system

Abstract

We provide the system. [Solution] A means for receiving input string data, A means for analyzing the aforementioned string data and generating visual data suitable for the string data, Means for adding string information based on the string data to the aforementioned visual data, Means for transmitting the aforementioned visual data and assigned string information to a communication terminal, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern communication, stamps are used as a means for users to visually express the intention and emotion of a character string. However, existing stamps have the problem that they cannot fully convey various expressions and individual intentions. In addition, there is a problem that the process for ordinary users to generate their own stamps has a high technical barrier and cannot be easily implemented.

Means for Solving the Problems

[0005] To solve this problem, the present invention provides a system that analyzes input string data and automatically generates visual data appropriate to the string. First, it receives string data, then analyzes the data and generates visual data based on its meaning and emotion. Furthermore, by providing means for attaching string information to the generated visual data and transmitting it to a communication terminal, the system enables users to easily create their own stamps and realize emotionally rich communication.

[0006] "String data" refers to the entered text information, and its content represents the message that the user wants to generate or send.

[0007] "Visual data" refers to image files and graphical representations generated based on text data, and is a means for users to communicate information visually.

[0008] "String information" refers to text elements added to visual data, serving to convey the user's intent as specific messages or captions.

[0009] A "communication terminal" refers to a device with communication capabilities that users typically use, such as a smartphone or tablet.

[0010] "Analysis" refers to a series of processes performed to understand input string data and determine its meaning and sentiment. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface that includes a communication processor and 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), or Bluetooth (registered trademark), etc.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] This invention provides a system that includes a process for generating visual data from a user inputting a string of characters. First, the user inputs a string of characters they want to convert into a stamp within a specific application using their usual communication terminal. This input string data is then transmitted from the terminal to the server.

[0033] The server uses natural language processing techniques to analyze the received string data. This analysis determines the meaning and emotion of the string and decides on the optimal representation as visual data. Next, the server uses a generative AI engine to automatically generate visual data based on the analysis results, that is, a graphical image that aligns with the user's intent.

[0034] The generated visual data is accompanied by the original text information as a caption. This allows the visual data to function as a message to the user. This visual data and text information are sent from the server to the communication terminal and displayed on the user's device.

[0035] For example, if a user enters the string "Thank you for your hard work!", this string is analyzed by the server and recognized as an expression of gratitude. Based on this, the server generates an image of a cat that gives a relaxed impression and creates a stamp with "Thank you for your hard work!" as the caption. Finally, this completed stamp is displayed on the device, and the user can easily use this stamp to communicate.

[0036] The following describes the processing flow.

[0037] Step 1:

[0038] The user opens a dedicated application on their communication terminal and enters a string of text into the text input field for stamp generation. Once the input is complete, the user presses the send button to begin sending the text data.

[0039] Step 2:

[0040] The terminal retrieves the string data entered by the user and generates an HTTP request to send it to the server. This request includes the string data and user identification information.

[0041] Step 3:

[0042] The server receives an HTTP request sent from the terminal and passes the string data contained within it to a natural language processing engine. Here, the server analyzes the meaning and sentiment of the input string and determines how best to represent it visually.

[0043] Step 4:

[0044] Based on the analyzed information, the server uses an image generation AI to generate visual data corresponding to the text. This includes applying themes and styles appropriate to the content of the text.

[0045] Step 5:

[0046] The server adds the user-entered text as a caption to the generated visual data. This caption is then overlaid and integrated with the image.

[0047] Step 6:

[0048] The server compresses and optimizes the completed stamp, then sends it to the terminal as an HTTP response. This response includes visual data and necessary metadata.

[0049] Step 7:

[0050] The device analyzes the stamp data received from the server and displays it within the application. The user can review the displayed stamps, select them as needed, and send them as messages.

[0051] (Example 1)

[0052] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0053] There is a need to represent information content simply and intuitively as visual information, enabling users to effectively utilize it for communication. However, conventional technologies have had the problem of difficulty in accurately analyzing the emotions and meaning of information content and automatically generating the most suitable visual information. In particular, when the transmitted information content contains a variety of emotions, the representation may be inappropriate, and the user's intentions may not be accurately conveyed.

[0054] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0055] In this invention, the server includes means for receiving input information content, means for analyzing the information content and generating visual information suitable for the information content, and means for adding information based on the information content to the visual information. This makes it possible to automatically generate appropriate visual information that takes into account the emotions and meanings of the information content entered by the user, and to easily use it for communication.

[0056] "Inputted information content" refers to strings of characters or data that the user provides to the system through the information processing device.

[0057] "Means of receiving" refers to the functions and devices that an information processing device uses to retrieve the input information content from a server.

[0058] "Means for analyzing and generating appropriate visual information" refers to methods and devices for understanding the meaning and emotions of input information and automatically creating corresponding visual data.

[0059] "Means for adding information based on visual information" refers to functions or devices used to add text or captions related to the original information content to generated visual information.

[0060] "Means of transmitting to an information processing device" refers to communication technologies and devices for transferring generated visual information and associated information to the user's information processing device.

[0061] This invention is a system that automatically generates visual information based on information input by a user using an information processing device and provides it in a manner that aligns with the user's intentions. Specific examples of hardware and software are provided below.

[0062] The user launches the application from a communication device and inputs the information they want to convert into the system. For example, the user might input the string "thank you." In this case, the communication device used could be a smartphone or a personal computer.

[0063] The terminal transmits the input information to the server via the internet. The server uses a natural language processing engine to analyze the received information. Examples of natural language processing technologies used here include commercial APIs and proprietary analysis algorithms. The server organizes the meaning and sentiment of the information and passes appropriate instructions to the generating AI model to generate visual information based on that.

[0064] Generative AI models could include algorithms and services like DALL·E and Midjourney, which generate images according to specified conditions. The server passes prompts to the generative AI model, which then generates visual information. A concrete example of such a prompt might be, "Generate a landscape expressing gratitude."

[0065] The server adds the input information as a caption to the generated visual information. This process associates the visual information with the original information content, resulting in a visual representation of the user's intent.

[0066] Finally, the server compresses this visual information and the associated information and sends it back to the communication terminal. The terminal displays the received data, and the user can easily use the completed visual information for communication. In this way, the aim is to significantly improve the user experience by conveying the meaning and emotions of the information content visually and intuitively.

[0067] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0068] Step 1:

[0069] The user launches the application using a communication terminal and enters the string they want to convert into a stamp. For example, they might enter the string "Hello". The terminal uses a touchscreen or keyboard for input, and the entered string is immediately visible within the application. The string data is then passed to the next processing step as output.

[0070] Step 2:

[0071] The terminal sends the entered string data to the server. This process involves data transmission via an internet connection. Specifically, an HTTP request is used, and the string data arrives at the server. The output of this step is the string data received by the server.

[0072] Step 3:

[0073] The server analyzes the received string data. Using a natural language processing engine, it extracts the meaning and sentiment of the string. For example, in the case of "hello," the meaning of friendliness and greeting is extracted. This analysis utilizes a vocabulary sentiment evaluation database, and the analysis results are passed to a generative AI model as output.

[0074] Step 4:

[0075] The server uses a generative AI model to generate visual information based on the analysis results. Specifically, it passes a prompt message to a generative AI model such as DALL·E. This prompt might be in the format of, for example, "Generate a friendly morning scene." The model generates an image, which is then returned to the server.

[0076] Step 5:

[0077] The server adds the original text information as a caption to the generated visual information. This allows the visual information to retain the meaning of the corresponding text. Specifically, it overlays the text onto the image. The output is data that combines the visual information and the text information.

[0078] Step 6:

[0079] The server compresses visual information and captions to improve communication efficiency. The compressed data is sent back to the terminal. The data is usually compressed using formats such as JPEG. The output is compressed data.

[0080] Step 7:

[0081] The device decompresses the received compressed data and displays it within the application. The user can then check the displayed stamps and see if they are ready to use. For example, generated stamps can be easily used for communication by pasting them into a chat screen. The output is the stamps displayed on the user's screen.

[0082] (Application Example 1)

[0083] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0084] In commercial facilities, traditional methods make it difficult to visually capture customer reviews and opinions, and to share them with other customers and staff. Therefore, new methods are needed to improve customer satisfaction and revitalize communication.

[0085] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0086] In this invention, the server includes means for receiving input string information, means for analyzing the string information and generating appropriate visual information, and means for adding linguistic information based on the visual information. This makes it possible to display the string information entered by the customer as visual information on a display device in a commercial facility or on the customer's personal device and share it with others.

[0087] "String information" refers to the text data entered by the user, and it forms the basis of the generated visual information.

[0088] "Visual information" refers to graphical images generated based on analyzed string information, intended for display in commercial facilities and on personal devices.

[0089] "Linguistic information" refers to text displayed alongside visual information, intended to clearly convey the user's intent or message.

[0090] "Information device" refers to electronic devices that operate on the server or client side and have functions for sending, receiving, and displaying data.

[0091] A "display device" is a device used to actually display visual information, and includes in-store displays and personal smartphones.

[0092] To realize this invention, a system is needed for use in commercial facilities and other applicable locations. This system generates visual information based on string information entered by the user and displays it on a display device.

[0093] First, the user inputs text information into a dedicated application using a device such as a smartphone or tablet. This text information specifically describes the user's thoughts and opinions. This text information is then transmitted to a server via the internet. The server uses natural language processing software, such as Google® NLP API, to perform sentiment analysis on the text information. Based on the analysis results, a generative AI model, such as Stable Diffusion, is used to generate visual information that reflects the user's intent. The generated visual information is then accompanied by the original text information as a caption.

[0094] This visual and linguistic information is transmitted to and displayed on display devices such as screens within commercial facilities, as well as on the user's smartphone. This makes it possible to share user feedback with other customers and staff, thereby stimulating communication.

[0095] For example, if a user enters the text "Today's meal was amazing!" at a restaurant, this information is analyzed by the server, and an image reflecting feelings of "deliciousness" and "satisfaction" is generated, such as a graphic of a chef smiling and holding a dish. This visual information is then captioned "Today's meal was amazing!" and displayed on the screen.

[0096] An example of a prompt message is: "User input: Today's meal was amazing! → Scene: Smiling chef, Expression: Happy." In this way, the present invention improves customer engagement in commercial facilities.

[0097] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0098] Step 1:

[0099] Users input text information into a smartphone or tablet application. During this input stage, specific feedback and comments from the user are described. This text information becomes the input data for the next processing step.

[0100] Step 2:

[0101] The terminal sends the entered string information to the server. This transmission process uses the HTTP protocol, including the string information in the request and sending it over the network. This string information becomes the data input for natural language processing on the server side.

[0102] Step 3:

[0103] The server performs sentiment analysis on received string information using natural language processing software such as the Google NLP API. The input for the analysis is string information, and the output is evaluation data of the emotions and intentions contained in the text. Through this analysis, the emotions contained in the string are quantified using data calculations.

