating a new story based on that text. The input is the displayed text, and the output is the user's confirmation of the text and new inspiration based on it. Specific actions taken by the user to confirm the text are included.

[0880] (Application example 2)

[0881] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0882] Conventional text generation systems present generated text without considering the user's emotions, making it impossible to provide text that is appropriate to the user's situation or emotions. As a result, the inspiration generated by the text generation system does not fully support the user's creative activities, and there are limitations to improving the interactive customer experience in physical stores. Furthermore, it is difficult to provide information that is in line with the user's emotions, making it difficult to maximize customer purchasing motivation.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0884] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, means for recognizing the user's emotions, and means for adjusting the generated sentences based on the recognized emotions. This allows optimal sentences to be generated based on the user's emotions, making it possible to significantly improve the customer experience in interactive environments such as brick-and-mortar stores.

[0885] The "means for receiving a request for sentence generation from a user" is a means for a user to send a request for generating a new sentence to a server via an interface.

[0886] The "means for maintaining a database containing elements for sentence generation" refers to a means for managing and maintaining a database that stores elements such as subjects, verbs, and actions required for sentence generation.

[0887] The "means for randomly selecting an element from the database" refers to a means including an algorithm for randomly selecting from among the stored elements.

[0888] The "means for generating a sentence by combining selected elements" is a means for constructing a sentence by combining randomly selected elements.

[0889] The "means for presenting the generated text to the user" refers to a means for displaying the generated text on a user interface or transmitting it to the user's device.

[0890] The "means for recognizing the user's emotions" refers to a means that uses technology to analyze the user's facial expressions and voice data and infer the user's emotional state.

[0891] The "means for adjusting the generated sentence based on the recognized emotion" is a means for appropriately changing the content and tone of the generated sentence based on the user's emotion data.

[0892] System configuration

[0893] A system for implementing the present invention comprises the following major components:

[0894] 1. User terminal: A device that provides an interface for users to operate. Examples include smart glasses and head-mounted displays (HMDs).

[0895] 2. Server: A central computer that holds the database for text generation and processes requests.

[0896] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0897] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated sentences accordingly.

[0898] System Operation

[0899] The system generates sentences based on the user's emotions as follows:

[0900] User operations

[0901] The user requests the generation of a new sentence, for example by clicking a button on the interface of the smart glasses or HMD.

[0902] emotion recognition

[0903] The camera and microphone of smart glasses or HMDs equipped with an emotion engine capture the user's facial expressions and voice and recognize their emotions. The emotion engine uses facial recognition software and voice analysis software to analyze emotion data in real time.

[0904] Submitting a Request

[0905] A request for sentence generation along with emotion data is sent to the server using HTTP or WebSocket as the communication protocol.

[0906] Random selection and adjustment of elements

[0907] The server accesses the database and randomly selects elements such as subjects, verbs, and actions. It then adjusts the selected elements based on the recognized emotional data. If the emotional information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one.

[0908] Text generation and display

[0909] The server uses a generative AI model to generate text from the adjusted elements, which is then converted into a data format and sent to the user's smart glasses or HMD for display.

[0910] Specific examples

[0911] For example, when a customer picks up a new product in a physical store, the emotion engine analyzes the customer's facial expressions and voice to recognize their emotional state. Based on the recognized emotion, the server receives a request such as "I'd like to know more about this product," selects appropriate elements from the database, and generates a tailored sentence.

[0912] Prompt Sentence Examples

[0913] "Please briefly describe the characteristics of this product. The emotion is 'joy'."

[0914] Such a highly interactive system is expected to enable users to obtain optimal information that matches their emotions, stimulating their purchasing desire.

[0915] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0916] Step 1:

[0917] The user requests the generation of a new sentence. The user clicks a button on the interface of smart glasses or a head-mounted display (HMD) to generate the request. This operation generates request data. The input is the user's operation, and the output is the request data.

[0918] Step 2:

[0919] The camera and microphone of smart glasses or HMD are used to capture the user's facial expressions and voice to obtain emotion data. The input is the user's real-time facial expressions and voice, and the output is emotion information (e.g., joy, sadness, etc.). The emotion engine processes this and generates emotion data.

[0920] Step 3:

[0921] The acquired emotion data and request data are sent to the server. The communication protocol is HTTP or WebSocket. The input is emotion data and request data, and the output is the data sent to the server.

[0922] Step 4:

[0923] The server analyzes the received emotion data and request data and accesses the database. The input is emotion data and request data, and the output is a database query. The server randomly selects elements such as subject, verb, and action.

[0924] Step 5:

[0925] The server adjusts the selected elements based on the emotion. If the emotion information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one. The input is the selected elements and the emotion information, and the output is the adjusted elements.

[0926] Step 6:

[0927] The server generates a sentence using a generative AI model based on the adjusted elements. The input is the adjusted elements, and the output is the generated sentence. The generative AI model constructs the optimal sentence based on the prompt sentence.

[0928] Step 7:

[0929] The generated text is converted into a data format (e.g., JSON, XML) and sent to the user's smart glasses or HMD. The input is the generated text, and the output is the transmitted data. The server sends the data using HTTPS or WebSocket.

[0930] Step 8:

[0931] The user's device analyzes the received data and displays the generated text on the interface. The input is the transmitted data, and the output is the text presented to the user. The user can visually check this text and get inspiration.

[0932] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0933] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0934] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0935] [Third embodiment]

[0936] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0937] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0938] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0939] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0940] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0941] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0942] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0943] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0944] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0945] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0946] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0947] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0948] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain inspiration.

[0949] System configuration

[0950] The system consists of the following main components:

[0951] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[0952] 2. Server: A central computer that holds the database for text generation and processes requests.

[0953] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[0954] System Operation

[0955] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[0956] 1. User Action:

[0957] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[0958] 2. Submit your request:

[0959] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[0960] 3. Receiving and Processing Requests:

[0961] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[0962] 4. Random selection of elements:

[0963] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[0964] 5. Sentence generation:

[0965] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[0966] 6. Sending the generated text:

[0967] The server sends the generated text to the user's terminal, formatting the data so that it can be immediately understood by the user.

[0968] 7. Display of text:

[0969] The user terminal displays the received text on the user interface, allowing the user to engage in creative activities based on the displayed text.

[0970] Specific examples

[0971] As a concrete example, the following spear-like action is envisioned:

[0972] 1. User Action:

[0973] A user is looking for new story ideas and clicks the "Generate New Text" button.

[0974] 2. Submit your request:

[0975] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[0976] 3. Receiving and Processing Requests:

[0977] The server receives the HTTP request and initiates access to the database.

[0978] 4. Random selection of elements:

[0979] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[0980] 5. Sentence generation:

[0981] The server generates the sentence "The cat walks."

[0982] 6. Sending the generated text:

[0983] The server sends the generated text to the user's smartphone.

[0984] 7. Display of text:

[0985] The user's device displays the sentence "A cat walks" on the screen, and the user begins writing a new story based on that sentence.

[0986] In this way, the system helps the user find inspiration and supports creative activities.

[0987] The processing flow will be explained below.

[0988] Step 1:

[0989] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[0990] Step 2:

[0991] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[0992] Step 3:

[0993] The server receives a request from the terminal, which includes instructions for generating a sentence.

[0994] Step 4:

[0995] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[0996] Step 5:

[0997] The server accesses the database and reads the list of elements (subject, verb, action) for sentence generation.

[0998] Step 6:

[0999] The server randomly selects a subject from the subject list using a random number generation algorithm that ensures statistical randomness.

[1000] Step 7:

[1001] The server randomly selects a verb from the verb list, again using an algorithm that ensures statistical randomness.

[1002] Step 8:

[1003] The server randomly selects an action from the list of actions, again based on a random number generation algorithm.

[1004] Step 9:

[1005] The server combines the selected subject, verb, and action to generate a sentence. For example, the sentence "The cat walks."

[1006] Step 10:

[1007] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1008] Step 11:

[1009] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1010] Step 12:

[1011] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1012] Step 13:

[1013] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[1014] Through the above steps, this system provides users with new inspiration and supports their creative activities.

[1015] Example 1

[1016] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1017] Conventional text generation systems have not provided users with an efficient way to gain new inspiration. Specifically, they often lack an interface that allows users to easily generate text, or a function to instantly receive and display the generated text. A new system is needed to resolve these issues and support users' creative activities.

[1018] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1019] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for transmitting the generated sentences to the user's terminal, and means for displaying the generated sentences on the user's terminal, thereby enabling the user to quickly and easily generate inspirational sentences and start creative activities based on them.

[1020] A "user" is an individual or group who wishes to generate text and operates the system.

[1021] The "means for receiving a request" is a mechanism for transmitting a request from a user to a server and starting processing.

[1022] The "means for maintaining the database" is a system component that has the function of storing and managing elements necessary for sentence generation (subject, verb, action, etc.).

[1023] The "means for randomly selecting elements" is a mechanism for randomly extracting elements from the database.

[1024] The "means for generating a sentence" is a program that has the function of combining selected elements to construct a single sentence.

[1025] "Means for transmitting the generated text to the user's terminal" refers to a mechanism by which the server transmits the generated text to the user's device via a network.

