system

Abstract

We provide the system. [Solution] A means of receiving inquiries from users, A means of analyzing received inquiries using natural language processing technology to identify frequently asked questions, A means of using generation technology to generate the optimal answer to a specific question, A means for generating video content using speech synthesis and image generation technology based on the generated response, A means of delivering the generated video content to users, 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 method for controlling a persona chatbot, which is performed by at least one processor, the method including receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In many companies, there is a situation where inquiries from customers cover a wide range, imposing a heavy burden on the customer service department. In the conventional support methods using text and still images, it may take time for users to accurately understand the information. In particular, for inquiries regarding complex procedures and operations, visual understanding is important, but the current systems have limited means to efficiently provide this. In such a situation, it is difficult for users to solve problems by themselves through self-service, and as a result, there is a problem that inquiries by phone and chat continue to increase. 【Means for Solving the Problems】 【0005】 This invention relates to a system that analyzes user inquiries and automatically generates video answers to frequently asked questions. Specifically, it includes means for receiving user inquiries, means for analyzing the content of inquiries using natural language processing technology, and means for identifying frequently asked questions. Subsequently, it provides means for generating optimal answers to those questions using generation technology and generating visually easy-to-understand video content using speech synthesis and image generation technology, thereby enabling users to obtain answers quickly and efficiently through visual information. This can reduce the burden on customer service and decrease the number of inquiries. 【0006】 "User inquiries" refer to questions and requests that system users submit to seek information or instructions. 【0007】 "Natural language processing technology" refers to technologies that enable computers to understand human language, and involves processes such as tokenization, part-of-speech tagging, and syntactic analysis. 【0008】 "Frequently asked questions" refer to questions or inquiries that are repeatedly sent by a large number of users. 【0009】 "Generative technology" refers to technologies for dynamically generating new data or text based on specific input information. 【0010】 "Speech synthesis" is a technology that generates speech that resembles a human voice from text information. 【0011】 "Image generation technology" refers to technologies for creating visual information, including computer graphics and animation. 【0012】 "Video content" refers to video data used to convey information in a dynamic media format that combines audio and visual information. 【0013】 "Means of delivering to users" refers to the communication and transmission functions necessary to deliver generated video content to users. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 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." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 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. 【0025】 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). 【0026】 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. 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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". 【0035】 This invention provides a system that automatically generates and delivers video responses to user inquiries. The system consists of a server, terminals, and users, with the program primarily running on the server. 【0036】 System Configuration 【0037】 The server acts as the central hub, receiving and analyzing user inquiries, generating responses, creating video content, and delivering it to the user. The terminal functions as an interface for users to input inquiries, and also acts as a device for receiving and displaying / playing the generated video content. 【0038】 Program processing 【0039】 Users send inquiries to the server using their devices. These inquiries are typically in text format, describing the problems or questions the user wants to resolve. The server uses natural language processing techniques to analyze the received text and understand the intent of the inquiry. This process involves extracting important keywords and analyzing sentence structure. Based on the analysis results, the server identifies frequently asked questions. 【0040】 For each identified question, the server uses generation technology to prepare the optimal answer. At this stage, relevant information is collected to generate a comprehensive and clear answer to the user's question. Once the answer is generated, the server uses speech synthesis to convert the answer text into speech and then utilizes image generation technology to create a visually appealing visual. 【0041】 Next, the server integrates the generated audio and images to complete the video content. This video is structured to be intuitively understandable to the user and helps to visually explain complex procedures and concepts. 【0042】 Once the video content is complete, the server prepares to deliver it to the user's device. The device receives the video and notifies the user, allowing them to view the generated video. This entire process allows users to quickly and efficiently obtain information for problem solving. 【0043】 Specific example 【0044】 For example, consider a scenario where a user asks from their device, "How do I set up my smartphone?" The server receives this inquiry and uses natural language processing to analyze it as a question about "smartphone initial setup." Based on this analysis, if it is recognized as a frequently asked question, the server uses generative technology to prepare text instructions for the setup process, performs speech synthesis and image generation, and integrates it all into a video. This video is then delivered to the device, allowing the user to visually learn how to set up their smartphone by playing the video. This entire process improves the user experience and reduces the burden on customer service. 【0045】 The following describes the processing flow. 【0046】 Step 1: 【0047】 Users use their devices to enter inquiries containing specific problems or questions and send them to the server. Inquiries are typically entered in text format. 【0048】 Step 2: 【0049】 The server receives the query and uses a natural language processing engine to parse the text. Here, the server performs tokenization, sentence structure analysis, and keyword extraction to understand the user's intent behind the question. 【0050】 Step 3: 【0051】 The server identifies frequently asked questions based on the analysis results by comparing the inquiries with an existing FAQ database. This process utilizes machine learning algorithms based on past inquiry patterns. 【0052】 Step 4: 【0053】 The server executes generation techniques to produce the best possible answer to the identified question. The server collects relevant information and generates a clear and comprehensive answer to the question. 【0054】 Step 5: 【0055】 The server converts the generated response text into audio data using speech synthesis technology. Simultaneously, it uses image generation technology to create related images and animations for visual explanation. 【0056】 Step 6: 【0057】 The server integrates audio data and images to generate the final video content. The video is structured to be easy for the user to understand. 【0058】 Step 7: 【0059】 The server delivers the completed video content to the user's device. At this time, a link or notification for delivery is generated. 【0060】 Step 8: 【0061】 The device displays a notification to the user about video content it has received, allowing the user to play the video. The user watches the video and obtains information through the device. 【0062】 (Example 1) 【0063】 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." 【0064】 In modern information delivery systems, responses to user inquiries are often handled manually, making rapid responses difficult. Furthermore, text-based information delivery presents challenges in understanding complex procedures and concepts. Current systems lack sufficient visual and auditory enrichment to enhance the user experience, highlighting the need for efficient and intuitive information delivery methods. 【0065】 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. 【0066】 In this invention, the server includes means for receiving and analyzing inquiries from users, means for extracting important words and phrases using natural language processing technology and performing sentence structure analysis, and means for generating optimal answers using a generative AI model and generating video content using speech synthesis and image generation technology. This makes it possible to provide users with information quickly and in a visually and aurally easy-to-understand format. 【0067】 A "user" is an entity that seeks to obtain information by using the system, and refers to an individual or organization that makes an inquiry. 【0068】 "Inquiry" refers to the act of a user sending a problem or question they want resolved to the system in text format, or the content of that inquiry. 【0069】 "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language, and encompasses methods for analyzing text and understanding its meaning. 【0070】 A "generative AI model" refers to a mathematical or algorithmic method that uses artificial intelligence technology to create new information from given data. 【0071】 "Speech synthesis" refers to the technology of artificially generating voices that resemble human voices based on text information. 【0072】 "Image generation technology" refers to the technology used by computers to generate digital images, and is a means of creating visual content to convey information visually. 【0073】 "Video content" refers to media delivered in a digital format that combines visual and auditory information, and is created with the purpose of aiding user understanding. 【0074】 "Distribution" refers to the means of communication and actions used to deliver generated information or content to users. 【0075】 This invention relates to a system that automatically generates and delivers video responses to user inquiries. This system consists of a server, terminals, and users. The program primarily runs on the server. 【0076】 The server receives user inquiries and analyzes the text using natural language processing (NLP) techniques. NLP includes extracting important keywords and analyzing sentence structure. This allows the server to understand the user's intent. During this process, generative AI models are used to generate optimal answers to frequently asked questions, and these answers are converted into speech using speech synthesis technology. Additionally, image generation technology is used to create relevant visual representations. 【0077】 The device functions as an interface for users to enter inquiries, and also receives video content delivered from the server and notifies the user. Users can watch the videos through the device and intuitively understand the information. For example, in response to an inquiry such as "How do I set up my smartphone?", the server generates a video based on the relevant information and delivers it to the device, allowing the user to receive visual guidance. 【0078】 An example of a prompt message is, "Please send instructions to the generative AI model to generate a video explaining how to set up a smartphone." 【0079】 Implementing this system will improve the user experience, automate time-consuming inquiry handling, and provide information efficiently. 【0080】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0081】 Step 1: 【0082】 Users input problems or questions they want to resolve in text format via their terminal and send the inquiry to the server. The entered text serves as the initial input data and is necessary to clarify the user's intent. 【0083】 Step 2: 【0084】 The server first receives the query from the user and analyzes it using natural language processing techniques. It extracts important words and phrases from the received text and analyzes the sentence structure. This is part of the data processing and creates basic data to identify the user's intent. 【0085】 Step 3: 【0086】 The server uses key vocabulary and syntactic information to determine whether a question is frequently asked. The natural language processing analysis results become the input data, and the identification of frequently occurring questions becomes the output. At this stage, the type of answer required becomes clear. 【0087】 Step 4: 【0088】 The server uses a generative AI model to generate the optimal answer to the identified question. Information based on the analysis results is input, and specific answer text is output. During this process, it is also possible to access external data sources to collect additional information. 【0089】 Step 5: 【0090】 The server uses speech synthesis technology to convert the generated responses into speech, and then uses image generation technology to create related visuals. Based on this processed data, audio files and image data are output. This makes it possible to provide visual information to the user. 【0091】 Step 6: 【0092】 The server integrates audio and video to generate video content. Audio and image files are input, and a video file is output. This video supports intuitive understanding. 【0093】 Step 7: 【0094】 The server delivers the generated video content to the user's device. Here, the video file is the input data, and playback on the user's device is the final output. The device receives this video and notifies the user so they can immediately review it. The user can then watch the video on their device and use it to resolve their questions. 【0095】 (Application Example 1) 【0096】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0097】 In today's world, where speed of information acquisition is paramount, users require quick and easily understandable information to solve complex problems. However, traditional text-based inquiry and answer systems struggle to achieve this, and are particularly insufficient for users who prefer to grasp information visually and aurally. To address this challenge, it is necessary to create guide videos based on the information users inquire about, providing them visually and intuitively. 【0098】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0099】 In this invention, the server includes means for receiving inquiries from users, means for analyzing the received inquiries using natural language processing technology to identify frequently asked questions, means for using generation technology to generate optimal answers to the identified questions, means for generating audiovisual content using speech synthesis and image generation technology based on the generated answers, means for generating guide videos combining the audiovisual content, and means for delivering the generated guide videos to users. As a result, users can utilize guide videos that are quick and intuitively understandable to address their questions, enabling efficient problem solving. 【0100】 A "user" is someone who makes inquiries to the system to obtain information or solutions. 【0101】 An "inquiry" is a way for a user to express a problem or question they want to resolve, and it is the content that the system will analyze. 【0102】 "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to extract the intent behind a query. 【0103】 "Generative technology" refers to technology that automatically generates appropriate answers to specific questions. 【0104】 "Speech synthesis" is a technology that converts text information into speech. 【0105】 "Image generation technology" refers to the technology of generating new digital images, with the aim of providing visual information. 【0106】 "Audiovisual content" is content that integrates sound and images to convey information visually and aurally. 【0107】 "Distributing" refers to the technical actions taken to deliver generated content to users. 【0108】 The system for realizing this invention mainly consists of a server and a user terminal. The specific technical configuration and operation for implementing this system are described below. 【0109】 The server first receives a query from the user. The query is typically in text format and is sent from the user's device to the server over the network. The server then uses natural language processing techniques to analyze the user's query. For this analysis, the server uses the Google® Cloud Natural Language API. This allows the server to understand the intent of the query and extract key terms. 【0110】 Based on the analysis results, the server identifies frequently asked questions and uses generation technology to prepare optimal answers. At this stage, it retrieves relevant data from external sources as needed and utilizes OpenAI®'s generative AI model to generate answers. 【0111】 Next, the server uses speech synthesis and image generation technologies to create visuals and audio. This involves using Amazon Polly to convert text to speech and OpenAI's DALL-E to generate visual elements. The generated audio and images are integrated into audiovisual content, forming an easy-to-understand guide video for the user. 【0112】 Finally, the server delivers the generated guide video to the user's device. The user receives and plays the guide video delivered via their device, obtaining information that is easy to understand intuitively. 【0113】 For example, if an inquiry is made asking "How do I use the new Instant Pot?", the system will automatically generate a guide video explaining the operation method, visually illustrating the detailed steps. 【0114】 An example of a prompt message would be, "Generate a video teaching the basic operation of the Instant Pot." In this way, the invention provides a system that enables users to efficiently obtain information and assists in problem-solving. 【0115】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0116】 Step 1: 【0117】 Users use a terminal to input inquiries in text format and send them to the server. The information entered often concerns problems or questions they want resolved. In this step, the terminal acts as an interface to accurately receive the user's text information. 【0118】 Step 2: 【0119】 The server analyzes incoming queries using natural language processing techniques. Specifically, it uses the Google Cloud Natural Language API to extract the intent and important keywords from the input text. The output is structured data that helps understand the meaning of the query. 