[0104] Step 4:

[0105] The server uses the analysis results to send prompt sentences to generative AI models such as Stable Diffusion, which then generate visual information. These prompt sentences are based on the "sentiment of the user input sentence" and include instructions for forming a concrete image. The input is the data from the analysis results, and the output is the generated graphical image.

[0106] Step 5:

[0107] The server adds the original text information as a caption to the generated visual information. The input consists of visual information and text information, and the output is the completed image data with the caption. This process enhances the visual representation of the user's text information.

[0108] Step 6:

[0109] The completed visual information is transmitted from the server to the user's terminal or a display in a commercial facility. Here, the image data is compressed to improve bandwidth efficiency. The input is visual information with captions, and the output is the display of that visual information on a display device.

[0110] Step 7:

[0111] On a terminal or display device, users, other customers, and staff can view and share visual information. At this stage, emotions gained through visual information can be shared with others, improving customer engagement.

[0112] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0113] The system of the present invention provides a stamp generation function based on user string data and incorporates an emotion engine to recognize the user's emotions and improve the quality of the stamps. The user launches the application using a communication terminal and inputs a string that expresses some emotion. This string and sensor information from the terminal are simultaneously transmitted to the server.

[0114] The server first passes the string data to a natural language processing engine, which analyzes its content to understand its meaning and context. Simultaneously, the emotion engine uses data collected from the user's device (e.g., camera and microphone data) to analyze the user's real-time emotions. This analysis allows the system to understand the user's emotions.

[0115] Based on the analysis results, the server considers the meaning of the string data and the user's emotions to determine the stamp's theme and visual style. The generation AI engine receives this data and generates visual data that harmonizes with the string data and emotions. At this time, the stamp's color scheme and atmosphere are adjusted according to the user's feelings as determined by the emotion engine.

[0116] For example, if a user smiles while typing the string "Hello!", the emotion engine recognizes the user's positive emotion, and the server determines a bright and friendly stamp design to match. It then generates visual data with the text "Hello!" added as a caption, compresses and transmits it, and displays it on the communication terminal.

[0117] In this way, the system can provide a more personalized and emotionally rich communication tool based on the user's text data and emotions.

[0118] The following describes the processing flow.

[0119] Step 1:

[0120] The user opens the application on their communication device and enters the text they want to turn into a stamp. The device's sensors (camera, microphone, etc.) also activate to collect the user's facial expressions and voice in real time.

[0121] Step 2:

[0122] The device sends input string data and emotion-related data obtained from sensors to the server. Encrypted HTTP requests are used for transmission to ensure secure data delivery.

[0123] Step 3:

[0124] The server analyzes the received string data using a natural language processing engine to analyze the content and emotion of the string, while simultaneously analyzing data from sensors using an emotion engine to estimate the user's emotional state.

[0125] Step 4:

[0126] The server combines the meaning of the text with emotional information obtained from the sentiment engine to determine the theme and style of the visual data. In this step, for example, if the user appears happy, it will select a design with bright and warm color tones.

[0127] Step 5:

[0128] The server uses a generation AI engine based on a determined theme to generate customized visual data. This data is accompanied by text information that reflects the user's emotions as captions.

[0129] Step 6:

[0130] The server compresses the generated visual data and sends it to the communication terminal along with emotional information. Data compression reduces transmission time and makes efficient use of network bandwidth.

[0131] Step 7:

[0132] The device decompresses and displays the received stamp data, allowing the user to easily select and add stamps to the conversation. The user can then review the final stamps and use them as appropriate.

[0133] (Example 2)

[0134] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0135] In modern communication, it is difficult to accurately convey emotions and nuances through mere text information. Therefore, there is a demand for more personal and emotionally rich communication methods. Traditional stamps and emojis have limited options and do not adequately support the creation of visuals that accurately reflect the user's psychological state.

[0136] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0137] In this invention, the server includes means for receiving input information, means for analyzing the information and generating visual information based on the information, and means for analyzing the user's psychological state. This enables the generation of personalized visual information that responds to the user's emotions and context, thereby facilitating richer communication.

[0138] "Information" refers to string data entered by the user and any accompanying information.

[0139] "Visual information" refers to visual materials generated based on information entered by the user.

[0140] "Character information" refers to the input string data itself, specifically the characters attached to the visual information.

[0141] "Communication device" refers to a terminal device used by a user that has the function of receiving generated visual and textual information.

[0142] "User's psychological state" refers to the emotions and nuances analyzed from the input information and accompanying information.

[0143] "Means of analysis" refers to methods and technologies for analyzing information on a server and understanding its meaning and context.

[0144] "Generative AI models" refer to artificial intelligence technologies that generate visual information based on information and the user's psychological state.

[0145] The system of this invention operates through the cooperation of three elements: a user, a terminal, and a server.

[0146] The user launches the application using a communication terminal and enters a string of characters to express their emotions. At this time, the terminal uses sensors such as a camera and microphone to collect supplementary information such as the user's facial expressions and tone of voice.

[0147] The device transmits input string data and sensor information to the server. The server analyzes the received string data using a natural language processing engine to understand the context and emotions of the information. Simultaneously, an emotion analysis engine analyzes the sensor information to grasp the user's psychological state. This allows the server to understand what emotions the user is experiencing at that moment.

[0148] The server uses a generation AI model based on the analysis results to generate text data and visual information that reflects the user's psychological state. This visual information is adjusted so that the theme and design match the user's emotions. For example, if the user enters the text "Thank you!" and a feeling of gratitude is detected, a bright and warm stamp will be selected to be generated.

[0149] The generated visual information and associated textual information are sent from the server to the terminal. The terminal receives the information and displays it appropriately for the user. In this way, the user can express their emotions more richly.

[0150] An example of a prompt might be, "The user typed 'Thank you!' and generated a stamp that expresses gratitude." Based on this prompt, the generation AI model can generate visual information that matches the emotion, providing a more personalized experience.

[0151] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0152] Step 1:

[0153] The user launches an application on a communication terminal and inputs a string of text expressing an emotion. The input data is, for example, a string indicating an emotion such as "I'm happy!". The terminal simultaneously uses camera and microphone sensors to capture the user's facial expressions and voice data. The input data consists of both the string and sensor information.

[0154] Step 2:

[0155] The terminal sends the acquired string data and sensor information to the server. A network connection is used for data transmission. The output here is the data transmission to the server.

[0156] Step 3:

[0157] The server feeds the received string data into a natural language processing engine to analyze the context and sentiment of the input text. The input is the user's string data, and the output is the analysis result. Specifically, it performs sentence structure analysis and keyword sentiment scoring.

[0158] Step 4:

[0159] The server feeds information collected from sensors into an emotion analysis engine to analyze the user's psychological state. Here, the user's facial expressions and voice tone are analyzed to determine their psychological state, such as positive or negative. The input is sensor information, and the output is the result of the psychological state analysis.

[0160] Step 5:

[0161] The server integrates results from both the natural language processing engine and the sentiment analysis engine, and uses a generative AI model to generate visual information. The input is the meaning of a string and the user's emotional state, and the output is visual information that harmonizes with this. Specifically, the theme and design of the stamp are determined and generated.

[0162] Step 6:

[0163] The server adds textual information related to the generated visual information, compresses the data, and sends it to the terminal. Here, the input is the generated visual information and textual information, and the output is the compressed data. Specifically, the process involves conversion to an image format and data compression.

[0164] Step 7:

[0165] The terminal receives data sent from the server and displays visual information to the user. The input here is compressed data, and the output is visual information that the user can view on the screen. Specifically, the process involves decompressing the data and displaying it on the user interface.

[0166] (Application Example 2)

[0167] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0168] In modern communication, users want to use a variety of stamps to effectively express their emotions. However, traditional stamps are not based on the user's real-time emotions and lack individual customization. Therefore, there is a need for a means to enrich users' emotional expression and strengthen individual communication.

[0169] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0170] In this invention, the server includes a device for receiving input string data, a device for analyzing the string data and generating suitable visual data, and a device for acquiring and analyzing user emotion data. This makes it possible to generate stamps that reflect the user's real-time emotions based on the string data and emotion data.

[0171] "String data" refers to text information entered by users, and is fundamental information for understanding emotions and context.

[0172] "Visual data" refers to visual content that expresses a user's emotions, generated based on text data and sentiment data.

[0173] "Emotional data" refers to data that represents the user's current emotional state, obtained from the user's facial expressions, voice, and other similar information.

[0174] "Visual data style" refers to the characteristics and themes of visual representation determined based on sentiment data and text data.

[0175] A "prompt statement" is an instruction given to a generative AI model, setting the conditions for generating specific visual content.

[0176] A "generative AI model" is a system that uses artificial intelligence to generate new content based on input data.

[0177] The system for realizing this application consists of the following: When a user inputs text data, a device such as a smartphone or smart glasses is used. This device receives the input text data and simultaneously acquires sentiment data using its camera and microphone. The acquired text data and sentiment data are sent to a server.

[0178] The server analyzes the received string data using a natural language processing engine (e.g., Google Cloud Natural Language API) to identify its context and meaning. Simultaneously, it analyzes the user's emotional data using an emotion analysis engine (e.g., Microsoft® Azure® Emotion API) to determine what emotions the user is experiencing. This information is used as foundational data for generating visual data.

[0179] Next, the server generates prompts for a generative AI model (e.g., OpenAI® GPT-3®) and requests it to generate visual data based on string data and sentiment data. An example of a prompt might be, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent a positive emotion."

[0180] The generated visual data is compressed using a predetermined compression method and sent to the user's device. Finally, the user's device displays stamps customized according to the user's text data and emotions, which the user can then share in chats and on social media.

[0181] This invention enables users to generate visual content that matches their individual emotional expressions in real time, thereby achieving personalized and emotionally rich communication.

[0182] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0183] Step 1:

[0184] The device receives string data entered by the user and uses the camera and microphone to acquire user emotion data. The input consists of raw string data and sensor data, and the output consists of string data and emotion data.

[0185] Step 2:

[0186] The terminal sends the acquired string data and sentiment data to the server. The input consists of the user's string data and sentiment data, and this data is passed to the server.

[0187] Step 3:

[0188] The server parses string data using a natural language processing engine. String data is passed as input, and its meaning and context are identified as output.

[0189] Step 4:

[0190] The server evaluates emotional data using an emotion analysis engine. The input is emotional data, and the output is the user's real-time emotional state.

[0191] Step 5:

[0192] The server generates prompt sentences based on the analysis results of the string data and sentiment data. This creates specific instructions for the generating AI model. An example of a prompt sentence generated in this step is the instruction, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent positive emotions."

[0193] Step 6:

[0194] The server generates visual data based on prompt text using a generative AI model. The input is the prompt text, and the output is customized visual data.

[0195] Step 7:

[0196] The server compresses the generated visual data and sends it to the user's terminal. Here, the input is uncompressed visual data, and the output is compressed visual data.

[0197] Step 8:

[0198] The terminal decompresses the received visual data and displays it to the user. In this step, the final output is a stamp customized specifically for the user, which the user can then use within the communication tool.

