system

Abstract

We provide the system. [Solution] An input method for entering questions regarding weddings, funerals, and other ceremonial occasions, A generation means that analyzes the input question and generates an appropriate answer, A presentation means for presenting the generated answer and related information to the user, A means of arranging goods and services based on the relevant information presented, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional system where questions and procedures related to weddings, funerals, and other ceremonies are complicated for ordinary consumers and often impose a mental and physical burden, it is necessary to provide a method that can efficiently solve such problems and enable users to save time and effort.

Means for Solving the Problems

[0005] The present invention provides a system in which a user inputs questions related to weddings, funerals, and other ceremonies, and the system analyzes the questions and generates appropriate answers. Specifically, by using a system including an input means, a generation means, a presentation means, and an arrangement means, it is possible to consistently perform not only the solution of questions but also the arrangement of related goods and services.

[0006] The "input method" refers to an interface that allows users to input questions about weddings, funerals, and other ceremonial occasions into the system.

[0007] A "generation method" is a device that analyzes an input question and generates an appropriate answer.

[0008] A "presentation means" is a device that has the function of displaying or communicating the generated response and related information to the user.

[0009] A "procurement method" is a system that automatically arranges necessary goods and services based on the relevant information provided. [Brief explanation of the drawing]

[0010] [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] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0011] 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.

[0012] First, the terms used in the following description will be explained.

[0013] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

[0014] 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.

[0015] In the following embodiments, the tagged storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memories (SSDs (Solid State Drives)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0016] In the following embodiments, the tagged communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0017] 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 only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0018] [First Embodiment]

[0019] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0020] As shown in FIG. 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.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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".

[0031] This invention is a system that provides automated support for questions and procedures related to weddings, funerals, and other ceremonial occasions. The system operates by integrating four main functions: "input means," "generation means," "presentation means," and "arrangement means."

[0032] Terminal: An interface is provided that allows users to easily input questions into the system using their own devices, such as smartphones or computers. This interface allows for voice input and text input, and users can choose the most convenient method depending on the situation.

[0033] Server: The input information is transferred to the server, where the generation mechanism works. The server analyzes the content of the question and generates an appropriate answer. This process utilizes natural language processing (NLP) and generative AI technology to accurately understand the user's needs and instantly generate an answer that meets those needs.

[0034] Terminal: The generated response is displayed to the user via a presentation mechanism. Relevant options and suggestions are also provided, prompting arrangements such as booking a venue for the ceremony, filling out necessary documents, and selecting appropriate gifts. This presentation is designed to allow the user to easily make selections and proceed to the next step.

[0035] User: Based on the information provided, the user selects the necessary arrangements, and the arrangement process is activated. The selected arrangements are executed via the server, and for example, payment processing is carried out securely. This reduces cumbersome procedures for the user, allowing them to efficiently proceed with the necessary preparations for weddings, funerals, and other ceremonial occasions.

[0036] For example, if a user enters a question such as, "Please tell me how to arrange flowers for my grandmother's funeral," the process would proceed as follows: The server analyzes this information and generates a list of appropriate flower types and arrangement methods. The terminal presents this information to the user visually or audibly, and the system ensures that the user can safely complete the flower arrangements they have selected. This allows the user to complete difficult arrangements quickly, enabling them to focus their time on essential matters.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions via voice or text input. The interface here is designed to be user-friendly and intuitive.

[0040] Step 2:

[0041] Terminal: Sends the entered question as text data to the server. In the case of voice input, it is converted to text using speech recognition technology.

[0042] Step 3:

[0043] Server: The server analyzes the received text data using natural language processing (NLP) techniques. This identifies the subject and keywords of the question and determines the user's needs.

[0044] Step 4:

[0045] Server: Based on the identified keywords, it searches databases and external sources to collect relevant information. Next, it uses generative AI to further analyze this information and generate the most useful answers for the user.

[0046] Step 5:

[0047] Server: Compiles the generated responses and creates a dataset to present to the user. This dataset includes not only the specific answers but also related additional options and suggestions.

[0048] Step 6:

[0049] Terminal: Receives the dataset sent from the server and displays the answers and options to the user. For visual displays, text and links are shown on the screen; for audio displays, the information is conveyed as audio output.

[0050] Step 7:

[0051] User: Select the necessary arrangements from the presented options and suggestions and proceed with the operation. The selected information is sent back to the server via the terminal.

[0052] Step 8:

[0053] Server: Based on user selections, it executes specific arrangements (e.g., facility reservations and product orders) and processes payments as needed. Secure and fast processing is ensured.

[0054] Step 9:

[0055] Terminal: Displays confirmation information and completion of the arrangement to the user. It then presents an interface to guide the user through further actions to facilitate the transition.

[0056] (Example 1)

[0057] 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."

[0058] The procedures and arrangements related to weddings, funerals, and other ceremonial occasions are often complex and time-consuming, posing a significant psychological burden for users. Furthermore, finding appropriate actions and options for each event can be difficult, especially when considering cultural backgrounds and individual circumstances. This can lead to users being unable to quickly obtain necessary information and feeling anxious about the preparations.

[0059] 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.

[0060] In this invention, the server includes communication means for receiving questions from users and transferring information to a processing device, generation means for analyzing the transferred information and generating appropriate answers using generation AI technology, and presentation means for presenting the generated answers and related information to the user terminal and providing choices visually or audibly. This enables users to quickly and accurately obtain the necessary information and to smoothly proceed with arrangements related to weddings, funerals, and other ceremonial occasions.

[0061] A "communication method" is a system that has the function of receiving questions from users and transferring them to a processing unit.

[0062] "Generation means" refers to a method of analyzing transmitted information and generating an appropriate response using generation AI technology.

[0063] "Presentation method" refers to a method of displaying generated answers and related information on the user's terminal and providing options visually or audibly.

[0064] "Management measures" refer to the function of managing arrangements for providing services or products based on the presented options.

[0065] To carry out this invention, the following components are used.

[0066] The server functions as a central data processing unit, equipped with a natural language processing (NLP) engine to receive and analyze user questions and requests. This allows it to properly understand user input and structure the information given in natural language. The server also uses a generative AI model to generate appropriate responses based on the analyzed data. This AI model implements advanced algorithms, such as those utilizing machine learning.

[0067] The terminal acts as a user interface, designed to allow users to directly input questions via client devices (smartphones and PCs). The terminal features speech recognition software that converts user voice input into text, as well as a graphical user interface (GUI) for touch devices. It also presents answers received from the server to the user visually or audibly.

[0068] Users interact with the system by operating a terminal and asking specific questions. For example, a user might input a question like, "What are some recommended wedding favors?" into the terminal, and the server analyzes that information, generates a list of suitable wedding favors, and presents it to the user through the terminal. This allows the user to make an appropriate choice and, if necessary, select their favorite from the displayed options.

[0069] An example of a prompt in this system might be, "Please tell me a suitable funeral plan for my grandmother." In this way, the system supports users in making quick decisions in a variety of situations.

[0070] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0071] Step 1:

[0072] The user enters a question using the terminal. The user can choose between voice input or text input, and enters a prompt such as, for example, "What seasonal flowers are suitable for a wedding?" The terminal converts this input data into text format and prepares to send it to the server.

[0073] Step 2:

[0074] The terminal sends user input data to the server. Encryption technology is used to ensure data security during transmission. In this communication process, the entered text data is passed to the server.

[0075] Step 3:

[0076] The server analyzes the received text data. The natural language processing (NLP) engine performs grammatical and semantic analysis to understand the intent of the question. The analysis results output a basic understanding of the user's question and the extraction of related keywords.

[0077] Step 4:

[0078] The server uses a generative AI model to generate answers based on the analyzed information. The generative AI utilizes the model based on past data and patterns to generate answers that best match the user's intent. In this process, the server outputs specific answers, such as "Roses and lilies are suitable for spring weddings."

[0079] Step 5:

[0080] The server sends the generated response to the terminal. Again, the data is sent using a secure communication protocol, and the generated text data is transmitted to the terminal.

[0081] Step 6:

[0082] The terminal displays the responses received from the server to the user. The terminal provides information in a user-friendly format and also has an audio playback function as needed. Specifically, it visually lists options and suggestions so that the user can easily review them.

[0083] Step 7:

[0084] Users can make selections from the presented information and proceed with the necessary arrangements. For example, they can choose their preferred flowers from the provided options and proceed with the purchase process.

[0085] (Application Example 1)

[0086] 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."

[0087] The procedures and preparations associated with special events such as weddings, funerals, and other ceremonial occasions require considerable time and effort. Furthermore, the need for social and cultural considerations in each event complicates finding suitable options and arrangements for individual needs. Even with services like food delivery, selecting the optimal option from a diverse range of choices is difficult. To address these challenges, it is necessary to automate procedures smoothly and efficiently to meet user demands.

[0088] 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.

[0089] In this invention, the server includes an input means for inputting questions related to weddings, funerals, and other ceremonial occasions; a means for analyzing the input questions and generating appropriate answers; and a means for presenting the generated answers and related information to the user. This allows the user to centrally handle a wide range of matters and quickly obtain the optimal choice.

[0090] An "input method" is an interface that allows users to input questions and requests related to weddings, funerals, and other ceremonial occasions using a device.

[0091] A "generation method" is a function that performs a process to generate appropriate answers or options based on the input information.

[0092] "Presentation means" refers to a function for displaying generated answers and related information to the user visually or audibly.

[0093] "Arrangement method" refers to a function that automatically processes necessary procedures and orders based on the information provided.

[0094] "Natural language processing" is a technology that recognizes user input as natural language and analyzes its meaning.

[0095] "Order processing automation" means that the system automatically processes related orders and arrangements based on the options selected by the user.

[0096] The system implementing this invention is configured to allow users to easily handle questions and procedures related to weddings, funerals, and other ceremonial occasions. First, users can input the necessary information using voice or text via a device such as a smartphone or computer. This information is then converted into text using speech recognition technology such as the Google® API.

[0097] The server analyzes the input text using a natural language processing engine such as AWS® Comprehend. Based on the analysis results, it generates the optimal answer and relevant information using generative AI technologies such as OpenAI®'s GPT model. The generated answer is presented to the user's device, allowing the user to review the information visually or audibly.

[0098] Once the user makes a selection based on the information presented, the ordering process is activated. Using cloud services such as AWS Lambda, the ordering process is automated, and secure payment processing is carried out.

[0099] For example, if a user enters a request such as, "Please tell me what kind of food would be appropriate for a home party," the system will analyze it and suggest a suitable menu. An example of a prompt message in this case would be, "Please suggest the best options for the user to choose food for a home party. Please complete the ordering process based on the selected options."

[0100] This allows users to efficiently handle complex procedures, saving time and allowing them to focus on the essential aspects of the event.

[0101] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0102] Step 1:

[0103] Users input questions or requests using their smartphones or computers via voice or text. The input voice is converted to text using Google API's speech recognition function. The input data consists of the user's requests or questions, and the output is text data.

[0104] Step 2:

[0105] The server uses AWS Comprehend's natural language processing engine to analyze the input text data. The input for this step is the user's textual request; the server analyzes its content to grasp the main point and extracts the information necessary to generate an appropriate response. The output is computer-readable information as a result of the analysis.

[0106] Step 3:

[0107] Based on the analyzed information, the server generates responses and suggestions tailored to the user's requests using generative AI technologies such as OpenAI's GPT model. The input for this step is the result of natural language processing analysis, and the generated responses and suggestions are output. These responses include the information and recommended options the user is seeking.

[0108] Step 4:

[0109] The generated answers and suggestions are displayed on the device, and the user receives the information visually or audibly. The output answers and suggestions are displayed, and the user can make selections and decisions based on them. The input is the generated answers, and the output is the information the user understands.