【0120】 Step 3: 【0121】 Based on the analysis results, the server identifies frequently asked questions. This identification process allows the server to build a foundation for generating optimal answers to relevant questions. The output is a list of the identified single or multiple questions. 【0122】 Step 4: 【0123】 The server leverages OpenAI's generative AI model to generate the best possible answer to the identified question. This generation process involves obtaining relevant data from external sources as needed to improve the quality of the answer generation. The output is a comprehensive answer text corresponding to the user's question. 【0124】 Step 5: 【0125】 The server uses Amazon Polly to synthesize speech based on the generated response text and OpenAI's DALL-E to create images. This provides audiovisual elements that are easy for the user to understand. The output consists of an audio file and an image file. 【0126】 Step 6: 【0127】 The server integrates the generated audio and image files to create visual content as a single guide video. This integration process allows users to understand the information visually and aurally. The output is a guide video file. 【0128】 Step 7: 【0129】 The server delivers the generated guide video to the user's device. The device notifies the user of the received video and displays it, making it available for viewing. This step allows the user to intuitively obtain the information. 【0130】 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. 【0131】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0132】 System Configuration 【0133】 The server is responsible for receiving and analyzing inquiries, generating responses, recognizing sentiment, creating video content, and delivering it. The terminal provides an interface for user inquiry input and is a device for displaying and playing the generated video content. Users use the terminal to submit inquiries and receive responses. 【0134】 Program processing 【0135】 Users input inquiries from their devices and send them to the server. This can be done via text input or voice input. The server analyzes the received inquiries using a natural language processing engine to understand their structure and intent. Simultaneously, an emotion engine analyzes the user's text and voice data to recognize their emotions. This helps the server understand the user's feelings when making the inquiry. 【0136】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. In doing so, it adjusts the tone and level of detail of the answers according to the recognized sentiment information. For example, if a user expresses dissatisfaction, it may consider adding a more polite and detailed explanation. 【0137】 Once the response is prepared, the server uses speech synthesis and image generation technologies to construct the video content. Speech synthesis uses emotionally appropriate tones, and image generation selects suitable visuals. By integrating these, the system creates a video that users can effectively understand both visually and aurally. 【0138】 Finally, the server sends the generated video content to the user's device. The device receives the video and displays a notification or link to the user for viewing. The user plays the video through the device, receives information, and experiences an emotionally sensitive response. 【0139】 Specific example 【0140】 As a concrete example, suppose a user asks, "I want to know why the server is slow to respond." The server receives this inquiry and analyzes it using natural language processing while simultaneously recognizing the user's "frustration" with an emotion engine. As a result, when preparing the answer, the server adds empathetic language and generates an answer that includes detailed troubleshooting and solutions. The completed video content uses a soft tone of voice and is accompanied by visuals that show the server's operating principles and related processes, allowing the user to accurately understand the problem. In this way, the present invention improves the user experience and facilitates smoother problem solving. 【0141】 The following describes the processing flow. 【0142】 Step 1: 【0143】 The user uses their device to type or record their inquiry via voice and send it to the server. The inquiry includes explanations and specific questions. 【0144】 Step 2: 【0145】 The server receives the query and starts the natural language processing engine to begin text analysis. Here, the server performs tokenization, analyzes the sentence structure, and understands the user's intent. 【0146】 Step 3: 【0147】 The server uses an emotion engine to recognize emotions from the user's input text or voice. The server analyzes the emotion data to determine whether the user is experiencing emotions such as anger, anxiety, or joy. 【0148】 Step 4: 【0149】 The server uses the analysis results and sentiment information to match frequently asked questions with those in the FAQ database. The server determines whether the inquiry has been received many times in the past. 【0150】 Step 5: 【0151】 The server uses generation technology to prepare the best possible answer to the identified question. At this stage, the server takes emotions into consideration and adjusts for gentle vocabulary selection and level of detail. 【0152】 Step 6: 【0153】 The server uses speech synthesis technology to convert the generated responses into speech. Furthermore, the server uses image generation technology to create visuals and animations that support the explanations. 【0154】 Step 7: 【0155】 The server integrates audio data and visuals to complete the video content. The video is composed with a tone that takes the user's emotions into consideration. 【0156】 Step 8: 【0157】 The server generates video content and delivers it to the user's device. The device receives the content and displays a viewing notification to the user. 【0158】 Step 9: 【0159】 The user plays the video through their device and reviews its content. This allows the user to understand the answer and solve the problem through both sight and sound. 【0160】 (Example 2) 【0161】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0162】 Traditional user support systems have struggled to generate responses that take user emotions into account, making it difficult to improve the user experience. In particular, there is a need to appropriately analyze the nuances of emotional inquiries and adjust the tone and content of responses in real time, but sufficient solutions have not been provided in this regard. 【0163】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0164】 In this invention, the server includes means for receiving inquiries from users, data processing means for analyzing the received inquiries using natural language processing techniques to identify frequently asked questions, and means for using generation techniques to generate optimal answers to the identified questions. This enables the recognition of user emotions and the generation and delivery of appropriate answers that correspond to those emotions. 【0165】 "Means for receiving inquiries" refers to a device or program for receiving inquiries from users in text or voice. 【0166】 "Natural language processing technology" is a technique that enables computers to understand and analyze human language, and is used to grasp the intent and content of inquiries. 【0167】 "Data processing means" refers to technology or apparatus for analyzing received inquiry data and performing calculations and decisions to identify frequently asked questions. 【0168】 "Generative technology" refers to techniques for creating mechanically optimized answers to specific questions. 【0169】 "Emotional analysis means" refers to a device or program that recognizes emotions from a user's text or voice and adjusts the content and tone of the response based on the results. 【0170】 "Speech synthesis technology" is a technology that generates human speech based on text data, and is used to generate the audio portion of video content. 【0171】 "Image generation technology" refers to the technology of creating images and animations to visually support the content of answers. 【0172】 "Means for generating video content" refers to a function that integrates speech synthesis technology and image generation technology to generate information transmission media through sight and sound. 【0173】 "Means of delivering video content" refers to communication technologies or network functions used to deliver generated video content to users. 【0174】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion analysis function that recognizes the user's emotions. The system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0175】 The server receives user inquiries and uses a natural language processing engine to analyze the input inquiries. The natural language processing engine is used to analyze the sentence structure of the inquiries and understand their content and intent. Furthermore, sentiment analysis tools diagnose the emotions contained in the user's inquiries and record them in a database. This makes it possible to generate optimal responses that are tailored to the user's emotions. 【0176】 Based on the analyzed data, the server generates answers to the identified questions using generation technology. By using a generation AI model, highly optimized answers can be created. Furthermore, accessing external data sources allows for the acquisition of additional information, enabling the provision of more detailed and accurate answers. 【0177】 The generated responses are converted into audio data with emotionally nuanced tones using speech synthesis technology. Simultaneously, visual data is created using image generation technology to clearly visualize the content of the responses. The server integrates this data to build video content that enhances the user experience. 【0178】 Finally, the server sends the generated video content to the user's device. After receiving the video, the device provides the user with a notification or link prompting them to watch it. The user can play the video on their device, receive information through sight and sound, and obtain a satisfactory answer to their inquiry. 【0179】 As a concrete example, consider a case where a user asks, "Please tell me how to install product X." The server analyzes the inquiry using natural language processing, and an emotion analysis tool recognizes the emotion of "confusion." The generative AI model provides an answer with installation instructions using comprehensive and easy-to-understand language. The generated video content visualizes the installation procedure with illustrations and is explained in a soft-toned voice. 【0180】 Example prompt: "Explain how to create an empathetic video response if a user is having trouble installing product X." 【0181】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0182】 Step 1: 【0183】 The user enters the inquiry from the terminal. The user can enter the question in text or voice format. This input data is converted into digital data by the terminal and sent to the server. There is text or voice data as input, and the output is digitized inquiry data. 【0184】 Step 2: 【0185】 The server passes the received digital data to a natural language processing engine, which analyzes the sentence structure and intent of the query. This analysis identifies the subject and main purpose of the query. The input is digitized query data, and the output is the analyzed query information. Specifically, the meaning and context of words are understood through natural language processing. 【0186】 Step 3: 【0187】 The server analyzes the user's emotions using emotion analysis tools. It extracts emotional elements from text and audio data to identify the user's emotional state. The input for this step is digitized inquiry data, and the output is user emotion information. Specifically, emotion analysis identifies emotions associated with the inquiry (e.g., "satisfied," "dissatisfied," "interested," etc.). 【0188】 Step 4: 【0189】 The server generates the optimal answer using a generative AI model based on the analyzed query and sentiment information. It selects the most appropriate answer for each query based on frequently occurring question patterns and adjusts the tone according to the sentiment. The input consists of analyzed query information and sentiment information, and the output is generated answer data. For specific questions, additional information is obtained from external data sources to refine the answer. 【0190】 Step 5: 【0191】 The server uses speech synthesis technology to convert responses into audio data and image generation technology to create visual representations. Audio tones tailored to the user's emotions and image materials relevant to the responses are generated and integrated into video content. The input is the generated response data, and the output is the video content. This effectively communicates information to the user through both sight and sound. 【0192】 Step 6: 【0193】 The server delivers the generated video content to the terminal. The terminal receives the video and provides the user with a notification or a viewing link. The input is video content, and the output is notification information for the user. The user can play the video and receive the information via the terminal. 【0194】 (Application Example 2) 【0195】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0196】 In modern information processing, responding quickly and appropriately to user inquiries is a crucial challenge. In particular, there is a demand for improved customer satisfaction by providing responses that consider user emotions, but current systems cannot fully meet this need. Therefore, technology is needed to recognize user emotions and appropriately customize responses. 【0197】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0198】 In this invention, the server includes means for receiving information from the user, means for analyzing the received information using natural language processing technology to identify frequently asked information, means for using generation technology to generate the optimal response to the identified information, means for analyzing the user's emotions using an emotion recognition engine to adjust the tone and details of the response, and means for delivering the generated visual content to the user. This makes it possible to quickly and effectively provide customized responses that take the user's emotions into consideration. 【0199】 "Means for receiving information from users" refers to a system or device for receiving voice or text inquiries sent by users and processing that data. 【0200】 "Natural language processing technology" is a technology that uses computers to analyze and understand human language, and has the ability to analyze the grammar and intent of user inquiries. 【0201】 "Means of identifying frequently asked information" refers to algorithms or processes for analyzing user inquiries and identifying the most frequently occurring questions or topics. 【0202】 "Means using generation technology" refers to technical means for automatically creating an appropriate response based on the aforementioned analysis results. 【0203】 An "emotion recognition engine" is an algorithm or system that analyzes a user's voice tone and text to identify their emotional state. 【0204】 "Means of adjusting the tone and details of responses" refers to technologies that modify the tone and content of generated responses based on the user's emotions. 【0205】 "Means of delivering generated visual content to users" refers to a function that sends the created video or other media to the user's device, enabling viewing and playback. 【0206】 This invention is a system that generates video content in response to user inquiries and provides responses that take the user's emotions into consideration. The following system configuration is possible for implementing the invention. 【0207】 The server uses Google Cloud's natural language processing API to analyze user inquiries from voice or text, understanding their structure and intent. It also utilizes IBM Watson® Tone Analyzer for sentiment recognition, recognizing the user's emotional state. This enables the generation of responses that match the user's emotions, providing detailed and optimal responses. 【0208】 Furthermore, the response generation utilizes the Adobe Premiere Pro API to construct video content combining speech synthesis and visuals. The generated video content is sent via the internet to the user's device, i.e., a smartphone or computer. The device receives this video and displays notifications and links to the user, and plays the video. 【0209】 For example, when a user inquires that an item they ordered was damaged, the system recognizes their frustration. The generated video explains the return process in detail, along with an apology. The video includes a gentle voice and clear visual guidance, allowing the user to resolve the issue with confidence. 【0210】 As an example of a prompt to a generating AI model, the text "Please create a customized video explaining the detailed procedures for handling damaged ordered items, including an apology for any inconvenience caused" is shown. This prompt allows the system to autonomously provide the most appropriate response to the user. 【0211】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0212】 Step 1: 【0213】 The user inputs their inquiry using voice or text from their device and sends it to the server. The input data is raw data about the user's question or opinion. The server receives this raw data and prepares it for the next processing step. 【0214】 Step 2: 【0215】 The server analyzes the received query data using Google Cloud's natural language processing API. During the analysis, it grasps the structure of the text and identifies its meaning and intent. This step generates data that clarifies the main points and subject of the question. 【0216】 Step 3: 【0217】 The server uses IBM Watson's Tone Analyzer to extract sentiment data from user inquiries. It analyzes voice tone and text content to identify the user's emotional state. This process outputs data indicating the emotional state the user is in when making the inquiry. 【0218】 Step 4: 【0219】 The server generates a response based on the analyzed query content and sentiment data. To prepare an appropriate answer, it performs data collection and information integration, including access to external sources. In this step, a generative AI model is utilized to create customized response data based on the prompt. 【0220】 Step 5: 【0221】 The server uses the Adobe Premiere Pro API to perform speech synthesis and image generation on the generated response, constructing video content. If necessary, it modifies the speech tone and selects visual elements based on emotional information. This results in the final video data. 【0222】 Step 6: 【0223】 The server delivers the generated video content to the user's device. During this delivery process, data is transmitted over the internet and made available for reception on the device. The output of this step is a video file playable on the device. 