[0199] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0200] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0201] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0205] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0206] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0207] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0208] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0209] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0210] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0211] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0212] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0213] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0214] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0215] This invention provides a system that includes a process for generating visual data from a user inputting a string of characters. First, the user inputs a string of characters they want to convert into a stamp within a specific application using their usual communication terminal. This input string data is then transmitted from the terminal to the server.

[0216] The server uses natural language processing techniques to analyze the received string data. This analysis determines the meaning and emotion of the string and decides on the optimal representation as visual data. Next, the server uses a generative AI engine to automatically generate visual data based on the analysis results, that is, a graphical image that aligns with the user's intent.

[0217] The generated visual data is accompanied by the original text information as a caption. This allows the visual data to function as a message to the user. This visual data and text information are sent from the server to the communication terminal and displayed on the user's device.

[0218] For example, if a user enters the string "Thank you for your hard work!", this string is analyzed by the server and recognized as an expression of gratitude. Based on this, the server generates an image of a cat that gives a relaxed impression and creates a stamp with "Thank you for your hard work!" as the caption. Finally, this completed stamp is displayed on the device, and the user can easily use this stamp to communicate.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The user opens a dedicated application on their communication terminal and enters a string of text into the text input field for stamp generation. Once the input is complete, the user presses the send button to begin sending the text data.

[0222] Step 2:

[0223] The terminal retrieves the string data entered by the user and generates an HTTP request to send it to the server. This request includes the string data and user identification information.

[0224] Step 3:

[0225] The server receives an HTTP request sent from the terminal and passes the string data contained within it to a natural language processing engine. Here, the server analyzes the meaning and sentiment of the input string and determines how best to represent it visually.

[0226] Step 4:

[0227] Based on the analyzed information, the server uses an image generation AI to generate visual data corresponding to the text. This includes applying themes and styles appropriate to the content of the text.

[0228] Step 5:

[0229] The server adds the user-entered text as a caption to the generated visual data. This caption is then overlaid and integrated with the image.

[0230] Step 6:

[0231] The server compresses and optimizes the completed stamp, then sends it to the terminal as an HTTP response. This response includes visual data and necessary metadata.

[0232] Step 7:

[0233] The device analyzes the stamp data received from the server and displays it within the application. The user can review the displayed stamps, select them as needed, and send them as messages.

[0234] (Example 1)

[0235] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0236] There is a need to represent information content simply and intuitively as visual information, enabling users to effectively utilize it for communication. However, conventional technologies have had the problem of difficulty in accurately analyzing the emotions and meaning of information content and automatically generating the most suitable visual information. In particular, when the transmitted information content contains a variety of emotions, the representation may be inappropriate, and the user's intentions may not be accurately conveyed.

[0237] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0238] In this invention, the server includes means for receiving input information content, means for analyzing the information content and generating visual information suitable for the information content, and means for adding information based on the information content to the visual information. This makes it possible to automatically generate appropriate visual information that takes into account the emotions and meanings of the information content entered by the user, and to easily use it for communication.

[0239] "Inputted information content" refers to strings of characters or data that the user provides to the system through the information processing device.

[0240] "Means of receiving" refers to the functions and devices that an information processing device uses to retrieve the input information content from a server.

[0241] "Means for analyzing and generating appropriate visual information" refers to methods and devices for understanding the meaning and emotions of input information and automatically creating corresponding visual data.

[0242] "Means for adding information based on visual information" refers to functions or devices used to add text or captions related to the original information content to generated visual information.

[0243] "Means of transmitting to an information processing device" refers to communication technologies and devices for transferring generated visual information and associated information to the user's information processing device.

[0244] This invention is a system that automatically generates visual information based on information input by a user using an information processing device and provides it in a manner that aligns with the user's intentions. Specific examples of hardware and software are provided below.

[0245] The user launches the application from a communication device and inputs the information they want to convert into the system. For example, the user might input the string "thank you." In this case, the communication device used could be a smartphone or a personal computer.

[0246] The terminal transmits the input information to the server via the internet. The server uses a natural language processing engine to analyze the received information. Examples of natural language processing technologies used here include commercial APIs and proprietary analysis algorithms. The server organizes the meaning and sentiment of the information and passes appropriate instructions to the generating AI model to generate visual information based on that.

[0247] Generative AI models could include algorithms and services like DALL·E and Midjourney, which generate images according to specified conditions. The server passes prompts to the generative AI model, which then generates visual information. A concrete example of such a prompt might be, "Generate a landscape expressing gratitude."

[0248] The server adds the input information as a caption to the generated visual information. This process associates the visual information with the original information content, resulting in a visual representation of the user's intent.

[0249] Finally, the server compresses this visual information and the associated information and sends it back to the communication terminal. The terminal displays the received data, and the user can easily use the completed visual information for communication. In this way, the aim is to significantly improve the user experience by conveying the meaning and emotions of the information content visually and intuitively.

[0250] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0251] Step 1:

[0252] The user launches the application using a communication terminal and enters the string they want to convert into a stamp. For example, they might enter the string "Hello". The terminal uses a touchscreen or keyboard for input, and the entered string is immediately visible within the application. The string data is then passed to the next processing step as output.

[0253] Step 2:

[0254] The terminal sends the entered string data to the server. This process involves data transmission via an internet connection. Specifically, an HTTP request is used, and the string data arrives at the server. The output of this step is the string data received by the server.

[0255] Step 3:

[0256] The server analyzes the received string data. Using a natural language processing engine, it extracts the meaning and sentiment of the string. For example, in the case of "hello," the meaning of friendliness and greeting is extracted. This analysis utilizes a vocabulary sentiment evaluation database, and the analysis results are passed to a generative AI model as output.

[0257] Step 4:

[0258] The server uses a generative AI model to generate visual information based on the analysis results. Specifically, it passes a prompt message to a generative AI model such as DALL·E. This prompt might be in the format of, for example, "Generate a friendly morning scene." The model generates an image, which is then returned to the server.

[0259] Step 5:

[0260] The server adds the original text information as a caption to the generated visual information. This allows the visual information to retain the meaning of the corresponding text. Specifically, it overlays the text onto the image. The output is data that combines the visual information and the text information.

[0261] Step 6:

[0262] The server compresses visual information and captions to improve communication efficiency. The compressed data is sent back to the terminal. The data is usually compressed using formats such as JPEG. The output is compressed data.

[0263] Step 7:

[0264] The device decompresses the received compressed data and displays it within the application. The user can then check the displayed stamps and see if they are ready to use. For example, generated stamps can be easily used for communication by pasting them into a chat screen. The output is the stamps displayed on the user's screen.

[0265] (Application Example 1)

[0266] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0267] In commercial facilities, traditional methods make it difficult to visually capture customer reviews and opinions, and to share them with other customers and staff. Therefore, new methods are needed to improve customer satisfaction and revitalize communication.

[0268] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0269] In this invention, the server includes means for receiving input string information, means for analyzing the string information and generating appropriate visual information, and means for adding linguistic information based on the visual information. This makes it possible to display the string information entered by the customer as visual information on a display device in a commercial facility or on the customer's personal device and share it with others.

[0270] "String information" refers to the text data entered by the user, and it forms the basis of the generated visual information.

[0271] "Visual information" refers to graphical images generated based on analyzed string information, intended for display in commercial facilities and on personal devices.

[0272] "Linguistic information" refers to text displayed alongside visual information, intended to clearly convey the user's intent or message.

[0273] "Information device" refers to electronic devices that operate on the server or client side and have functions for sending, receiving, and displaying data.

[0274] A "display device" is a device used to actually display visual information, and includes in-store displays and personal smartphones.

[0275] To realize this invention, a system is needed for use in commercial facilities and other applicable locations. This system generates visual information based on string information entered by the user and displays it on a display device.

[0276] First, the user inputs text information into a dedicated application using a device such as a smartphone or tablet. This text information specifically describes the user's thoughts and opinions. This text information is then transmitted to a server via the internet. The server uses natural language processing software, such as the Google NLP API, to perform sentiment analysis on the text information. Based on the analysis results, a generative AI model, such as Stable Diffusion, is used to generate visual information that reflects the user's intent. The generated visual information is then accompanied by the original text information as a caption.

[0277] This visual and linguistic information is transmitted to and displayed on display devices such as screens within commercial facilities, as well as on the user's smartphone. This makes it possible to share user feedback with other customers and staff, thereby stimulating communication.

[0278] For example, if a user enters the text "Today's meal was amazing!" at a restaurant, this information is analyzed by the server, and an image reflecting feelings of "deliciousness" and "satisfaction" is generated, such as a graphic of a chef smiling and holding a dish. This visual information is then captioned "Today's meal was amazing!" and displayed on the screen.

[0279] An example of a prompt message is: "User input: Today's meal was amazing! → Scene: Smiling chef, Expression: Happy." In this way, the present invention improves customer engagement in commercial facilities.

[0280] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0281] Step 1:

[0282] The user inputs string information into an application on a smartphone or tablet. At this input stage, feedback and impressions from the user are specifically described. This string information becomes the input data for the next processing step.

[0283] Step 2:

[0284] The terminal sends the input string information to the server. In this transmission process, the HTTP protocol is used, and the string information is included in the request and sent via the network. This string information becomes the data input for natural language analysis on the server side.

[0285] Step 3:

[0286] The server performs sentiment analysis on the received string information using natural language processing software such as the Google NLP API. The input for the analysis is the string information, and the output is the evaluation data of the sentiment and intention included in the text. Through this analysis, the sentiment of the string is quantified by data calculation.

[0287] Step 4:

[0288] The server uses the analysis result to send a prompt sentence to a generative AI model such as Stable Diffusion to generate visual information. This prompt sentence includes instructions for forming a specific image based on the "sentiment of the user input sentence". The input is the data of the analysis result, and the output is the generated graphical image.

[0289] Step 5:

[0290] The server assigns the original string information as a caption to the generated visual information. The input is the visual information and the string information, and the output is the completed image data with a caption. Through this process, the string information provided by the user is enhanced as a visual representation.

[0291] Step 6:

[0292] The completed visual information is transmitted from the server to the user's terminal or a display in a commercial facility. Here, the image data is compressed to improve bandwidth efficiency. The input is visual information with captions, and the output is the display of that visual information on a display device.

[0293] Step 7:

[0294] On a terminal or display device, users, other customers, and staff can view and share visual information. At this stage, emotions gained through visual information can be shared with others, improving customer engagement.

[0295] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0296] The system of the present invention provides a stamp generation function based on user string data and incorporates an emotion engine to recognize the user's emotions and improve the quality of the stamps. The user launches the application using a communication terminal and inputs a string that expresses some emotion. This string and sensor information from the terminal are simultaneously transmitted to the server.

[0297] The server first passes the string data to a natural language processing engine, which analyzes its content to understand its meaning and context. Simultaneously, the emotion engine uses data collected from the user's device (e.g., camera and microphone data) to analyze the user's real-time emotions. This analysis allows the system to understand the user's emotions.

[0298] Based on the analysis results, the server considers the meaning of the string data and the user's emotions to determine the stamp's theme and visual style. The generation AI engine receives this data and generates visual data that harmonizes with the string data and emotions. At this time, the stamp's color scheme and atmosphere are adjusted according to the user's feelings as determined by the emotion engine.