[0110] Step 5:

[0111] When a user makes a selection based on the information presented, that information is sent to the server as a means of completing the procedure. The input is the user's selection, and the server prepares the data necessary for the next processing based on it. The output is the detailed information necessary for the procedure.

[0112] Step 6:

[0113] The server uses AWS Lambda to automatically arrange orders, such as food delivery, based on the selected options. The input for this step is the user's selected options, and the output is the details of the completed order confirmation. Payment processing is handled securely, and confirmation notifications are sent to the user as needed.

[0114] These steps allow users to complete the necessary procedures and arrangements for the event efficiently and smoothly.

[0115] 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.

[0116] This invention is a system aimed at resolving questions related to weddings, funerals, and other ceremonial occasions. In addition to analyzing user input and providing appropriate answers, it is designed to recognize the user's emotional state and respond accordingly. The system operates by integrating an "input means," a "generation means," a "presentation means," a "procedure means," and an "emotion engine."

[0117] Terminal: Provides an interface for users to input questions. This includes an operating environment that supports voice and text input and is designed for intuitive use. The terminal also collects data to infer emotions from the user's facial expressions and tone of voice.

[0118] Server: Receives information sent from the user via the terminal and analyzes the content of the question using natural language processing (NLP). Based on this analysis data, the generation unit creates an answer that meets the user's needs. In addition, the emotion engine analyzes the user's emotional state and makes emotion-based adjustments to the generated answer. For example, if the emotion engine recognizes that the user is in a state of sadness, the generation unit will generate an answer that contains more comforting elements.

[0119] Terminal: Presents the generated responses and adjusted information to the user. Here, the presentation format of the information (e.g., tone of voice output, text style, etc.) changes according to the user's emotions. This allows the user to receive the information with confidence.

[0120] User: Based on the information presented, the user can choose the next action. For example, a user who wants to arrange flowers suitable for a funeral can choose from emotionally sensitive suggestions and proceed with the arrangement.

[0121] For example, if a user enters the question, "What kind of greeting should I say at my grandfather's funeral?" into the device, the system analyzes the question and generates an appropriate greeting example. At the same time, the emotion engine reads the user's voice to indicate sadness, and the generation method adjusts to include a gentler tone and more comforting wording. The user receives this information and can take the necessary actions according to their mood. In this way, this system, which incorporates an emotion engine, can provide users with more flexible and personalized support.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions into the terminal using voice or text input. The terminal also utilizes a camera and microphone to collect the user's facial expressions and tone of voice.

[0125] Step 2:

[0126] Terminal: Sends digital data of the user's voice and facial expressions, along with the entered data, to the server.

[0127] Step 3:

[0128] Server: Analyzes the received question text data using natural language processing (NLP) to extract the intent of the question and keywords. Based on this information, it generates initial answer candidates.

[0129] Step 4:

[0130] Server: Simultaneously, the transmitted voice and facial expression data is analyzed by an emotion engine to identify the user's emotional state.

[0131] Step 5:

[0132] Server: Adjusts the generated response options according to the user's emotional state. For example, if the user is sad, elements of kindness and comfort will be added to the response.

[0133] Step 6:

[0134] Server: Configures and transmits the adjusted response and related information to the terminal. This data also includes necessary operating instructions and options.

[0135] Step 7:

[0136] Terminal: Receives data from the server and displays responses and information to the user. The display uses emotionally appropriate fonts and voice tones to convey information in a way that is more easily received by the user.

[0137] Step 8:

[0138] User: Based on the displayed information, select and execute the necessary arrangements and next actions. The system is designed to guide the user through the appropriate subsequent steps depending on the options they choose.

[0139] (Example 2)

[0140] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0141] Regarding questions related to weddings, funerals, and other ceremonial occasions, users face the challenge of not being able to quickly obtain appropriate and emotionally sensitive answers. Furthermore, conventional systems lack personalized responses that take into account the user's emotional state, resulting in a poor user experience.

[0142] 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.

[0143] In this invention, the server includes means for analyzing input questions using natural language processing technology, means for generating appropriate answers using a generative AI model, and means for adjusting the generated answers based on the user's emotional state. This enables users to quickly receive flexible and personalized support that takes their emotions into consideration for questions regarding weddings, funerals, and other ceremonial occasions.

[0144] An "input method" is a device that provides an interface for users to input questions about weddings, funerals, and other ceremonial occasions in voice or text format.

[0145] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract information from text and audio.

[0146] "Generation means" refers to a technology that has the function of creating appropriate answers using a generative AI model based on the data of the analyzed questions.

[0147] An "emotion adjustment mechanism" is a mechanism that analyzes the user's emotional state, adjusts the generated response accordingly, and provides content that is more relatable to the user.

[0148] "Presentation method" refers to an interface for displaying the finalized answer and related information to the user, providing information in either audio or text format.

[0149] "Arrangement method" refers to a system that manages the process of arranging goods or services based on the relevant information presented.

[0150] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates appropriate answers to user questions.

[0151] "Emotion recognition means" refers to technology that detects the user's voice and facial expressions and determines the user's emotions based on that.

[0152] To implement this invention, three main entities are required: a terminal, a server, and a user. Their respective roles are described in detail below.

[0153] terminal

[0154] The terminal is a device that provides an interface for users to input questions and inquiries. It supports both voice and text input and is equipped with a microphone and camera. This allows it to capture the user's voice and facial expression data. This data is sent to a server and used as a basis for identifying the user's emotional state.

[0155] server

[0156] The server receives data sent from the terminal and analyzes the entered question using natural language processing (NLP) techniques. The server uses NLP libraries such as the Google Cloud Natural Language API to identify keywords and key context in the input text. Furthermore, it analyzes the user's emotional state using an emotion engine, leveraging Azure Cognitive Services and similar solutions. Finally, a generative AI model is used to generate appropriate answers to the user's questions. This generation process involves designing prompt sentences and feeding them into the model to obtain responses. For example, a prompt such as "Please give me an example of an appropriate speech at a funeral" is input into the generative AI model.

[0157] User

[0158] The user receives generated and adjusted responses through their device. These responses are presented in a way that respects the user's emotions and are provided in audio and text formats. The user can then use this information to choose their next course of action. For example, they can arrange services based on the information provided.

[0159] For example, if a user enters the question, "What kind of greeting should I give at my grandfather's funeral?", the server analyzes the question, determines the user's emotional state, generates an appropriate greeting in a gentle tone, and presents it to the user via the terminal. In this way, the present invention can provide users with flexible support that is sensitive to their emotions.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] Receiving user input

[0163] The terminal receives user inquiries and questions in either voice or text format. Specifically, it records audio using the terminal's microphone and obtains text information through a text input field. The input data consists of strings or audio files entered by the user into the terminal. The terminal temporarily stores this data in a buffer before sending it to the server.

[0164] Step 2:

[0165] Analysis of the question

[0166] The server receives user input data sent from the terminal. It then analyzes the text or audio data using natural language processing techniques. The input data becomes string or audio data, which the server passes to the natural language processing engine. During processing, the Google Cloud Natural Language API or similar services are used to extract keywords and perform contextual analysis, thereby identifying the content and context of the question. The output consists of the analyzed text data and keyword set.

[0167] Step 3:

[0168] sentiment analysis

[0169] The server performs sentiment analysis on user input data. During this process, the sentiment engine determines the user's emotional state based on voice and facial expression data. The input data consists of voice and facial expression metadata, which is used for sentiment inference by a machine learning model. Specifically, Azure Cognitive Services is used to identify emotion labels (such as joy, sadness, or surprise). The output is a set of labels indicating the user's emotional state.

[0170] Step 4:

[0171] Generating an answer

[0172] The server generates an appropriate answer using a generative AI model based on the analyzed question content and sentiment analysis results. The input consists of structured question data and sentiment information. The server inputs this as a prompt into a generative AI model, such as OpenAI's GPT model, to generate an answer. Specifically, it creates a prompt sentence, inputs it into the generative AI model, and retrieves the answer. The output is the generated answer text.

[0173] Step 5:

[0174] Adjusting responses based on emotions

[0175] The server adjusts the generated response to match the user's emotions. The input consists of the response from the generation AI model and data on the user's emotional state. Based on the emotional information, the server adjusts the tone and content to create an emotionally resonant response. This involves changing the tone of the response and adding emotional considerations. The output is the final response text after the adjustments are complete.

[0176] Step 6:

[0177] Providing an answer

[0178] The terminal presents the user with a pre-configured answer. The input is the final answer text obtained from the server. The terminal displays the text on the screen and also provides an audio version using speech synthesis technology. Specifically, it displays the answer on the screen and plays it back using a speaker for text-to-speech synthesis. The output is the visual and auditory information provided to the user.

[0179] Step 7:

[0180] User action selection

[0181] The user selects their next action based on the information provided. Input is the information presented by the terminal. The user uses this information to proceed with their next action, such as arranging related services or goods. Specific actions include clicking on links to related options using the terminal and selecting arrangements. Output is a record of the actions and decisions made by the user.

[0182] (Application Example 2)

[0183] 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".

[0184] In addition to the difficulty in obtaining immediate and accurate answers to questions regarding procedures and etiquette at weddings, funerals, and other ceremonial occasions, there is a need for responses that take into consideration the feelings of the users. This invention aims to solve these problems and provide an information system that provides more personalized services to users.

[0185] 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.

[0186] In this invention, the server includes an operating environment, processing means, display means, adjustment means, and emotion recognition means. This makes it possible to instantly generate an answer to a user's question about weddings, funerals, and other ceremonial occasions, and to present it in an appropriate tone based on emotion recognition.

[0187] The "operating environment" is an interface for users to input questions and information, and it supports voice input and text input.

[0188] A "processing means" is a device that has the function of analyzing input information and generating appropriate responses or information.

[0189] "Display means" refers to a means of presenting generated information and related information to users in an easily understandable manner.

[0190] A "coordination mechanism" is a device that has the function of adjusting the preparation and procedures for goods and services desired by the user based on the displayed information.

[0191] An "emotion recognition tool" is a device that analyzes the user's emotional state and adjusts the information and tone presented accordingly.

[0192] This invention provides an information system for users to resolve questions related to weddings, funerals, and other ceremonial occasions. The system mainly consists of an operating environment, processing means, display means, adjustment means, and emotion recognition means.

[0193] First, the operating environment provides an interface for users to input questions via smart glasses or voice input devices. In the case of voice input, Google Cloud Speech-to-Text is used to convert speech to text.

[0194] Next, the processing mechanism is executed by the server, which analyzes the input text using spaCy as a natural language processing (NLP) engine. This generates accurate and appropriate responses and information to the user's questions.

[0195] The display method utilizes the smart glasses' display and audio output functions to present generated information to the user in an easy-to-understand manner. Crucially, the display method is adjusted by emotion recognition technology.

[0196] The coordinating mechanism is responsible for selecting and arranging the goods and services to be offered. This mechanism features a user-friendly interface for selecting desired options and proceeding accordingly.

[0197] Furthermore, the emotion recognition system uses a camera and microphone built into the smart glasses to analyze the user's emotions using the Google Cloud Vision API and Google Cloud Speech API. This allows the tone and expression of the generated information to be adjusted according to the user's emotional state.

[0198] For example, if a user inputs a question via voice, such as "What kind of greeting should I give at my grandfather's funeral?", the system analyzes the question and generates appropriate greeting examples. Furthermore, if the emotion recognition system identifies that the user is feeling depressed based on their tone of voice, the response is adjusted to include elements of comfort.

[0199] An example of a prompt might be: "Consider an appropriate answer based on the customer's question and its context, and adjust the tone according to their emotions."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The device receives voice input from the user and sends that data to the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data. Converting this voice data to text prepares it for the next processing step.

[0203] Step 2:

[0204] The server receives the text data obtained in Step 1 and begins analysis using spaCy, a natural language processing engine. This analysis extracts keywords, question types, and intents from the input text. The input is text data, and the output is structured data as a result of the analysis. Based on this data, preparations are made to generate appropriate answers.