【0224】 Step 7: 【0225】 The device notifies and displays the received video content to the user. The user can play the video and receive information visually and aurally. As a result, problem solving is facilitated through customized responses. 【0226】 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. 【0227】 Data generation model 58 is a type of 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. 【0228】 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. 【0229】 [Second Embodiment] 【0230】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0231】 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. 【0232】 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). 【0233】 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. 【0234】 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. 【0235】 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). 【0236】 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. 【0237】 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. 【0238】 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. 【0239】 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. 【0240】 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. 【0241】 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". 【0242】 This invention provides a system that automatically generates and delivers video responses to user inquiries. The system consists of a server, terminals, and users, with the program primarily running on the server. 【0243】 System Configuration 【0244】 The server acts as the central hub, receiving and analyzing user inquiries, generating responses, creating video content, and delivering it to the user. The terminal functions as an interface for users to input inquiries, and also acts as a device for receiving and displaying / playing the generated video content. 【0245】 Program processing 【0246】 Users send inquiries to the server using their devices. These inquiries are typically in text format, describing the problems or questions the user wants to resolve. The server uses natural language processing techniques to analyze the received text and understand the intent of the inquiry. This process involves extracting important keywords and analyzing sentence structure. Based on the analysis results, the server identifies frequently asked questions. 【0247】 For each identified question, the server uses generation technology to prepare the optimal answer. At this stage, relevant information is collected to generate a comprehensive and clear answer to the user's question. Once the answer is generated, the server uses speech synthesis to convert the answer text into speech and then utilizes image generation technology to create a visually appealing visual. 【0248】 Next, the server integrates the generated audio and images to complete the video content. This video is structured to be intuitively understandable to the user and helps to visually explain complex procedures and concepts. 【0249】 Once the video content is complete, the server prepares to deliver it to the user's device. The device receives the video and notifies the user, allowing them to view the generated video. This entire process allows users to quickly and efficiently obtain information for problem solving. 【0250】 Specific example 【0251】 For example, consider a scenario where a user asks from their device, "How do I set up my smartphone?" The server receives this inquiry and uses natural language processing to analyze it as a question about "smartphone initial setup." Based on this analysis, if it is recognized as a frequently asked question, the server uses generative technology to prepare text instructions for the setup process, performs speech synthesis and image generation, and integrates it all into a video. This video is then delivered to the device, allowing the user to visually learn how to set up their smartphone by playing the video. This entire process improves the user experience and reduces the burden on customer service. 【0252】 The following describes the processing flow. 【0253】 Step 1: 【0254】 Users use their devices to enter inquiries containing specific problems or questions and send them to the server. Inquiries are typically entered in text format. 【0255】 Step 2: 【0256】 The server receives the query and uses a natural language processing engine to parse the text. Here, the server performs tokenization, sentence structure analysis, and keyword extraction to understand the user's intent behind the question. 【0257】 Step 3: 【0258】 The server identifies frequently asked questions based on the analysis results by comparing the inquiries with an existing FAQ database. This process utilizes machine learning algorithms based on past inquiry patterns. 【0259】 Step 4: 【0260】 The server executes generation techniques to produce the best possible answer to the identified question. The server collects relevant information and generates a clear and comprehensive answer to the question. 【0261】 Step 5: 【0262】 The server converts the generated response text into audio data using speech synthesis technology. Simultaneously, it uses image generation technology to create related images and animations for visual explanation. 【0263】 Step 6: 【0264】 The server integrates audio data and images to generate the final video content. The video is structured to be easy for the user to understand. 【0265】 Step 7: 【0266】 The server delivers the completed video content to the user's device. At this time, a link or notification for delivery is generated. 【0267】 Step 8: 【0268】 The device displays a notification to the user about video content it has received, allowing the user to play the video. The user watches the video and obtains information through the device. 【0269】 (Example 1) 【0270】 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." 【0271】 In modern information delivery systems, responses to user inquiries are often handled manually, making rapid responses difficult. Furthermore, text-based information delivery presents challenges in understanding complex procedures and concepts. Current systems lack sufficient visual and auditory enrichment to enhance the user experience, highlighting the need for efficient and intuitive information delivery methods. 【0272】 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. 【0273】 In this invention, the server includes means for receiving and analyzing inquiries from users, means for extracting important words and phrases using natural language processing technology and performing sentence structure analysis, and means for generating optimal answers using a generative AI model and generating video content using speech synthesis and image generation technology. This makes it possible to provide users with information quickly and in a visually and aurally easy-to-understand format. 【0274】 A "user" is an entity that seeks to obtain information by using the system, and refers to an individual or organization that makes an inquiry. 【0275】 "Inquiry" refers to the act of a user sending a problem or question they want resolved to the system in text format, or the content of that inquiry. 【0276】 "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language, and encompasses methods for analyzing text and understanding its meaning. 【0277】 A "generative AI model" refers to a mathematical or algorithmic method that uses artificial intelligence technology to create new information from given data. 【0278】 "Speech synthesis" refers to the technology of artificially generating voices that resemble human voices based on text information. 【0279】 "Image generation technology" refers to the technology for a computer to generate digital images and means of creating visual content for transmitting information visually. 【0280】 "Video content" refers to media provided in a digital format that combines visual and auditory information and is generated for the purpose of assisting user understanding. 【0281】 "Distribution" refers to the communication means or actions for delivering the generated information or content to users. 【0282】 The present invention relates to a system that automatically generates and distributes video responses to user inquiries. This system is composed of a server, a terminal, and a user. The program is mainly executed on the server. 【0283】 The server receives inquiries from users and analyzes the text using natural language processing technology. Natural language processing includes extraction of important phrases and parsing of sentence structures. Thereby, the server can understand the user's intention. In this process, an optimal response to frequent inquiries is generated using a generative AI model, and the response is converted into speech using speech synthesis technology. Also, related visual visuals are created using image generation technology. 【0284】 The terminal functions as an interface for the user to input inquiries, receives video content distributed from the server, and notifies the user. The user can watch the video through the terminal and intuitively understand the information. For example, for a received inquiry such as "Please teach me how to initialize a smartphone", the server generates a video based on the corresponding information and distributes it to the terminal, enabling the user to receive visual guidance. 【0285】 Examples of prompt texts include "Please send an instruction to generate a video explaining how to initialize a smartphone on a generative AI model." 【0286】 By implementing this system, the user experience is improved, time-consuming inquiries are automated, and information is provided efficiently. 【0287】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0288】 Step 1: 【0289】 The user inputs the problem or question to be solved via the terminal in text form and sends the inquiry to the server. The input text is the initial input data and is necessary to clarify the user's intention. 【0290】 Step 2: 【0291】 The server first receives the inquiry from the user and performs analysis using natural language processing technology. It extracts important phrases with the received text as input and analyzes the sentence structure. This is part of data processing and creates basic data for identifying the user's intention. 【0292】 Step 3: 【0293】 The server uses the important phrases and syntactic information to determine whether it is a frequently asked question. Here, the analysis result of natural language processing becomes the input data, and the identification of frequently asked questions becomes the output. At this stage, it becomes clear what kind of answer is required. 【0294】 Step 4: 【0295】 The server uses the generative AI model to generate an optimal answer to the identified question. Information based on the analysis result is input, and specific answer text is output. It is also possible to access external data sources to collect additional information in this process. 【0296】 Step 5: 【0297】 The server uses speech synthesis technology to convert the generated responses into speech, and then uses image generation technology to create related visuals. Based on this processed data, audio files and image data are output. This makes it possible to provide visual information to the user. 【0298】 Step 6: 【0299】 The server integrates audio and video to generate video content. Audio and image files are input, and a video file is output. This video supports intuitive understanding. 【0300】 Step 7: 【0301】 The server delivers the generated video content to the user's device. Here, the video file is the input data, and playback on the user's device is the final output. The device receives this video and notifies the user so they can immediately review it. The user can then watch the video on their device and use it to resolve their questions. 【0302】 (Application Example 1) 【0303】 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." 【0304】 In today's world, where speed of information acquisition is paramount, users require quick and easily understandable information to solve complex problems. However, traditional text-based inquiry and answer systems struggle to achieve this, and are particularly insufficient for users who prefer to grasp information visually and aurally. To address this challenge, it is necessary to create guide videos based on the information users inquire about, providing them visually and intuitively. 【0305】 The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0306】 In this invention, the server includes means for receiving an inquiry from a user, means for analyzing the received inquiry using natural language processing technology to identify frequently asked questions, means for using a generation technology to generate an optimal answer to the identified question, means for generating audiovisual content using speech synthesis and image generation technologies based on the generated answer, means for generating a guide video combining the audiovisual content, and means for distributing the generated guide video to the user. As a result, the user can utilize a guide video that is quickly and intuitively understandable for doubts, enabling efficient problem-solving. 【0307】 A "user" is a person who makes an inquiry to the system to obtain information or a solution. 【0308】 An "inquiry" is an expression of a problem or doubt that a user wants to solve, and is the content to be analyzed by the system. 【0309】 "Natural language processing technology" is a technology for a computer to understand and analyze human language, and is used to extract the intention of an inquiry. 【0310】 "Generation technology" is a technology for automatically creating an appropriate answer to a specific question. 【0311】 "Speech synthesis" is a technology for converting text information into speech. 【0312】 "Image generation technology" is a technology for newly generating a digital image and is for the purpose of providing visual information. 【0313】 "Audiovisual content" integrates sound and images and conveys information visually and auditorily. 【0314】 "Distributing" refers to the technical actions taken to deliver generated content to users. 【0315】 The system for realizing this invention mainly consists of a server and a user terminal. The specific technical configuration and operation for implementing this system are described below. 【0316】 The server first receives a query from the user. The query is typically in text format and is sent from the user's device to the server over the network. The server then uses natural language processing techniques to analyze the user's query. For this analysis, the server uses the Google Cloud Natural Language API to understand the intent of the query and extract key terms. 【0317】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. At this stage, it retrieves relevant data from external sources as needed and utilizes OpenAI's generative AI model to generate the answers. 【0318】 Next, the server uses speech synthesis and image generation technologies to create visuals and audio. This involves using Amazon Polly to convert text to speech and OpenAI's DALL-E to generate visual elements. The generated audio and images are integrated into audiovisual content, forming an easy-to-understand guide video for the user. 【0319】 Finally, the server delivers the generated guide video to the user's device. The user receives and plays the guide video delivered via their device, obtaining information that is easy to understand intuitively. 【0320】 For example, if an inquiry is made asking "How do I use the new Instant Pot?", the system will automatically generate a guide video explaining the operation method, visually illustrating the detailed steps. 【0321】 An example of a prompt message would be, "Generate a video teaching the basic operation of the Instant Pot." In this way, the invention provides a system that enables users to efficiently obtain information and assists in problem-solving. 【0322】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0323】 Step 1: 【0324】 Users use a terminal to input inquiries in text format and send them to the server. The information entered often concerns problems or questions they want resolved. In this step, the terminal acts as an interface to accurately receive the user's text information. 【0325】 Step 2: 【0326】 The server analyzes incoming queries using natural language processing techniques. Specifically, it uses the Google Cloud Natural Language API to extract the intent and important keywords from the input text. The output is structured data that helps understand the meaning of the query. 【0327】 Step 3: 【0328】 Based on the analysis results, the server identifies frequently asked questions. This identification process allows the server to build a foundation for generating optimal answers to relevant questions. The output is a list of the identified single or multiple questions. 【0329】 Step 4: 【0330】 The server leverages OpenAI's generative AI model to generate the best possible answer to the identified question. This generation process involves obtaining relevant data from external sources as needed to improve the quality of the answer generation. The output is a comprehensive answer text corresponding to the user's question. 【0331】 Step 5: 【0332】 The server uses Amazon Polly to synthesize speech based on the generated response text and OpenAI's DALL-E to create images. This provides audiovisual elements that are easy for the user to understand. The output consists of an audio file and an image file. 【0333】 Step 6: 【0334】 The server integrates the generated audio and image files to create visual content as a single guide video. This integration process allows users to understand the information visually and aurally. The output is a guide video file. 【0335】 Step 7: 【0336】 The server delivers the generated guide video to the user's device. The device notifies the user of the received video and displays it, making it available for viewing. This step allows the user to intuitively obtain the information. 【0337】 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. 【0338】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0339】 System Configuration 【0340】 The server is responsible for receiving and analyzing inquiries, generating responses, recognizing sentiment, creating video content, and delivering it. The terminal provides an interface for user inquiry input and is a device for displaying and playing the generated video content. Users use the terminal to submit inquiries and receive responses. 【0341】 Program processing 【0342】 Users input inquiries from their devices and send them to the server. This can be done via text input or voice input. The server analyzes the received inquiries using a natural language processing engine to understand their structure and intent. Simultaneously, an emotion engine analyzes the user's text and voice data to recognize their emotions. This helps the server understand the user's feelings when making the inquiry. 【0343】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. In doing so, it adjusts the tone and level of detail of the answers according to the recognized sentiment information. For example, if a user expresses dissatisfaction, it may consider adding a more polite and detailed explanation. 