[1026] The "means for displaying the generated text on the user's terminal" is a component that has the function of visually displaying the received text on the user interface.

[1027] A "subject" is a noun or pronoun that is the subject of an action in a sentence.

[1028] A "verb" is a word that expresses the action or state that the subject of a sentence performs.

[1029] An "action" is a specific action in a sentence in which a verb is performed by the subject.

[1030] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain new inspiration.

[1031] System configuration

[1032] The system consists of the following main components:

[1033] 1. User terminal: A device used by a user to perform operations, including computers, smartphones, tablets, etc.

[1034] 2. Server: This is the central system that holds the database for text generation and processes requests.

[1035] 3. Database: This is where the elements necessary for sentence generation (subject, verb, action) are stored.

[1036] System Operation

[1037] In this system, when a user wishes to create a new sentence, the following process is carried out:

[1038] User operations

[1039] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[1040] Submitting a Request

[1041] In response to a user's operation, the device sends an HTTP POST request to the server, which includes information such as the user ID and the request type.

[1042] Receiving and processing requests

[1043] The server receives the request, analyzes it, and prepares the necessary data based on the information contained in the request.

[1044] Random selection of elements

[1045] The server accesses the database and uses a random number generation algorithm to randomly select elements from the subject list, verb list, and action list.

[1046] Sentence generation

[1047] The server combines the selected elements to generate a sentence. For example, if the elements "cat," "ga," and "aruku" are selected, the sentence "The cat walks" is generated.

[1048] Sending generated text

[1049] The server sends the generated text to the user's device, often in JSON format.

[1050] Displaying text

[1051] The device displays the received text on the user interface, allowing users to create new stories and engage in creative activities based on the displayed text.

[1052] Specific examples

[1053] As a specific example, the following exchange is envisioned.

[1054] 1. User action: A user is looking for a new story idea and clicks the "Generate new text" button on their smartphone UI.

[1055] 2. Sending a request: The device catches the button click event and sends an HTTP POST request to the server.

[1056] 3. Receiving and processing the request: The server receives the request and parses it.

[1057] 4. Random selection of elements: The server obtains the subject "dog", the verb "ga", and the action "bark" randomly selected from the database.

[1058] 5. Sentence generation: The server generates the sentence "The dog is barking."

[1059] 6. Sending the generated text: The server sends the generated text to the terminal in JSON format.

[1060] 7. Displaying the text: The device displays the received text on the UI, and the user uses it as a reference to create a new story.

[1061] Prompt Sentence Examples

[1062] For example, if a user wants to generate text on a specific topic or setting, they might input the following prompt into a generative AI model:

[1063] "Generate the opening phrase of a new adventure story."

[1064] This system functions as a tool that allows users to easily obtain creative ideas and promotes inspiration.

[1065] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1066] Step 1:

[1067] The user clicks the "Generate new text" button on the user device interface. This operation initiates a request to generate text. The input is the user's click operation, and the output is the generation of the request. Specifically, the event listener of the user interface catches the click event.

[1068] Step 2:

[1069] The device catches the user's click event and creates an HTTP POST request. The request includes the user ID and request type. The input is the user's click operation, and the output is the request sent to the server. Specifically, the device program generates data in JSON format and prepares the HTTP request.

[1070] Step 3:

[1071] The server receives a request from the device. The server analyzes the request data and obtains the user ID and request type. The input is the HTTP request, and the output is the analyzed user ID and request type. Specifically, the server receives the request at an API endpoint using a framework such as Flask.

[1072] Step 4:

[1073] The server accesses the database and obtains a list of elements (subject, verb, action) required for sentence generation. The input is the parsed request information, and the output is a list of elements. Specifically, the server executes SQL queries or NoSQL read operations.

[1074] Step 5:

[1075] The server uses a random number generation algorithm to randomly select a subject, verb, and action from a database. The input is a list of elements, and the output is a randomly selected element. Specifically, the server selects a random element using a Python module such as the random module.

[1076] Step 6:

[1077] The server combines the selected elements to generate a sentence. The input is the randomly selected elements, and the output is the generated sentence. Specifically, the server combines the selected elements as a string to build a complete sentence.

[1078] Step 7:

[1079] The server sends the generated text in JSON format to the user's device. The input is the generated text, and the output is the transmitted data. Specifically, the server constructs an HTTP response and transmits it along with the data.

[1080] Step 8:

[1081] The terminal receives the response from the server and displays the generated text on the UI. The input is JSON format data sent from the server, and the output is the display on the UI. Specifically, the terminal analyzes the response data and displays the text on the user interface.

[1082] Through these steps, users can quickly and efficiently generate new inspirational writing.

[1083] (Application example 1)

[1084] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1085] In virtual stores, the product descriptions are fixed, which means that users are unable to get a fresh perspective when considering purchasing a product, making it difficult to stimulate their purchasing motivation. Furthermore, conventional systems lack a means to stimulate purchasing motivation by presenting randomly generated text to users.

[1086] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1087] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, and means for generating product descriptions and presenting them to the user in the virtual store. This makes it possible to provide fresh product information to users in the virtual store and increase their desire to purchase.

[1088] "Means for receiving a sentence generation request from a user" refers to an interface used to send a request to generate a new sentence to the server from a terminal operated by the user.

[1089] "Means for maintaining a database containing elements for sentence generation" refers to a system for saving a database for storing and managing elements such as subjects, verbs, and adjectives necessary for sentence generation.

[1090] The "means for randomly selecting an element from the database" refers to a processing mechanism for randomly selecting an element from among a plurality of elements stored in the database using a random number generation algorithm.

[1091] "Means for combining selected elements to generate a sentence" refers to an algorithm for combining randomly selected elements to generate a single meaningful sentence.

[1092] "Means for presenting the generated text to the user" refers to a system that displays the generated text on the screen or interface of the user's terminal.

[1093] "Means for generating product descriptions and presenting them to users in a virtual store" refers to a function for generating descriptions about products in a virtual store using random elements and displaying the descriptions to users.

[1094] "Subject, verb, and adjective" are the basic elements that make up a sentence. A subject refers to the subject of an action or state, a verb refers to that action or state, and an adjective refers to the word that modifies them.

[1095] "Means for transmitting to the user's terminal" refers to a communication system for transmitting the generated text via a network to a terminal such as a smartphone or tablet operated by the user.

[1096] The configuration and operation of a product description generation system for a virtual store will be described in detail below as an embodiment of the present invention. The system is composed of the following main components.

[1097] 1. User Device:

[1098] The user uses devices such as smartphones, tablets, and head-mounted displays as interfaces for operation. These devices communicate with a server via the Internet.

[1099] 2. Server:

[1100] This is the central computer that holds the database necessary for sentence generation and processes user requests. The sentence generation program is installed on the server, which is built using Python and the Flask framework.

[1101] 3. Database:

[1102] This is where the elements necessary for sentence generation (subject, verb, adjective) are stored. For example, a database such as SQLite is used.

[1103] System Operation

[1104] 1. User Action:

[1105] The user uses the virtual store interface to send a request to generate a new product description, for example by clicking a "Generate New Description" button.

[1106] 2. Submit your request:

[1107] The user device receives the button click event and sends an HTTP request to the server using HTTP / HTTPS as the communication protocol.

[1108] 3. Receiving and Processing Requests:

[1109] The server receives and analyzes the HTTP request, and prepares the necessary data based on the user information and request type included in the request.

[1110] 4. Random selection of elements:

[1111] The server accesses the database and randomly selects elements from the subject list, verb list, and adjective list using a random number generation algorithm.

[1112] 5. Sentence generation:

[1113] By combining the selected elements, the server generates a sentence, such as "This product is of the highest quality and will change your life."

[1114] 6. Sending the generated text:

[1115] The server sends the generated text to the user's terminal, where it is formatted so that the user can immediately understand it.

[1116] 7. Display of text:

[1117] The user terminal displays the received text on the user interface, allowing the user to gain a new perspective on the product based on the displayed text.

[1118] This makes it possible to provide users with fresh product information in the virtual store, thereby increasing their desire to purchase.

[1119] Use of concrete examples and prompts

[1120] For example, when a user clicks the "Generate new description" button in a virtual store, the server randomly selects elements from a database and generates a sentence like this:

[1121] "This product is of the highest quality and will change your life."

[1122] "Get this item now with your own unique design"

[1123] Example prompts to input to a generative AI model:

[1124] Please generate a new product description. Please randomly select and combine product-related elements (subject, adjective, verb) from the list below. The target product is a "smartphone."

[1125] Subject: "This product," "This item," "This product"

[1126] Adjectives: "Top quality," "Convenient," "Unique design"

[1127] Verbs: "is amazing," "will change your life," "get it now"

[1128] In this way, the system helps make the shopping experience in virtual stores more engaging and creative.

[1129] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1130] Step 1:

[1131] The user terminal clicks the "Generate new description" button through the virtual store interface.

[1132] Input: User clicks.

[1133] Data processing: Catching click events.

[1134] Output: HTTP request ready to send.

[1135] Specific operation: By clicking a button on the interface of the user terminal, a click event occurs, and the system is ready to request the server to generate a new sentence.