[0205] Step 3:

[0206] The server uses a generative AI model to generate answers to user questions from structured data. The input is structured data, and the output is response text. The generated response is tailored to the user's needs, and the process proceeds to the next sentiment adjustment step.

[0207] Step 4:

[0208] The device captures the user's facial expressions and voice tone using its camera and microphone, and sends this data to the Google Cloud Vision API and Google Cloud Speech API. The input consists of audio and visual data, and the output is an analysis of the user's emotional state. Based on these results, the tone and expression of the response are adjusted.

[0209] Step 5:

[0210] The server adjusts the tone of the response text according to the user's emotional state. The input is the response text and sentiment analysis data, and the output is the adjusted response text. This adjustment enables more user-friendly and emotionally sensitive responses.

[0211] Step 6:

[0212] The device displays the adjusted response text on the smart glasses' display. The input is the adjusted response text, and the output is presented visually or audibly. This allows the user to receive accurate answers to their questions.

[0213] 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.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is a system that provides automated support for questions and procedures related to weddings, funerals, and other ceremonial occasions. The system operates by integrating four main functions: "input means," "generation means," "presentation means," and "arrangement means."

[0230] Terminal: An interface is provided that allows users to easily input questions into the system using their own devices, such as smartphones or computers. This interface allows for voice input and text input, and users can choose the most convenient method depending on the situation.

[0231] Server: The input information is transferred to the server, where the generation mechanism works. The server analyzes the content of the question and generates an appropriate answer. This process utilizes natural language processing (NLP) and generative AI technology to accurately understand the user's needs and instantly generate an answer that meets those needs.

[0232] Terminal: The generated response is displayed to the user via a presentation mechanism. Relevant options and suggestions are also provided, prompting arrangements such as booking a venue for the ceremony, filling out necessary documents, and selecting appropriate gifts. This presentation is designed to allow the user to easily make selections and proceed to the next step.

[0233] User: Based on the information provided, the user selects the necessary arrangements, and the arrangement process is activated. The selected arrangements are executed via the server, and for example, payment processing is carried out securely. This reduces cumbersome procedures for the user, allowing them to efficiently proceed with the necessary preparations for weddings, funerals, and other ceremonial occasions.

[0234] For example, if a user enters a question such as, "Please tell me how to arrange flowers for my grandmother's funeral," the process would proceed as follows: The server analyzes this information and generates a list of appropriate flower types and arrangement methods. The terminal presents this information to the user visually or audibly, and the system ensures that the user can safely complete the flower arrangements they have selected. This allows the user to complete difficult arrangements quickly, enabling them to focus their time on essential matters.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions via voice or text input. The interface here is designed to be user-friendly and intuitive.

[0238] Step 2:

[0239] Terminal: Sends the entered question as text data to the server. In the case of voice input, it is converted to text using speech recognition technology.

[0240] Step 3:

[0241] Server: The server analyzes the received text data using natural language processing (NLP) techniques. This identifies the subject and keywords of the question and determines the user's needs.

[0242] Step 4:

[0243] Server: Based on the identified keywords, it searches databases and external sources to collect relevant information. Next, it uses generative AI to further analyze this information and generate the most useful answers for the user.

[0244] Step 5:

[0245] Server: Compiles the generated responses and creates a dataset to present to the user. This dataset includes not only the specific answers but also related additional options and suggestions.

[0246] Step 6:

[0247] Terminal: Receives the dataset sent from the server and displays the answers and options to the user. For visual displays, text and links are shown on the screen; for audio displays, the information is conveyed as audio output.

[0248] Step 7:

[0249] User: Select the necessary arrangements from the presented options and suggestions and proceed with the operation. The selected information is sent back to the server via the terminal.

[0250] Step 8:

[0251] Server: Based on user selections, it executes specific arrangements (e.g., facility reservations and product orders) and processes payments as needed. Secure and fast processing is ensured.

[0252] Step 9:

[0253] Terminal: Displays confirmation information and completion of the arrangement to the user. It then presents an interface to guide the user through further actions to facilitate the transition.

[0254] (Example 1)

[0255] 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."

[0256] The procedures and arrangements related to weddings, funerals, and other ceremonial occasions are often complex and time-consuming, posing a significant psychological burden for users. Furthermore, finding appropriate actions and options for each event can be difficult, especially when considering cultural backgrounds and individual circumstances. This can lead to users being unable to quickly obtain necessary information and feeling anxious about the preparations.

[0257] 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.

[0258] In this invention, the server includes communication means for receiving questions from users and transferring information to a processing device, generation means for analyzing the transferred information and generating appropriate answers using generation AI technology, and presentation means for presenting the generated answers and related information to the user terminal and providing choices visually or audibly. This enables users to quickly and accurately obtain the necessary information and to smoothly proceed with arrangements related to weddings, funerals, and other ceremonial occasions.

[0259] A "communication method" is a system that has the function of receiving questions from users and transferring them to a processing unit.

[0260] "Generation means" refers to a method of analyzing transmitted information and generating an appropriate response using generation AI technology.

[0261] "Presentation method" refers to a method of displaying generated answers and related information on the user's terminal and providing options visually or audibly.

[0262] "Management measures" refer to the function of managing arrangements for providing services or products based on the presented options.

[0263] To carry out this invention, the following components are used.

[0264] The server functions as a central data processing unit, equipped with a natural language processing (NLP) engine to receive and analyze user questions and requests. This allows it to properly understand user input and structure the information given in natural language. The server also uses a generative AI model to generate appropriate responses based on the analyzed data. This AI model implements advanced algorithms, such as those utilizing machine learning.

[0265] The terminal acts as a user interface, designed to allow users to directly input questions via client devices (smartphones and PCs). The terminal features speech recognition software that converts user voice input into text, as well as a graphical user interface (GUI) for touch devices. It also presents answers received from the server to the user visually or audibly.

[0266] Users interact with the system by operating a terminal and asking specific questions. For example, a user might input a question like, "What are some recommended wedding favors?" into the terminal, and the server analyzes that information, generates a list of suitable wedding favors, and presents it to the user through the terminal. This allows the user to make an appropriate choice and, if necessary, select their favorite from the displayed options.

[0267] An example of a prompt in this system might be, "Please tell me a suitable funeral plan for my grandmother." In this way, the system supports users in making quick decisions in a variety of situations.

[0268] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0269] Step 1:

[0270] The user enters a question using the terminal. The user can choose between voice input or text input, and enters a prompt such as, for example, "What seasonal flowers are suitable for a wedding?" The terminal converts this input data into text format and prepares to send it to the server.

[0271] Step 2:

[0272] The terminal sends user input data to the server. Encryption technology is used to ensure data security during transmission. In this communication process, the entered text data is passed to the server.

[0273] Step 3:

[0274] The server analyzes the received text data. The natural language processing (NLP) engine performs grammatical and semantic analysis to understand the intent of the question. The analysis results output a basic understanding of the user's question and the extraction of related keywords.

[0275] Step 4:

[0276] Based on the analyzed information, the server creates an answer using a generative AI model. The generative AI utilizes the model based on past data and patterns to generate an answer that best matches the user's intent. At this time, the server outputs a specific answer such as "Roses and lilies are suitable for a spring wedding."

[0277] Step 5:

[0278] The server sends the generated answer to the terminal. Also in this case, the data is sent using a secure communication protocol, and the generated text data is sent to the terminal.

[0279] Step 6:

[0280] The terminal displays the answer received from the server to the user. The terminal provides information in a format that is easy for the user to understand and also has a function to reproduce it in voice if necessary. Specifically, options and suggestions are visually listed so that the user can easily confirm them.

[0281] Step 7:

[0282] The user can make a selection from the presented information and proceed with the necessary arrangements. For example, the user can select their favorite flower from the provided options and the purchase procedure can be advanced.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] Procedures and preparations related to special events such as weddings, funerals, and coming-of-age ceremonies require a lot of time and effort. Also, since social and cultural considerations are necessary for each event, it has become more complicated to find options and arrangement procedures suitable for individual needs. Furthermore, even in food delivery services, it is difficult to choose the optimal one from a variety of options. It is necessary to solve these problems and automate smooth and efficient procedures according to user requests.

[0286] 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.

[0287] In this invention, the server includes an input means for inputting questions related to weddings, funerals, and coming-of-age ceremonies, a means for analyzing the input questions and generating appropriate answers, and a means for presenting the generated answers and related information to the user. As a result, the user can handle a wide variety of processes in a unified manner and can quickly obtain the optimal option.

[0288] The "input means" is an interface for the user to input questions and requests related to weddings, funerals, and coming-of-age ceremonies using a device.

[0289] The "generation means" is a function that performs a process for generating appropriate answers and options based on the input information.

[0290] The "presentation means" is a function for visually or audibly presenting the generated answers and related information to the user.

[0291] The "arrangement means" is a function for automatically processing necessary procedures and orders based on the presented information.

[0292] "Natural language analysis" is a technology that recognizes the user's input as natural language and analyzes its meaning.

[0293] "Order processing automation" means that the system automatically processes related orders and arrangements based on the options selected by the user.

[0294] The system implementing this invention is configured to allow users to easily handle questions and procedures related to weddings, funerals, and other ceremonial occasions. First, users can input the necessary information using voice or text via a device such as a smartphone or computer. This information is then converted into text using speech recognition technology such as the Google API.

[0295] The server analyzes the input text using a natural language processing engine such as AWS Comprehend. Based on the analysis results, it generates the optimal response and relevant information using generative AI technologies such as OpenAI's GPT model. The generated response is presented to the user's device, allowing the user to review the information visually or audibly.

[0296] Once the user makes a selection based on the information presented, the ordering process is activated. Using cloud services such as AWS Lambda, the ordering process is automated, and secure payment processing is carried out.

[0297] For example, if a user enters a request such as, "Please tell me what kind of food would be appropriate for a home party," the system will analyze it and suggest a suitable menu. An example of a prompt message in this case would be, "Please suggest the best options for the user to choose food for a home party. Please complete the ordering process based on the selected options."

[0298] This allows users to efficiently handle complex procedures, saving time and allowing them to focus on the essential aspects of the event.

[0299] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0300] Step 1:

[0301] The user uses a terminal such as a smartphone or computer to input questions or requests in voice or text. The input voice is converted into text by the voice recognition function of the Google API. The data input is the user's requests and questions, and the output is text data.

[0302] Step 2:

[0303] The server uses the natural language processing engine of AWS Comprehend to analyze the input text data. The input for this step is the user's texturized request, and the server analyzes its content to grasp the main idea and extracts the information necessary for generating an appropriate answer. The output is information that can be understood by the computer as the analysis result.

[0304] Step 3:

[0305] Based on the analyzed information, the server uses generative AI technologies such as the GPT model of OpenAI to generate answers and suggestions according to the user's requests. The input for this step is the analysis result by natural language processing, and the generated answers and suggestions are output. And it contains the information and recommended options that the user is seeking.

[0306] Step 4:

[0307] The generated answers and suggestions are displayed on the terminal, and the user receives the information visually or audibly. The output answers and suggestions are displayed, and the user can make selections and decisions based on them. The input is the generated answer, and the output is the information understood by the user.

[0308] Step 5:

[0309] When a user makes a selection based on the information presented, that information is sent to the server as a means of completing the procedure. The input is the user's selection, and the server prepares the data necessary for the next processing based on it. The output is the detailed information necessary for the procedure.

[0310] Step 6:

[0311] The server uses AWS Lambda to automatically arrange orders, such as food delivery, based on the selected options. The input for this step is the user's selected options, and the output is the details of the completed order confirmation. Payment processing is handled securely, and confirmation notifications are sent to the user as needed.

[0312] These steps allow users to complete the necessary procedures and arrangements for the event efficiently and smoothly.

[0313] 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.