【0344】 Once the response is prepared, the server uses speech synthesis and image generation technologies to construct the video content. Speech synthesis uses emotionally appropriate tones, and image generation selects suitable visuals. By integrating these, the system creates a video that users can effectively understand both visually and aurally. 【0345】 Finally, the server sends the generated video content to the user's device. The device receives the video and displays a notification or link to the user for viewing. The user plays the video through the device, receives information, and experiences an emotionally sensitive response. 【0346】 Specific example 【0347】 As a concrete example, suppose a user asks, "I want to know why the server is slow to respond." The server receives this inquiry and analyzes it using natural language processing while simultaneously recognizing the user's "frustration" with an emotion engine. As a result, when preparing the answer, the server adds empathetic language and generates an answer that includes detailed troubleshooting and solutions. The completed video content uses a soft tone of voice and is accompanied by visuals that show the server's operating principles and related processes, allowing the user to accurately understand the problem. In this way, the present invention improves the user experience and facilitates smoother problem solving. 【0348】 The following describes the processing flow. 【0349】 Step 1: 【0350】 The user uses their device to type or record their inquiry via voice and send it to the server. The inquiry includes explanations and specific questions. 【0351】 Step 2: 【0352】 The server receives the query and starts the natural language processing engine to begin text analysis. Here, the server performs tokenization, analyzes the sentence structure, and understands the user's intent. 【0353】 Step 3: 【0354】 The server uses an emotion engine to recognize emotions from the user's input text or voice. The server analyzes the emotion data to determine whether the user is experiencing emotions such as anger, anxiety, or joy. 【0355】 Step 4: 【0356】 The server uses the analysis results and sentiment information to match frequently asked questions with those in the FAQ database. The server determines whether the inquiry has been received many times in the past. 【0357】 Step 5: 【0358】 The server uses generation technology to prepare the best possible answer to the identified question. At this stage, the server takes emotions into consideration and adjusts for gentle vocabulary selection and level of detail. 【0359】 Step 6: 【0360】 The server uses speech synthesis technology to convert the generated responses into speech. Furthermore, the server uses image generation technology to create visuals and animations that support the explanations. 【0361】 Step 7: 【0362】 The server integrates audio data and visuals to complete the video content. The video is composed with a tone that takes the user's emotions into consideration. 【0363】 Step 8: 【0364】 The server generates video content and delivers it to the user's device. The device receives the content and displays a viewing notification to the user. 【0365】 Step 9: 【0366】 The user plays the video through their device and reviews its content. This allows the user to understand the answer and solve the problem through both sight and sound. 【0367】 (Example 2) 【0368】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0369】 Traditional user support systems have struggled to generate responses that take user emotions into account, making it difficult to improve the user experience. In particular, there is a need to appropriately analyze the nuances of emotional inquiries and adjust the tone and content of responses in real time, but sufficient solutions have not been provided in this regard. 【0370】 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. 【0371】 In this invention, the server includes means for receiving inquiries from users, data processing means for analyzing the received inquiries using natural language processing techniques to identify frequently asked questions, and means for using generation techniques to generate optimal answers to the identified questions. This enables the recognition of user emotions and the generation and delivery of appropriate answers that correspond to those emotions. 【0372】 "Means for receiving inquiries" refers to a device or program for receiving inquiries from users in text or voice. 【0373】 "Natural language processing technology" is a technique that enables computers to understand and analyze human language, and is used to grasp the intent and content of inquiries. 【0374】 "Data processing means" refers to technology or apparatus for analyzing received inquiry data and performing calculations and decisions to identify frequently asked questions. 【0375】 "Generative technology" refers to techniques for creating mechanically optimized answers to specific questions. 【0376】 "Emotional analysis means" refers to a device or program that recognizes emotions from a user's text or voice and adjusts the content and tone of the response based on the results. 【0377】 "Speech synthesis technology" is a technology that generates human speech based on text data, and is used to generate the audio portion of video content. 【0378】 "Image generation technology" refers to the technology of creating images and animations to visually support the content of answers. 【0379】 "Means for generating video content" refers to a function that integrates speech synthesis technology and image generation technology to generate information transmission media through sight and sound. 【0380】 "Means of delivering video content" refers to communication technologies or network functions used to deliver generated video content to users. 【0381】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion analysis function that recognizes the user's emotions. The system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0382】 The server receives user inquiries and uses a natural language processing engine to analyze the input inquiries. The natural language processing engine is used to analyze the sentence structure of the inquiries and understand their content and intent. Furthermore, sentiment analysis tools diagnose the emotions contained in the user's inquiries and record them in a database. This makes it possible to generate optimal responses that are tailored to the user's emotions. 【0383】 Based on the analyzed data, the server generates answers to the identified questions using generation technology. By using a generation AI model, highly optimized answers can be created. Furthermore, accessing external data sources allows for the acquisition of additional information, enabling the provision of more detailed and accurate answers. 【0384】 The generated responses are converted into audio data with emotionally nuanced tones using speech synthesis technology. Simultaneously, visual data is created using image generation technology to clearly visualize the content of the responses. The server integrates this data to build video content that enhances the user experience. 【0385】 Finally, the server sends the generated video content to the user's device. After receiving the video, the device provides the user with a notification or link prompting them to watch it. The user can play the video on their device, receive information through sight and sound, and obtain a satisfactory answer to their inquiry. 【0386】 As a concrete example, consider a case where a user asks, "Please tell me how to install product X." The server analyzes the inquiry using natural language processing, and an emotion analysis tool recognizes the emotion of "confusion." The generative AI model provides an answer with installation instructions using comprehensive and easy-to-understand language. The generated video content visualizes the installation procedure with illustrations and is explained in a soft-toned voice. 【0387】 Example prompt: "Explain how to create an empathetic video response if a user is having trouble installing product X." 【0388】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0389】 Step 1: 【0390】 The user enters the inquiry from the terminal. The user can enter the question in text or voice format. This input data is converted into digital data by the terminal and sent to the server. There is text or voice data as input, and the output is digitized inquiry data. 【0391】 Step 2: 【0392】 The server passes the received digital data to a natural language processing engine, which analyzes the sentence structure and intent of the query. This analysis identifies the subject and main purpose of the query. The input is digitized query data, and the output is the analyzed query information. Specifically, the meaning and context of words are understood through natural language processing. 【0393】 Step 3: 【0394】 The server analyzes the user's emotions using emotion analysis tools. It extracts emotional elements from text and audio data to identify the user's emotional state. The input for this step is digitized inquiry data, and the output is user emotion information. Specifically, emotion analysis identifies emotions associated with the inquiry (e.g., "satisfied," "dissatisfied," "interested," etc.). 【0395】 Step 4: 【0396】 The server generates the optimal answer using a generative AI model based on the analyzed query and sentiment information. It selects the most appropriate answer for each query based on frequently occurring question patterns and adjusts the tone according to the sentiment. The input consists of analyzed query information and sentiment information, and the output is generated answer data. For specific questions, additional information is obtained from external data sources to refine the answer. 【0397】 Step 5: 【0398】 The server uses speech synthesis technology to convert responses into audio data and image generation technology to create visual representations. Audio tones tailored to the user's emotions and image materials relevant to the responses are generated and integrated into video content. The input is the generated response data, and the output is the video content. This effectively communicates information to the user through both sight and sound. 【0399】 Step 6: 【0400】 The server delivers the generated video content to the terminal. The terminal receives the video and provides the user with a notification or a viewing link. The input is video content, and the output is notification information for the user. The user can play the video and receive the information via the terminal. 【0401】 (Application Example 2) 【0402】 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." 【0403】 In modern information processing, responding quickly and appropriately to user inquiries is a crucial challenge. In particular, there is a demand for improved customer satisfaction by providing responses that consider user emotions, but current systems cannot fully meet this need. Therefore, technology is needed to recognize user emotions and appropriately customize responses. 【0404】 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. 【0405】 In this invention, the server includes means for receiving information from the user, means for analyzing the received information using natural language processing technology to identify frequently asked information, means for using generation technology to generate the optimal response to the identified information, means for analyzing the user's emotions using an emotion recognition engine to adjust the tone and details of the response, and means for delivering the generated visual content to the user. This makes it possible to quickly and effectively provide customized responses that take the user's emotions into consideration. 【0406】 "Means for receiving information from users" refers to a system or device for receiving voice or text inquiries sent by users and processing that data. 【0407】 "Natural language processing technology" is a technology that uses computers to analyze and understand human language, and has the ability to analyze the grammar and intent of user inquiries. 【0408】 "Means of identifying frequently asked information" refers to algorithms or processes for analyzing user inquiries and identifying the most frequently occurring questions or topics. 【0409】 "Means using generation technology" refers to technical means for automatically creating an appropriate response based on the aforementioned analysis results. 【0410】 An "emotion recognition engine" is an algorithm or system that analyzes a user's voice tone and text to identify their emotional state. 【0411】 "Means of adjusting the tone and details of responses" refers to technologies that modify the tone and content of generated responses based on the user's emotions. 【0412】 "Means of delivering generated visual content to users" refers to a function that sends the created video or other media to the user's device, enabling viewing and playback. 【0413】 This invention is a system that generates video content in response to user inquiries and provides responses that take the user's emotions into consideration. The following system configuration is possible for implementing the invention. 【0414】 The server uses Google Cloud's natural language processing API to analyze user inquiries from voice or text, understanding their structure and intent. It also utilizes IBM Watson Tone Analyzer for sentiment recognition, recognizing the user's emotional state. This enables the generation of responses that match the user's emotions, providing detailed and optimal responses. 【0415】 Furthermore, the response generation utilizes the Adobe Premiere Pro API to construct video content combining speech synthesis and visuals. The generated video content is sent via the internet to the user's device, i.e., a smartphone or computer. The device receives this video and displays notifications and links to the user, and plays the video. 【0416】 For example, when a user inquires that an item they ordered was damaged, the system recognizes their frustration. The generated video explains the return process in detail, along with an apology. The video includes a gentle voice and clear visual guidance, allowing the user to resolve the issue with confidence. 【0417】 As an example of a prompt to a generating AI model, the text "Please create a customized video explaining the detailed procedures for handling damaged ordered items, including an apology for any inconvenience caused" is shown. This prompt allows the system to autonomously provide the most appropriate response to the user. 【0418】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0419】 Step 1: 【0420】 The user inputs their inquiry using voice or text from their device and sends it to the server. The input data is raw data about the user's question or opinion. The server receives this raw data and prepares it for the next processing step. 【0421】 Step 2: 【0422】 The server analyzes the received query data using Google Cloud's natural language processing API. During the analysis, it grasps the structure of the text and identifies its meaning and intent. This step generates data that clarifies the main points and subject of the question. 【0423】 Step 3: 【0424】 The server uses IBM Watson's Tone Analyzer to extract sentiment data from user inquiries. It analyzes voice tone and text content to identify the user's emotional state. This process outputs data indicating the emotional state the user is in when making the inquiry. 【0425】 Step 4: 【0426】 The server generates a response based on the analyzed query content and sentiment data. To prepare an appropriate answer, it performs data collection and information integration, including access to external sources. In this step, a generative AI model is utilized to create customized response data based on the prompt. 【0427】 Step 5: 【0428】 The server uses the Adobe Premiere Pro API to perform speech synthesis and image generation on the generated response, constructing video content. If necessary, it modifies the speech tone and selects visual elements based on emotional information. This results in the final video data. 【0429】 Step 6: 【0430】 The server delivers the generated video content to the user's device. During this delivery process, data is transmitted over the internet and made available for reception on the device. The output of this step is a video file playable on the device. 【0431】 Step 7: 【0432】 The device notifies and displays the received video content to the user. The user can play the video and receive information visually and aurally. As a result, problem solving is facilitated through customized responses. 【0433】 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. 【0434】 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. 【0435】 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. 【0436】 [Third Embodiment] 【0437】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0438】 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. 【0439】 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). 【0440】 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. 【0441】 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. 【0442】 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). 【0443】 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. 【0444】 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. 【0445】 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. 【0446】 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. 【0447】 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. 【0448】 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". 【0449】 This invention provides a system that automatically generates and delivers video responses to user inquiries. The system consists of a server, terminals, and users, with the program primarily running on the server. 【0450】 System Configuration 【0451】 The server acts as the central hub, receiving and analyzing user inquiries, generating responses, creating video content, and delivering it to the user. The terminal functions as an interface for users to input inquiries, and also acts as a device for receiving and displaying / playing the generated video content. 【0452】 Program processing 【0453】 Users send inquiries to the server using their devices. These inquiries are typically in text format, describing the problems or questions the user wants to resolve. The server uses natural language processing techniques to analyze the received text and understand the intent of the inquiry. This process involves extracting important keywords and analyzing sentence structure. Based on the analysis results, the server identifies frequently asked questions. 【0454】 For each identified question, the server uses generation technology to prepare the optimal answer. At this stage, relevant information is collected to generate a comprehensive and clear answer to the user's question. Once the answer is generated, the server uses speech synthesis to convert the answer text into speech and then utilizes image generation technology to create a visually appealing visual. 