[0299] For example, if a user smiles while typing the string "Hello!", the emotion engine recognizes the user's positive emotion, and the server determines a bright and friendly stamp design to match. It then generates visual data with the text "Hello!" added as a caption, compresses and transmits it, and displays it on the communication terminal.

[0300] In this way, the system can provide a more personalized and emotionally rich communication tool based on the user's text data and emotions.

[0301] The following describes the processing flow.

[0302] Step 1:

[0303] The user opens the application on their communication device and enters the text they want to turn into a stamp. The device's sensors (camera, microphone, etc.) also activate to collect the user's facial expressions and voice in real time.

[0304] Step 2:

[0305] The device sends input string data and emotion-related data obtained from sensors to the server. Encrypted HTTP requests are used for transmission to ensure secure data delivery.

[0306] Step 3:

[0307] The server analyzes the received string data using a natural language processing engine, analyzes the content and sentiment of the string, while analyzing the data from the sensor using a sentiment engine to estimate the user's emotional state.

[0308] Step 4:

[0309] The server combines the meaning of the string and the sentiment information obtained from the sentiment engine to determine the theme and style of the visual data. In this step, for example, when the user seems happy, a design with bright and warm colors is selected.

[0310] Step 5:

[0311] The server uses a generation AI engine based on the determined theme to generate customized visual data. Text information corresponding to the user's emotion is attached as a caption to this data.

[0312] Step 6:

[0313] The server compresses the generated visual data and transmits it to the communication terminal together with the sentiment information. Data compression reduces the transmission time and efficiently uses the network bandwidth.

[0314] Step 7:

[0315] The terminal decompresses and displays the received stamp data so that the user can easily select a stamp and add it to the conversation. The user can check the final stamp and use it as appropriate.

[0316] (Example 2)

[0317] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0318] In modern communication, it is difficult to accurately convey emotions and nuances through mere text information. Therefore, there is a demand for more personal and emotionally rich communication methods. Traditional stamps and emojis have limited options and do not adequately support the creation of visuals that accurately reflect the user's psychological state.

[0319] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0320] In this invention, the server includes means for receiving input information, means for analyzing the information and generating visual information based on the information, and means for analyzing the user's psychological state. This enables the generation of personalized visual information that responds to the user's emotions and context, thereby facilitating richer communication.

[0321] "Information" refers to string data entered by the user and any accompanying information.

[0322] "Visual information" refers to visual materials generated based on information entered by the user.

[0323] "Character information" refers to the input string data itself, specifically the characters attached to the visual information.

[0324] "Communication device" refers to a terminal device used by a user that has the function of receiving generated visual and textual information.

[0325] "User's psychological state" refers to the emotions and nuances analyzed from the input information and accompanying information.

[0326] "Means of analysis" refers to methods and technologies for analyzing information on a server and understanding its meaning and context.

[0327] "Generative AI models" refer to artificial intelligence technologies that generate visual information based on information and the user's psychological state.

[0328] The system of this invention operates through the cooperation of three elements: a user, a terminal, and a server.

[0329] The user launches the application using a communication terminal and enters a string of characters to express their emotions. At this time, the terminal uses sensors such as a camera and microphone to collect supplementary information such as the user's facial expressions and tone of voice.

[0330] The device transmits input string data and sensor information to the server. The server analyzes the received string data using a natural language processing engine to understand the context and emotions of the information. Simultaneously, an emotion analysis engine analyzes the sensor information to grasp the user's psychological state. This allows the server to understand what emotions the user is experiencing at that moment.

[0331] The server uses a generation AI model based on the analysis results to generate text data and visual information that reflects the user's psychological state. This visual information is adjusted so that the theme and design match the user's emotions. For example, if the user enters the text "Thank you!" and a feeling of gratitude is detected, a bright and warm stamp will be selected to be generated.

[0332] The generated visual information and associated textual information are sent from the server to the terminal. The terminal receives the information and displays it appropriately for the user. In this way, the user can express their emotions more richly.

[0333] An example of a prompt might be, "The user typed 'Thank you!' and generated a stamp that expresses gratitude." Based on this prompt, the generation AI model can generate visual information that matches the emotion, providing a more personalized experience.

[0334] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0335] Step 1:

[0336] The user launches an application on a communication terminal and inputs a string of text expressing an emotion. The input data is, for example, a string indicating an emotion such as "I'm happy!". The terminal simultaneously uses camera and microphone sensors to capture the user's facial expressions and voice data. The input data consists of both the string and sensor information.

[0337] Step 2:

[0338] The terminal sends the acquired string data and sensor information to the server. A network connection is used for data transmission. The output here is the data transmission to the server.

[0339] Step 3:

[0340] The server feeds the received string data into a natural language processing engine to analyze the context and sentiment of the input text. The input is the user's string data, and the output is the analysis result. Specifically, it performs sentence structure analysis and keyword sentiment scoring.

[0341] Step 4:

[0342] The server feeds information collected from sensors into an emotion analysis engine to analyze the user's psychological state. Here, the user's facial expressions and voice tone are analyzed to determine their psychological state, such as positive or negative. The input is sensor information, and the output is the result of the psychological state analysis.

[0343] Step 5:

[0344] The server integrates results from both the natural language processing engine and the sentiment analysis engine, and uses a generative AI model to generate visual information. The input is the meaning of a string and the user's emotional state, and the output is visual information that harmonizes with this. Specifically, the theme and design of the stamp are determined and generated.

[0345] Step 6:

[0346] The server adds textual information related to the generated visual information, compresses the data, and sends it to the terminal. Here, the input is the generated visual information and textual information, and the output is the compressed data. Specifically, the process involves conversion to an image format and data compression.

[0347] Step 7:

[0348] The terminal receives data sent from the server and displays visual information to the user. The input here is compressed data, and the output is visual information that the user can view on the screen. Specifically, the process involves decompressing the data and displaying it on the user interface.

[0349] (Application Example 2)

[0350] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0351] In modern communication, users want to use a variety of stamps to effectively express their emotions. However, traditional stamps are not based on the user's real-time emotions and lack individual customization. Therefore, there is a need for a means to enrich users' emotional expression and strengthen individual communication.

[0352] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0353] In this invention, the server includes a device for receiving input string data, a device for analyzing the string data and generating suitable visual data, and a device for acquiring and analyzing user emotion data. This makes it possible to generate stamps that reflect the user's real-time emotions based on the string data and emotion data.

[0354] "String data" refers to text information entered by users, and is fundamental information for understanding emotions and context.

[0355] "Visual data" refers to visual content that expresses a user's emotions, generated based on text data and sentiment data.

[0356] "Emotional data" refers to data that represents the user's current emotional state, obtained from the user's facial expressions, voice, and other similar information.

[0357] "Visual data style" refers to the characteristics and themes of visual representation determined based on sentiment data and text data.

[0358] A "prompt statement" is an instruction given to a generative AI model, setting the conditions for generating specific visual content.

[0359] A "generative AI model" is a system that uses artificial intelligence to generate new content based on input data.

[0360] The system for realizing this application consists of the following: When a user inputs text data, a device such as a smartphone or smart glasses is used. This device receives the input text data and simultaneously acquires sentiment data using its camera and microphone. The acquired text data and sentiment data are sent to a server.

[0361] The server analyzes the received string data using a natural language processing engine (e.g., Google Cloud Natural Language API) to identify its context and meaning. Simultaneously, it analyzes the user's emotional data using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to determine what emotions the user is experiencing. This information is used as foundational data for generating visual data.

[0362] Next, the server generates prompts for a generative AI model (e.g., OpenAI GPT-3), requesting it to generate visual data based on string data and sentiment data. An example of a prompt might be, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent a positive emotion."

[0363] The generated visual data is compressed using a predetermined compression method and sent to the user's device. Finally, the user's device displays stamps customized according to the user's text data and emotions, which the user can then share in chats and on social media.

[0364] This invention enables users to generate visual content that matches their individual emotional expressions in real time, thereby achieving personalized and emotionally rich communication.

[0365] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0366] Step 1:

[0367] The device receives string data entered by the user and uses the camera and microphone to acquire user emotion data. The input consists of raw string data and sensor data, and the output consists of string data and emotion data.

[0368] Step 2:

[0369] The terminal sends the acquired string data and sentiment data to the server. The input consists of the user's string data and sentiment data, and this data is passed to the server.

[0370] Step 3:

[0371] The server parses string data using a natural language processing engine. String data is passed as input, and its meaning and context are identified as output.

[0372] Step 4:

[0373] The server evaluates emotional data using an emotion analysis engine. The input is emotional data, and the output is the user's real-time emotional state.

[0374] Step 5:

[0375] The server generates prompt sentences based on the analysis results of the string data and sentiment data. This creates specific instructions for the generating AI model. An example of a prompt sentence generated in this step is the instruction, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent positive emotions."

[0376] Step 6:

[0377] The server generates visual data based on prompt text using a generative AI model. The input is the prompt text, and the output is customized visual data.

[0378] Step 7:

[0379] The server compresses the generated visual data and sends it to the user's terminal. Here, the input is uncompressed visual data, and the output is compressed visual data.

[0380] Step 8:

[0381] The terminal decompresses the received visual data and displays it to the user. In this step, the final output is a stamp customized specifically for the user, which the user can then use within the communication tool.

[0382] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0383] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0384] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0385] [Third Embodiment]

[0386] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0387] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0388] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0389] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0390] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0391] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0392] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0393] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0394] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0395] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0396] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0397] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0398] This invention provides a system that includes a process for generating visual data from a user inputting a string of characters. First, the user inputs a string of characters they want to convert into a stamp within a specific application using their usual communication terminal. This input string data is then transmitted from the terminal to the server.

[0399] The server uses natural language processing techniques to analyze the received string data. This analysis determines the meaning and emotion of the string and decides on the optimal representation as visual data. Next, the server uses a generative AI engine to automatically generate visual data based on the analysis results, that is, a graphical image that aligns with the user's intent.

[0400] The generated visual data is accompanied by the original text information as a caption. This allows the visual data to function as a message to the user. This visual data and text information are sent from the server to the communication terminal and displayed on the user's device.

[0401] For example, if a user enters the string "Thank you for your hard work!", this string is analyzed by the server and recognized as an expression of gratitude. Based on this, the server generates an image of a cat that gives a relaxed impression and creates a stamp with "Thank you for your hard work!" as the caption. Finally, this completed stamp is displayed on the device, and the user can easily use this stamp to communicate.

[0402] The following describes the processing flow.

[0403] Step 1:

[0404] The user opens a dedicated application on their communication terminal and enters a string of text into the text input field for stamp generation. Once the input is complete, the user presses the send button to begin sending the text data.

[0405] Step 2:

[0406] The terminal retrieves the string data entered by the user and generates an HTTP request to send it to the server. This request includes the string data and user identification information.