[0314] This invention is a system aimed at resolving questions related to weddings, funerals, and other ceremonial occasions. In addition to analyzing user input and providing appropriate answers, it is designed to recognize the user's emotional state and respond accordingly. The system operates by integrating an "input means," a "generation means," a "presentation means," a "procedure means," and an "emotion engine."

[0315] Terminal: Provides an interface for users to input questions. This includes an operating environment that supports voice and text input and is designed for intuitive use. The terminal also collects data to infer emotions from the user's facial expressions and tone of voice.

[0316] Server: Receives information sent from the user via the terminal and analyzes the content of the question using natural language processing (NLP). Based on this analysis data, the generation unit creates an answer that meets the user's needs. In addition, the emotion engine analyzes the user's emotional state and makes emotion-based adjustments to the generated answer. For example, if the emotion engine recognizes that the user is in a state of sadness, the generation unit will generate an answer that contains more comforting elements.

[0317] Terminal: Presents the generated responses and adjusted information to the user. Here, the presentation format of the information (e.g., tone of voice output, text style, etc.) changes according to the user's emotions. This allows the user to receive the information with confidence.

[0318] User: Based on the information presented, the user can choose the next action. For example, a user who wants to arrange flowers suitable for a funeral can choose from emotionally sensitive suggestions and proceed with the arrangement.

[0319] For example, if a user enters the question, "What kind of greeting should I say at my grandfather's funeral?" into the device, the system analyzes the question and generates an appropriate greeting example. At the same time, the emotion engine reads the user's voice to indicate sadness, and the generation method adjusts to include a gentler tone and more comforting wording. The user receives this information and can take the necessary actions according to their mood. In this way, this system, which incorporates an emotion engine, can provide users with more flexible and personalized support.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions into the terminal using voice or text input. The terminal also utilizes a camera and microphone to collect the user's facial expressions and tone of voice.

[0323] Step 2:

[0324] Terminal: Sends digital data of the user's voice and facial expressions, along with the entered data, to the server.

[0325] Step 3:

[0326] Server: Analyzes the received question text data using natural language processing (NLP) to extract the intent of the question and keywords. Based on this information, it generates initial answer candidates.

[0327] Step 4:

[0328] Server: Simultaneously, the transmitted voice and facial expression data is analyzed by an emotion engine to identify the user's emotional state.

[0329] Step 5:

[0330] Server: Adjusts the generated response options according to the user's emotional state. For example, if the user is sad, elements of kindness and comfort will be added to the response.

[0331] Step 6:

[0332] Server: Configures and transmits the adjusted response and related information to the terminal. This data also includes necessary operating instructions and options.

[0333] Step 7:

[0334] Terminal: Receives data from the server and displays responses and information to the user. The display uses emotionally appropriate fonts and voice tones to convey information in a way that is more easily received by the user.

[0335] Step 8:

[0336] User: Based on the displayed information, select and execute the necessary arrangements and next actions. The system is designed to guide the user through the appropriate subsequent steps depending on the options they choose.

[0337] (Example 2)

[0338] 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".

[0339] Regarding questions related to weddings, funerals, and other ceremonial occasions, users face the challenge of not being able to quickly obtain appropriate and emotionally sensitive answers. Furthermore, conventional systems lack personalized responses that take into account the user's emotional state, resulting in a poor user experience.

[0340] 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.

[0341] In this invention, the server includes means for analyzing input questions using natural language processing technology, means for generating appropriate answers using a generative AI model, and means for adjusting the generated answers based on the user's emotional state. This enables users to quickly receive flexible and personalized support that takes their emotions into consideration for questions regarding weddings, funerals, and other ceremonial occasions.

[0342] An "input method" is a device that provides an interface for users to input questions about weddings, funerals, and other ceremonial occasions in voice or text format.

[0343] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract information from text and audio.

[0344] "Generation means" refers to a technology that has the function of creating appropriate answers using a generative AI model based on the data of the analyzed questions.

[0345] An "emotion adjustment mechanism" is a mechanism that analyzes the user's emotional state, adjusts the generated response accordingly, and provides content that is more relatable to the user.

[0346] "Presentation method" refers to an interface for displaying the finalized answer and related information to the user, providing information in either audio or text format.

[0347] "Arrangement method" refers to a system that manages the process of arranging goods or services based on the relevant information presented.

[0348] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates appropriate answers to user questions.

[0349] "Emotion recognition means" refers to technology that detects the user's voice and facial expressions and determines the user's emotions based on that.

[0350] To implement this invention, three main entities are required: a terminal, a server, and a user. Their respective roles are described in detail below.

[0351] terminal

[0352] The terminal is a device that provides an interface for users to input questions and inquiries. It supports both voice and text input and is equipped with a microphone and camera. This allows it to capture the user's voice and facial expression data. This data is sent to a server and used as a basis for identifying the user's emotional state.

[0353] server

[0354] The server receives data sent from the terminal and analyzes the entered question using natural language processing (NLP) techniques. The server uses NLP libraries such as the Google Cloud Natural Language API to identify keywords and key context in the input text. Furthermore, it utilizes an emotion engine, leveraging Azure Cognitive Services and similar solutions, to analyze the user's emotional state. Finally, a generative AI model is used to generate appropriate answers to the user's questions. This generation process involves designing prompt sentences and feeding them into the model to obtain responses. For example, a prompt such as "Please give me an example of an appropriate speech at a funeral" might be input into the generative AI model.

[0355] User

[0356] The user receives generated and adjusted responses through their device. These responses are presented in a way that respects the user's emotions and are provided in audio and text formats. The user can then use this information to choose their next course of action. For example, they can arrange services based on the information provided.

[0357] For example, if a user enters the question, "What kind of greeting should I give at my grandfather's funeral?", the server analyzes the question, determines the user's emotional state, generates an appropriate greeting in a gentle tone, and presents it to the user via the terminal. In this way, the present invention can provide users with flexible support that is sensitive to their emotions.

[0358] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0359] Step 1:

[0360] Receiving user input

[0361] The terminal receives user inquiries and questions in either voice or text format. Specifically, it records audio using the terminal's microphone and obtains text information through a text input field. The input data consists of strings or audio files entered by the user into the terminal. The terminal temporarily stores this data in a buffer before sending it to the server.

[0362] Step 2:

[0363] Analysis of the question

[0364] The server receives user input data sent from the terminal. It then analyzes the text or audio data using natural language processing techniques. The input data becomes string or audio data, which the server passes to the natural language processing engine. During processing, the Google Cloud Natural Language API or similar services are used to extract keywords and perform contextual analysis, thereby identifying the content and context of the question. The output consists of the analyzed text data and keyword set.

[0365] Step 3:

[0366] sentiment analysis

[0367] The server performs sentiment analysis on user input data. During this process, the sentiment engine determines the user's emotional state based on voice and facial expression data. The input data consists of voice and facial expression metadata, which is used for sentiment inference by a machine learning model. Specifically, Azure Cognitive Services is used to identify emotion labels (such as joy, sadness, or surprise). The output is a set of labels indicating the user's emotional state.

[0368] Step 4:

[0369] Generating an answer

[0370] The server generates an appropriate answer using a generative AI model based on the analyzed question content and sentiment analysis results. The input consists of structured question data and sentiment information. The server inputs this as a prompt into a generative AI model, such as OpenAI's GPT model, to generate an answer. Specifically, it creates a prompt sentence, inputs it into the generative AI model, and retrieves the answer. The output is the generated answer text.

[0371] Step 5:

[0372] Adjusting responses based on emotions

[0373] The server adjusts the generated response to match the user's emotions. The input consists of the response from the generation AI model and data on the user's emotional state. Based on the emotional information, the server adjusts the tone and content to create an emotionally resonant response. This involves changing the tone of the response and adding emotional considerations. The output is the final response text after the adjustments are complete.

[0374] Step 6:

[0375] Providing an answer

[0376] The terminal presents the user with a pre-configured answer. The input is the final answer text obtained from the server. The terminal displays the text on the screen and also provides an audio version using speech synthesis technology. Specifically, it displays the answer on the screen and plays it back using a speaker for text-to-speech synthesis. The output is the visual and auditory information provided to the user.

[0377] Step 7:

[0378] User action selection

[0379] The user selects their next action based on the information provided. Input is the information presented by the terminal. The user uses this information to proceed with their next action, such as arranging related services or goods. Specific actions include clicking on links to related options using the terminal and selecting arrangements. Output is a record of the actions and decisions made by the user.

[0380] (Application Example 2)

[0381] 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."

[0382] In addition to the difficulty in obtaining immediate and accurate answers to questions regarding procedures and etiquette at weddings, funerals, and other ceremonial occasions, there is a need for responses that take into consideration the feelings of the users. This invention aims to solve these problems and provide an information system that provides more personalized services to users.

[0383] 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.

[0384] In this invention, the server includes an operating environment, processing means, display means, adjustment means, and emotion recognition means. This makes it possible to instantly generate an answer to a user's question about weddings, funerals, and other ceremonial occasions, and to present it in an appropriate tone based on emotion recognition.

[0385] The "operating environment" is an interface for users to input questions and information, and it supports voice input and text input.

[0386] A "processing means" is a device that has the function of analyzing input information and generating appropriate responses or information.

[0387] "Display means" refers to a means of presenting generated information and related information to users in an easily understandable manner.

[0388] A "coordination mechanism" is a device that has the function of adjusting the preparation and procedures for goods and services desired by the user based on the displayed information.

[0389] An "emotion recognition tool" is a device that analyzes the user's emotional state and adjusts the information and tone presented accordingly.

[0390] This invention provides an information system for users to resolve questions related to weddings, funerals, and other ceremonial occasions. The system mainly consists of an operating environment, processing means, display means, adjustment means, and emotion recognition means.

[0391] First, the operating environment provides an interface for users to input questions via smart glasses or voice input devices. In the case of voice input, Google Cloud Speech-to-Text is used to convert speech to text.

[0392] Next, the processing mechanism is executed by the server, which analyzes the input text using spaCy as a natural language processing (NLP) engine. This generates accurate and appropriate responses and information to the user's questions.

[0393] The display method utilizes the smart glasses' display and audio output functions to present generated information to the user in an easy-to-understand manner. Crucially, the display method is adjusted by emotion recognition technology.

[0394] The coordinating mechanism is responsible for selecting and arranging the goods and services to be offered. This mechanism features a user-friendly interface for selecting desired options and proceeding accordingly.

[0395] Furthermore, the emotion recognition system uses a camera and microphone built into the smart glasses to analyze the user's emotions using the Google Cloud Vision API and Google Cloud Speech API. This allows the tone and expression of the generated information to be adjusted according to the user's emotional state.

[0396] For example, if a user inputs a question via voice, such as "What kind of greeting should I give at my grandfather's funeral?", the system analyzes the question and generates appropriate greeting examples. Furthermore, if the emotion recognition system identifies that the user is feeling depressed based on their tone of voice, the response is adjusted to include elements of comfort.

[0397] An example of a prompt might be: "Consider an appropriate answer based on the customer's question and its context, and adjust the tone according to their emotions."

[0398] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0399] Step 1:

[0400] The device receives voice input from the user and sends that data to the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data. Converting this voice data to text prepares it for the next processing step.

[0401] Step 2:

[0402] The server receives the text data obtained in Step 1 and begins analysis using spaCy, a natural language processing engine. This analysis extracts keywords, question types, and intents from the input text. The input is text data, and the output is structured data as a result of the analysis. Based on this data, preparations are made to generate appropriate answers.

[0403] Step 3:

[0404] The server uses a generative AI model to generate answers to user questions from structured data. The input is structured data, and the output is response text. The generated response is tailored to the user's needs, and the process proceeds to the next sentiment adjustment step.

[0405] Step 4:

[0406] The device captures the user's facial expressions and voice tone using its camera and microphone, and sends this data to the Google Cloud Vision API and Google Cloud Speech API. The input consists of audio and visual data, and the output is an analysis of the user's emotional state. Based on these results, the tone and expression of the response are adjusted.