【0455】 Next, the server integrates the generated audio and images to complete the video content. This video is structured to be intuitively understandable to the user and helps to visually explain complex procedures and concepts. 【0456】 Once the video content is complete, the server prepares to deliver it to the user's device. The device receives the video and notifies the user, allowing them to view the generated video. This entire process allows users to quickly and efficiently obtain information for problem solving. 【0457】 Specific example 【0458】 For example, consider a scenario where a user asks from their device, "How do I set up my smartphone?" The server receives this inquiry and uses natural language processing to analyze it as a question about "smartphone initial setup." Based on this analysis, if it is recognized as a frequently asked question, the server uses generative technology to prepare text instructions for the setup process, performs speech synthesis and image generation, and integrates it all into a video. This video is then delivered to the device, allowing the user to visually learn how to set up their smartphone by playing the video. This entire process improves the user experience and reduces the burden on customer service. 【0459】 The following describes the processing flow. 【0460】 Step 1: 【0461】 Users use their devices to enter inquiries containing specific problems or questions and send them to the server. Inquiries are typically entered in text format. 【0462】 Step 2: 【0463】 The server receives the query and uses a natural language processing engine to parse the text. Here, the server performs tokenization, sentence structure analysis, and keyword extraction to understand the user's intent behind the question. 【0464】 Step 3: 【0465】 The server identifies frequently asked questions based on the analysis results by comparing the inquiries with an existing FAQ database. This process utilizes machine learning algorithms based on past inquiry patterns. 【0466】 Step 4: 【0467】 The server executes generation techniques to produce the best possible answer to the identified question. The server collects relevant information and generates a clear and comprehensive answer to the question. 【0468】 Step 5: 【0469】 The server converts the generated response text into audio data using speech synthesis technology. Simultaneously, it uses image generation technology to create related images and animations for visual explanation. 【0470】 Step 6: 【0471】 The server integrates audio data and images to generate the final video content. The video is structured to be easy for the user to understand. 【0472】 Step 7: 【0473】 The server delivers the completed video content to the user's device. At this time, a link or notification for delivery is generated. 【0474】 Step 8: 【0475】 The device displays a notification to the user about video content it has received, allowing the user to play the video. The user watches the video and obtains information through the device. 【0476】 (Example 1) 【0477】 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." 【0478】 In modern information delivery systems, responses to user inquiries are often handled manually, making rapid responses difficult. Furthermore, text-based information delivery presents challenges in understanding complex procedures and concepts. Current systems lack sufficient visual and auditory enrichment to enhance the user experience, highlighting the need for efficient and intuitive information delivery methods. 【0479】 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. 【0480】 In this invention, the server includes means for receiving and analyzing inquiries from users, means for extracting important words and phrases using natural language processing technology and performing sentence structure analysis, and means for generating optimal answers using a generative AI model and generating video content using speech synthesis and image generation technology. This makes it possible to provide users with information quickly and in a visually and aurally easy-to-understand format. 【0481】 A "user" is an entity that seeks to obtain information by using the system, and refers to an individual or organization that makes an inquiry. 【0482】 "Inquiry" refers to the act of a user sending a problem or question they want resolved to the system in text format, or the content of that inquiry. 【0483】 "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language, and encompasses methods for analyzing text and understanding its meaning. 【0484】 A "generative AI model" refers to a mathematical or algorithmic method that uses artificial intelligence technology to create new information from given data. 【0485】 "Speech synthesis" refers to the technology of artificially generating voices that resemble human voices based on text information. 【0486】 "Image generation technology" refers to the technology used by computers to generate digital images, and is a means of creating visual content to convey information visually. 【0487】 "Video content" refers to media delivered in a digital format that combines visual and auditory information, and is created with the purpose of aiding user understanding. 【0488】 "Distribution" refers to the means of communication and actions used to deliver generated information or content to users. 【0489】 This invention relates to a system that automatically generates and delivers video responses to user inquiries. This system consists of a server, terminals, and users. The program primarily runs on the server. 【0490】 The server receives user inquiries and analyzes the text using natural language processing (NLP) techniques. NLP includes extracting important keywords and analyzing sentence structure. This allows the server to understand the user's intent. During this process, generative AI models are used to generate optimal answers to frequently asked questions, and these answers are converted into speech using speech synthesis technology. Additionally, image generation technology is used to create relevant visual representations. 【0491】 The device functions as an interface for users to enter inquiries, and also receives video content delivered from the server and notifies the user. Users can watch the videos through the device and intuitively understand the information. For example, in response to an inquiry such as "How do I set up my smartphone?", the server generates a video based on the relevant information and delivers it to the device, allowing the user to receive visual guidance. 【0492】 An example of a prompt message is, "Please send instructions to the generative AI model to generate a video explaining how to set up a smartphone." 【0493】 Implementing this system will improve the user experience, automate time-consuming inquiry handling, and provide information efficiently. 【0494】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0495】 Step 1: 【0496】 Users input problems or questions they want to resolve in text format via their terminal and send the inquiry to the server. The entered text serves as the initial input data and is necessary to clarify the user's intent. 【0497】 Step 2: 【0498】 The server first receives the query from the user and analyzes it using natural language processing techniques. It extracts important words and phrases from the received text and analyzes the sentence structure. This is part of the data processing and creates basic data to identify the user's intent. 【0499】 Step 3: 【0500】 The server uses key vocabulary and syntactic information to determine whether a question is frequently asked. The natural language processing analysis results become the input data, and the identification of frequently occurring questions becomes the output. At this stage, the type of answer required becomes clear. 【0501】 Step 4: 【0502】 The server uses a generative AI model to generate the optimal answer to the identified question. Information based on the analysis results is input, and specific answer text is output. During this process, it is also possible to access external data sources to collect additional information. 【0503】 Step 5: 【0504】 The server uses speech synthesis technology to convert the generated responses into speech, and then uses image generation technology to create related visuals. Based on this processed data, audio files and image data are output. This makes it possible to provide visual information to the user. 【0505】 Step 6: 【0506】 The server integrates audio and video to generate video content. Audio and image files are input, and a video file is output. This video supports intuitive understanding. 【0507】 Step 7: 【0508】 The server delivers the generated video content to the user's device. Here, the video file is the input data, and playback on the user's device is the final output. The device receives this video and notifies the user so they can immediately review it. The user can then watch the video on their device and use it to resolve their questions. 【0509】 (Application Example 1) 【0510】 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." 【0511】 In today's world, where speed of information acquisition is paramount, users require quick and easily understandable information to solve complex problems. However, traditional text-based inquiry and answer systems struggle to achieve this, and are particularly insufficient for users who prefer to grasp information visually and aurally. To address this challenge, it is necessary to create guide videos based on the information users inquire about, providing them visually and intuitively. 【0512】 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. 【0513】 In this invention, the server includes means for receiving inquiries from users, means for analyzing the received inquiries using natural language processing technology to identify frequently asked questions, means for using generation technology to generate optimal answers to the identified questions, means for generating audiovisual content using speech synthesis and image generation technology based on the generated answers, means for generating guide videos combining the audiovisual content, and means for delivering the generated guide videos to users. As a result, users can utilize guide videos that are quick and intuitively understandable to address their questions, enabling efficient problem solving. 【0514】 A "user" is someone who makes inquiries to the system to obtain information or solutions. 【0515】 An "inquiry" is a way for a user to express a problem or question they want to resolve, and it is the content that the system will analyze. 【0516】 "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to extract the intent behind a query. 【0517】 "Generative technology" refers to technology that automatically generates appropriate answers to specific questions. 【0518】 "Speech synthesis" is a technology that converts text information into speech. 【0519】 "Image generation technology" refers to the technology of generating new digital images, with the aim of providing visual information. 【0520】 "Audiovisual content" is content that integrates sound and images to convey information visually and aurally. 【0521】 "Distributing" refers to the technical actions taken to deliver generated content to users. 【0522】 The system for realizing this invention mainly consists of a server and a user terminal. The specific technical configuration and operation for implementing this system are described below. 【0523】 The server first receives a query from the user. The query is typically in text format and is sent from the user's device to the server over the network. The server then uses natural language processing techniques to analyze the user's query. For this analysis, the server uses the Google Cloud Natural Language API to understand the intent of the query and extract key terms. 【0524】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. At this stage, it retrieves relevant data from external sources as needed and utilizes OpenAI's generative AI model to generate the answers. 【0525】 Next, the server uses speech synthesis and image generation technologies to create visuals and audio. This involves using Amazon Polly to convert text to speech and OpenAI's DALL-E to generate visual elements. The generated audio and images are integrated into audiovisual content, forming an easy-to-understand guide video for the user. 【0526】 Finally, the server delivers the generated guide video to the user's device. The user receives and plays the guide video delivered via their device, obtaining information that is easy to understand intuitively. 【0527】 For example, if an inquiry is made asking "How do I use the new Instant Pot?", the system will automatically generate a guide video explaining the operation method, visually illustrating the detailed steps. 【0528】 An example of a prompt message would be, "Generate a video teaching the basic operation of the Instant Pot." In this way, the invention provides a system that enables users to efficiently obtain information and assists in problem-solving. 【0529】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0530】 Step 1: 【0531】 Users use a terminal to input inquiries in text format and send them to the server. The information entered often concerns problems or questions they want resolved. In this step, the terminal acts as an interface to accurately receive the user's text information. 【0532】 Step 2: 【0533】 The server analyzes incoming queries using natural language processing techniques. Specifically, it uses the Google Cloud Natural Language API to extract the intent and important keywords from the input text. The output is structured data that helps understand the meaning of the query. 【0534】 Step 3: 【0535】 Based on the analysis results, the server identifies frequently asked questions. This identification process allows the server to build a foundation for generating optimal answers to relevant questions. The output is a list of the identified single or multiple questions. 【0536】 Step 4: 【0537】 The server leverages OpenAI's generative AI model to generate the best possible answer to the identified question. This generation process involves obtaining relevant data from external sources as needed to improve the quality of the answer generation. The output is a comprehensive answer text corresponding to the user's question. 【0538】 Step 5: 【0539】 The server uses Amazon Polly to synthesize speech based on the generated response text and OpenAI's DALL-E to create images. This provides audiovisual elements that are easy for the user to understand. The output consists of an audio file and an image file. 【0540】 Step 6: 【0541】 The server integrates the generated audio and image files to create visual content as a single guide video. This integration process allows users to understand the information visually and aurally. The output is a guide video file. 【0542】 Step 7: 【0543】 The server delivers the generated guide video to the user's device. The device notifies the user of the received video and displays it, making it available for viewing. This step allows the user to intuitively obtain the information. 【0544】 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. 【0545】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0546】 System Configuration 【0547】 The server is responsible for receiving and analyzing inquiries, generating responses, recognizing sentiment, creating video content, and delivering it. The terminal provides an interface for user inquiry input and is a device for displaying and playing the generated video content. Users use the terminal to submit inquiries and receive responses. 【0548】 Program processing 【0549】 Users input inquiries from their devices and send them to the server. This can be done via text input or voice input. The server analyzes the received inquiries using a natural language processing engine to understand their structure and intent. Simultaneously, an emotion engine analyzes the user's text and voice data to recognize their emotions. This helps the server understand the user's feelings when making the inquiry. 【0550】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. In doing so, it adjusts the tone and level of detail of the answers according to the recognized sentiment information. For example, if a user expresses dissatisfaction, it may consider adding a more polite and detailed explanation. 【0551】 Once the response is prepared, the server uses speech synthesis and image generation technologies to construct the video content. Speech synthesis uses emotionally appropriate tones, and image generation selects suitable visuals. By integrating these, the system creates a video that users can effectively understand both visually and aurally. 【0552】 Finally, the server sends the generated video content to the user's device. The device receives the video and displays a notification or link to the user for viewing. The user plays the video through the device, receives information, and experiences an emotionally sensitive response. 【0553】 Specific example 【0554】 As a concrete example, suppose a user asks, "I want to know why the server is slow to respond." The server receives this inquiry and analyzes it using natural language processing while simultaneously recognizing the user's "frustration" with an emotion engine. As a result, when preparing the answer, the server adds empathetic language and generates an answer that includes detailed troubleshooting and solutions. The completed video content uses a soft tone of voice and is accompanied by visuals that show the server's operating principles and related processes, allowing the user to accurately understand the problem. In this way, the present invention improves the user experience and facilitates smoother problem solving. 【0555】 The following describes the processing flow. 【0556】 Step 1: 【0557】 The user uses their device to type or record their inquiry via voice and send it to the server. The inquiry includes explanations and specific questions. 【0558】 Step 2: 【0559】 The server receives the query and starts the natural language processing engine to begin text analysis. Here, the server performs tokenization, analyzes the sentence structure, and understands the user's intent. 【0560】 Step 3: 【0561】 The server uses an emotion engine to recognize emotions from the user's input text or voice. The server analyzes the emotion data to determine whether the user is experiencing emotions such as anger, anxiety, or joy. 【0562】 Step 4: 【0563】 The server uses the analysis results and sentiment information to match frequently asked questions with those in the FAQ database. The server determines whether the inquiry has been received many times in the past. 【0564】 Step 5: 【0565】 The server uses generation technology to prepare the best possible answer to the identified question. At this stage, the server takes emotions into consideration and adjusts for gentle vocabulary selection and level of detail. 