[0407] Step 3:

[0408] The server receives an HTTP request sent from the terminal and passes the string data contained within it to a natural language processing engine. Here, the server analyzes the meaning and sentiment of the input string and determines how best to represent it visually.

[0409] Step 4:

[0410] Based on the analyzed information, the server uses an image generation AI to generate visual data corresponding to the text. This includes applying themes and styles appropriate to the content of the text.

[0411] Step 5:

[0412] The server adds the user-entered text as a caption to the generated visual data. This caption is then overlaid and integrated with the image.

[0413] Step 6:

[0414] The server compresses and optimizes the completed stamp, then sends it to the terminal as an HTTP response. This response includes visual data and necessary metadata.

[0415] Step 7:

[0416] The device analyzes the stamp data received from the server and displays it within the application. The user can review the displayed stamps, select them as needed, and send them as messages.

[0417] (Example 1)

[0418] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0419] There is a need to represent information content simply and intuitively as visual information, enabling users to effectively utilize it for communication. However, conventional technologies have had the problem of difficulty in accurately analyzing the emotions and meaning of information content and automatically generating the most suitable visual information. In particular, when the transmitted information content contains a variety of emotions, the representation may be inappropriate, and the user's intentions may not be accurately conveyed.

[0420] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0421] In this invention, the server includes means for receiving input information content, means for analyzing the information content and generating visual information suitable for the information content, and means for adding information based on the information content to the visual information. This makes it possible to automatically generate appropriate visual information that takes into account the emotions and meanings of the information content entered by the user, and to easily use it for communication.

[0422] "Inputted information content" refers to strings of characters or data that the user provides to the system through the information processing device.

[0423] "Means of receiving" refers to the functions and devices that an information processing device uses to retrieve the input information content from a server.

[0424] "Means for analyzing and generating appropriate visual information" refers to methods and devices for understanding the meaning and emotions of input information and automatically creating corresponding visual data.

[0425] "Means for adding information based on visual information" refers to functions or devices used to add text or captions related to the original information content to generated visual information.

[0426] "Means of transmitting to an information processing device" refers to communication technologies and devices for transferring generated visual information and associated information to the user's information processing device.

[0427] This invention is a system that automatically generates visual information based on information input by a user using an information processing device and provides it in a manner that aligns with the user's intentions. Specific examples of hardware and software are provided below.

[0428] The user launches the application from a communication device and inputs the information they want to convert into the system. For example, the user might input the string "thank you." In this case, the communication device used could be a smartphone or a personal computer.

[0429] The terminal transmits the input information to the server via the internet. The server uses a natural language processing engine to analyze the received information. Examples of natural language processing technologies used here include commercial APIs and proprietary analysis algorithms. The server organizes the meaning and sentiment of the information and passes appropriate instructions to the generating AI model to generate visual information based on that.

[0430] Generative AI models could include algorithms and services like DALL·E and Midjourney, which generate images according to specified conditions. The server passes prompts to the generative AI model, which then generates visual information. A concrete example of such a prompt might be, "Generate a landscape expressing gratitude."

[0431] The server adds the input information as a caption to the generated visual information. This process associates the visual information with the original information content, resulting in a visual representation of the user's intent.

[0432] Finally, the server compresses this visual information and the associated information and sends it back to the communication terminal. The terminal displays the received data, and the user can easily use the completed visual information for communication. In this way, the aim is to significantly improve the user experience by conveying the meaning and emotions of the information content visually and intuitively.

[0433] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0434] Step 1:

[0435] The user launches the application using a communication terminal and enters the string they want to convert into a stamp. For example, they might enter the string "Hello". The terminal uses a touchscreen or keyboard for input, and the entered string is immediately visible within the application. The string data is then passed to the next processing step as output.

[0436] Step 2:

[0437] The terminal sends the entered string data to the server. This process involves data transmission via an internet connection. Specifically, an HTTP request is used, and the string data arrives at the server. The output of this step is the string data received by the server.

[0438] Step 3:

[0439] The server analyzes the received string data. Using a natural language processing engine, it extracts the meaning and sentiment of the string. For example, in the case of "hello," the meaning of friendliness and greeting is extracted. This analysis utilizes a vocabulary sentiment evaluation database, and the analysis results are passed to a generative AI model as output.

[0440] Step 4:

[0441] The server uses a generative AI model to generate visual information based on the analysis results. Specifically, it passes a prompt message to a generative AI model such as DALL·E. This prompt might be in the format of, for example, "Generate a friendly morning scene." The model generates an image, which is then returned to the server.

[0442] Step 5:

[0443] The server adds the original text information as a caption to the generated visual information. This allows the visual information to retain the meaning of the corresponding text. Specifically, it overlays the text onto the image. The output is data that combines the visual information and the text information.

[0444] Step 6:

[0445] The server compresses visual information and captions to improve communication efficiency. The compressed data is sent back to the terminal. The data is usually compressed using formats such as JPEG. The output is compressed data.

[0446] Step 7:

[0447] The device decompresses the received compressed data and displays it within the application. The user can then check the displayed stamps and see if they are ready to use. For example, generated stamps can be easily used for communication by pasting them into a chat screen. The output is the stamps displayed on the user's screen.

[0448] (Application Example 1)

[0449] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0450] In commercial facilities, traditional methods make it difficult to visually capture customer reviews and opinions, and to share them with other customers and staff. Therefore, new methods are needed to improve customer satisfaction and revitalize communication.

[0451] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0452] In this invention, the server includes means for receiving input string information, means for analyzing the string information and generating appropriate visual information, and means for adding linguistic information based on the visual information. This makes it possible to display the string information entered by the customer as visual information on a display device in a commercial facility or on the customer's personal device and share it with others.

[0453] "String information" refers to the text data entered by the user, and it forms the basis of the generated visual information.

[0454] "Visual information" refers to graphical images generated based on analyzed string information, intended for display in commercial facilities and on personal devices.

[0455] "Linguistic information" refers to text displayed alongside visual information, intended to clearly convey the user's intent or message.

[0456] "Information device" refers to electronic devices that operate on the server or client side and have functions for sending, receiving, and displaying data.

[0457] A "display device" is a device used to actually display visual information, and includes in-store displays and personal smartphones.

[0458] To realize this invention, a system is needed for use in commercial facilities and other applicable locations. This system generates visual information based on string information entered by the user and displays it on a display device.

[0459] First, the user inputs text information into a dedicated application using a device such as a smartphone or tablet. This text information specifically describes the user's thoughts and opinions. This text information is then transmitted to a server via the internet. The server uses natural language processing software, such as the Google NLP API, to perform sentiment analysis on the text information. Based on the analysis results, a generative AI model, such as Stable Diffusion, is used to generate visual information that reflects the user's intent. The generated visual information is then accompanied by the original text information as a caption.

[0460] This visual and linguistic information is transmitted to and displayed on display devices such as screens within commercial facilities, as well as on the user's smartphone. This makes it possible to share user feedback with other customers and staff, thereby stimulating communication.

[0461] For example, if a user enters the text "Today's meal was amazing!" at a restaurant, this information is analyzed by the server, and an image reflecting feelings of "deliciousness" and "satisfaction" is generated, such as a graphic of a chef smiling and holding a dish. This visual information is then captioned "Today's meal was amazing!" and displayed on the screen.

[0462] An example of a prompt message is: "User input: Today's meal was amazing! → Scene: Smiling chef, Expression: Happy." In this way, the present invention improves customer engagement in commercial facilities.

[0463] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0464] Step 1:

[0465] Users input text information into a smartphone or tablet application. During this input stage, specific feedback and comments from the user are described. This text information becomes the input data for the next processing step.

[0466] Step 2:

[0467] The terminal sends the entered string information to the server. This transmission process uses the HTTP protocol, including the string information in the request and sending it over the network. This string information becomes the data input for natural language processing on the server side.

[0468] Step 3:

[0469] The server performs sentiment analysis on received string information using natural language processing software such as the Google NLP API. The input for the analysis is string information, and the output is evaluation data of the emotions and intentions contained in the text. Through this analysis, the emotions contained in the string are quantified using data calculations.

[0470] Step 4:

[0471] The server uses the analysis results to send prompt sentences to generative AI models such as Stable Diffusion, which then generate visual information. These prompt sentences are based on the "sentiment of the user input sentence" and include instructions for forming a concrete image. The input is the data from the analysis results, and the output is the generated graphical image.

[0472] Step 5:

[0473] The server adds the original text information as a caption to the generated visual information. The input consists of visual information and text information, and the output is the completed image data with the caption. This process enhances the visual representation of the user's text information.

[0474] Step 6:

[0475] The completed visual information is transmitted from the server to the user's terminal or a display in a commercial facility. Here, the image data is compressed to improve bandwidth efficiency. The input is visual information with captions, and the output is the display of that visual information on a display device.

[0476] Step 7:

[0477] On a terminal or display device, users, other customers, and staff can view and share visual information. At this stage, emotions gained through visual information can be shared with others, improving customer engagement.

[0478] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0479] The system of the present invention provides a stamp generation function based on user string data and incorporates an emotion engine to recognize the user's emotions and improve the quality of the stamps. The user launches the application using a communication terminal and inputs a string that expresses some emotion. This string and sensor information from the terminal are simultaneously transmitted to the server.

[0480] The server first passes the string data to a natural language processing engine, which analyzes its content to understand its meaning and context. Simultaneously, the emotion engine uses data collected from the user's device (e.g., camera and microphone data) to analyze the user's real-time emotions. This analysis allows the system to understand the user's emotions.

[0481] Based on the analysis results, the server considers the meaning of the string data and the user's emotions to determine the stamp's theme and visual style. The generation AI engine receives this data and generates visual data that harmonizes with the string data and emotions. At this time, the stamp's color scheme and atmosphere are adjusted according to the user's feelings as determined by the emotion engine.

[0482] For example, if a user smiles while typing the string "Hello!", the emotion engine recognizes the user's positive emotion, and the server determines a bright and friendly stamp design to match. It then generates visual data with the text "Hello!" added as a caption, compresses and transmits it, and displays it on the communication terminal.

[0483] In this way, the system can provide a more personalized and emotionally rich communication tool based on the user's text data and emotions.

[0484] The following describes the processing flow.

[0485] Step 1:

[0486] The user opens the application on their communication device and enters the text they want to turn into a stamp. The device's sensors (camera, microphone, etc.) also activate to collect the user's facial expressions and voice in real time.

[0487] Step 2:

[0488] The device sends input string data and emotion-related data obtained from sensors to the server. Encrypted HTTP requests are used for transmission to ensure secure data delivery.

[0489] Step 3:

[0490] The server analyzes the received string data using a natural language processing engine to analyze the content and emotion of the string, while simultaneously analyzing data from sensors using an emotion engine to estimate the user's emotional state.

[0491] Step 4:

[0492] The server combines the meaning of the text with emotional information obtained from the sentiment engine to determine the theme and style of the visual data. In this step, for example, if the user appears happy, it will select a design with bright and warm color tones.

[0493] Step 5:

[0494] The server uses a generation AI engine based on a determined theme to generate customized visual data. This data is accompanied by text information that reflects the user's emotions as captions.