[0407] Step 5:

[0408] The server adjusts the tone of the response text according to the user's emotional state. The input is the response text and sentiment analysis data, and the output is the adjusted response text. This adjustment enables more user-friendly and emotionally sensitive responses.

[0409] Step 6:

[0410] The device displays the adjusted response text on the smart glasses' display. The input is the adjusted response text, and the output is presented visually or audibly. This allows the user to receive accurate answers to their questions.

[0411] 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.

[0412] 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.

[0413] 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.

[0414] [Third Embodiment]

[0415] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0416] 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.

[0417] 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).

[0418] 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.

[0419] 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.

[0420] 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).

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] 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".

[0427] This invention is a system that provides automated support for questions and procedures related to weddings, funerals, and other ceremonial occasions. The system operates by integrating four main functions: "input means," "generation means," "presentation means," and "arrangement means."

[0428] Terminal: An interface is provided that allows users to easily input questions into the system using their own devices, such as smartphones or computers. This interface allows for voice input and text input, and users can choose the most convenient method depending on the situation.

[0429] Server: The input information is transferred to the server, where the generation mechanism works. The server analyzes the content of the question and generates an appropriate answer. This process utilizes natural language processing (NLP) and generative AI technology to accurately understand the user's needs and instantly generate an answer that meets those needs.

[0430] Terminal: The generated response is displayed to the user via a presentation mechanism. Relevant options and suggestions are also provided, prompting arrangements such as booking a venue for the ceremony, filling out necessary documents, and selecting appropriate gifts. This presentation is designed to allow the user to easily make selections and proceed to the next step.

[0431] User: Based on the information provided, the user selects the necessary arrangements, and the arrangement process is activated. The selected arrangements are executed via the server, and for example, payment processing is carried out securely. This reduces cumbersome procedures for the user, allowing them to efficiently proceed with the necessary preparations for weddings, funerals, and other ceremonial occasions.

[0432] For example, if a user enters a question such as, "Please tell me how to arrange flowers for my grandmother's funeral," the process would proceed as follows: The server analyzes this information and generates a list of appropriate flower types and arrangement methods. The terminal presents this information to the user visually or audibly, and the system ensures that the user can safely complete the flower arrangements they have selected. This allows the user to complete difficult arrangements quickly, enabling them to focus their time on essential matters.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions via voice or text input. The interface here is designed to be user-friendly and intuitive.

[0436] Step 2:

[0437] Terminal: Sends the entered question as text data to the server. In the case of voice input, it is converted to text using speech recognition technology.

[0438] Step 3:

[0439] Server: The server analyzes the received text data using natural language processing (NLP) techniques. This identifies the subject and keywords of the question and determines the user's needs.

[0440] Step 4:

[0441] Server: Based on the identified keywords, it searches databases and external sources to collect relevant information. Next, it uses generative AI to further analyze this information and generate the most useful answers for the user.

[0442] Step 5:

[0443] Server: Compiles the generated responses and creates a dataset to present to the user. This dataset includes not only the specific answers but also related additional options and suggestions.

[0444] Step 6:

[0445] Terminal: Receives the dataset sent from the server and displays the answers and options to the user. For visual displays, text and links are shown on the screen; for audio displays, the information is conveyed as audio output.

[0446] Step 7:

[0447] User: Select the necessary arrangements from the presented options and suggestions and proceed with the operation. The selected information is sent back to the server via the terminal.

[0448] Step 8:

[0449] Server: Based on user selections, it executes specific arrangements (e.g., facility reservations and product orders) and processes payments as needed. Secure and fast processing is ensured.

[0450] Step 9:

[0451] Terminal: Displays confirmation information and completion of the arrangement to the user. It then presents an interface to guide the user through further actions to facilitate the transition.

[0452] (Example 1)

[0453] 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."

[0454] The procedures and arrangements related to weddings, funerals, and other ceremonial occasions are often complex and time-consuming, posing a significant psychological burden for users. Furthermore, finding appropriate actions and options for each event can be difficult, especially when considering cultural backgrounds and individual circumstances. This can lead to users being unable to quickly obtain necessary information and feeling anxious about the preparations.

[0455] 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.

[0456] In this invention, the server includes communication means for receiving questions from users and transferring information to a processing device, generation means for analyzing the transferred information and generating appropriate answers using generation AI technology, and presentation means for presenting the generated answers and related information to the user terminal and providing choices visually or audibly. This enables users to quickly and accurately obtain the necessary information and to smoothly proceed with arrangements related to weddings, funerals, and other ceremonial occasions.

[0457] A "communication method" is a system that has the function of receiving questions from users and transferring them to a processing unit.

[0458] "Generation means" refers to a method of analyzing transmitted information and generating an appropriate response using generation AI technology.

[0459] "Presentation method" refers to a method of displaying generated answers and related information on the user's terminal and providing options visually or audibly.

[0460] "Management measures" refer to the function of managing arrangements for providing services or products based on the presented options.

[0461] To carry out this invention, the following components are used.

[0462] The server functions as a central data processing unit, equipped with a natural language processing (NLP) engine to receive and analyze user questions and requests. This allows it to properly understand user input and structure the information given in natural language. The server also uses a generative AI model to generate appropriate responses based on the analyzed data. This AI model implements advanced algorithms, such as those utilizing machine learning.

[0463] The terminal acts as a user interface, designed to allow users to directly input questions via client devices (smartphones and PCs). The terminal features speech recognition software that converts user voice input into text, as well as a graphical user interface (GUI) for touch devices. It also presents answers received from the server to the user visually or audibly.

[0464] Users interact with the system by operating a terminal and asking specific questions. For example, a user might input a question like, "What are some recommended wedding favors?" into the terminal, and the server analyzes that information, generates a list of suitable wedding favors, and presents it to the user through the terminal. This allows the user to make an appropriate choice and, if necessary, select their favorite from the displayed options.

[0465] An example of a prompt in this system might be, "Please tell me a suitable funeral plan for my grandmother." In this way, the system supports users in making quick decisions in a variety of situations.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] The user enters a question using the terminal. The user can choose between voice input or text input, and enters a prompt such as, for example, "What seasonal flowers are suitable for a wedding?" The terminal converts this input data into text format and prepares to send it to the server.

[0469] Step 2:

[0470] The terminal sends user input data to the server. Encryption technology is used to ensure data security during transmission. In this communication process, the entered text data is passed to the server.

[0471] Step 3:

[0472] The server analyzes the received text data. The natural language processing (NLP) engine performs grammatical and semantic analysis to understand the intent of the question. The analysis results output a basic understanding of the user's question and the extraction of related keywords.

[0473] Step 4:

[0474] The server uses a generative AI model to generate answers based on the analyzed information. The generative AI utilizes the model based on past data and patterns to generate answers that best match the user's intent. In this process, the server outputs specific answers, such as "Roses and lilies are suitable for spring weddings."

[0475] Step 5:

[0476] The server sends the generated response to the terminal. Again, the data is sent using a secure communication protocol, and the generated text data is transmitted to the terminal.

[0477] Step 6:

[0478] The terminal displays the responses received from the server to the user. The terminal provides information in a user-friendly format and also has an audio playback function as needed. Specifically, it visually lists options and suggestions so that the user can easily review them.

[0479] Step 7:

[0480] Users can make selections from the presented information and proceed with the necessary arrangements. For example, they can choose their preferred flowers from the provided options and proceed with the purchase process.

[0481] (Application Example 1)

[0482] 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."

[0483] The procedures and preparations associated with special events such as weddings, funerals, and other ceremonial occasions require considerable time and effort. Furthermore, the need for social and cultural considerations in each event complicates finding suitable options and arrangements for individual needs. Even with services like food delivery, selecting the optimal option from a diverse range of choices is difficult. To address these challenges, it is necessary to automate procedures smoothly and efficiently to meet user demands.

[0484] 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.

[0485] In this invention, the server includes an input means for inputting questions related to weddings, funerals, and other ceremonial occasions; a means for analyzing the input questions and generating appropriate answers; and a means for presenting the generated answers and related information to the user. This allows the user to centrally handle a wide range of matters and quickly obtain the optimal choice.

[0486] An "input method" is an interface that allows users to input questions and requests related to weddings, funerals, and other ceremonial occasions using a device.

[0487] A "generation method" is a function that performs a process to generate appropriate answers or options based on the input information.

[0488] "Presentation means" refers to a function for displaying generated answers and related information to the user visually or audibly.

[0489] "Arrangement method" refers to a function that automatically processes necessary procedures and orders based on the information provided.

[0490] "Natural language processing" is a technology that recognizes user input as natural language and analyzes its meaning.

[0491] "Order processing automation" means that the system automatically processes related orders and arrangements based on the options selected by the user.

[0492] The system implementing this invention is configured to allow users to easily handle questions and procedures related to weddings, funerals, and other ceremonial occasions. First, users can input the necessary information using voice or text via a device such as a smartphone or computer. This information is then converted into text using speech recognition technology such as the Google API.

[0493] The server analyzes the input text using a natural language processing engine such as AWS Comprehend. Based on the analysis results, it generates the optimal response and relevant information using generative AI technologies such as OpenAI's GPT model. The generated response is presented to the user's device, allowing the user to review the information visually or audibly.

[0494] Once the user makes a selection based on the information presented, the ordering process is activated. Using cloud services such as AWS Lambda, the ordering process is automated, and secure payment processing is carried out.

[0495] For example, if a user enters a request such as, "Please tell me what kind of food would be appropriate for a home party," the system will analyze it and suggest a suitable menu. An example of a prompt message in this case would be, "Please suggest the best options for the user to choose food for a home party. Please complete the ordering process based on the selected options."

[0496] This allows users to efficiently handle complex procedures, saving time and allowing them to focus on the essential aspects of the event.

[0497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0498] Step 1:

[0499] Users input questions or requests using their smartphones or computers via voice or text. The input voice is converted to text using Google API's speech recognition function. The input data consists of the user's requests or questions, and the output is text data.

[0500] Step 2:

[0501] The server uses AWS Comprehend's natural language processing engine to analyze the input text data. The input for this step is the user's textual request; the server analyzes its content to grasp the main point and extracts the information necessary to generate an appropriate response. The output is computer-readable information as a result of the analysis.

[0502] Step 3:

[0503] Based on the analyzed information, the server generates responses and suggestions tailored to the user's requests using generative AI technologies such as OpenAI's GPT model. The input for this step is the result of natural language processing analysis, and the generated responses and suggestions are output. These responses include the information and recommended options the user is seeking.

[0504] Step 4:

[0505] The generated answers and suggestions are displayed on the device, and the user receives the information visually or audibly. The output answers and suggestions are displayed, and the user can make selections and decisions based on them. The input is the generated answers, and the output is the information the user understands.

[0506] Step 5:

[0507] When a user makes a selection based on the information presented, that information is sent to the server as a means of completing the procedure. The input is the user's selection, and the server prepares the data necessary for the next processing based on it. The output is the detailed information necessary for the procedure.

[0508] Step 6:

[0509] The server uses AWS Lambda to automatically arrange orders, such as food delivery, based on the selected options. The input for this step is the user's selected options, and the output is the details of the completed order confirmation. Payment processing is handled securely, and confirmation notifications are sent to the user as needed.

[0510] These steps allow users to complete the necessary procedures and arrangements for the event efficiently and smoothly.

[0511] 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.

[0512] This invention is a system aimed at resolving questions related to weddings, funerals, and other ceremonial occasions. In addition to analyzing user input and providing appropriate answers, it is designed to recognize the user's emotional state and respond accordingly. The system operates by integrating an "input means," a "generation means," a "presentation means," a "procedure means," and an "emotion engine."

[0513] Terminal: Provides an interface for users to input questions. This includes an operating environment that supports voice and text input and is designed for intuitive use. The terminal also collects data to infer emotions from the user's facial expressions and tone of voice.