【0566】 Step 6: 【0567】 The server uses speech synthesis technology to convert the generated responses into speech. Furthermore, the server uses image generation technology to create visuals and animations that support the explanations. 【0568】 Step 7: 【0569】 The server integrates audio data and visuals to complete the video content. The video is composed with a tone that takes the user's emotions into consideration. 【0570】 Step 8: 【0571】 The server generates video content and delivers it to the user's device. The device receives the content and displays a viewing notification to the user. 【0572】 Step 9: 【0573】 The user plays the video through their device and reviews its content. This allows the user to understand the answer and solve the problem through both sight and sound. 【0574】 (Example 2) 【0575】 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." 【0576】 Traditional user support systems have struggled to generate responses that take user emotions into account, making it difficult to improve the user experience. In particular, there is a need to appropriately analyze the nuances of emotional inquiries and adjust the tone and content of responses in real time, but sufficient solutions have not been provided in this regard. 【0577】 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. 【0578】 In this invention, the server includes means for receiving inquiries from users, data processing means for analyzing the received inquiries using natural language processing techniques to identify frequently asked questions, and means for using generation techniques to generate optimal answers to the identified questions. This enables the recognition of user emotions and the generation and delivery of appropriate answers that correspond to those emotions. 【0579】 "Means for receiving inquiries" refers to a device or program for receiving inquiries from users in text or voice. 【0580】 "Natural language processing technology" is a technique that enables computers to understand and analyze human language, and is used to grasp the intent and content of inquiries. 【0581】 "Data processing means" refers to technology or apparatus for analyzing received inquiry data and performing calculations and decisions to identify frequently asked questions. 【0582】 "Generative technology" refers to techniques for creating mechanically optimized answers to specific questions. 【0583】 "Emotional analysis means" refers to a device or program that recognizes emotions from a user's text or voice and adjusts the content and tone of the response based on the results. 【0584】 "Speech synthesis technology" is a technology that generates human speech based on text data, and is used to generate the audio portion of video content. 【0585】 "Image generation technology" refers to the technology of creating images and animations to visually support the content of answers. 【0586】 "Means for generating video content" refers to a function that integrates speech synthesis technology and image generation technology to generate information transmission media through sight and sound. 【0587】 "Means of delivering video content" refers to communication technologies or network functions used to deliver generated video content to users. 【0588】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion analysis function that recognizes the user's emotions. The system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0589】 The server receives user inquiries and uses a natural language processing engine to analyze the input inquiries. The natural language processing engine is used to analyze the sentence structure of the inquiries and understand their content and intent. Furthermore, sentiment analysis tools diagnose the emotions contained in the user's inquiries and record them in a database. This makes it possible to generate optimal responses that are tailored to the user's emotions. 【0590】 Based on the analyzed data, the server generates answers to the identified questions using generation technology. By using a generation AI model, highly optimized answers can be created. Furthermore, accessing external data sources allows for the acquisition of additional information, enabling the provision of more detailed and accurate answers. 【0591】 The generated responses are converted into audio data with emotionally nuanced tones using speech synthesis technology. Simultaneously, visual data is created using image generation technology to clearly visualize the content of the responses. The server integrates this data to build video content that enhances the user experience. 【0592】 Finally, the server sends the generated video content to the user's device. After receiving the video, the device provides the user with a notification or link prompting them to watch it. The user can play the video on their device, receive information through sight and sound, and obtain a satisfactory answer to their inquiry. 【0593】 As a concrete example, consider a case where a user asks, "Please tell me how to install product X." The server analyzes the inquiry using natural language processing, and an emotion analysis tool recognizes the emotion of "confusion." The generative AI model provides an answer with installation instructions using comprehensive and easy-to-understand language. The generated video content visualizes the installation procedure with illustrations and is explained in a soft-toned voice. 【0594】 Example prompt: "Explain how to create an empathetic video response if a user is having trouble installing product X." 【0595】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0596】 Step 1: 【0597】 The user enters the inquiry from the terminal. The user can enter the question in text or voice format. This input data is converted into digital data by the terminal and sent to the server. There is text or voice data as input, and the output is digitized inquiry data. 【0598】 Step 2: 【0599】 The server passes the received digital data to a natural language processing engine, which analyzes the sentence structure and intent of the query. This analysis identifies the subject and main purpose of the query. The input is digitized query data, and the output is the analyzed query information. Specifically, the meaning and context of words are understood through natural language processing. 【0600】 Step 3: 【0601】 The server analyzes the user's emotions using emotion analysis tools. It extracts emotional elements from text and audio data to identify the user's emotional state. The input for this step is digitized inquiry data, and the output is user emotion information. Specifically, emotion analysis identifies emotions associated with the inquiry (e.g., "satisfied," "dissatisfied," "interested," etc.). 【0602】 Step 4: 【0603】 The server generates the optimal answer using a generative AI model based on the analyzed query and sentiment information. It selects the most appropriate answer for each query based on frequently occurring question patterns and adjusts the tone according to the sentiment. The input consists of analyzed query information and sentiment information, and the output is generated answer data. For specific questions, additional information is obtained from external data sources to refine the answer. 【0604】 Step 5: 【0605】 The server uses speech synthesis technology to convert responses into audio data and image generation technology to create visual representations. Audio tones tailored to the user's emotions and image materials relevant to the responses are generated and integrated into video content. The input is the generated response data, and the output is the video content. This effectively communicates information to the user through both sight and sound. 【0606】 Step 6: 【0607】 The server delivers the generated video content to the terminal. The terminal receives the video and provides the user with a notification or a viewing link. The input is video content, and the output is notification information for the user. The user can play the video and receive the information via the terminal. 【0608】 (Application Example 2) 【0609】 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." 【0610】 In modern information processing, responding quickly and appropriately to user inquiries is a crucial challenge. In particular, there is a demand for improved customer satisfaction by providing responses that consider user emotions, but current systems cannot fully meet this need. Therefore, technology is needed to recognize user emotions and appropriately customize responses. 【0611】 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. 【0612】 In this invention, the server includes means for receiving information from the user, means for analyzing the received information using natural language processing technology to identify frequently asked information, means for using generation technology to generate the optimal response to the identified information, means for analyzing the user's emotions using an emotion recognition engine to adjust the tone and details of the response, and means for delivering the generated visual content to the user. This makes it possible to quickly and effectively provide customized responses that take the user's emotions into consideration. 【0613】 "Means for receiving information from users" refers to a system or device for receiving voice or text inquiries sent by users and processing that data. 【0614】 "Natural language processing technology" is a technology that uses computers to analyze and understand human language, and has the ability to analyze the grammar and intent of user inquiries. 【0615】 "Means of identifying frequently asked information" refers to algorithms or processes for analyzing user inquiries and identifying the most frequently occurring questions or topics. 【0616】 "Means using generation technology" refers to technical means for automatically creating an appropriate response based on the aforementioned analysis results. 【0617】 An "emotion recognition engine" is an algorithm or system that analyzes a user's voice tone and text to identify their emotional state. 【0618】 "Means of adjusting the tone and details of responses" refers to technologies that modify the tone and content of generated responses based on the user's emotions. 【0619】 "Means of delivering generated visual content to users" refers to a function that sends the created video or other media to the user's device, enabling viewing and playback. 【0620】 This invention is a system that generates video content in response to user inquiries and provides responses that take the user's emotions into consideration. The following system configuration is possible for implementing the invention. 【0621】 The server uses Google Cloud's natural language processing API to analyze user inquiries from voice or text, understanding their structure and intent. It also utilizes IBM Watson Tone Analyzer for sentiment recognition, recognizing the user's emotional state. This enables the generation of responses that match the user's emotions, providing detailed and optimal responses. 【0622】 Furthermore, the response generation utilizes the Adobe Premiere Pro API to construct video content combining speech synthesis and visuals. The generated video content is sent via the internet to the user's device, i.e., a smartphone or computer. The device receives this video and displays notifications and links to the user, and plays the video. 【0623】 For example, when a user inquires that an item they ordered was damaged, the system recognizes their frustration. The generated video explains the return process in detail, along with an apology. The video includes a gentle voice and clear visual guidance, allowing the user to resolve the issue with confidence. 【0624】 As an example of a prompt to a generating AI model, the text "Please create a customized video explaining the detailed procedures for handling damaged ordered items, including an apology for any inconvenience caused" is shown. This prompt allows the system to autonomously provide the most appropriate response to the user. 【0625】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0626】 Step 1: 【0627】 The user inputs their inquiry using voice or text from their device and sends it to the server. The input data is raw data about the user's question or opinion. The server receives this raw data and prepares it for the next processing step. 【0628】 Step 2: 【0629】 The server analyzes the received query data using Google Cloud's natural language processing API. During the analysis, it grasps the structure of the text and identifies its meaning and intent. This step generates data that clarifies the main points and subject of the question. 【0630】 Step 3: 【0631】 The server uses IBM Watson's Tone Analyzer to extract sentiment data from user inquiries. It analyzes voice tone and text content to identify the user's emotional state. This process outputs data indicating the emotional state the user is in when making the inquiry. 【0632】 Step 4: 【0633】 The server generates a response based on the analyzed query content and sentiment data. To prepare an appropriate answer, it performs data collection and information integration, including access to external sources. In this step, a generative AI model is utilized to create customized response data based on the prompt. 【0634】 Step 5: 【0635】 The server uses the Adobe Premiere Pro API to perform speech synthesis and image generation on the generated response, constructing video content. If necessary, it modifies the speech tone and selects visual elements based on emotional information. This results in the final video data. 【0636】 Step 6: 【0637】 The server delivers the generated video content to the user's device. During this delivery process, data is transmitted over the internet and made available for reception on the device. The output of this step is a video file playable on the device. 【0638】 Step 7: 【0639】 The device notifies and displays the received video content to the user. The user can play the video and receive information visually and aurally. As a result, problem solving is facilitated through customized responses. 【0640】 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. 【0641】 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. 【0642】 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. 【0643】 [Fourth Embodiment] 【0644】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0645】 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. 【0646】 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). 【0647】 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. 【0648】 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. 【0649】 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). 【0650】 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. 【0651】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0652】 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. 【0653】 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. 【0654】 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. 【0655】 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. 【0656】 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". 【0657】 This invention provides a system that automatically generates and delivers video responses to user inquiries. The system consists of a server, terminals, and users, with the program primarily running on the server. 【0658】 System Configuration 【0659】 The server acts as the central hub, receiving and analyzing user inquiries, generating responses, creating video content, and delivering it to the user. The terminal functions as an interface for users to input inquiries, and also acts as a device for receiving and displaying / playing the generated video content. 【0660】 Program processing 【0661】 Users send inquiries to the server using their devices. These inquiries are typically in text format, describing the problems or questions the user wants to resolve. The server uses natural language processing techniques to analyze the received text and understand the intent of the inquiry. This process involves extracting important keywords and analyzing sentence structure. Based on the analysis results, the server identifies frequently asked questions. 【0662】 For each identified question, the server uses generation technology to prepare the optimal answer. At this stage, relevant information is collected to generate a comprehensive and clear answer to the user's question. Once the answer is generated, the server uses speech synthesis to convert the answer text into speech and then utilizes image generation technology to create a visually appealing visual. 【0663】 Next, the server integrates the generated audio and images to complete the video content. This video is structured to be intuitively understandable to the user and helps to visually explain complex procedures and concepts. 【0664】 Once the video content is complete, the server prepares to deliver it to the user's device. The device receives the video and notifies the user, allowing them to view the generated video. This entire process allows users to quickly and efficiently obtain information for problem solving. 【0665】 Specific example 【0666】 For example, consider a scenario where a user asks from their device, "How do I set up my smartphone?" The server receives this inquiry and uses natural language processing to analyze it as a question about "smartphone initial setup." Based on this analysis, if it is recognized as a frequently asked question, the server uses generative technology to prepare text instructions for the setup process, performs speech synthesis and image generation, and integrates it all into a video. This video is then delivered to the device, allowing the user to visually learn how to set up their smartphone by playing the video. This entire process improves the user experience and reduces the burden on customer service. 【0667】 The following describes the processing flow. 【0668】 Step 1: 【0669】 Users use their devices to enter inquiries containing specific problems or questions and send them to the server. Inquiries are typically entered in text format. 【0670】 Step 2: 【0671】 The server receives the query and uses a natural language processing engine to parse the text. Here, the server performs tokenization, sentence structure analysis, and keyword extraction to understand the user's intent behind the question. 【0672】 Step 3: 【0673】 The server identifies frequently asked questions based on the analysis results by comparing the inquiries with an existing FAQ database. This process utilizes machine learning algorithms based on past inquiry patterns. 【0674】 Step 4: 【0675】 The server executes generation techniques to produce the best possible answer to the identified question. The server collects relevant information and generates a clear and comprehensive answer to the question. 【0676】 Step 5: 【0677】 The server converts the generated response text into audio data using speech synthesis technology. Simultaneously, it uses image generation technology to create related images and animations for visual explanation. 