[0495] Step 6:

[0496] The server compresses the generated visual data and sends it to the communication terminal along with emotional information. Data compression reduces transmission time and makes efficient use of network bandwidth.

[0497] Step 7:

[0498] The device decompresses and displays the received stamp data, allowing the user to easily select and add stamps to the conversation. The user can then review the final stamps and use them as appropriate.

[0499] (Example 2)

[0500] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0501] In modern communication, it is difficult to accurately convey emotions and nuances through mere text information. Therefore, there is a demand for more personal and emotionally rich communication methods. Traditional stamps and emojis have limited options and do not adequately support the creation of visuals that accurately reflect the user's psychological state.

[0502] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0503] In this invention, the server includes means for receiving input information, means for analyzing the information and generating visual information based on the information, and means for analyzing the user's psychological state. This enables the generation of personalized visual information that responds to the user's emotions and context, thereby facilitating richer communication.

[0504] "Information" refers to string data entered by the user and any accompanying information.

[0505] "Visual information" refers to visual materials generated based on information entered by the user.

[0506] "Character information" refers to the input string data itself, specifically the characters attached to the visual information.

[0507] "Communication device" refers to a terminal device used by a user that has the function of receiving generated visual and textual information.

[0508] "User's psychological state" refers to the emotions and nuances analyzed from the input information and accompanying information.

[0509] "Means of analysis" refers to methods and technologies for analyzing information on a server and understanding its meaning and context.

[0510] "Generative AI models" refer to artificial intelligence technologies that generate visual information based on information and the user's psychological state.

[0511] The system of this invention operates through the cooperation of three elements: a user, a terminal, and a server.

[0512] The user launches the application using a communication terminal and enters a string of characters to express their emotions. At this time, the terminal uses sensors such as a camera and microphone to collect supplementary information such as the user's facial expressions and tone of voice.

[0513] The device transmits input string data and sensor information to the server. The server analyzes the received string data using a natural language processing engine to understand the context and emotions of the information. Simultaneously, an emotion analysis engine analyzes the sensor information to grasp the user's psychological state. This allows the server to understand what emotions the user is experiencing at that moment.

[0514] The server uses a generation AI model based on the analysis results to generate text data and visual information that reflects the user's psychological state. This visual information is adjusted so that the theme and design match the user's emotions. For example, if the user enters the text "Thank you!" and a feeling of gratitude is detected, a bright and warm stamp will be selected to be generated.

[0515] The generated visual information and associated textual information are sent from the server to the terminal. The terminal receives the information and displays it appropriately for the user. In this way, the user can express their emotions more richly.

[0516] An example of a prompt might be, "The user typed 'Thank you!' and generated a stamp that expresses gratitude." Based on this prompt, the generation AI model can generate visual information that matches the emotion, providing a more personalized experience.

[0517] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0518] Step 1:

[0519] The user launches an application on a communication terminal and inputs a string of text expressing an emotion. The input data is, for example, a string indicating an emotion such as "I'm happy!". The terminal simultaneously uses camera and microphone sensors to capture the user's facial expressions and voice data. The input data consists of both the string and sensor information.

[0520] Step 2:

[0521] The terminal sends the acquired string data and sensor information to the server. A network connection is used for data transmission. The output here is the data transmission to the server.

[0522] Step 3:

[0523] The server feeds the received string data into a natural language processing engine to analyze the context and sentiment of the input text. The input is the user's string data, and the output is the analysis result. Specifically, it performs sentence structure analysis and keyword sentiment scoring.

[0524] Step 4:

[0525] The server feeds information collected from sensors into an emotion analysis engine to analyze the user's psychological state. Here, the user's facial expressions and voice tone are analyzed to determine their psychological state, such as positive or negative. The input is sensor information, and the output is the result of the psychological state analysis.

[0526] Step 5:

[0527] The server integrates results from both the natural language processing engine and the sentiment analysis engine, and uses a generative AI model to generate visual information. The input is the meaning of a string and the user's emotional state, and the output is visual information that harmonizes with this. Specifically, the theme and design of the stamp are determined and generated.

[0528] Step 6:

[0529] The server adds textual information related to the generated visual information, compresses the data, and sends it to the terminal. Here, the input is the generated visual information and textual information, and the output is the compressed data. Specifically, the process involves conversion to an image format and data compression.

[0530] Step 7:

[0531] The terminal receives data sent from the server and displays visual information to the user. The input here is compressed data, and the output is visual information that the user can view on the screen. Specifically, the process involves decompressing the data and displaying it on the user interface.

[0532] (Application Example 2)

[0533] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0534] In modern communication, users want to use a variety of stamps to effectively express their emotions. However, traditional stamps are not based on the user's real-time emotions and lack individual customization. Therefore, there is a need for a means to enrich users' emotional expression and strengthen individual communication.

[0535] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0536] In this invention, the server includes a device for receiving input string data, a device for analyzing the string data and generating suitable visual data, and a device for acquiring and analyzing user emotion data. This makes it possible to generate stamps that reflect the user's real-time emotions based on the string data and emotion data.

[0537] "String data" refers to text information entered by users, and is fundamental information for understanding emotions and context.

[0538] "Visual data" refers to visual content that expresses a user's emotions, generated based on text data and sentiment data.

[0539] "Emotional data" refers to data that represents the user's current emotional state, obtained from the user's facial expressions, voice, and other similar information.

[0540] "Visual data style" refers to the characteristics and themes of visual representation determined based on sentiment data and text data.

[0541] A "prompt statement" is an instruction given to a generative AI model, setting the conditions for generating specific visual content.

[0542] A "generative AI model" is a system that uses artificial intelligence to generate new content based on input data.

[0543] The system for realizing this application consists of the following: When a user inputs text data, a device such as a smartphone or smart glasses is used. This device receives the input text data and simultaneously acquires sentiment data using its camera and microphone. The acquired text data and sentiment data are sent to a server.

[0544] The server analyzes the received string data using a natural language processing engine (e.g., Google Cloud Natural Language API) to identify its context and meaning. Simultaneously, it analyzes the user's emotional data using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to determine what emotions the user is experiencing. This information is used as foundational data for generating visual data.

[0545] Next, the server generates prompts for a generative AI model (e.g., OpenAI GPT-3), requesting it to generate visual data based on string data and sentiment data. An example of a prompt might be, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent a positive emotion."

[0546] The generated visual data is compressed using a predetermined compression method and sent to the user's device. Finally, the user's device displays stamps customized according to the user's text data and emotions, which the user can then share in chats and on social media.

[0547] This invention enables users to generate visual content that matches their individual emotional expressions in real time, thereby achieving personalized and emotionally rich communication.

[0548] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0549] Step 1:

[0550] The device receives string data entered by the user and uses the camera and microphone to acquire user emotion data. The input consists of raw string data and sensor data, and the output consists of string data and emotion data.

[0551] Step 2:

[0552] The terminal sends the acquired string data and sentiment data to the server. The input consists of the user's string data and sentiment data, and this data is passed to the server.

[0553] Step 3:

[0554] The server parses string data using a natural language processing engine. String data is passed as input, and its meaning and context are identified as output.

[0555] Step 4:

[0556] The server evaluates emotional data using an emotion analysis engine. The input is emotional data, and the output is the user's real-time emotional state.

[0557] Step 5:

[0558] The server generates prompt sentences based on the analysis results of the string data and sentiment data. This creates specific instructions for the generating AI model. An example of a prompt sentence generated in this step is the instruction, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent positive emotions."

[0559] Step 6:

[0560] The server generates visual data based on prompt text using a generative AI model. The input is the prompt text, and the output is customized visual data.

[0561] Step 7:

[0562] The server compresses the generated visual data and sends it to the user's terminal. Here, the input is uncompressed visual data, and the output is compressed visual data.

[0563] Step 8:

[0564] The terminal decompresses the received visual data and displays it to the user. In this step, the final output is a stamp customized specifically for the user, which the user can then use within the communication tool.

[0565] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0566] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0567] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0568] [Fourth Embodiment]

[0569] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0570] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0571] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0572] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0573] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0574] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0575] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0576] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors in the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0577] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0578] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0579] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0580] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0581] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0582] This invention provides a system that includes a process for generating visual data from a user inputting a string of characters. First, the user inputs a string of characters they want to convert into a stamp within a specific application using their usual communication terminal. This input string data is then transmitted from the terminal to the server.

[0583] The server uses natural language processing techniques to analyze the received string data. This analysis determines the meaning and emotion of the string and decides on the optimal representation as visual data. Next, the server uses a generative AI engine to automatically generate visual data based on the analysis results, that is, a graphical image that aligns with the user's intent.

[0584] The generated visual data is accompanied by the original text information as a caption. This allows the visual data to function as a message to the user. This visual data and text information are sent from the server to the communication terminal and displayed on the user's device.

[0585] For example, if a user enters the string "Thank you for your hard work!", this string is analyzed by the server and recognized as an expression of gratitude. Based on this, the server generates an image of a cat that gives a relaxed impression and creates a stamp with "Thank you for your hard work!" as the caption. Finally, this completed stamp is displayed on the device, and the user can easily use this stamp to communicate.

[0586] The following describes the processing flow.

[0587] Step 1:

[0588] The user opens a dedicated application on their communication terminal and enters a string of text into the text input field for stamp generation. Once the input is complete, the user presses the send button to begin sending the text data.

[0589] Step 2:

[0590] The terminal retrieves the string data entered by the user and generates an HTTP request to send it to the server. This request includes the string data and user identification information.

[0591] Step 3:

[0592] The server receives an HTTP request sent from the terminal and passes the string data contained within it to a natural language processing engine. Here, the server analyzes the meaning and sentiment of the input string and determines how best to represent it visually.

[0593] Step 4:

[0594] Based on the analyzed information, the server uses an image generation AI to generate visual data corresponding to the text. This includes applying themes and styles appropriate to the content of the text.

[0595] Step 5:

[0596] The server adds the user-entered text as a caption to the generated visual data. This caption is then overlaid and integrated with the image.

[0597] Step 6:

[0598] The server compresses and optimizes the completed stamp, then sends it to the terminal as an HTTP response. This response includes visual data and necessary metadata.

[0599] Step 7:

[0600] The device analyzes the stamp data received from the server and displays it within the application. The user can review the displayed stamps, select them as needed, and send them as messages.

[0601] (Example 1)

[0602] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0603] There is a need to represent information content simply and intuitively as visual information, enabling users to effectively utilize it for communication. However, conventional technologies have had the problem of difficulty in accurately analyzing the emotions and meaning of information content and automatically generating the most suitable visual information. In particular, when the transmitted information content contains a variety of emotions, the representation may be inappropriate, and the user's intentions may not be accurately conveyed.

[0604] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0605] In this invention, the server includes means for receiving input information content, means for analyzing the information content and generating visual information suitable for the information content, and means for adding information based on the information content to the visual information. This makes it possible to automatically generate appropriate visual information that takes into account the emotions and meanings of the information content entered by the user, and to easily use it for communication.