[0514] Server: Receives information sent from the user via the terminal and analyzes the content of the question using natural language processing (NLP). Based on this analysis data, the generation unit creates an answer that meets the user's needs. In addition, the emotion engine analyzes the user's emotional state and makes emotion-based adjustments to the generated answer. For example, if the emotion engine recognizes that the user is in a state of sadness, the generation unit will generate an answer that contains more comforting elements.

[0515] Terminal: Presents the generated responses and adjusted information to the user. Here, the presentation format of the information (e.g., tone of voice output, text style, etc.) changes according to the user's emotions. This allows the user to receive the information with confidence.

[0516] User: Based on the information presented, the user can choose the next action. For example, a user who wants to arrange flowers suitable for a funeral can choose from emotionally sensitive suggestions and proceed with the arrangement.

[0517] For example, if a user enters the question, "What kind of greeting should I say at my grandfather's funeral?" into the device, the system analyzes the question and generates an appropriate greeting example. At the same time, the emotion engine reads the user's voice to indicate sadness, and the generation method adjusts to include a gentler tone and more comforting wording. The user receives this information and can take the necessary actions according to their mood. In this way, this system, which incorporates an emotion engine, can provide users with more flexible and personalized support.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions into the terminal using voice or text input. The terminal also utilizes a camera and microphone to collect the user's facial expressions and tone of voice.

[0521] Step 2:

[0522] Terminal: Sends digital data of the user's voice and facial expressions, along with the entered data, to the server.

[0523] Step 3:

[0524] Server: Analyzes the received question text data using natural language processing (NLP) to extract the intent of the question and keywords. Based on this information, it generates initial answer candidates.

[0525] Step 4:

[0526] Server: Simultaneously, the transmitted voice and facial expression data is analyzed by an emotion engine to identify the user's emotional state.

[0527] Step 5:

[0528] Server: Adjusts the generated response options according to the user's emotional state. For example, if the user is sad, elements of kindness and comfort will be added to the response.

[0529] Step 6:

[0530] Server: Configures and transmits the adjusted response and related information to the terminal. This data also includes necessary operating instructions and options.

[0531] Step 7:

[0532] Terminal: Receives data from the server and displays responses and information to the user. The display uses emotionally appropriate fonts and voice tones to convey information in a way that is more easily received by the user.

[0533] Step 8:

[0534] User: Based on the displayed information, select and execute the necessary arrangements and next actions. The system is designed to guide the user through the appropriate subsequent steps depending on the options they choose.

[0535] (Example 2)

[0536] 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."

[0537] Regarding questions related to weddings, funerals, and other ceremonial occasions, users face the challenge of not being able to quickly obtain appropriate and emotionally sensitive answers. Furthermore, conventional systems lack personalized responses that take into account the user's emotional state, resulting in a poor user experience.

[0538] 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.

[0539] In this invention, the server includes means for analyzing input questions using natural language processing technology, means for generating appropriate answers using a generative AI model, and means for adjusting the generated answers based on the user's emotional state. This enables users to quickly receive flexible and personalized support that takes their emotions into consideration for questions regarding weddings, funerals, and other ceremonial occasions.

[0540] An "input method" is a device that provides an interface for users to input questions about weddings, funerals, and other ceremonial occasions in voice or text format.

[0541] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract information from text and audio.

[0542] "Generation means" refers to a technology that has the function of creating appropriate answers using a generative AI model based on the data of the analyzed questions.

[0543] An "emotion adjustment mechanism" is a mechanism that analyzes the user's emotional state, adjusts the generated response accordingly, and provides content that is more relatable to the user.

[0544] "Presentation method" refers to an interface for displaying the finalized answer and related information to the user, providing information in either audio or text format.

[0545] "Arrangement method" refers to a system that manages the process of arranging goods or services based on the relevant information presented.

[0546] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates appropriate answers to user questions.

[0547] "Emotion recognition means" refers to technology that detects the user's voice and facial expressions and determines the user's emotions based on that.

[0548] To implement this invention, three main entities are required: a terminal, a server, and a user. Their respective roles are described in detail below.

[0549] terminal

[0550] The terminal is a device that provides an interface for users to input questions and inquiries. It supports both voice and text input and is equipped with a microphone and camera. This allows it to capture the user's voice and facial expression data. This data is sent to a server and used as a basis for identifying the user's emotional state.

[0551] server

[0552] The server receives data sent from the terminal and analyzes the entered question using natural language processing (NLP) techniques. The server uses NLP libraries such as the Google Cloud Natural Language API to identify keywords and key context in the input text. Furthermore, it utilizes an emotion engine, leveraging Azure Cognitive Services and similar solutions, to analyze the user's emotional state. Finally, a generative AI model is used to generate appropriate answers to the user's questions. This generation process involves designing prompt sentences and feeding them into the model to obtain responses. For example, a prompt such as "Please give me an example of an appropriate speech at a funeral" might be input into the generative AI model.

[0553] User

[0554] The user receives generated and adjusted responses through their device. These responses are presented in a way that respects the user's emotions and are provided in audio and text formats. The user can then use this information to choose their next course of action. For example, they can arrange services based on the information provided.

[0555] For example, if a user enters the question, "What kind of greeting should I give at my grandfather's funeral?", the server analyzes the question, determines the user's emotional state, generates an appropriate greeting in a gentle tone, and presents it to the user via the terminal. In this way, the present invention can provide users with flexible support that is sensitive to their emotions.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] Receiving user input

[0559] The terminal receives user inquiries and questions in either voice or text format. Specifically, it records audio using the terminal's microphone and obtains text information through a text input field. The input data consists of strings or audio files entered by the user into the terminal. The terminal temporarily stores this data in a buffer before sending it to the server.

[0560] Step 2:

[0561] Analysis of the question

[0562] The server receives user input data sent from the terminal. It then analyzes the text or audio data using natural language processing techniques. The input data becomes string or audio data, which the server passes to the natural language processing engine. During processing, the Google Cloud Natural Language API or similar services are used to extract keywords and perform contextual analysis, thereby identifying the content and context of the question. The output consists of the analyzed text data and keyword set.

[0563] Step 3:

[0564] sentiment analysis

[0565] The server performs sentiment analysis on user input data. During this process, the sentiment engine determines the user's emotional state based on voice and facial expression data. The input data consists of voice and facial expression metadata, which is used for sentiment inference by a machine learning model. Specifically, Azure Cognitive Services is used to identify emotion labels (such as joy, sadness, or surprise). The output is a set of labels indicating the user's emotional state.

[0566] Step 4:

[0567] Generating an answer

[0568] The server generates an appropriate answer using a generative AI model based on the analyzed question content and sentiment analysis results. The input consists of structured question data and sentiment information. The server inputs this as a prompt into a generative AI model, such as OpenAI's GPT model, to generate an answer. Specifically, it creates a prompt sentence, inputs it into the generative AI model, and retrieves the answer. The output is the generated answer text.

[0569] Step 5:

[0570] Adjusting responses based on emotions

[0571] The server adjusts the generated response to match the user's emotions. The input consists of the response from the generation AI model and data on the user's emotional state. Based on the emotional information, the server adjusts the tone and content to create an emotionally resonant response. This involves changing the tone of the response and adding emotional considerations. The output is the final response text after the adjustments are complete.

[0572] Step 6:

[0573] Providing an answer

[0574] The terminal presents the user with a pre-configured answer. The input is the final answer text obtained from the server. The terminal displays the text on the screen and also provides an audio version using speech synthesis technology. Specifically, it displays the answer on the screen and plays it back using a speaker for text-to-speech synthesis. The output is the visual and auditory information provided to the user.

[0575] Step 7:

[0576] User action selection

[0577] The user selects their next action based on the information provided. Input is the information presented by the terminal. The user uses this information to proceed with their next action, such as arranging related services or goods. Specific actions include clicking on links to related options using the terminal and selecting arrangements. Output is a record of the actions and decisions made by the user.

[0578] (Application Example 2)

[0579] 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."

[0580] In addition to the difficulty in obtaining immediate and accurate answers to questions regarding procedures and etiquette at weddings, funerals, and other ceremonial occasions, there is a need for responses that take into consideration the feelings of the users. This invention aims to solve these problems and provide an information system that provides more personalized services to users.

[0581] 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.

[0582] In this invention, the server includes an operating environment, processing means, display means, adjustment means, and emotion recognition means. This makes it possible to instantly generate an answer to a user's question about weddings, funerals, and other ceremonial occasions, and to present it in an appropriate tone based on emotion recognition.

[0583] The "operating environment" is an interface for users to input questions and information, and it supports voice input and text input.

[0584] A "processing means" is a device that has the function of analyzing input information and generating appropriate responses or information.

[0585] "Display means" refers to a means of presenting generated information and related information to users in an easily understandable manner.

[0586] A "coordination mechanism" is a device that has the function of adjusting the preparation and procedures for goods and services desired by the user based on the displayed information.

[0587] An "emotion recognition tool" is a device that analyzes the user's emotional state and adjusts the information and tone presented accordingly.

[0588] This invention provides an information system for users to resolve questions related to weddings, funerals, and other ceremonial occasions. The system mainly consists of an operating environment, processing means, display means, adjustment means, and emotion recognition means.

[0589] First, the operating environment provides an interface for users to input questions via smart glasses or voice input devices. In the case of voice input, Google Cloud Speech-to-Text is used to convert speech to text.

[0590] Next, the processing mechanism is executed by the server, which analyzes the input text using spaCy as a natural language processing (NLP) engine. This generates accurate and appropriate responses and information to the user's questions.

[0591] The display method utilizes the smart glasses' display and audio output functions to present generated information to the user in an easy-to-understand manner. Crucially, the display method is adjusted by emotion recognition technology.

[0592] The coordinating mechanism is responsible for selecting and arranging the goods and services to be offered. This mechanism features a user-friendly interface for selecting desired options and proceeding accordingly.

[0593] Furthermore, the emotion recognition system uses a camera and microphone built into the smart glasses to analyze the user's emotions using the Google Cloud Vision API and Google Cloud Speech API. This allows the tone and expression of the generated information to be adjusted according to the user's emotional state.

[0594] For example, if a user inputs a question via voice, such as "What kind of greeting should I give at my grandfather's funeral?", the system analyzes the question and generates appropriate greeting examples. Furthermore, if the emotion recognition system identifies that the user is feeling depressed based on their tone of voice, the response is adjusted to include elements of comfort.

[0595] An example of a prompt might be: "Consider an appropriate answer based on the customer's question and its context, and adjust the tone according to their emotions."

[0596] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0597] Step 1:

[0598] The device receives voice input from the user and sends that data to the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data. Converting this voice data to text prepares it for the next processing step.

[0599] Step 2:

[0600] The server receives the text data obtained in Step 1 and begins analysis using spaCy, a natural language processing engine. This analysis extracts keywords, question types, and intents from the input text. The input is text data, and the output is structured data as a result of the analysis. Based on this data, preparations are made to generate appropriate answers.

[0601] Step 3:

[0602] The server uses a generative AI model to generate answers to user questions from structured data. The input is structured data, and the output is response text. The generated response is tailored to the user's needs, and the process proceeds to the next sentiment adjustment step.

[0603] Step 4:

[0604] The device captures the user's facial expressions and voice tone using its camera and microphone, and sends this data to the Google Cloud Vision API and Google Cloud Speech API. The input consists of audio and visual data, and the output is an analysis of the user's emotional state. Based on these results, the tone and expression of the response are adjusted.

[0605] Step 5:

[0606] The server adjusts the tone of the response text according to the user's emotional state. The input is the response text and sentiment analysis data, and the output is the adjusted response text. This adjustment enables more user-friendly and emotionally sensitive responses.