【0678】 Step 6: 【0679】 The server integrates audio data and images to generate the final video content. The video is structured to be easy for the user to understand. 【0680】 Step 7: 【0681】 The server delivers the completed video content to the user's device. At this time, a link or notification for delivery is generated. 【0682】 Step 8: 【0683】 The device displays a notification to the user about video content it has received, allowing the user to play the video. The user watches the video and obtains information through the device. 【0684】 (Example 1) 【0685】 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". 【0686】 In modern information delivery systems, responses to user inquiries are often handled manually, making rapid responses difficult. Furthermore, text-based information delivery presents challenges in understanding complex procedures and concepts. Current systems lack sufficient visual and auditory enrichment to enhance the user experience, highlighting the need for efficient and intuitive information delivery methods. 【0687】 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. 【0688】 In this invention, the server includes means for receiving and analyzing inquiries from users, means for extracting important words and phrases using natural language processing technology and performing sentence structure analysis, and means for generating optimal answers using a generative AI model and generating video content using speech synthesis and image generation technology. This makes it possible to provide users with information quickly and in a visually and aurally easy-to-understand format. 【0689】 A "user" is an entity that seeks to obtain information by using the system, and refers to an individual or organization that makes an inquiry. 【0690】 "Inquiry" refers to the act of a user sending a problem or question they want resolved to the system in text format, or the content of that inquiry. 【0691】 "Natural language processing technology" refers to the technology that enables computers to understand, interpret, and generate human language, and encompasses methods for analyzing text and understanding its meaning. 【0692】 A "generative AI model" refers to a mathematical or algorithmic method that uses artificial intelligence technology to create new information from given data. 【0693】 "Speech synthesis" refers to the technology of artificially generating voices that resemble human voices based on text information. 【0694】 "Image generation technology" refers to the technology used by computers to generate digital images, and is a means of creating visual content to convey information visually. 【0695】 "Video content" refers to media delivered in a digital format that combines visual and auditory information, and is created with the purpose of aiding user understanding. 【0696】 "Distribution" refers to the means of communication and actions used to deliver generated information or content to users. 【0697】 This invention relates to a system that automatically generates and delivers video responses to user inquiries. This system consists of a server, terminals, and users. The program primarily runs on the server. 【0698】 The server receives user inquiries and analyzes the text using natural language processing (NLP) techniques. NLP includes extracting important keywords and analyzing sentence structure. This allows the server to understand the user's intent. During this process, generative AI models are used to generate optimal answers to frequently asked questions, and these answers are converted into speech using speech synthesis technology. Additionally, image generation technology is used to create relevant visual representations. 【0699】 The device functions as an interface for users to enter inquiries, and also receives video content delivered from the server and notifies the user. Users can watch the videos through the device and intuitively understand the information. For example, in response to an inquiry such as "How do I set up my smartphone?", the server generates a video based on the relevant information and delivers it to the device, allowing the user to receive visual guidance. 【0700】 An example of a prompt message is, "Please send instructions to the generative AI model to generate a video explaining how to set up a smartphone." 【0701】 Implementing this system will improve the user experience, automate time-consuming inquiry handling, and provide information efficiently. 【0702】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0703】 Step 1: 【0704】 Users input problems or questions they want to resolve in text format via their terminal and send the inquiry to the server. The entered text serves as the initial input data and is necessary to clarify the user's intent. 【0705】 Step 2: 【0706】 The server first receives the query from the user and analyzes it using natural language processing techniques. It extracts important words and phrases from the received text and analyzes the sentence structure. This is part of the data processing and creates basic data to identify the user's intent. 【0707】 Step 3: 【0708】 The server uses key vocabulary and syntactic information to determine whether a question is frequently asked. The natural language processing analysis results become the input data, and the identification of frequently occurring questions becomes the output. At this stage, the type of answer required becomes clear. 【0709】 Step 4: 【0710】 The server uses a generative AI model to generate the optimal answer to the identified question. Information based on the analysis results is input, and specific answer text is output. During this process, it is also possible to access external data sources to collect additional information. 【0711】 Step 5: 【0712】 The server uses speech synthesis technology to convert the generated responses into speech, and then uses image generation technology to create related visuals. Based on this processed data, audio files and image data are output. This makes it possible to provide visual information to the user. 【0713】 Step 6: 【0714】 The server integrates audio and video to generate video content. Audio and image files are input, and a video file is output. This video supports intuitive understanding. 【0715】 Step 7: 【0716】 The server delivers the generated video content to the user's device. Here, the video file is the input data, and playback on the user's device is the final output. The device receives this video and notifies the user so they can immediately review it. The user can then watch the video on their device and use it to resolve their questions. 【0717】 (Application Example 1) 【0718】 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". 【0719】 In today's world, where speed of information acquisition is paramount, users require quick and easily understandable information to solve complex problems. However, traditional text-based inquiry and answer systems struggle to achieve this, and are particularly insufficient for users who prefer to grasp information visually and aurally. To address this challenge, it is necessary to create guide videos based on the information users inquire about, providing them visually and intuitively. 【0720】 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. 【0721】 In this invention, the server includes means for receiving inquiries from users, means for analyzing the received inquiries using natural language processing technology to identify frequently asked questions, means for using generation technology to generate optimal answers to the identified questions, means for generating audiovisual content using speech synthesis and image generation technology based on the generated answers, means for generating guide videos combining the audiovisual content, and means for delivering the generated guide videos to users. As a result, users can utilize guide videos that are quick and intuitively understandable to address their questions, enabling efficient problem solving. 【0722】 A "user" is someone who makes inquiries to the system to obtain information or solutions. 【0723】 An "inquiry" is a way for a user to express a problem or question they want to resolve, and it is the content that the system will analyze. 【0724】 "Natural language processing technology" is a technique that allows computers to understand and analyze human language, and is used to extract the intent behind a query. 【0725】 "Generative technology" refers to technology that automatically generates appropriate answers to specific questions. 【0726】 "Speech synthesis" is a technology that converts text information into speech. 【0727】 "Image generation technology" refers to the technology of generating new digital images, with the aim of providing visual information. 【0728】 "Audiovisual content" is content that integrates sound and images to convey information visually and aurally. 【0729】 "Distributing" refers to the technical actions taken to deliver generated content to users. 【0730】 The system for realizing this invention mainly consists of a server and a user terminal. The specific technical configuration and operation for implementing this system are described below. 【0731】 The server first receives a query from the user. The query is typically in text format and is sent from the user's device to the server over the network. The server then uses natural language processing techniques to analyze the user's query. For this analysis, the server uses the Google Cloud Natural Language API to understand the intent of the query and extract key terms. 【0732】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. At this stage, it retrieves relevant data from external sources as needed and utilizes OpenAI's generative AI model to generate the answers. 【0733】 Next, the server uses speech synthesis and image generation technologies to create visuals and audio. This involves using Amazon Polly to convert text to speech and OpenAI's DALL-E to generate visual elements. The generated audio and images are integrated into audiovisual content, forming an easy-to-understand guide video for the user. 【0734】 Finally, the server delivers the generated guide video to the user's device. The user receives and plays the guide video delivered via their device, obtaining information that is easy to understand intuitively. 【0735】 For example, if an inquiry is made asking "How do I use the new Instant Pot?", the system will automatically generate a guide video explaining the operation method, visually illustrating the detailed steps. 【0736】 An example of a prompt message would be, "Generate a video teaching the basic operation of the Instant Pot." In this way, the invention provides a system that enables users to efficiently obtain information and assists in problem-solving. 【0737】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0738】 Step 1: 【0739】 Users use a terminal to input inquiries in text format and send them to the server. The information entered often concerns problems or questions they want resolved. In this step, the terminal acts as an interface to accurately receive the user's text information. 【0740】 Step 2: 【0741】 The server analyzes incoming queries using natural language processing techniques. Specifically, it uses the Google Cloud Natural Language API to extract the intent and important keywords from the input text. The output is structured data that helps understand the meaning of the query. 【0742】 Step 3: 【0743】 Based on the analysis results, the server identifies frequently asked questions. This identification process allows the server to build a foundation for generating optimal answers to relevant questions. The output is a list of the identified single or multiple questions. 【0744】 Step 4: 【0745】 The server leverages OpenAI's generative AI model to generate the best possible answer to the identified question. This generation process involves obtaining relevant data from external sources as needed to improve the quality of the answer generation. The output is a comprehensive answer text corresponding to the user's question. 【0746】 Step 5: 【0747】 The server uses Amazon Polly to synthesize speech based on the generated response text and OpenAI's DALL-E to create images. This provides audiovisual elements that are easy for the user to understand. The output consists of an audio file and an image file. 【0748】 Step 6: 【0749】 The server integrates the generated audio and image files to create visual content as a single guide video. This integration process allows users to understand the information visually and aurally. The output is a guide video file. 【0750】 Step 7: 【0751】 The server delivers the generated guide video to the user's device. The device notifies the user of the received video and displays it, making it available for viewing. This step allows the user to intuitively obtain the information. 【0752】 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. 【0753】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0754】 System Configuration 【0755】 The server is responsible for receiving and analyzing inquiries, generating responses, recognizing sentiment, creating video content, and delivering it. The terminal provides an interface for user inquiry input and is a device for displaying and playing the generated video content. Users use the terminal to submit inquiries and receive responses. 【0756】 Program processing 【0757】 Users input inquiries from their devices and send them to the server. This can be done via text input or voice input. The server analyzes the received inquiries using a natural language processing engine to understand their structure and intent. Simultaneously, an emotion engine analyzes the user's text and voice data to recognize their emotions. This helps the server understand the user's feelings when making the inquiry. 【0758】 Based on the analysis results, the server identifies frequently asked questions and uses generation techniques to prepare optimal answers. In doing so, it adjusts the tone and level of detail of the answers according to the recognized sentiment information. For example, if a user expresses dissatisfaction, it may consider adding a more polite and detailed explanation. 【0759】 Once the response is prepared, the server uses speech synthesis and image generation technologies to construct the video content. Speech synthesis uses emotionally appropriate tones, and image generation selects suitable visuals. By integrating these, the system creates a video that users can effectively understand both visually and aurally. 【0760】 Finally, the server sends the generated video content to the user's device. The device receives the video and displays a notification or link to the user for viewing. The user plays the video through the device, receives information, and experiences an emotionally sensitive response. 【0761】 Specific example 【0762】 As a concrete example, suppose a user asks, "I want to know why the server is slow to respond." The server receives this inquiry and analyzes it using natural language processing while simultaneously recognizing the user's "frustration" with an emotion engine. As a result, when preparing the answer, the server adds empathetic language and generates an answer that includes detailed troubleshooting and solutions. The completed video content uses a soft tone of voice and is accompanied by visuals that show the server's operating principles and related processes, allowing the user to accurately understand the problem. In this way, the present invention improves the user experience and facilitates smoother problem solving. 【0763】 The following describes the processing flow. 【0764】 Step 1: 【0765】 The user uses their device to type or record their inquiry via voice and send it to the server. The inquiry includes explanations and specific questions. 【0766】 Step 2: 【0767】 The server receives the query and starts the natural language processing engine to begin text analysis. Here, the server performs tokenization, analyzes the sentence structure, and understands the user's intent. 【0768】 Step 3: 【0769】 The server uses an emotion engine to recognize emotions from the user's input text or voice. The server analyzes the emotion data to determine whether the user is experiencing emotions such as anger, anxiety, or joy. 【0770】 Step 4: 【0771】 The server uses the analysis results and sentiment information to match frequently asked questions with those in the FAQ database. The server determines whether the inquiry has been received many times in the past. 【0772】 Step 5: 【0773】 The server uses generation technology to prepare the best possible answer to the identified question. At this stage, the server takes emotions into consideration and adjusts for gentle vocabulary selection and level of detail. 【0774】 Step 6: 【0775】 The server uses speech synthesis technology to convert the generated responses into speech. Furthermore, the server uses image generation technology to create visuals and animations that support the explanations. 【0776】 Step 7: 【0777】 The server integrates audio data and visuals to complete the video content. The video is composed with a tone that takes the user's emotions into consideration. 【0778】 Step 8: 【0779】 The server generates video content and delivers it to the user's device. The device receives the content and displays a viewing notification to the user. 【0780】 Step 9: 【0781】 The user plays the video through their device and reviews its content. This allows the user to understand the answer and solve the problem through both sight and sound. 【0782】 (Example 2) 【0783】 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". 【0784】 Traditional user support systems have struggled to generate responses that take user emotions into account, making it difficult to improve the user experience. In particular, there is a need to appropriately analyze the nuances of emotional inquiries and adjust the tone and content of responses in real time, but sufficient solutions have not been provided in this regard. 【0785】 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. 【0786】 In this invention, the server includes means for receiving inquiries from users, data processing means for analyzing the received inquiries using natural language processing techniques to identify frequently asked questions, and means for using generation techniques to generate optimal answers to the identified questions. This enables the recognition of user emotions and the generation and delivery of appropriate answers that correspond to those emotions. 【0787】 "Means for receiving inquiries" refers to a device or program for receiving inquiries from users in text or voice. 【0788】 "Natural language processing technology" is a technique that enables computers to understand and analyze human language, and is used to grasp the intent and content of inquiries. 【0789】 "Data processing means" refers to technology or apparatus for analyzing received inquiry data and performing calculations and decisions to identify frequently asked questions. 【0790】 "Generative technology" refers to techniques for creating mechanically optimized answers to specific questions. 