[1136] Step 2:

[1137] The user terminal sends an HTTP request to the server.

[1138] Input: The HTTP request to the server.

[1139] Data processing: Formatting the request data.

[1140] Output: Sending a request to the server.

[1141] Specific operation: Request data is formatted from the user terminal and sent to the server using the HTTP protocol.

[1142] Step 3:

[1143] The server receives an HTTP request from the user terminal.

[1144] Input: HTTP request from the user's device.

[1145] Data processing: Parsing the request.

[1146] Output: Confirm the request content and prepare to access the database.

[1147] Specific operation: The server analyzes the request data received, checks the required information and type of request, and prepares to access the database.

[1148] Step 4:

[1149] The server randomly selects elements necessary for sentence generation from the database.

[1150] Input: A request to access the database.

[1151] Data processing: selection of random elements.

[1152] Output: Random selection of subject, verb, and adjective.

[1153] What it does: The server accesses a database and uses a random number generation algorithm to randomly select a subject, verb, and adjective.

[1154] Step 5:

[1155] The server combines the selected elements to generate a sentence.

[1156] Input: Randomly selected elements (subject, verb, adjective).

[1157] Data processing: Combining elements and generating sentences.

[1158] Output: The generated sentence.

[1159] What it does: The server combines the selected elements to generate natural-sounding sentences, such as "This product is of the highest quality and will change your life."

[1160] Step 6:

[1161] The server transmits the generated text to the user terminal.

[1162] Input: The generated sentence.

[1163] Data processing: data formatting.

[1164] Output: Ready to send to user terminal.

[1165] Specific operation: The generated text is formatted and prepared for sending to the user's terminal as an HTTP response.

[1166] Step 7:

[1167] The user terminal displays the text received from the server.

[1168] Input: HTTP response from the server (generated text).

[1169] Data processing: Displaying text on the interface.

[1170] Output: The text displayed on the user interface.

[1171] Specific operation: The user device analyzes the text received from the server and displays it on the user interface. Using the displayed text, the user can gain a new perspective on the product.

[1172] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1173] The following describes in detail the configuration and operation of a system for implementing the present invention. The system supports a user in writing sentences to gain inspiration, recognizes the user's emotions, and adjusts the writing based on the emotions.

[1174] System configuration

[1175] The system consists of the following main components:

[1176] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[1177] 2. Server: A central computer that holds the database for text generation and processes requests.

[1178] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[1179] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly.

[1180] System Operation

[1181] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[1182] 1. User Action:

[1183] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[1184] 2. Submit your request:

[1185] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[1186] 3. Receiving and Processing Requests:

[1187] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[1188] 4. Emotion Recognition with Emotion Engine:

[1189] The server uses an emotion engine to recognize the user's emotional state, using technologies such as voice input and facial expression analysis.

[1190] 5. Random selection of elements:

[1191] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[1192] 6. Adjusting emotional factors:

[1193] The server adjusts the selected elements based on the emotional information obtained from the emotion engine, for example, choosing a positive action if the user is happy, or adjusting the tone appropriately if the user is sad.

[1194] 7. Sentence Generation:

[1195] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[1196] 8. Sending the generated text:

[1197] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1198] 9. Sending generated text:

[1199] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1200] 10. Display of text:

[1201] The user terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1202] 11. User Verification:

[1203] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[1204] Specific examples

[1205] As a concrete example, the following exchange can be envisioned:

[1206] 1. User Action:

[1207] A user is looking for new story ideas and clicks the "Generate New Text" button.

[1208] 2. Submit your request:

[1209] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[1210] 3. Receiving and Processing Requests:

[1211] The server receives the HTTP request and initiates access to the database.

[1212] 4. Emotion Recognition with Emotion Engine:

[1213] The server uses an emotion engine to recognize the user's emotions from their voice and facial expressions. For example, it determines that the user is happy.

[1214] 5. Random selection of elements:

[1215] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[1216] 6. Adjusting emotional factors:

[1217] The server adjusts the tone of the generated text to be more positive based on the emotional information.

[1218] 7. Sentence Generation:

[1219] The server generates the sentence "The cat is walking happily."

[1220] 8. Sending the generated text:

[1221] The server sends the generated text to the user's smartphone.

[1222] 9. Display of text:

[1223] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[1224] In this way, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[1225] The processing flow will be explained below.

[1226] Step 1:

[1227] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[1228] Step 2:

[1229] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[1230] Step 3:

[1231] The server receives a request from the terminal, which includes instructions for generating a sentence.

[1232] Step 4:

[1233] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[1234] Step 5:

[1235] The server launches an emotion engine to analyze the user's emotions, which uses voice input and facial expression data to determine the user's emotional state.

[1236] Step 6:

[1237] The emotion engine passes the obtained emotion information to the server. For example, the emotion information passed may indicate whether the user is "happy" or "sad."

[1238] Step 7:

[1239] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[1240] Step 8:

[1241] The server adjusts the selected elements based on the emotional information, for example, choosing positive actions if the user is happy, or generating text that matches the tone if the user is sad.

[1242] Step 9:

[1243] The server combines the selected elements to generate a sentence, such as "The cat is walking happily."

[1244] Step 10:

[1245] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1246] Step 11:

[1247] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1248] Step 12:

[1249] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1250] Step 13:

[1251] The user checks the text displayed on the device screen and can then engage in creative activities based on the displayed text.

[1252] Through the above steps, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[1253] Example 2

[1254] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1255] Conventional text generation systems simply combine randomly selected elements without considering the user's emotions, making it difficult to obtain inspiration appropriate to the user's emotional state. Furthermore, the generated text is not adjusted to reflect the user's current emotions, resulting in insufficient support for creative activities.

[1256] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1257] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for recognizing the user's emotion, means for adjusting the selected elements based on the recognized emotion, means for generating a sentence by combining the selected elements, and means for presenting the generated sentence to the user. This enables the generation of sentences suited to the user's emotional state, thereby more effectively supporting creative activities.

[1258] The "means for receiving a sentence generation request from a user" refers to the interface through which a user requests the generation of a new sentence and the method by which the system receives the request.

[1259] "Means for maintaining a database containing elements for sentence generation" refers to a database for storing and managing elements necessary for sentence generation, such as subjects, verbs, and actions, and a method for operating the database.

[1260] The "means for randomly selecting elements from said database" refers to algorithms and methods for randomly selecting from among elements stored in the database.

[1261] "Means for recognizing user emotions" refers to a system or technology that detects the user's emotional state from their voice, facial expressions, etc., and analyzes that information.

[1262] The "means for adjusting selected elements based on recognized emotions" are algorithms and methods for optimizing selected elements depending on the emotional state of the user.

[1263] The "means for generating a sentence by combining selected elements" refers to an algorithm and method for generating a sentence by combining randomly selected elements.

[1264] The "means for presenting the generated text to the user" refers to a method and system for transmitting the generated text to the user's terminal and displaying it.

[1265] The present invention provides a system for generating sentences based on the user's emotions and presenting the generated sentences to the user.

[1266] System configuration

[1267] The system consists of the following major hardware and software components:

[1268] 1. User terminal: Computer, smartphone, tablet, etc. A device that provides an interface for users to perform operations.

[1269] 2. Server: A central computer that processes requests for text generation and manages the database and emotion engine.

[1270] 3. Database: Stores the elements necessary for sentence generation (subject, verb, action).

[1271] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly. It can use Microsoft Azure's Emotion API or IBM Watson's Emotion Analysis API.

[1272] System Operation

[1273] The operation of the system is explained in the following sequence.

[1274] User operations

[1275] When a user wants to generate a new sentence, they click the "Generate New Sentence" button on the user device interface. This operation is performed by a button element on a web browser or a touch operation on a mobile app.

[1276] Submitting a Request

[1277] The user device catches the user's click event and sends an HTTP request to the server, which includes information such as the user ID and the request type.

[1278] Receiving and processing requests

[1279] The server analyzes the received HTTP request and prepares the necessary database operations and emotion recognition processes.

[1280] Emotion recognition by emotion engine

[1281] The server uses an emotion engine to recognize the user's emotional state, using voice input (microphone) and facial expression analysis (camera) technologies.

[1282] Random selection of elements

[1283] The server accesses a database and randomly selects an element from the subject, verb, and action list using a random number generation algorithm.

[1284] Adjusting elements based on emotions

[1285] The server adjusts randomly selected elements based on the emotion recognition results, for example, choosing a positive expression if the user is happy, or adjusting the appropriate tone if the user is sad.

[1286] Sentence generation

[1287] The server combines the selected and adjusted elements to generate a sentence, which is concisely expressed, for example, "The cat is walking happily."

[1288] Sending generated text

[1289] The server converts the generated text into JSON format and sends it to the user's terminal.

[1290] Displaying text

[1291] The user terminal analyzes the received data and displays the generated text on the user interface.

[1292] User Verification

[1293] The user checks the displayed text and starts a new creative activity based on that text.

[1294] Specific examples

[1295] As a concrete example, the following exchange can be envisioned:

[1296] 1. User operations

[1297] A user clicks the "Generate New Text" button for new story ideas.