[0607] Step 6:

[0608] The device displays the adjusted response text on the smart glasses' display. The input is the adjusted response text, and the output is presented visually or audibly. This allows the user to receive accurate answers to their questions.

[0609] 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.

[0610] 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.

[0611] 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.

[0612] [Fourth Embodiment]

[0613] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0614] 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.

[0615] 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).

[0616] 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.

[0617] 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.

[0618] 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).

[0619] 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.

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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.

[0624] 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.

[0625] 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".

[0626] This invention is a system that provides automated support for questions and procedures related to weddings, funerals, and other ceremonial occasions. The system operates by integrating four main functions: "input means," "generation means," "presentation means," and "arrangement means."

[0627] Terminal: An interface is provided that allows users to easily input questions into the system using their own devices, such as smartphones or computers. This interface allows for voice input and text input, and users can choose the most convenient method depending on the situation.

[0628] Server: The input information is transferred to the server, where the generation mechanism works. The server analyzes the content of the question and generates an appropriate answer. This process utilizes natural language processing (NLP) and generative AI technology to accurately understand the user's needs and instantly generate an answer that meets those needs.

[0629] Terminal: The generated response is displayed to the user via a presentation mechanism. Relevant options and suggestions are also provided, prompting arrangements such as booking a venue for the ceremony, filling out necessary documents, and selecting appropriate gifts. This presentation is designed to allow the user to easily make selections and proceed to the next step.

[0630] User: Based on the information provided, the user selects the necessary arrangements, and the arrangement process is activated. The selected arrangements are executed via the server, and for example, payment processing is carried out securely. This reduces cumbersome procedures for the user, allowing them to efficiently proceed with the necessary preparations for weddings, funerals, and other ceremonial occasions.

[0631] For example, if a user enters a question such as, "Please tell me how to arrange flowers for my grandmother's funeral," the process would proceed as follows: The server analyzes this information and generates a list of appropriate flower types and arrangement methods. The terminal presents this information to the user visually or audibly, and the system ensures that the user can safely complete the flower arrangements they have selected. This allows the user to complete difficult arrangements quickly, enabling them to focus their time on essential matters.

[0632] The following describes the processing flow.

[0633] Step 1:

[0634] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions via voice or text input. The interface here is designed to be user-friendly and intuitive.

[0635] Step 2:

[0636] Terminal: Sends the entered question as text data to the server. In the case of voice input, it is converted to text using speech recognition technology.

[0637] Step 3:

[0638] Server: The server analyzes the received text data using natural language processing (NLP) techniques. This identifies the subject and keywords of the question and determines the user's needs.

[0639] Step 4:

[0640] Server: Based on the identified keywords, it searches databases and external sources to collect relevant information. Next, it uses generative AI to further analyze this information and generate the most useful answers for the user.

[0641] Step 5:

[0642] Server: Compiles the generated responses and creates a dataset to present to the user. This dataset includes not only the specific answers but also related additional options and suggestions.

[0643] Step 6:

[0644] Terminal: Receives the dataset sent from the server and displays the answers and options to the user. For visual displays, text and links are shown on the screen; for audio displays, the information is conveyed as audio output.

[0645] Step 7:

[0646] User: Select the necessary arrangements from the presented options and suggestions and proceed with the operation. The selected information is sent back to the server via the terminal.

[0647] Step 8:

[0648] Server: Based on user selections, it executes specific arrangements (e.g., facility reservations and product orders) and processes payments as needed. Secure and fast processing is ensured.

[0649] Step 9:

[0650] Terminal: Displays confirmation information and completion of the arrangement to the user. It then presents an interface to guide the user through further actions to facilitate the transition.

[0651] (Example 1)

[0652] 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".

[0653] The procedures and arrangements related to weddings, funerals, and other ceremonial occasions are often complex and time-consuming, posing a significant psychological burden for users. Furthermore, finding appropriate actions and options for each event can be difficult, especially when considering cultural backgrounds and individual circumstances. This can lead to users being unable to quickly obtain necessary information and feeling anxious about the preparations.

[0654] 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.

[0655] In this invention, the server includes communication means for receiving questions from users and transferring information to a processing device, generation means for analyzing the transferred information and generating appropriate answers using generation AI technology, and presentation means for presenting the generated answers and related information to the user terminal and providing choices visually or audibly. This enables users to quickly and accurately obtain the necessary information and to smoothly proceed with arrangements related to weddings, funerals, and other ceremonial occasions.

[0656] A "communication method" is a system that has the function of receiving questions from users and transferring them to a processing unit.

[0657] "Generation means" refers to a method of analyzing transmitted information and generating an appropriate response using generation AI technology.

[0658] "Presentation method" refers to a method of displaying generated answers and related information on the user's terminal and providing options visually or audibly.

[0659] "Management measures" refer to the function of managing arrangements for providing services or products based on the presented options.

[0660] To carry out this invention, the following components are used.

[0661] The server functions as a central data processing unit, equipped with a natural language processing (NLP) engine to receive and analyze user questions and requests. This allows it to properly understand user input and structure the information given in natural language. The server also uses a generative AI model to generate appropriate responses based on the analyzed data. This AI model implements advanced algorithms, such as those utilizing machine learning.

[0662] The terminal acts as a user interface, designed to allow users to directly input questions via client devices (smartphones and PCs). The terminal features speech recognition software that converts user voice input into text, as well as a graphical user interface (GUI) for touch devices. It also presents answers received from the server to the user visually or audibly.

[0663] Users interact with the system by operating a terminal and asking specific questions. For example, a user might input a question like, "What are some recommended wedding favors?" into the terminal, and the server analyzes that information, generates a list of suitable wedding favors, and presents it to the user through the terminal. This allows the user to make an appropriate choice and, if necessary, select their favorite from the displayed options.

[0664] An example of a prompt in this system might be, "Please tell me a suitable funeral plan for my grandmother." In this way, the system supports users in making quick decisions in a variety of situations.

[0665] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0666] Step 1:

[0667] The user enters a question using the terminal. The user can choose between voice input or text input, and enters a prompt such as, for example, "What seasonal flowers are suitable for a wedding?" The terminal converts this input data into text format and prepares to send it to the server.

[0668] Step 2:

[0669] The terminal sends user input data to the server. Encryption technology is used to ensure data security during transmission. In this communication process, the entered text data is passed to the server.

[0670] Step 3:

[0671] The server analyzes the received text data. The natural language processing (NLP) engine performs grammatical and semantic analysis to understand the intent of the question. The analysis results output a basic understanding of the user's question and the extraction of related keywords.

[0672] Step 4:

[0673] The server uses a generative AI model to generate answers based on the analyzed information. The generative AI utilizes the model based on past data and patterns to generate answers that best match the user's intent. In this process, the server outputs specific answers, such as "Roses and lilies are suitable for spring weddings."

[0674] Step 5:

[0675] The server sends the generated response to the terminal. Again, the data is sent using a secure communication protocol, and the generated text data is transmitted to the terminal.

[0676] Step 6:

[0677] The terminal displays the responses received from the server to the user. The terminal provides information in a user-friendly format and also has an audio playback function as needed. Specifically, it visually lists options and suggestions so that the user can easily review them.

[0678] Step 7:

[0679] Users can make selections from the presented information and proceed with the necessary arrangements. For example, they can choose their preferred flowers from the provided options and proceed with the purchase process.

[0680] (Application Example 1)

[0681] 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".

[0682] The procedures and preparations associated with special events such as weddings, funerals, and other ceremonial occasions require considerable time and effort. Furthermore, the need for social and cultural considerations in each event complicates finding suitable options and arrangements for individual needs. Even with services like food delivery, selecting the optimal option from a diverse range of choices is difficult. To address these challenges, it is necessary to automate procedures smoothly and efficiently to meet user demands.

[0683] 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.

[0684] In this invention, the server includes an input means for inputting questions related to weddings, funerals, and other ceremonial occasions; a means for analyzing the input questions and generating appropriate answers; and a means for presenting the generated answers and related information to the user. This allows the user to centrally handle a wide range of matters and quickly obtain the optimal choice.

[0685] An "input method" is an interface that allows users to input questions and requests related to weddings, funerals, and other ceremonial occasions using a device.

[0686] A "generation method" is a function that performs a process to generate appropriate answers or options based on the input information.

[0687] "Presentation means" refers to a function for displaying generated answers and related information to the user visually or audibly.

[0688] "Arrangement method" refers to a function that automatically processes necessary procedures and orders based on the information provided.

[0689] "Natural language processing" is a technology that recognizes user input as natural language and analyzes its meaning.

[0690] "Order processing automation" means that the system automatically processes related orders and arrangements based on the options selected by the user.

[0691] The system implementing this invention is configured to allow users to easily handle questions and procedures related to weddings, funerals, and other ceremonial occasions. First, users can input the necessary information using voice or text via a device such as a smartphone or computer. This information is then converted into text using speech recognition technology such as the Google API.

[0692] The server analyzes the input text using a natural language processing engine such as AWS Comprehend. Based on the analysis results, it generates the optimal response and relevant information using generative AI technologies such as OpenAI's GPT model. The generated response is presented to the user's device, allowing the user to review the information visually or audibly.

[0693] Once the user makes a selection based on the information presented, the ordering process is activated. Using cloud services such as AWS Lambda, the ordering process is automated, and secure payment processing is carried out.

[0694] For example, if a user enters a request such as, "Please tell me what kind of food would be appropriate for a home party," the system will analyze it and suggest a suitable menu. An example of a prompt message in this case would be, "Please suggest the best options for the user to choose food for a home party. Please complete the ordering process based on the selected options."

[0695] This allows users to efficiently handle complex procedures, saving time and allowing them to focus on the essential aspects of the event.

[0696] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0697] Step 1:

[0698] Users input questions or requests using their smartphones or computers via voice or text. The input voice is converted to text using Google API's speech recognition function. The input data consists of the user's requests or questions, and the output is text data.

[0699] Step 2:

[0700] The server uses AWS Comprehend's natural language processing engine to analyze the input text data. The input for this step is the user's textual request; the server analyzes its content to grasp the main point and extracts the information necessary to generate an appropriate response. The output is computer-readable information as a result of the analysis.

[0701] Step 3:

[0702] Based on the analyzed information, the server generates responses and suggestions tailored to the user's requests using generative AI technologies such as OpenAI's GPT model. The input for this step is the result of natural language processing analysis, and the generated responses and suggestions are output. These responses include the information and recommended options the user is seeking.

[0703] Step 4:

[0704] The generated answers and suggestions are displayed on the device, and the user receives the information visually or audibly. The output answers and suggestions are displayed, and the user can make selections and decisions based on them. The input is the generated answers, and the output is the information the user understands.

[0705] Step 5:

[0706] When a user makes a selection based on the information presented, that information is sent to the server as a means of completing the procedure. The input is the user's selection, and the server prepares the data necessary for the next processing based on it. The output is the detailed information necessary for the procedure.

[0707] Step 6:

[0708] The server uses AWS Lambda to automatically arrange orders, such as food delivery, based on the selected options. The input for this step is the user's selected options, and the output is the details of the completed order confirmation. Payment processing is handled securely, and confirmation notifications are sent to the user as needed.

[0709] These steps allow users to complete the necessary procedures and arrangements for the event efficiently and smoothly.

[0710] 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.

[0711] This invention is a system aimed at resolving questions related to weddings, funerals, and other ceremonial occasions. In addition to analyzing user input and providing appropriate answers, it is designed to recognize the user's emotional state and respond accordingly. The system operates by integrating an "input means," a "generation means," a "presentation means," a "procedure means," and an "emotion engine."

[0712] Terminal: Provides an interface for users to input questions. This includes an operating environment that supports voice and text input and is designed for intuitive use. The terminal also collects data to infer emotions from the user's facial expressions and tone of voice.