【0791】 "Emotional analysis means" refers to a device or program that recognizes emotions from a user's text or voice and adjusts the content and tone of the response based on the results. 【0792】 "Speech synthesis technology" is a technology that generates human speech based on text data, and is used to generate the audio portion of video content. 【0793】 "Image generation technology" refers to the technology of creating images and animations to visually support the content of answers. 【0794】 "Means for generating video content" refers to a function that integrates speech synthesis technology and image generation technology to generate information transmission media through sight and sound. 【0795】 "Means of delivering video content" refers to communication technologies or network functions used to deliver generated video content to users. 【0796】 This invention combines a system that automatically generates and delivers video responses to user inquiries with an emotion analysis function that recognizes the user's emotions. The system consists of a server, a terminal, and a user, and each component works in cooperation with the others. 【0797】 The server receives user inquiries and uses a natural language processing engine to analyze the input inquiries. The natural language processing engine is used to analyze the sentence structure of the inquiries and understand their content and intent. Furthermore, sentiment analysis tools diagnose the emotions contained in the user's inquiries and record them in a database. This makes it possible to generate optimal responses that are tailored to the user's emotions. 【0798】 Based on the analyzed data, the server generates answers to the identified questions using generation technology. By using a generation AI model, highly optimized answers can be created. Furthermore, accessing external data sources allows for the acquisition of additional information, enabling the provision of more detailed and accurate answers. 【0799】 The generated responses are converted into audio data with emotionally nuanced tones using speech synthesis technology. Simultaneously, visual data is created using image generation technology to clearly visualize the content of the responses. The server integrates this data to build video content that enhances the user experience. 【0800】 Finally, the server sends the generated video content to the user's device. After receiving the video, the device provides the user with a notification or link prompting them to watch it. The user can play the video on their device, receive information through sight and sound, and obtain a satisfactory answer to their inquiry. 【0801】 As a concrete example, consider a case where a user asks, "Please tell me how to install product X." The server analyzes the inquiry using natural language processing, and an emotion analysis tool recognizes the emotion of "confusion." The generative AI model provides an answer with installation instructions using comprehensive and easy-to-understand language. The generated video content visualizes the installation procedure with illustrations and is explained in a soft-toned voice. 【0802】 Example prompt: "Explain how to create an empathetic video response if a user is having trouble installing product X." 【0803】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0804】 Step 1: 【0805】 The user enters the inquiry from the terminal. The user can enter the question in text or voice format. This input data is converted into digital data by the terminal and sent to the server. There is text or voice data as input, and the output is digitized inquiry data. 【0806】 Step 2: 【0807】 The server passes the received digital data to a natural language processing engine, which analyzes the sentence structure and intent of the query. This analysis identifies the subject and main purpose of the query. The input is digitized query data, and the output is the analyzed query information. Specifically, the meaning and context of words are understood through natural language processing. 【0808】 Step 3: 【0809】 The server analyzes the user's emotions using emotion analysis tools. It extracts emotional elements from text and audio data to identify the user's emotional state. The input for this step is digitized inquiry data, and the output is user emotion information. Specifically, emotion analysis identifies emotions associated with the inquiry (e.g., "satisfied," "dissatisfied," "interested," etc.). 【0810】 Step 4: 【0811】 The server generates the optimal answer using a generative AI model based on the analyzed query and sentiment information. It selects the most appropriate answer for each query based on frequently occurring question patterns and adjusts the tone according to the sentiment. The input consists of analyzed query information and sentiment information, and the output is generated answer data. For specific questions, additional information is obtained from external data sources to refine the answer. 【0812】 Step 5: 【0813】 The server uses speech synthesis technology to convert responses into audio data and image generation technology to create visual representations. Audio tones tailored to the user's emotions and image materials relevant to the responses are generated and integrated into video content. The input is the generated response data, and the output is the video content. This effectively communicates information to the user through both sight and sound. 【0814】 Step 6: 【0815】 The server delivers the generated video content to the terminal. The terminal receives the video and provides the user with a notification or a viewing link. The input is video content, and the output is notification information for the user. The user can play the video and receive the information via the terminal. 【0816】 (Application Example 2) 【0817】 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". 【0818】 In modern information processing, responding quickly and appropriately to user inquiries is a crucial challenge. In particular, there is a demand for improved customer satisfaction by providing responses that consider user emotions, but current systems cannot fully meet this need. Therefore, technology is needed to recognize user emotions and appropriately customize responses. 【0819】 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. 【0820】 In this invention, the server includes means for receiving information from the user, means for analyzing the received information using natural language processing technology to identify frequently asked information, means for using generation technology to generate the optimal response to the identified information, means for analyzing the user's emotions using an emotion recognition engine to adjust the tone and details of the response, and means for delivering the generated visual content to the user. This makes it possible to quickly and effectively provide customized responses that take the user's emotions into consideration. 【0821】 "Means for receiving information from users" refers to a system or device for receiving voice or text inquiries sent by users and processing that data. 【0822】 "Natural language processing technology" is a technology that uses computers to analyze and understand human language, and has the ability to analyze the grammar and intent of user inquiries. 【0823】 "Means of identifying frequently asked information" refers to algorithms or processes for analyzing user inquiries and identifying the most frequently occurring questions or topics. 【0824】 "Means using generation technology" refers to technical means for automatically creating an appropriate response based on the aforementioned analysis results. 【0825】 An "emotion recognition engine" is an algorithm or system that analyzes a user's voice tone and text to identify their emotional state. 【0826】 "Means of adjusting the tone and details of responses" refers to technologies that modify the tone and content of generated responses based on the user's emotions. 【0827】 "Means of delivering generated visual content to users" refers to a function that sends the created video or other media to the user's device, enabling viewing and playback. 【0828】 This invention is a system that generates video content in response to user inquiries and provides responses that take the user's emotions into consideration. The following system configuration is possible for implementing the invention. 【0829】 The server uses Google Cloud's natural language processing API to analyze user inquiries from voice or text, understanding their structure and intent. It also utilizes IBM Watson Tone Analyzer for sentiment recognition, recognizing the user's emotional state. This enables the generation of responses that match the user's emotions, providing detailed and optimal responses. 【0830】 Furthermore, the response generation utilizes the Adobe Premiere Pro API to construct video content combining speech synthesis and visuals. The generated video content is sent via the internet to the user's device, i.e., a smartphone or computer. The device receives this video and displays notifications and links to the user, and plays the video. 【0831】 For example, when a user inquires that an item they ordered was damaged, the system recognizes their frustration. The generated video explains the return process in detail, along with an apology. The video includes a gentle voice and clear visual guidance, allowing the user to resolve the issue with confidence. 【0832】 As an example of a prompt to a generating AI model, the text "Please create a customized video explaining the detailed procedures for handling damaged ordered items, including an apology for any inconvenience caused" is shown. This prompt allows the system to autonomously provide the most appropriate response to the user. 【0833】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0834】 Step 1: 【0835】 The user inputs their inquiry using voice or text from their device and sends it to the server. The input data is raw data about the user's question or opinion. The server receives this raw data and prepares it for the next processing step. 【0836】 Step 2: 【0837】 The server analyzes the received query data using Google Cloud's natural language processing API. During the analysis, it grasps the structure of the text and identifies its meaning and intent. This step generates data that clarifies the main points and subject of the question. 【0838】 Step 3: 【0839】 The server uses IBM Watson's Tone Analyzer to extract sentiment data from user inquiries. It analyzes voice tone and text content to identify the user's emotional state. This process outputs data indicating the emotional state the user is in when making the inquiry. 【0840】 Step 4: 【0841】 The server generates a response based on the analyzed query content and sentiment data. To prepare an appropriate answer, it performs data collection and information integration, including access to external sources. In this step, a generative AI model is utilized to create customized response data based on the prompt. 【0842】 Step 5: 【0843】 The server uses the Adobe Premiere Pro API to perform speech synthesis and image generation on the generated response, constructing video content. If necessary, it modifies the speech tone and selects visual elements based on emotional information. This results in the final video data. 【0844】 Step 6: 【0845】 The server delivers the generated video content to the user's device. During this delivery process, data is transmitted over the internet and made available for reception on the device. The output of this step is a video file playable on the device. 【0846】 Step 7: 【0847】 The device notifies and displays the received video content to the user. The user can play the video and receive information visually and aurally. As a result, problem solving is facilitated through customized responses. 【0848】 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. 【0849】 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. 【0850】 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. 【0851】 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. 【0852】 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. 【0853】 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. 【0854】 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. 【0855】 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. 【0856】 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." 【0857】 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. 【0858】 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. 【0859】 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. 【0860】 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. 【0861】 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. 【0862】 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. 【0863】 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. 【0864】 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. 【0865】 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. 【0866】 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. 【0867】 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. 【0868】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0869】 The following is further disclosed regarding the embodiments described above. 【0870】 (Claim 1) 【0871】 A means of receiving inquiries from users, 【0872】 A means of analyzing received inquiries using natural language processing technology to identify frequently asked questions, 【0873】 A means of using generation technology to generate the optimal answer to a specific question, 【0874】 A means for generating video content using speech synthesis and image generation technology based on the generated response, 【0875】 A means of delivering the generated video content to users, 【0876】 A system that includes this. 【0877】 (Claim 2) 【0878】 The system according to claim 1, wherein natural language processing technology performs sentence structure analysis. 【0879】 (Claim 3) 【0880】 The system according to claim 1, wherein the generation technology accesses an external data source when generating a response. 【0881】 "Example 1" 【0882】 (Claim 1) 【0883】 A device that receives user inquiries, 【0884】 A device that analyzes received inquiries using natural language processing technology and understands their intent, 【0885】 A device that extracts important words and performs sentence structure analysis, 【0886】 A device for identifying frequently asked questions, 【0887】 A device that generates the optimal answer to a specified question using an AI model, 【0888】 A device that generates video content using speech synthesis and image generation technology based on the generated response, 【0889】 A device that delivers the generated video content to users, 【0890】 A system that includes this. 【0891】 (Claim 2) 【0892】 The system according to claim 1, further comprising means for collecting relevant information based on the analysis results. 【0893】 (Claim 3) 【0894】 The system according to claim 1, wherein the generation technology accesses external data resources in generating responses. 【0895】 "Application Example 1" 【0896】 (Claim 1) 【0897】 A means of receiving inquiries from users, 【0898】 A means of analyzing received inquiries using natural language processing technology to identify frequently asked questions, 【0899】 A means of using generation technology to generate the optimal answer to a specific question, 【0900】 A means for generating audiovisual content using speech synthesis and image generation technologies based on the generated responses, 【0901】 A means for generating guide videos that combine audiovisual content, 【0902】 A means of distributing the generated guide video to users, 【0903】 A system that includes this. 【0904】 (Claim 2) 【0905】 The system according to claim 1, wherein natural language processing technology performs sentence structure analysis. 【0906】 (Claim 3) 【0907】 The system according to claim 1, wherein the generation technology accesses external information sources in generating answers. 【0908】 "Example 2 of combining an emotion engine" 【0909】 (Claim 1) 【0910】 A means of receiving inquiries from users, 【0911】 A data processing means for analyzing received inquiries using natural language processing technology to identify frequently asked questions, 【0912】 Means for using generation techniques to generate the best answer to a specific question, 【0913】 It includes an emotion analysis means for recognizing the user's emotions, and means for adjusting the response based on the recognized emotions, 【0914】 A means for generating emotionally relevant video content using speech synthesis and image generation technologies based on the generated responses, 【0915】 A means of delivering the generated video content to users, 【0916】 A system that includes this. 【0917】 (Claim 2) 【0918】 The system according to claim 1, wherein the emotion analysis means analyzes the user's input data to identify emotions and influence the response. 【0919】 (Claim 3) 【0920】 The system according to claim 1, wherein the generation technology accesses external information sources to obtain information when generating an answer. 【0921】 "Application example 2 when combining with an emotional engine" 【0922】 (Claim 1) 【0923】 A means of receiving information from users, 【0924】 A means of analyzing received information using natural language processing technology to identify frequently requested information, 【0925】 A means of using generation techniques to generate the optimal response to identified information, 【0926】 A means for generating visual content using speech synthesis and image generation technologies based on the generated response, 【0927】 A means of analyzing a user's emotions using an emotion recognition engine and adjusting the tone and details of the response using generation technology, 【0928】 A means of delivering the generated visual content to users, 【0929】 A system that includes this. 【0930】 (Claim 2) 【0931】 The system according to claim 1, wherein natural language processing technology performs sentence structure analysis. 【0932】 (Claim 3) 【0933】 The system according to claim 1, wherein the generation technology accesses an external information source when generating a response. [Explanation of symbols] 【0934】 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

[Claim 1] A means of receiving inquiries from users, A means of analyzing received inquiries using natural language processing technology to identify frequently asked questions, A means of using generation technology to generate the optimal answer to a specific question, A means for generating video content using speech synthesis and image generation technology based on the generated response, A means of delivering the generated video content to users, A system that includes this. [Claim 2] The system according to claim 1, wherein natural language processing technology performs sentence structure analysis. [Claim 3] The system according to claim 1, wherein the generation technology accesses an external data source when generating an answer.

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