[1298] 2. Submitting a Request

[1299] The user device catches the button click event and sends an HTTP request to the server, for example, sending a prompt such as "Please create a new sentence."

[1300] 3. Receiving and Processing Requests

[1301] The server receives the HTTP request and prepares to access the database.

[1302] 4. Emotion Recognition by Emotion Engine

[1303] The server uses an emotion engine to recognize emotions from the user's voice and facial expressions. For example, it determines that the user is happy.

[1304] 5. Random selection of elements

[1305] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[1306] 6. Adjusting emotional elements

[1307] Based on the emotional information, the server adds modifiers such as "happily" to adjust the tone of the sentence to a more positive one.

[1308] 7. Sentence Generation

[1309] The server generates the sentence "The cat is walking happily."

[1310] 8. Sending the generated text

[1311] The server transmits the generated text to the user terminal.

[1312] 9. Display of text

[1313] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[1314] In this way, the system can provide new inspiration while taking into account the user's emotions and support creative activities.

[1315] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1316] Program processing flow

[1317] Step 1: User interaction

[1318] The user clicks the "Create a new document" button in the user device interface. This requests the creation of a new document. The input is a specific user action (the button click), and the output is this action being sent to the server as an HTTP request.

[1319] Step 2: Submitting the request

[1320] The device catches the user's click event and sends an HTTP request to the server based on that information. This request includes the user ID, request type, etc. The specific input is the user's click event, and the output is the HTTP request sent to the server.

[1321] Step 3: Receiving and Processing the Request

[1322] The server receives an HTTP request from the device and extracts the user ID and request type from the request body. Based on the analysis results of this request, it performs the necessary database operations and prepares for emotion recognition. The input is the content of the HTTP request, and the output is the analyzed user ID and request type.

[1323] Step 4: Emotion Recognition with the Emotion Engine

[1324] The server uses an emotion engine (e.g., emotion recognition API) to recognize the user's emotional state. At this time, voice data and facial photo data are used as input, and the user's emotional state (joy, anger, sadness, etc.) is output as a result. Specifically, this includes the operation of sending voice input data and image data taken by a camera to the emotion engine and receiving the results of the recognized emotion.

[1325] Step 5: Random selection of elements

[1326] The server accesses the database and randomly selects elements from the subject list, verb list, and action list. The input is each list in the database, and the output is the selected subject, verb, and action elements. The specific operation of randomly selecting elements using a random number generation algorithm is included.

[1327] Step 6: Adjusting emotional elements

[1328] The server adjusts randomly selected elements based on the emotional information obtained from the emotion engine. The input is the recognized emotional state and the randomly selected elements, and based on these, it adds positive or negative modifiers and obtains the adjusted elements as the output. For example, it performs a specific action to select a modifier such as "happy."

[1329] Step 7: Sentence generation

[1330] The server generates sentences by combining the selected and adjusted elements. The input is the adjusted subject, verb, and action elements, and the output is a sentence that combines them. For example, it performs operations including string manipulation to generate the sentence "The cat is walking happily."

[1331] Step 8: Sending the generated text

[1332] The server converts the generated text into JSON format and sends it to the user's terminal. The input is the generated text, and the output is JSON format data sent to the terminal. The specific operations of conversion and transmission are performed.

[1333] Step 9: Displaying the generated text

[1334] The user device analyzes the JSON data received from the server and displays the text at the specified location on the user interface. The input is the JSON data sent from the server, and the output is the text displayed on the user interface. For example, it performs specific operations to display on the screen using HTML or JavaScript.

[1335] Step 10: Verify the user

[1336] The user checks the text displayed on the screen of the user device and begins creative activities such as creating a new story based on that text. The input is the displayed text, and the output is the user's confirmation of the text and new inspiration based on it. Specific actions taken by the user to confirm the text are included.

[1337] (Application example 2)

[1338] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1339] Conventional text generation systems present generated text without considering the user's emotions, making it impossible to provide text that is appropriate to the user's situation or emotions. As a result, the inspiration generated by the text generation system does not fully support the user's creative activities, and there are limitations to improving the interactive customer experience in physical stores. Furthermore, it is difficult to provide information that is in line with the user's emotions, making it difficult to maximize customer purchasing motivation.

[1340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1341] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, means for recognizing the user's emotions, and means for adjusting the generated sentences based on the recognized emotions. This allows optimal sentences to be generated based on the user's emotions, making it possible to significantly improve the customer experience in interactive environments such as brick-and-mortar stores.

[1342] The "means for receiving a request for sentence generation from a user" is a means for a user to send a request for generating a new sentence to a server via an interface.

[1343] The "means for maintaining a database containing elements for sentence generation" refers to a means for managing and maintaining a database that stores elements such as subjects, verbs, and actions required for sentence generation.

[1344] The "means for randomly selecting an element from the database" refers to a means including an algorithm for randomly selecting from among the stored elements.

[1345] The "means for generating a sentence by combining selected elements" is a means for constructing a sentence by combining randomly selected elements.

[1346] The "means for presenting the generated text to the user" refers to a means for displaying the generated text on a user interface or transmitting it to the user's device.

[1347] The "means for recognizing the user's emotions" refers to a means that uses technology to analyze the user's facial expressions and voice data and infer the user's emotional state.

[1348] The "means for adjusting the generated sentence based on the recognized emotion" is a means for appropriately changing the content and tone of the generated sentence based on the user's emotion data.

[1349] System configuration

[1350] A system for implementing the present invention comprises the following major components:

[1351] 1. User terminal: A device that provides an interface for users to operate. Examples include smart glasses and head-mounted displays (HMDs).

[1352] 2. Server: A central computer that holds the database for text generation and processes requests.

[1353] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[1354] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated sentences accordingly.

[1355] System Operation

[1356] The system generates sentences based on the user's emotions as follows:

[1357] User operations

[1358] The user requests the generation of a new sentence, for example by clicking a button on the interface of the smart glasses or HMD.

[1359] emotion recognition

[1360] The camera and microphone of smart glasses or HMDs equipped with an emotion engine capture the user's facial expressions and voice and recognize their emotions. The emotion engine uses facial recognition software and voice analysis software to analyze emotion data in real time.

[1361] Submitting a Request

[1362] A request for sentence generation along with emotion data is sent to the server using HTTP or WebSocket as the communication protocol.

[1363] Random selection and adjustment of elements

[1364] The server accesses the database and randomly selects elements such as subjects, verbs, and actions. It then adjusts the selected elements based on the recognized emotional data. If the emotional information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one.

[1365] Text generation and display

[1366] The server uses a generative AI model to generate text from the adjusted elements, which is then converted into a data format and sent to the user's smart glasses or HMD for display.

[1367] Specific examples

[1368] For example, when a customer picks up a new product in a physical store, the emotion engine analyzes the customer's facial expressions and voice to recognize their emotional state. Based on the recognized emotion, the server receives a request such as "I'd like to know more about this product," selects appropriate elements from the database, and generates a tailored sentence.

[1369] Prompt Sentence Examples

[1370] "Please briefly describe the characteristics of this product. The emotion is 'joy'."

[1371] Such a highly interactive system is expected to enable users to obtain optimal information that matches their emotions, stimulating their purchasing desire.

[1372] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1373] Step 1:

[1374] The user requests the generation of a new sentence. The user clicks a button on the interface of smart glasses or a head-mounted display (HMD) to generate the request. This operation generates request data. The input is the user's operation, and the output is the request data.

[1375] Step 2:

[1376] The camera and microphone of smart glasses or HMD are used to capture the user's facial expressions and voice to obtain emotion data. The input is the user's real-time facial expressions and voice, and the output is emotion information (e.g., joy, sadness, etc.). The emotion engine processes this and generates emotion data.

[1377] Step 3:

[1378] The acquired emotion data and request data are sent to the server. The communication protocol is HTTP or WebSocket. The input is emotion data and request data, and the output is the data sent to the server.

[1379] Step 4:

[1380] The server analyzes the received emotion data and request data and accesses the database. The input is emotion data and request data, and the output is a database query. The server randomly selects elements such as subject, verb, and action.

[1381] Step 5:

[1382] The server adjusts the selected elements based on the emotion. If the emotion information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one. The input is the selected elements and the emotion information, and the output is the adjusted elements.

[1383] Step 6:

[1384] The server generates a sentence using a generative AI model based on the adjusted elements. The input is the adjusted elements, and the output is the generated sentence. The generative AI model constructs the optimal sentence based on the prompt sentence.

[1385] Step 7:

[1386] The generated text is converted into a data format (e.g., JSON, XML) and sent to the user's smart glasses or HMD. The input is the generated text, and the output is the transmitted data. The server sends the data using HTTPS or WebSocket.

[1387] Step 8:

[1388] The user's device analyzes the received data and displays the generated text on the interface. The input is the transmitted data, and the output is the text presented to the user. The user can visually check this text and get inspiration.

[1389] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1390] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1391] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1392] [Fourth embodiment]

[1393] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1394] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1395] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1396] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1397] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1398] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1399] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1400] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1401] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1402] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1403] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1404] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1405] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1406] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain inspiration.