[0606] "Inputted information content" refers to strings of characters or data that the user provides to the system through the information processing device.

[0607] "Means of receiving" refers to the functions and devices that an information processing device uses to retrieve the input information content from a server.

[0608] "Means for analyzing and generating appropriate visual information" refers to methods and devices for understanding the meaning and emotions of input information and automatically creating corresponding visual data.

[0609] "Means for adding information based on visual information" refers to functions or devices used to add text or captions related to the original information content to generated visual information.

[0610] "Means of transmitting to an information processing device" refers to communication technologies and devices for transferring generated visual information and associated information to the user's information processing device.

[0611] This invention is a system that automatically generates visual information based on information input by a user using an information processing device and provides it in a manner that aligns with the user's intentions. Specific examples of hardware and software are provided below.

[0612] The user launches the application from a communication device and inputs the information they want to convert into the system. For example, the user might input the string "thank you." In this case, the communication device used could be a smartphone or a personal computer.

[0613] The terminal transmits the input information to the server via the internet. The server uses a natural language processing engine to analyze the received information. Examples of natural language processing technologies used here include commercial APIs and proprietary analysis algorithms. The server organizes the meaning and sentiment of the information and passes appropriate instructions to the generating AI model to generate visual information based on that.

[0614] Generative AI models could include algorithms and services like DALL·E and Midjourney, which generate images according to specified conditions. The server passes prompts to the generative AI model, which then generates visual information. A concrete example of such a prompt might be, "Generate a landscape expressing gratitude."

[0615] The server adds the input information as a caption to the generated visual information. This process associates the visual information with the original information content, resulting in a visual representation of the user's intent.

[0616] Finally, the server compresses this visual information and the associated information and sends it back to the communication terminal. The terminal displays the received data, and the user can easily use the completed visual information for communication. In this way, the aim is to significantly improve the user experience by conveying the meaning and emotions of the information content visually and intuitively.

[0617] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0618] Step 1:

[0619] The user launches the application using a communication terminal and enters the string they want to convert into a stamp. For example, they might enter the string "Hello". The terminal uses a touchscreen or keyboard for input, and the entered string is immediately visible within the application. The string data is then passed to the next processing step as output.

[0620] Step 2:

[0621] The terminal sends the entered string data to the server. This process involves data transmission via an internet connection. Specifically, an HTTP request is used, and the string data arrives at the server. The output of this step is the string data received by the server.

[0622] Step 3:

[0623] The server analyzes the received string data. Using a natural language processing engine, it extracts the meaning and sentiment of the string. For example, in the case of "hello," the meaning of friendliness and greeting is extracted. This analysis utilizes a vocabulary sentiment evaluation database, and the analysis results are passed to a generative AI model as output.

[0624] Step 4:

[0625] The server uses a generative AI model to generate visual information based on the analysis results. Specifically, it passes a prompt message to a generative AI model such as DALL·E. This prompt might be in the format of, for example, "Generate a friendly morning scene." The model generates an image, which is then returned to the server.

[0626] Step 5:

[0627] The server adds the original text information as a caption to the generated visual information. This allows the visual information to retain the meaning of the corresponding text. Specifically, it overlays the text onto the image. The output is data that combines the visual information and the text information.

[0628] Step 6:

[0629] The server compresses visual information and captions to improve communication efficiency. The compressed data is sent back to the terminal. The data is usually compressed using formats such as JPEG. The output is compressed data.

[0630] Step 7:

[0631] The device decompresses the received compressed data and displays it within the application. The user can then check the displayed stamps and see if they are ready to use. For example, generated stamps can be easily used for communication by pasting them into a chat screen. The output is the stamps displayed on the user's screen.

[0632] (Application Example 1)

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

[0634] In commercial facilities, traditional methods make it difficult to visually capture customer reviews and opinions, and to share them with other customers and staff. Therefore, new methods are needed to improve customer satisfaction and revitalize communication.

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

[0636] In this invention, the server includes means for receiving input string information, means for analyzing the string information and generating appropriate visual information, and means for adding linguistic information based on the visual information. This makes it possible to display the string information entered by the customer as visual information on a display device in a commercial facility or on the customer's personal device and share it with others.

[0637] "String information" refers to the text data entered by the user, and it forms the basis of the generated visual information.

[0638] "Visual information" refers to graphical images generated based on analyzed string information, intended for display in commercial facilities and on personal devices.

[0639] "Linguistic information" refers to text displayed alongside visual information, intended to clearly convey the user's intent or message.

[0640] "Information device" refers to electronic devices that operate on the server or client side and have functions for sending, receiving, and displaying data.

[0641] A "display device" is a device used to actually display visual information, and includes in-store displays and personal smartphones.

[0642] To realize this invention, a system is needed for use in commercial facilities and other applicable locations. This system generates visual information based on string information entered by the user and displays it on a display device.

[0643] First, the user inputs text information into a dedicated application using a device such as a smartphone or tablet. This text information specifically describes the user's thoughts and opinions. This text information is then transmitted to a server via the internet. The server uses natural language processing software, such as the Google NLP API, to perform sentiment analysis on the text information. Based on the analysis results, a generative AI model, such as Stable Diffusion, is used to generate visual information that reflects the user's intent. The generated visual information is then accompanied by the original text information as a caption.

[0644] This visual and linguistic information is transmitted to and displayed on display devices such as screens within commercial facilities, as well as on the user's smartphone. This makes it possible to share user feedback with other customers and staff, thereby stimulating communication.

[0645] For example, if a user enters the text "Today's meal was amazing!" at a restaurant, this information is analyzed by the server, and an image reflecting feelings of "deliciousness" and "satisfaction" is generated, such as a graphic of a chef smiling and holding a dish. This visual information is then captioned "Today's meal was amazing!" and displayed on the screen.

[0646] An example of a prompt message is: "User input: Today's meal was amazing! → Scene: Smiling chef, Expression: Happy." In this way, the present invention improves customer engagement in commercial facilities.

[0647] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0648] Step 1:

[0649] Users input text information into a smartphone or tablet application. During this input stage, specific feedback and comments from the user are described. This text information becomes the input data for the next processing step.

[0650] Step 2:

[0651] The terminal sends the entered string information to the server. This transmission process uses the HTTP protocol, including the string information in the request and sending it over the network. This string information becomes the data input for natural language processing on the server side.

[0652] Step 3:

[0653] The server performs sentiment analysis on received string information using natural language processing software such as the Google NLP API. The input for the analysis is string information, and the output is evaluation data of the emotions and intentions contained in the text. Through this analysis, the emotions contained in the string are quantified using data calculations.

[0654] Step 4:

[0655] The server uses the analysis results to send prompt sentences to generative AI models such as Stable Diffusion, which then generate visual information. These prompt sentences are based on the "sentiment of the user input sentence" and include instructions for forming a concrete image. The input is the data from the analysis results, and the output is the generated graphical image.

[0656] Step 5:

[0657] The server adds the original text information as a caption to the generated visual information. The input consists of visual information and text information, and the output is the completed image data with the caption. This process enhances the visual representation of the user's text information.

[0658] Step 6:

[0659] The completed visual information is transmitted from the server to the user's terminal or a display in a commercial facility. Here, the image data is compressed to improve bandwidth efficiency. The input is visual information with captions, and the output is the display of that visual information on a display device.

[0660] Step 7:

[0661] On a terminal or display device, users, other customers, and staff can view and share visual information. At this stage, emotions gained through visual information can be shared with others, improving customer engagement.

[0662] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0663] The system of the present invention provides a stamp generation function based on user string data and incorporates an emotion engine to recognize the user's emotions and improve the quality of the stamps. The user launches the application using a communication terminal and inputs a string that expresses some emotion. This string and sensor information from the terminal are simultaneously transmitted to the server.

[0664] The server first passes the string data to a natural language processing engine, which analyzes its content to understand its meaning and context. Simultaneously, the emotion engine uses data collected from the user's device (e.g., camera and microphone data) to analyze the user's real-time emotions. This analysis allows the system to understand the user's emotions.

[0665] Based on the analysis results, the server considers the meaning of the string data and the user's emotions to determine the stamp's theme and visual style. The generation AI engine receives this data and generates visual data that harmonizes with the string data and emotions. At this time, the stamp's color scheme and atmosphere are adjusted according to the user's feelings as determined by the emotion engine.

[0666] For example, if a user smiles while typing the string "Hello!", the emotion engine recognizes the user's positive emotion, and the server determines a bright and friendly stamp design to match. It then generates visual data with the text "Hello!" added as a caption, compresses and transmits it, and displays it on the communication terminal.

[0667] In this way, the system can provide a more personalized and emotionally rich communication tool based on the user's text data and emotions.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The user opens the application on their communication device and enters the text they want to turn into a stamp. The device's sensors (camera, microphone, etc.) also activate to collect the user's facial expressions and voice in real time.

[0671] Step 2:

[0672] The device sends input string data and emotion-related data obtained from sensors to the server. Encrypted HTTP requests are used for transmission to ensure secure data delivery.

[0673] Step 3:

[0674] The server analyzes the received string data using a natural language processing engine to analyze the content and emotion of the string, while simultaneously analyzing data from sensors using an emotion engine to estimate the user's emotional state.

[0675] Step 4:

[0676] The server combines the meaning of the text with emotional information obtained from the sentiment engine to determine the theme and style of the visual data. In this step, for example, if the user appears happy, it will select a design with bright and warm color tones.

[0677] Step 5:

[0678] The server uses a generation AI engine based on a determined theme to generate customized visual data. This data is accompanied by text information that reflects the user's emotions as captions.

[0679] Step 6:

[0680] The server compresses the generated visual data and sends it to the communication terminal along with emotional information. Data compression reduces transmission time and makes efficient use of network bandwidth.

[0681] Step 7:

[0682] The device decompresses and displays the received stamp data, allowing the user to easily select and add stamps to the conversation. The user can then review the final stamps and use them as appropriate.

[0683] (Example 2)

[0684] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0685] In modern communication, it is difficult to accurately convey emotions and nuances through mere text information. Therefore, there is a demand for more personal and emotionally rich communication methods. Traditional stamps and emojis have limited options and do not adequately support the creation of visuals that accurately reflect the user's psychological state.

[0686] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0687] In this invention, the server includes means for receiving input information, means for analyzing the information and generating visual information based on the information, and means for analyzing the user's psychological state. This enables the generation of personalized visual information that responds to the user's emotions and context, thereby facilitating richer communication.

[0688] "Information" refers to string data entered by the user and any accompanying information.

[0689] "Visual information" refers to visual materials generated based on information entered by the user.

[0690] "Character information" refers to the input string data itself, specifically the characters attached to the visual information.

[0691] "Communication device" refers to a terminal device used by a user that has the function of receiving generated visual and textual information.

[0692] "User's psychological state" refers to the emotions and nuances analyzed from the input information and accompanying information.

[0693] "Means of analysis" refers to methods and technologies for analyzing information on a server and understanding its meaning and context.

[0694] "Generative AI models" refer to artificial intelligence technologies that generate visual information based on information and the user's psychological state.