[1407] System configuration

[1408] The system consists of the following main components:

[1409] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[1410] 2. Server: A central computer that holds the database for text generation and processes requests.

[1411] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[1412] System Operation

[1413] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[1414] 1. User Action:

[1415] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[1416] 2. Submit your request:

[1417] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[1418] 3. Receiving and Processing Requests:

[1419] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[1420] 4. Random selection of elements:

[1421] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[1422] 5. Sentence generation:

[1423] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[1424] 6. Sending the generated text:

[1425] The server sends the generated text to the user's terminal, formatting the data so that it can be immediately understood by the user.

[1426] 7. Display of text:

[1427] The user terminal displays the received text on the user interface, allowing the user to engage in creative activities based on the displayed text.

[1428] Specific examples

[1429] As a concrete example, the following spear-like action is envisioned:

[1430] 1. User Action:

[1431] A user is looking for new story ideas and clicks the "Generate New Text" button.

[1432] 2. Submit your request:

[1433] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[1434] 3. Receiving and Processing Requests:

[1435] The server receives the HTTP request and initiates access to the database.

[1436] 4. Random selection of elements:

[1437] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[1438] 5. Sentence generation:

[1439] The server generates the sentence "The cat walks."

[1440] 6. Sending the generated text:

[1441] The server sends the generated text to the user's smartphone.

[1442] 7. Display of text:

[1443] The user's device displays the sentence "A cat walks" on the screen, and the user begins writing a new story based on that sentence.

[1444] In this way, the system helps the user find inspiration and supports creative activities.

[1445] The processing flow will be explained below.

[1446] Step 1:

[1447] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[1448] Step 2:

[1449] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[1450] Step 3:

[1451] The server receives a request from the terminal, which includes instructions for generating a sentence.

[1452] Step 4:

[1453] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[1454] Step 5:

[1455] The server accesses the database and reads the list of elements (subject, verb, action) for sentence generation.

[1456] Step 6:

[1457] The server randomly selects a subject from the subject list using a random number generation algorithm that ensures statistical randomness.

[1458] Step 7:

[1459] The server randomly selects a verb from the verb list, again using an algorithm that ensures statistical randomness.

[1460] Step 8:

[1461] The server randomly selects an action from the list of actions, again based on a random number generation algorithm.

[1462] Step 9:

[1463] The server combines the selected subject, verb, and action to generate a sentence. For example, the sentence "The cat walks."

[1464] Step 10:

[1465] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1466] Step 11:

[1467] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1468] Step 12:

[1469] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1470] Step 13:

[1471] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[1472] Through the above steps, this system provides users with new inspiration and supports their creative activities.

[1473] Example 1

[1474] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1475] Conventional text generation systems have not provided users with an efficient way to gain new inspiration. Specifically, they often lack an interface that allows users to easily generate text, or a function to instantly receive and display the generated text. A new system is needed to resolve these issues and support users' creative activities.

[1476] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1477] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for transmitting the generated sentences to the user's terminal, and means for displaying the generated sentences on the user's terminal, thereby enabling the user to quickly and easily generate inspirational sentences and start creative activities based on them.

[1478] A "user" is an individual or group who wishes to generate text and operates the system.

[1479] The "means for receiving a request" is a mechanism for transmitting a request from a user to a server and starting processing.

[1480] The "means for maintaining the database" is a system component that has the function of storing and managing elements necessary for sentence generation (subject, verb, action, etc.).

[1481] The "means for randomly selecting elements" is a mechanism for randomly extracting elements from the database.

[1482] The "means for generating a sentence" is a program that has the function of combining selected elements to construct a single sentence.

[1483] "Means for transmitting the generated text to the user's terminal" refers to a mechanism by which the server transmits the generated text to the user's device via a network.

[1484] The "means for displaying the generated text on the user's terminal" is a component that has the function of visually displaying the received text on the user interface.

[1485] A "subject" is a noun or pronoun that is the subject of an action in a sentence.

[1486] A "verb" is a word that expresses the action or state that the subject of a sentence performs.

[1487] An "action" is a specific action in a sentence in which a verb is performed by the subject.

[1488] The configuration and operation of a system for carrying out the present invention will be described in detail below. This system supports users in creating sentences to gain new inspiration.

[1489] System configuration

[1490] The system consists of the following main components:

[1491] 1. User terminal: A device used by a user to perform operations, including computers, smartphones, tablets, etc.

[1492] 2. Server: This is the central system that holds the database for text generation and processes requests.

[1493] 3. Database: This is where the elements necessary for sentence generation (subject, verb, action) are stored.

[1494] System Operation

[1495] In this system, when a user wishes to create a new sentence, the following process is carried out:

[1496] User operations

[1497] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[1498] Submitting a Request

[1499] In response to a user's operation, the device sends an HTTP POST request to the server, which includes information such as the user ID and the request type.

[1500] Receiving and processing requests

[1501] The server receives the request, analyzes it, and prepares the necessary data based on the information contained in the request.

[1502] Random selection of elements

[1503] The server accesses the database and uses a random number generation algorithm to randomly select elements from the subject list, verb list, and action list.

[1504] Sentence generation

[1505] The server combines the selected elements to generate a sentence. For example, if the elements "cat," "ga," and "aruku" are selected, the sentence "The cat walks" is generated.

[1506] Sending generated text

[1507] The server sends the generated text to the user's device, often in JSON format.

[1508] Displaying text

[1509] The device displays the received text on the user interface, allowing users to create new stories and engage in creative activities based on the displayed text.

[1510] Specific examples

[1511] As a specific example, the following exchange is envisioned.

[1512] 1. User action: A user is looking for a new story idea and clicks the "Generate new text" button on their smartphone UI.

[1513] 2. Sending a request: The device catches the button click event and sends an HTTP POST request to the server.

[1514] 3. Receiving and processing the request: The server receives the request and parses it.

[1515] 4. Random selection of elements: The server obtains the subject "dog", the verb "ga", and the action "bark" randomly selected from the database.

[1516] 5. Sentence generation: The server generates the sentence "The dog is barking."

[1517] 6. Sending the generated text: The server sends the generated text to the terminal in JSON format.

[1518] 7. Displaying the text: The device displays the received text on the UI, and the user uses it as a reference to create a new story.

[1519] Prompt Sentence Examples

[1520] For example, if a user wants to generate text on a specific topic or setting, they might input the following prompt into a generative AI model:

[1521] "Generate the opening phrase of a new adventure story."

[1522] This system functions as a tool that allows users to easily obtain creative ideas and promotes inspiration.

[1523] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1524] Step 1:

[1525] The user clicks the "Generate new text" button on the user device interface. This operation initiates a request to generate text. The input is the user's click operation, and the output is the generation of the request. Specifically, the event listener of the user interface catches the click event.

[1526] Step 2:

[1527] The device catches the user's click event and creates an HTTP POST request. The request includes the user ID and request type. The input is the user's click operation, and the output is the request sent to the server. Specifically, the device program generates data in JSON format and prepares the HTTP request.

[1528] Step 3:

[1529] The server receives a request from the device. The server analyzes the request data and obtains the user ID and request type. The input is the HTTP request, and the output is the analyzed user ID and request type. Specifically, the server receives the request at an API endpoint using a framework such as Flask.

[1530] Step 4:

[1531] The server accesses the database and obtains a list of elements (subject, verb, action) required for sentence generation. The input is the parsed request information, and the output is a list of elements. Specifically, the server executes SQL queries or NoSQL read operations.

[1532] Step 5:

[1533] The server uses a random number generation algorithm to randomly select a subject, verb, and action from a database. The input is a list of elements, and the output is a randomly selected element. Specifically, the server selects a random element using a Python module such as the random module.

[1534] Step 6:

[1535] The server combines the selected elements to generate a sentence. The input is the randomly selected elements, and the output is the generated sentence. Specifically, the server combines the selected elements as a string to build a complete sentence.

[1536] Step 7:

[1537] The server sends the generated text in JSON format to the user's device. The input is the generated text, and the output is the transmitted data. Specifically, the server constructs an HTTP response and transmits it along with the data.

[1538] Step 8:

[1539] The terminal receives the response from the server and displays the generated text on the UI. The input is JSON format data sent from the server, and the output is the display on the UI. Specifically, the terminal analyzes the response data and displays the text on the user interface.

[1540] Through these steps, users can quickly and efficiently generate new inspirational writing.

[1541] (Application example 1)

[1542] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1543] In virtual stores, the product descriptions are fixed, which means that users are unable to get a fresh perspective when considering purchasing a product, making it difficult to stimulate their purchasing motivation. Furthermore, conventional systems lack a means to stimulate purchasing motivation by presenting randomly generated text to users.

[1544] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1545] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, and means for generating product descriptions and presenting them to the user in the virtual store. This makes it possible to provide fresh product information to users in the virtual store and increase their desire to purchase.

[1546] "Means for receiving a sentence generation request from a user" refers to an interface used to send a request to generate a new sentence to the server from a terminal operated by the user.

[1547] "Means for maintaining a database containing elements for sentence generation" refers to a system for saving a database for storing and managing elements such as subjects, verbs, and adjectives necessary for sentence generation.

[1548] The "means for randomly selecting an element from the database" refers to a processing mechanism for randomly selecting an element from among a plurality of elements stored in the database using a random number generation algorithm.

[1549] "Means for combining selected elements to generate a sentence" refers to an algorithm for combining randomly selected elements to generate a single meaningful sentence.

[1550] "Means for presenting the generated text to the user" refers to a system that displays the generated text on the screen or interface of the user's terminal.

[1551] "Means for generating product descriptions and presenting them to users in a virtual store" refers to a function for generating descriptions about products in a virtual store using random elements and displaying the descriptions to users.

[1552] "Subject, verb, and adjective" are the basic elements that make up a sentence. A subject refers to the subject of an action or state, a verb refers to that action or state, and an adjective refers to the word that modifies them.

[1553] "Means for transmitting to the user's terminal" refers to a communication system for transmitting the generated text via a network to a terminal such as a smartphone or tablet operated by the user.

[1554] The configuration and operation of a product description generation system for a virtual store will be described in detail below as an embodiment of the present invention. The system is composed of the following main components.

[1555] 1. User Device:

[1556] The user uses devices such as smartphones, tablets, and head-mounted displays as interfaces for operation. These devices communicate with a server via the Internet.

[1557] 2. Server:

[1558] This is the central computer that holds the database necessary for sentence generation and processes user requests. The sentence generation program is installed on the server, which is built using Python and the Flask framework.

[1559] 3. Database:

[1560] This is where the elements necessary for sentence generation (subject, verb, adjective) are stored. For example, a database such as SQLite is used.

[1561] System Operation

[1562] 1. User Action:

[1563] The user uses the virtual store interface to send a request to generate a new product description, for example by clicking a "Generate New Description" button.

[1564] 2. Submit your request:

[1565] The user device receives the button click event and sends an HTTP request to the server using HTTP / HTTPS as the communication protocol.

[1566] 3. Receiving and Processing Requests:

[1567] The server receives and analyzes the HTTP request, and prepares the necessary data based on the user information and request type included in the request.

[1568] 4. Random selection of elements:

[1569] The server accesses the database and randomly selects elements from the subject list, verb list, and adjective list using a random number generation algorithm.

[1570] 5. Sentence generation:

[1571] By combining the selected elements, the server generates a sentence, such as "This product is of the highest quality and will change your life."

[1572] 6. Sending the generated text:

[1573] The server sends the generated text to the user's terminal, where it is formatted so that the user can immediately understand it.

[1574] 7. Display of text:

[1575] The user terminal displays the received text on the user interface, allowing the user to gain a new perspective on the product based on the displayed text.

[1576] This makes it possible to provide users with fresh product information in the virtual store, thereby increasing their desire to purchase.

[1577] Use of concrete examples and prompts

[1578] For example, when a user clicks the "Generate new description" button in a virtual store, the server randomly selects elements from a database and generates a sentence like this:

[1579] "This product is of the highest quality and will change your life."

[1580] "Get this item now with your own unique design"

[1581] Example prompts to input to a generative AI model:

[1582] Please generate a new product description. Please randomly select and combine product-related elements (subject, adjective, verb) from the list below. The target product is a "smartphone."

[1583] Subject: "This product," "This item," "This product"

[1584] Adjectives: "Top quality," "Convenient," "Unique design"

[1585] Verbs: "is amazing," "will change your life," "get it now"

[1586] In this way, the system helps make the shopping experience in virtual stores more engaging and creative.

[1587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1588] Step 1:

[1589] The user terminal clicks the "Generate new description" button through the virtual store interface.

[1590] Input: User clicks.

[1591] Data processing: Catching click events.

[1592] Output: HTTP request ready to send.

[1593] Specific operation: By clicking a button on the interface of the user terminal, a click event occurs, and the system is ready to request the server to generate a new sentence.

[1594] Step 2:

[1595] The user terminal sends an HTTP request to the server.

[1596] Input: The HTTP request to the server.

[1597] Data processing: Formatting the request data.

[1598] Output: Sending a request to the server.

[1599] Specific operation: Request data is formatted from the user terminal and sent to the server using the HTTP protocol.

[1600] Step 3:

[1601] The server receives an HTTP request from the user terminal.

[1602] Input: HTTP request from the user's device.

[1603] Data processing: Parsing the request.

[1604] Output: Confirm the request content and prepare to access the database.

[1605] Specific operation: The server analyzes the request data received, checks the required information and type of request, and prepares to access the database.

[1606] Step 4:

[1607] The server randomly selects elements necessary for sentence generation from the database.

[1608] Input: A request to access the database.

[1609] Data processing: selection of random elements.

[1610] Output: Random selection of subject, verb, and adjective.

[1611] What it does: The server accesses a database and uses a random number generation algorithm to randomly select a subject, verb, and adjective.

[1612] Step 5:

[1613] The server combines the selected elements to generate a sentence.

[1614] Input: Randomly selected elements (subject, verb, adjective).

[1615] Data processing: Combining elements and generating sentences.

[1616] Output: The generated sentence.

[1617] What it does: The server combines the selected elements to generate natural-sounding sentences, such as "This product is of the highest quality and will change your life."

[1618] Step 6:

[1619] The server transmits the generated text to the user terminal.

[1620] Input: The generated sentence.

[1621] Data processing: data formatting.

[1622] Output: Ready to send to user terminal.

[1623] Specific operation: The generated text is formatted and prepared for sending to the user's terminal as an HTTP response.

[1624] Step 7:

[1625] The user terminal displays the text received from the server.

[1626] Input: HTTP response from the server (generated text).

[1627] Data processing: Displaying text on the interface.

[1628] Output: The text displayed on the user interface.

[1629] Specific operation: The user device analyzes the text received from the server and displays it on the user interface. Using the displayed text, the user can gain a new perspective on the product.

[1630] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1631] The following describes in detail the configuration and operation of a system for implementing the present invention. The system supports a user in writing sentences to gain inspiration, recognizes the user's emotions, and adjusts the writing based on the emotions.

[1632] System configuration

[1633] The system consists of the following main components:

[1634] 1. User device: A computer, smartphone, tablet, etc. that provides an interface for users to perform operations.

[1635] 2. Server: A central computer that holds the database for text generation and processes requests.

[1636] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[1637] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly.

[1638] System Operation

[1639] In our system, when a user wants to generate a new sentence, the procedure is as follows:

[1640] 1. User Action:

[1641] The user requests the generation of a new sentence using the user terminal, for example by clicking a button on the user interface.

[1642] 2. Submit your request:

[1643] The user's device sends the user's request to the server, using a standard communication protocol such as HTTP or WebSocket.

[1644] 3. Receiving and Processing Requests:

[1645] The server receives and analyzes the request from the device, and prepares the necessary data based on the user information and request type included in the request.

[1646] 4. Emotion Recognition with Emotion Engine:

[1647] The server uses an emotion engine to recognize the user's emotional state, using technologies such as voice input and facial expression analysis.

[1648] 5. Random selection of elements:

[1649] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[1650] 6. Adjusting emotional factors:

[1651] The server adjusts the selected elements based on the emotional information obtained from the emotion engine, for example, choosing a positive action if the user is happy, or adjusting the tone appropriately if the user is sad.

[1652] 7. Sentence Generation:

[1653] The server generates a sentence by combining the selected elements. The generated sentence is in a concise form, such as "The cat walks."

[1654] 8. Sending the generated text:

[1655] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1656] 9. Sending generated text:

[1657] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1658] 10. Display of text:

[1659] The user terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1660] 11. User Verification:

[1661] The user checks the text displayed on the device screen and can then begin a new creative activity based on the generated text.

[1662] Specific examples

[1663] As a concrete example, the following exchange can be envisioned:

[1664] 1. User Action:

[1665] A user is looking for new story ideas and clicks the "Generate New Text" button.

[1666] 2. Submit your request:

[1667] The user device (e.g., smartphone) catches the button click event and sends an HTTP request to the server.

[1668] 3. Receiving and Processing Requests:

[1669] The server receives the HTTP request and initiates access to the database.

[1670] 4. Emotion Recognition with Emotion Engine:

[1671] The server uses an emotion engine to recognize the user's emotions from their voice and facial expressions. For example, it determines that the user is happy.

[1672] 5. Random selection of elements:

[1673] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[1674] 6. Adjusting emotional factors:

[1675] The server adjusts the tone of the generated text to be more positive based on the emotional information.

[1676] 7. Sentence Generation:

[1677] The server generates the sentence "The cat is walking happily."

[1678] 8. Sending the generated text:

[1679] The server sends the generated text to the user's smartphone.

[1680] 9. Display of text:

[1681] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[1682] In this way, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[1683] The processing flow will be explained below.

[1684] Step 1:

[1685] The user operates the terminal and clicks the "Generate new sentence" button. This operation generates a new sentence generation request.

[1686] Step 2:

[1687] The device detects user operations and sends that information to the server as a request. This request is sent using an HTTP request or WebSocket.

[1688] Step 3:

[1689] The server receives a request from the terminal, which includes instructions for generating a sentence.

[1690] Step 4:

[1691] The server parses the request and prepares to begin generating text, including setting up database access and initializing a random number generator for random selection.