[0695] The system of this invention operates through the cooperation of three elements: a user, a terminal, and a server.

[0696] The user launches the application using a communication terminal and enters a string of characters to express their emotions. At this time, the terminal uses sensors such as a camera and microphone to collect supplementary information such as the user's facial expressions and tone of voice.

[0697] The device transmits input string data and sensor information to the server. The server analyzes the received string data using a natural language processing engine to understand the context and emotions of the information. Simultaneously, an emotion analysis engine analyzes the sensor information to grasp the user's psychological state. This allows the server to understand what emotions the user is experiencing at that moment.

[0698] The server uses a generation AI model based on the analysis results to generate text data and visual information that reflects the user's psychological state. This visual information is adjusted so that the theme and design match the user's emotions. For example, if the user enters the text "Thank you!" and a feeling of gratitude is detected, a bright and warm stamp will be selected to be generated.

[0699] The generated visual information and associated textual information are sent from the server to the terminal. The terminal receives the information and displays it appropriately for the user. In this way, the user can express their emotions more richly.

[0700] An example of a prompt might be, "The user typed 'Thank you!' and generated a stamp that expresses gratitude." Based on this prompt, the generation AI model can generate visual information that matches the emotion, providing a more personalized experience.

[0701] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0702] Step 1:

[0703] The user launches an application on a communication terminal and inputs a string of text expressing an emotion. The input data is, for example, a string indicating an emotion such as "I'm happy!". The terminal simultaneously uses camera and microphone sensors to capture the user's facial expressions and voice data. The input data consists of both the string and sensor information.

[0704] Step 2:

[0705] The terminal sends the acquired string data and sensor information to the server. A network connection is used for data transmission. The output here is the data transmission to the server.

[0706] Step 3:

[0707] The server feeds the received string data into a natural language processing engine to analyze the context and sentiment of the input text. The input is the user's string data, and the output is the analysis result. Specifically, it performs sentence structure analysis and keyword sentiment scoring.

[0708] Step 4:

[0709] The server feeds information collected from sensors into an emotion analysis engine to analyze the user's psychological state. Here, the user's facial expressions and voice tone are analyzed to determine their psychological state, such as positive or negative. The input is sensor information, and the output is the result of the psychological state analysis.

[0710] Step 5:

[0711] The server integrates results from both the natural language processing engine and the sentiment analysis engine, and uses a generative AI model to generate visual information. The input is the meaning of a string and the user's emotional state, and the output is visual information that harmonizes with this. Specifically, the theme and design of the stamp are determined and generated.

[0712] Step 6:

[0713] The server adds textual information related to the generated visual information, compresses the data, and sends it to the terminal. Here, the input is the generated visual information and textual information, and the output is the compressed data. Specifically, the process involves conversion to an image format and data compression.

[0714] Step 7:

[0715] The terminal receives data sent from the server and displays visual information to the user. The input here is compressed data, and the output is visual information that the user can view on the screen. Specifically, the process involves decompressing the data and displaying it on the user interface.

[0716] (Application Example 2)

[0717] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0718] In modern communication, users want to use a variety of stamps to effectively express their emotions. However, traditional stamps are not based on the user's real-time emotions and lack individual customization. Therefore, there is a need for a means to enrich users' emotional expression and strengthen individual communication.

[0719] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0720] In this invention, the server includes a device for receiving input string data, a device for analyzing the string data and generating suitable visual data, and a device for acquiring and analyzing user emotion data. This makes it possible to generate stamps that reflect the user's real-time emotions based on the string data and emotion data.

[0721] "String data" refers to text information entered by users, and is fundamental information for understanding emotions and context.

[0722] "Visual data" refers to visual content that expresses a user's emotions, generated based on text data and sentiment data.

[0723] "Emotional data" refers to data that represents the user's current emotional state, obtained from the user's facial expressions, voice, and other similar information.

[0724] "Visual data style" refers to the characteristics and themes of visual representation determined based on sentiment data and text data.

[0725] A "prompt statement" is an instruction given to a generative AI model, setting the conditions for generating specific visual content.

[0726] A "generative AI model" is a system that uses artificial intelligence to generate new content based on input data.

[0727] The system for realizing this application consists of the following: When a user inputs text data, a device such as a smartphone or smart glasses is used. This device receives the input text data and simultaneously acquires sentiment data using its camera and microphone. The acquired text data and sentiment data are sent to a server.

[0728] The server analyzes the received string data using a natural language processing engine (e.g., Google Cloud Natural Language API) to identify its context and meaning. Simultaneously, it analyzes the user's emotional data using an emotion analysis engine (e.g., Microsoft Azure Emotion API) to determine what emotions the user is experiencing. This information is used as foundational data for generating visual data.

[0729] Next, the server generates prompts for a generative AI model (e.g., OpenAI GPT-3), requesting it to generate visual data based on string data and sentiment data. An example of a prompt might be, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent a positive emotion."

[0730] The generated visual data is compressed using a predetermined compression method and sent to the user's device. Finally, the user's device displays stamps customized according to the user's text data and emotions, which the user can then share in chats and on social media.

[0731] This invention enables users to generate visual content that matches their individual emotional expressions in real time, thereby achieving personalized and emotionally rich communication.

[0732] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0733] Step 1:

[0734] The device receives string data entered by the user and uses the camera and microphone to acquire user emotion data. The input consists of raw string data and sensor data, and the output consists of string data and emotion data.

[0735] Step 2:

[0736] The terminal sends the acquired string data and sentiment data to the server. The input consists of the user's string data and sentiment data, and this data is passed to the server.

[0737] Step 3:

[0738] The server parses string data using a natural language processing engine. String data is passed as input, and its meaning and context are identified as output.

[0739] Step 4:

[0740] The server evaluates emotional data using an emotion analysis engine. The input is emotional data, and the output is the user's real-time emotional state.

[0741] Step 5:

[0742] The server generates prompt sentences based on the analysis results of the string data and sentiment data. This creates specific instructions for the generating AI model. An example of a prompt sentence generated in this step is the instruction, "Display the text 'I had a great time today!' and generate a stamp with bright colors that represent positive emotions."

[0743] Step 6:

[0744] The server generates visual data based on prompt text using a generative AI model. The input is the prompt text, and the output is customized visual data.

[0745] Step 7:

[0746] The server compresses the generated visual data and sends it to the user's terminal. Here, the input is uncompressed visual data, and the output is compressed visual data.

[0747] Step 8:

[0748] The terminal decompresses the received visual data and displays it to the user. In this step, the final output is a stamp customized specifically for the user, which the user can then use within the communication tool.

[0749] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0750] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0751] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0752] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0753] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0754] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0755] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0756] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0757] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0758] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0759] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0760] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0761] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0762] 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.

[0763] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0764] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0765] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0766] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0767] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0768] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0769] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0770] The following is further disclosed regarding the embodiments described above.

[0771] (Claim 1)

[0772] A means for receiving input string data,

[0773] A means for analyzing the aforementioned string data and generating visual data suitable for the string data,

[0774] Means for adding string information based on the string data to the aforementioned visual data,

[0775] Means for transmitting the aforementioned visual data and assigned string information to a communication terminal,

[0776] A system that includes this.

[0777] (Claim 2)

[0778] The system according to claim 1, further comprising means for performing sentiment analysis on the string data and determining the style of the visual data based on the analysis results.

[0779] (Claim 3)

[0780] The system according to claim 1, further comprising means for compressing the aforementioned visual data and string information and transmitting it to a communication terminal.

[0781] "Example 1"

[0782] (Claim 1)

[0783] A means for receiving the input information content,

[0784] Means for analyzing the aforementioned information content and generating visual information suitable for said information content,

[0785] Means for adding information based on the content of the information to the aforementioned visual information,

[0786] Means for transmitting the aforementioned visual information and the assigned information to an information processing device,

[0787] A system that includes this.

[0788] (Claim 2)

[0789] The system according to claim 1, further comprising means for performing emotional analysis on the aforementioned information content and determining the representation of visual information based on the analysis results.

[0790] (Claim 3)

[0791] The system according to claim 1, comprising means for reducing the visual information and information and transmitting it to an information processing device.

[0792] "Application Example 1"

[0793] (Claim 1)

[0794] A means for receiving input string information,

[0795] means for analyzing the aforementioned string information and generating visual information suitable for the string information,

[0796] Means for adding linguistic information based on the string information to the aforementioned visual information,

[0797] Means for transmitting the aforementioned visual information and assigned linguistic information to an information device,

[0798] means comprising a display device that receives and displays the aforementioned visual information,

[0799] A system that includes this.

[0800] (Claim 2)

[0801] The system according to claim 1, comprising means for performing sentiment analysis on the string information, determining the format of visual information based on the analysis results, and displaying the visual information on a display device in a commercial facility.

[0802] (Claim 3)

[0803] The system according to claim 1, comprising means for compressing the visual information and language information and transmitting it to an information device, and receiving the visual information in a format that can be displayed on a user's device.

[0804] "Example 2 of combining an emotion engine"

[0805] (Claim 1)

[0806] A means for receiving input information,

[0807] means for analyzing the aforementioned information and generating visual information based on said information,

[0808] Means for adding textual information based on said visual information,

[0809] Means for transmitting the aforementioned visual information and assigned character information to a communication device,

[0810] A means of analyzing the user's psychological state,

[0811] A means for determining the subject and design format of visual information based on the analysis results,

[0812] A system that includes this.

[0813] (Claim 2)

[0814] The system according to claim 1, further comprising means for compressing the visual information and textual information and transmitting it to a communication device.

[0815] (Claim 3)

[0816] The system according to claim 1, comprising means for generating visual information that is in harmony with the information and the user's psychological state, using a generative AI model.

[0817] "Application example 2 when combining with an emotional engine"

[0818] (Claim 1)

[0819] A device that receives input string data,

[0820] A device that analyzes the aforementioned string data and generates visual data suitable for the string data,

[0821] A device for acquiring user emotion data,

[0822] A device that analyzes the aforementioned emotional data and determines a style of visual data that is in harmony with the emotion,

[0823] A device for adding string information based on string data to the aforementioned visual data,

[0824] A device that transmits the aforementioned visual data and assigned string information to a communication device,

[0825] A system that includes this.

[0826] (Claim 2)

[0827] The system according to claim 1, comprising an apparatus that generates prompt sentences based on the string data and sentiment data, and creates visual data using a generation AI model.

[0828] (Claim 3)

[0829] The system according to claim 1, further comprising a device for compressing the aforementioned visual data and string information and transmitting it to a communication device. [Explanation of Symbols]

[0830] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving input string data, means for analyzing the aforementioned string data and generating visual data suitable for the string data, Means for adding string information based on the string data to the aforementioned visual data, Means for transmitting the aforementioned visual data and assigned string information to a communication terminal, A system that includes this.

2. The system according to claim 1, further comprising means for performing sentiment analysis on the string data and determining the style of the visual data based on the analysis results.

3. The system according to claim 1, further comprising means for compressing the aforementioned visual data and string information and transmitting it to a communication terminal.

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