[1692] Step 5:

[1693] The server launches an emotion engine to analyze the user's emotions, which uses voice input and facial expression data to determine the user's emotional state.

[1694] Step 6:

[1695] The emotion engine passes the obtained emotion information to the server. For example, the emotion information passed may indicate whether the user is "happy" or "sad."

[1696] Step 7:

[1697] The server accesses the database and randomly selects elements from the subject list, verb list, and action list using a random number generation algorithm.

[1698] Step 8:

[1699] The server adjusts the selected elements based on the emotional information, for example, choosing positive actions if the user is happy, or generating text that matches the tone if the user is sad.

[1700] Step 9:

[1701] The server combines the selected elements to generate a sentence, such as "The cat is walking happily."

[1702] Step 10:

[1703] The server converts the generated text into a data format (such as JSON or XML) and prepares it for transmission to the terminal.

[1704] Step 11:

[1705] The server sends the generated text to the terminal, also via HTTP or WebSocket.

[1706] Step 12:

[1707] The terminal analyzes the data received from the server and extracts the generated text, which is then displayed on the user interface.

[1708] Step 13:

[1709] The user checks the text displayed on the device screen and can then engage in creative activities based on the displayed text.

[1710] Through the above steps, the system provides new inspiration while taking into account the user's emotions, and supports creative activities.

[1711] Example 2

[1712] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1713] Conventional text generation systems simply combine randomly selected elements without considering the user's emotions, making it difficult to obtain inspiration appropriate to the user's emotional state. Furthermore, the generated text is not adjusted to reflect the user's current emotions, resulting in insufficient support for creative activities.

[1714] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1715] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for recognizing the user's emotion, means for adjusting the selected elements based on the recognized emotion, means for generating a sentence by combining the selected elements, and means for presenting the generated sentence to the user. This enables the generation of sentences suited to the user's emotional state, thereby more effectively supporting creative activities.

[1716] The "means for receiving a sentence generation request from a user" refers to the interface through which a user requests the generation of a new sentence and the method by which the system receives the request.

[1717] "Means for maintaining a database containing elements for sentence generation" refers to a database for storing and managing elements necessary for sentence generation, such as subjects, verbs, and actions, and a method for operating the database.

[1718] The "means for randomly selecting elements from said database" refers to algorithms and methods for randomly selecting from among elements stored in the database.

[1719] "Means for recognizing user emotions" refers to a system or technology that detects the user's emotional state from their voice, facial expressions, etc., and analyzes that information.

[1720] The "means for adjusting selected elements based on recognized emotions" are algorithms and methods for optimizing selected elements depending on the emotional state of the user.

[1721] The "means for generating a sentence by combining selected elements" refers to an algorithm and method for generating a sentence by combining randomly selected elements.

[1722] The "means for presenting the generated text to the user" refers to a method and system for transmitting the generated text to the user's terminal and displaying it.

[1723] The present invention provides a system for generating sentences based on the user's emotions and presenting the generated sentences to the user.

[1724] System configuration

[1725] The system consists of the following major hardware and software components:

[1726] 1. User terminal: Computer, smartphone, tablet, etc. A device that provides an interface for users to perform operations.

[1727] 2. Server: A central computer that processes requests for text generation and manages the database and emotion engine.

[1728] 3. Database: Stores the elements necessary for sentence generation (subject, verb, action).

[1729] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated text accordingly. It can use Microsoft Azure's Emotion API or IBM Watson's Emotion Analysis API.

[1730] System Operation

[1731] The operation of the system is explained in the following sequence.

[1732] User operations

[1733] When a user wants to generate a new sentence, they click the "Generate New Sentence" button on the user device interface. This operation is performed by a button element on a web browser or a touch operation on a mobile app.

[1734] Submitting a Request

[1735] The user device catches the user's click event and sends an HTTP request to the server, which includes information such as the user ID and the request type.

[1736] Receiving and processing requests

[1737] The server analyzes the received HTTP request and prepares the necessary database operations and emotion recognition processes.

[1738] Emotion recognition by emotion engine

[1739] The server uses an emotion engine to recognize the user's emotional state, using voice input (microphone) and facial expression analysis (camera) technologies.

[1740] Random selection of elements

[1741] The server accesses a database and randomly selects an element from the subject, verb, and action list using a random number generation algorithm.

[1742] Adjusting elements based on emotions

[1743] The server adjusts randomly selected elements based on the emotion recognition results, for example, choosing a positive expression if the user is happy, or adjusting the appropriate tone if the user is sad.

[1744] Sentence generation

[1745] The server combines the selected and adjusted elements to generate a sentence, which is concisely expressed, for example, "The cat is walking happily."

[1746] Sending generated text

[1747] The server converts the generated text into JSON format and sends it to the user's terminal.

[1748] Displaying text

[1749] The user terminal analyzes the received data and displays the generated text on the user interface.

[1750] User Verification

[1751] The user checks the displayed text and starts a new creative activity based on that text.

[1752] Specific examples

[1753] As a concrete example, the following exchange can be envisioned:

[1754] 1. User operations

[1755] A user clicks the "Generate New Text" button for new story ideas.

[1756] 2. Submitting a Request

[1757] The user device catches the button click event and sends an HTTP request to the server, for example, sending a prompt such as "Please create a new sentence."

[1758] 3. Receiving and Processing Requests

[1759] The server receives the HTTP request and prepares to access the database.

[1760] 4. Emotion Recognition by Emotion Engine

[1761] The server uses an emotion engine to recognize emotions from the user's voice and facial expressions. For example, it determines that the user is happy.

[1762] 5. Random selection of elements

[1763] The server randomly selects "cat" from the subject list, "ga" from the verb list, and "walk" from the action list.

[1764] 6. Adjusting emotional elements

[1765] Based on the emotional information, the server adds modifiers such as "happily" to adjust the tone of the sentence to a more positive one.

[1766] 7. Sentence Generation

[1767] The server generates the sentence "The cat is walking happily."

[1768] 8. Sending the generated text

[1769] The server transmits the generated text to the user terminal.

[1770] 9. Display of text

[1771] The user's device displays the sentence "The cat is walking happily" on the screen, and the user begins writing a new story based on that sentence.

[1772] In this way, the system can provide new inspiration while taking into account the user's emotions and support creative activities.

[1773] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1774] Program processing flow

[1775] Step 1: User interaction

[1776] The user clicks the "Create a new document" button in the user device interface. This requests the creation of a new document. The input is a specific user action (the button click), and the output is this action being sent to the server as an HTTP request.

[1777] Step 2: Submitting the request

[1778] The device catches the user's click event and sends an HTTP request to the server based on that information. This request includes the user ID, request type, etc. The specific input is the user's click event, and the output is the HTTP request sent to the server.

[1779] Step 3: Receiving and Processing the Request

[1780] The server receives an HTTP request from the device and extracts the user ID and request type from the request body. Based on the analysis results of this request, it performs the necessary database operations and prepares for emotion recognition. The input is the content of the HTTP request, and the output is the analyzed user ID and request type.

[1781] Step 4: Emotion Recognition with the Emotion Engine

[1782] The server uses an emotion engine (e.g., emotion recognition API) to recognize the user's emotional state. At this time, voice data and facial photo data are used as input, and the user's emotional state (joy, anger, sadness, etc.) is output as a result. Specifically, this includes the operation of sending voice input data and image data taken by a camera to the emotion engine and receiving the results of the recognized emotion.

[1783] Step 5: Random selection of elements

[1784] The server accesses the database and randomly selects elements from the subject list, verb list, and action list. The input is each list in the database, and the output is the selected subject, verb, and action elements. The specific operation of randomly selecting elements using a random number generation algorithm is included.

[1785] Step 6: Adjusting emotional elements

[1786] The server adjusts randomly selected elements based on the emotional information obtained from the emotion engine. The input is the recognized emotional state and the randomly selected elements, and based on these, it adds positive or negative modifiers and obtains the adjusted elements as the output. For example, it performs a specific action to select a modifier such as "happy."

[1787] Step 7: Sentence generation

[1788] The server generates sentences by combining the selected and adjusted elements. The input is the adjusted subject, verb, and action elements, and the output is a sentence that combines them. For example, it performs operations including string manipulation to generate the sentence "The cat is walking happily."

[1789] Step 8: Sending the generated text

[1790] The server converts the generated text into JSON format and sends it to the user's terminal. The input is the generated text, and the output is JSON format data sent to the terminal. The specific operations of conversion and transmission are performed.

[1791] Step 9: Displaying the generated text

[1792] The user device analyzes the JSON data received from the server and displays the text at the specified location on the user interface. The input is the JSON data sent from the server, and the output is the text displayed on the user interface. For example, it performs specific operations to display on the screen using HTML or JavaScript.

[1793] Step 10: Verify the user

[1794] The user checks the text displayed on the screen of the user device and begins creative activities such as creating a new story based on that text. The input is the displayed text, and the output is the user's confirmation of the text and new inspiration based on it. Specific actions taken by the user to confirm the text are included.

[1795] (Application example 2)

[1796] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1797] Conventional text generation systems present generated text without considering the user's emotions, making it impossible to provide text that is appropriate to the user's situation or emotions. As a result, the inspiration generated by the text generation system does not fully support the user's creative activities, and there are limitations to improving the interactive customer experience in physical stores. Furthermore, it is difficult to provide information that is in line with the user's emotions, making it difficult to maximize customer purchasing motivation.

[1798] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1799] In this invention, the server includes means for receiving a sentence generation request from a user, means for maintaining a database containing elements for sentence generation, means for randomly selecting elements from the database, means for generating sentences by combining the selected elements, means for presenting the generated sentences to the user, means for recognizing the user's emotions, and means for adjusting the generated sentences based on the recognized emotions. This allows optimal sentences to be generated based on the user's emotions, making it possible to significantly improve the customer experience in interactive environments such as brick-and-mortar stores.

[1800] The "means for receiving a request for sentence generation from a user" is a means for a user to send a request for generating a new sentence to a server via an interface.

[1801] The "means for maintaining a database containing elements for sentence generation" refers to a means for managing and maintaining a database that stores elements such as subjects, verbs, and actions required for sentence generation.

[1802] The "means for randomly selecting an element from the database" refers to a means including an algorithm for randomly selecting from among the stored elements.

[1803] The "means for generating a sentence by combining selected elements" is a means for constructing a sentence by combining randomly selected elements.

[1804] The "means for presenting the generated text to the user" refers to a means for displaying the generated text on a user interface or transmitting it to the user's device.

[1805] The "means for recognizing the user's emotions" refers to a means that uses technology to analyze the user's facial expressions and voice data and infer the user's emotional state.

[1806] The "means for adjusting the generated sentence based on the recognized emotion" is a means for appropriately changing the content and tone of the generated sentence based on the user's emotion data.

[1807] System configuration

[1808] A system for implementing the present invention comprises the following major components:

[1809] 1. User terminal: A device that provides an interface for users to operate. Examples include smart glasses and head-mounted displays (HMDs).

[1810] 2. Server: A central computer that holds the database for text generation and processes requests.

[1811] 3. Database: A place to store the elements necessary for sentence generation (subject, verb, action).

[1812] 4. Emotion engine: A module that recognizes the user's emotions and adjusts the generated sentences accordingly.

[1813] System Operation

[1814] The system generates sentences based on the user's emotions as follows:

[1815] User operations

[1816] The user requests the generation of a new sentence, for example by clicking a button on the interface of the smart glasses or HMD.

[1817] emotion recognition

[1818] The camera and microphone of smart glasses or HMDs equipped with an emotion engine capture the user's facial expressions and voice and recognize their emotions. The emotion engine uses facial recognition software and voice analysis software to analyze emotion data in real time.

[1819] Submitting a Request

[1820] A request for sentence generation along with emotion data is sent to the server using HTTP or WebSocket as the communication protocol.

[1821] Random selection and adjustment of elements

[1822] The server accesses the database and randomly selects elements such as subjects, verbs, and actions. It then adjusts the selected elements based on the recognized emotional data. If the emotional information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one.

[1823] Text generation and display

[1824] The server uses a generative AI model to generate text from the adjusted elements, which is then converted into a data format and sent to the user's smart glasses or HMD for display.

[1825] Specific examples

[1826] For example, when a customer picks up a new product in a physical store, the emotion engine analyzes the customer's facial expressions and voice to recognize their emotional state. Based on the recognized emotion, the server receives a request such as "I'd like to know more about this product," selects appropriate elements from the database, and generates a tailored sentence.

[1827] Prompt Sentence Examples

[1828] "Please briefly describe the characteristics of this product. The emotion is 'joy'."

[1829] Such a highly interactive system is expected to enable users to obtain optimal information that matches their emotions, stimulating their purchasing desire.

[1830] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1831] Step 1:

[1832] The user requests the generation of a new sentence. The user clicks a button on the interface of smart glasses or a head-mounted display (HMD) to generate the request. This operation generates request data. The input is the user's operation, and the output is the request data.

[1833] Step 2:

[1834] The camera and microphone of smart glasses or HMD are used to capture the user's facial expressions and voice to obtain emotion data. The input is the user's real-time facial expressions and voice, and the output is emotion information (e.g., joy, sadness, etc.). The emotion engine processes this and generates emotion data.

[1835] Step 3:

[1836] The acquired emotion data and request data are sent to the server. The communication protocol is HTTP or WebSocket. The input is emotion data and request data, and the output is the data sent to the server.

[1837] Step 4:

[1838] The server analyzes the received emotion data and request data and accesses the database. The input is emotion data and request data, and the output is a database query. The server randomly selects elements such as subject, verb, and action.

[1839] Step 5:

[1840] The server adjusts the selected elements based on the emotion. If the emotion information is positive, the tone of the sentence is adjusted to a positive one, and if it is negative, the tone is adjusted to a harmonious one. The input is the selected elements and the emotion information, and the output is the adjusted elements.

[1841] Step 6:

[1842] The server generates a sentence using a generative AI model based on the adjusted elements. The input is the adjusted elements, and the output is the generated sentence. The generative AI model constructs the optimal sentence based on the prompt sentence.

[1843] Step 7:

[1844] The generated text is converted into a data format (e.g., JSON, XML) and sent to the user's smart glasses or HMD. The input is the generated text, and the output is the transmitted data. The server sends the data using HTTPS or WebSocket.

[1845] Step 8:

[1846] The user's device analyzes the received data and displays the generated text on the interface. The input is the transmitted data, and the output is the text presented to the user. The user can visually check this text and get inspiration.

[1847] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1848] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1849] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1850] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1851] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1852] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1853] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1854] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1855] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1856] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1857] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1858] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1859] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1860] 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.

[1861] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1862] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1863] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1864] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1865] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1866] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1867] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1868] The following is further disclosed regarding the above embodiment.

[1869] (Claim 1)

[1870] means for receiving a sentence generation request from a user;

[1871] means for maintaining a database containing elements for sentence generation;

[1872] means for randomly selecting elements from said database;

[1873] means for combining the selected elements to generate a sentence;

[1874] means for presenting the generated sentence to a user;

[1875] A system including:

[1876] (Claim 2)

[1877] 10. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an action.

[1878] (Claim 3)

[1879] 10. The system of claim 1, further comprising means for transmitting the generated sentence to a user terminal.

[1880] "Example 1"

[1881] (Claim 1)

[1882] means for receiving a sentence generation request from a user;

[1883] means for maintaining a database containing elements for sentence generation;

[1884] means for randomly selecting elements from said database;

[1885] means for combining the selected elements to generate a sentence;

[1886] means for transmitting the generated text to a user's terminal;

[1887] means for displaying the generated text on a user's terminal;

[1888] A system including:

[1889] (Claim 2)

[1890] 10. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an action.

[1891] (Claim 3)

[1892] 10. The system of claim 1, wherein the generated sentence is displayed through a user interface.

[1893] "Application Example 1"

[1894] (Claim 1)

[1895] means for receiving a sentence generation request from a user;

[1896] means for maintaining a database containing elements for sentence generation;

[1897] means for randomly selecting elements from said database;

[1898] means for combining the selected elements to generate a sentence;

[1899] means for presenting the generated sentence to a user;

[1900] The system further includes means for generating product descriptions and presenting them to the user within the virtual store.

[1901] (Claim 2)

[1902] 10. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an adjective.

[1903] (Claim 3)

[1904] 10. The system of claim 1, further comprising means for transmitting the generated sentence to a user terminal.

[1905] "Example 2: Combining Emotion Engines"

[1906] (Claim 1)

[1907] means for receiving a sentence generation request from a user;

[1908] means for maintaining a database containing elements for sentence generation;

[1909] means for randomly selecting elements from said database;

[1910] means for recognizing a user's emotion;

[1911] means for adjusting the selected elements based on the recognized emotion;

[1912] means for combining the selected elements to generate a sentence;

[1913] means for presenting the generated sentence to a user;

[1914] A system including:

[1915] (Claim 2)

[1916] 10. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an action.

[1917] (Claim 3)

[1918] 10. The system of claim 1, further comprising means for transmitting the generated sentence to a user terminal.

[1919] "Application example 2 when combining emotion engines"

[1920] (Claim 1)

[1921] means for receiving a sentence generation request from a user;

[1922] means for maintaining a database containing elements for sentence generation;

[1923] means for randomly selecting elements from said database;

[1924] means for combining the selected elements to generate a sentence;

[1925] means for presenting the generated sentence to a user;

[1926] means for recognizing a user's emotion;

[1927] a means for adjusting the generated text based on the recognized sentiment;

[1928] A system including:

[1929] (Claim 2)

[1930] 10. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an action.

[1931] (Claim 3)

[1932] 10. The system of claim 1, further comprising means for transmitting the generated sentence to a user terminal. [Explanation of symbols]

[1933] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a sentence generation request from a user; means for maintaining a database containing elements for sentence generation; means for randomly selecting elements from said database; means for combining the selected elements to generate a sentence; means for presenting the generated sentence to a user; A system including:

2. 2. The system of claim 1, wherein the randomly selected elements include a subject, a verb, and an action.

3. 2. The system of claim 1, further comprising means for transmitting the generated sentence to a user terminal.

Images