[0713] Server: Receives information sent from the user via the terminal and analyzes the content of the question using natural language processing (NLP). Based on this analysis data, the generation unit creates an answer that meets the user's needs. In addition, the emotion engine analyzes the user's emotional state and makes emotion-based adjustments to the generated answer. For example, if the emotion engine recognizes that the user is in a state of sadness, the generation unit will generate an answer that contains more comforting elements.

[0714] Terminal: Presents the generated responses and adjusted information to the user. Here, the presentation format of the information (e.g., tone of voice output, text style, etc.) changes according to the user's emotions. This allows the user to receive the information with confidence.

[0715] User: Based on the information presented, the user can choose the next action. For example, a user who wants to arrange flowers suitable for a funeral can choose from emotionally sensitive suggestions and proceed with the arrangement.

[0716] For example, if a user enters the question, "What kind of greeting should I say at my grandfather's funeral?" into the device, the system analyzes the question and generates an appropriate greeting example. At the same time, the emotion engine reads the user's voice to indicate sadness, and the generation method adjusts to include a gentler tone and more comforting wording. The user receives this information and can take the necessary actions according to their mood. In this way, this system, which incorporates an emotion engine, can provide users with more flexible and personalized support.

[0717] The following describes the processing flow.

[0718] Step 1:

[0719] Terminal: Users input questions about weddings, funerals, and other ceremonial occasions into the terminal using voice or text input. The terminal also utilizes a camera and microphone to collect the user's facial expressions and tone of voice.

[0720] Step 2:

[0721] Terminal: Sends digital data of the user's voice and facial expressions, along with the entered data, to the server.

[0722] Step 3:

[0723] Server: Analyzes the received question text data using natural language processing (NLP) to extract the intent of the question and keywords. Based on this information, it generates initial answer candidates.

[0724] Step 4:

[0725] Server: Simultaneously, the transmitted voice and facial expression data is analyzed by an emotion engine to identify the user's emotional state.

[0726] Step 5:

[0727] Server: Adjusts the generated response options according to the user's emotional state. For example, if the user is sad, elements of kindness and comfort will be added to the response.

[0728] Step 6:

[0729] Server: Configures and transmits the adjusted response and related information to the terminal. This data also includes necessary operating instructions and options.

[0730] Step 7:

[0731] Terminal: Receives data from the server and displays responses and information to the user. The display uses emotionally appropriate fonts and voice tones to convey information in a way that is more easily received by the user.

[0732] Step 8:

[0733] User: Based on the displayed information, select and execute the necessary arrangements and next actions. The system is designed to guide the user through the appropriate subsequent steps depending on the options they choose.

[0734] (Example 2)

[0735] 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".

[0736] Regarding questions related to weddings, funerals, and other ceremonial occasions, users face the challenge of not being able to quickly obtain appropriate and emotionally sensitive answers. Furthermore, conventional systems lack personalized responses that take into account the user's emotional state, resulting in a poor user experience.

[0737] 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.

[0738] In this invention, the server includes means for analyzing input questions using natural language processing technology, means for generating appropriate answers using a generative AI model, and means for adjusting the generated answers based on the user's emotional state. This enables users to quickly receive flexible and personalized support that takes their emotions into consideration for questions regarding weddings, funerals, and other ceremonial occasions.

[0739] An "input method" is a device that provides an interface for users to input questions about weddings, funerals, and other ceremonial occasions in voice or text format.

[0740] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract information from text and audio.

[0741] "Generation means" refers to a technology that has the function of creating appropriate answers using a generative AI model based on the data of the analyzed questions.

[0742] An "emotion adjustment mechanism" is a mechanism that analyzes the user's emotional state, adjusts the generated response accordingly, and provides content that is more relatable to the user.

[0743] "Presentation method" refers to an interface for displaying the finalized answer and related information to the user, providing information in either audio or text format.

[0744] "Arrangement method" refers to a system that manages the process of arranging goods or services based on the relevant information presented.

[0745] A "generative AI model" refers to artificial intelligence technology that learns from large amounts of data and automatically generates appropriate answers to user questions.

[0746] "Emotion recognition means" refers to technology that detects the user's voice and facial expressions and determines the user's emotions based on that.

[0747] To implement this invention, three main entities are required: a terminal, a server, and a user. Their respective roles are described in detail below.

[0748] terminal

[0749] The terminal is a device that provides an interface for users to input questions and inquiries. It supports both voice and text input and is equipped with a microphone and camera. This allows it to capture the user's voice and facial expression data. This data is sent to a server and used as a basis for identifying the user's emotional state.

[0750] server

[0751] The server receives data sent from the terminal and analyzes the entered question using natural language processing (NLP) techniques. The server uses NLP libraries such as the Google Cloud Natural Language API to identify keywords and key context in the input text. Furthermore, it utilizes an emotion engine, leveraging Azure Cognitive Services and similar solutions, to analyze the user's emotional state. Finally, a generative AI model is used to generate appropriate answers to the user's questions. This generation process involves designing prompt sentences and feeding them into the model to obtain responses. For example, a prompt such as "Please give me an example of an appropriate speech at a funeral" might be input into the generative AI model.

[0752] User

[0753] The user receives generated and adjusted responses through their device. These responses are presented in a way that respects the user's emotions and are provided in audio and text formats. The user can then use this information to choose their next course of action. For example, they can arrange services based on the information provided.

[0754] For example, if a user enters the question, "What kind of greeting should I give at my grandfather's funeral?", the server analyzes the question, determines the user's emotional state, generates an appropriate greeting in a gentle tone, and presents it to the user via the terminal. In this way, the present invention can provide users with flexible support that is sensitive to their emotions.

[0755] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0756] Step 1:

[0757] Receiving user input

[0758] The terminal receives user inquiries and questions in either voice or text format. Specifically, it records audio using the terminal's microphone and obtains text information through a text input field. The input data consists of strings or audio files entered by the user into the terminal. The terminal temporarily stores this data in a buffer before sending it to the server.

[0759] Step 2:

[0760] Analysis of the question

[0761] The server receives user input data sent from the terminal. It then analyzes the text or audio data using natural language processing techniques. The input data becomes string or audio data, which the server passes to the natural language processing engine. During processing, the Google Cloud Natural Language API or similar services are used to extract keywords and perform contextual analysis, thereby identifying the content and context of the question. The output consists of the analyzed text data and keyword set.

[0762] Step 3:

[0763] sentiment analysis

[0764] The server performs sentiment analysis on user input data. During this process, the sentiment engine determines the user's emotional state based on voice and facial expression data. The input data consists of voice and facial expression metadata, which is used for sentiment inference by a machine learning model. Specifically, Azure Cognitive Services is used to identify emotion labels (such as joy, sadness, or surprise). The output is a set of labels indicating the user's emotional state.

[0765] Step 4:

[0766] Generating an answer

[0767] The server generates an appropriate answer using a generative AI model based on the analyzed question content and sentiment analysis results. The input consists of structured question data and sentiment information. The server inputs this as a prompt into a generative AI model, such as OpenAI's GPT model, to generate an answer. Specifically, it creates a prompt sentence, inputs it into the generative AI model, and retrieves the answer. The output is the generated answer text.

[0768] Step 5:

[0769] Adjusting responses based on emotions

[0770] The server adjusts the generated response to match the user's emotions. The input consists of the response from the generation AI model and data on the user's emotional state. Based on the emotional information, the server adjusts the tone and content to create an emotionally resonant response. This involves changing the tone of the response and adding emotional considerations. The output is the final response text after the adjustments are complete.

[0771] Step 6:

[0772] Providing an answer

[0773] The terminal presents the user with a pre-configured answer. The input is the final answer text obtained from the server. The terminal displays the text on the screen and also provides an audio version using speech synthesis technology. Specifically, it displays the answer on the screen and plays it back using a speaker for text-to-speech synthesis. The output is the visual and auditory information provided to the user.

[0774] Step 7:

[0775] User action selection

[0776] The user selects their next action based on the information provided. Input is the information presented by the terminal. The user uses this information to proceed with their next action, such as arranging related services or goods. Specific actions include clicking on links to related options using the terminal and selecting arrangements. Output is a record of the actions and decisions made by the user.

[0777] (Application Example 2)

[0778] 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".

[0779] In addition to the difficulty in obtaining immediate and accurate answers to questions regarding procedures and etiquette at weddings, funerals, and other ceremonial occasions, there is a need for responses that take into consideration the feelings of the users. This invention aims to solve these problems and provide an information system that provides more personalized services to users.

[0780] 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.

[0781] In this invention, the server includes an operating environment, processing means, display means, adjustment means, and emotion recognition means. This makes it possible to instantly generate an answer to a user's question about weddings, funerals, and other ceremonial occasions, and to present it in an appropriate tone based on emotion recognition.

[0782] The "operating environment" is an interface for users to input questions and information, and it supports voice input and text input.

[0783] A "processing means" is a device that has the function of analyzing input information and generating appropriate responses or information.

[0784] "Display means" refers to a means of presenting generated information and related information to users in an easily understandable manner.

[0785] A "coordination mechanism" is a device that has the function of adjusting the preparation and procedures for goods and services desired by the user based on the displayed information.

[0786] An "emotion recognition tool" is a device that analyzes the user's emotional state and adjusts the information and tone presented accordingly.

[0787] This invention provides an information system for users to resolve questions related to weddings, funerals, and other ceremonial occasions. The system mainly consists of an operating environment, processing means, display means, adjustment means, and emotion recognition means.

[0788] First, the operating environment provides an interface for users to input questions via smart glasses or voice input devices. In the case of voice input, Google Cloud Speech-to-Text is used to convert speech to text.

[0789] Next, the processing mechanism is executed by the server, which analyzes the input text using spaCy as a natural language processing (NLP) engine. This generates accurate and appropriate responses and information to the user's questions.

[0790] The display method utilizes the smart glasses' display and audio output functions to present generated information to the user in an easy-to-understand manner. Crucially, the display method is adjusted by emotion recognition technology.

[0791] The coordinating mechanism is responsible for selecting and arranging the goods and services to be offered. This mechanism features a user-friendly interface for selecting desired options and proceeding accordingly.

[0792] Furthermore, the emotion recognition system uses a camera and microphone built into the smart glasses to analyze the user's emotions using the Google Cloud Vision API and Google Cloud Speech API. This allows the tone and expression of the generated information to be adjusted according to the user's emotional state.

[0793] For example, if a user inputs a question via voice, such as "What kind of greeting should I give at my grandfather's funeral?", the system analyzes the question and generates appropriate greeting examples. Furthermore, if the emotion recognition system identifies that the user is feeling depressed based on their tone of voice, the response is adjusted to include elements of comfort.

[0794] An example of a prompt might be: "Consider an appropriate answer based on the customer's question and its context, and adjust the tone according to their emotions."

[0795] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0796] Step 1:

[0797] The device receives voice input from the user and sends that data to the Google Cloud Speech-to-Text API. The input is voice data, and the output is text data. Converting this voice data to text prepares it for the next processing step.

[0798] Step 2:

[0799] The server receives the text data obtained in Step 1 and begins analysis using spaCy, a natural language processing engine. This analysis extracts keywords, question types, and intents from the input text. The input is text data, and the output is structured data as a result of the analysis. Based on this data, preparations are made to generate appropriate answers.

[0800] Step 3:

[0801] The server uses a generative AI model to generate answers to user questions from structured data. The input is structured data, and the output is response text. The generated response is tailored to the user's needs, and the process proceeds to the next sentiment adjustment step.

[0802] Step 4:

[0803] The device captures the user's facial expressions and voice tone using its camera and microphone, and sends this data to the Google Cloud Vision API and Google Cloud Speech API. The input consists of audio and visual data, and the output is an analysis of the user's emotional state. Based on these results, the tone and expression of the response are adjusted.

[0804] Step 5:

[0805] The server adjusts the tone of the response text according to the user's emotional state. The input is the response text and sentiment analysis data, and the output is the adjusted response text. This adjustment enables more user-friendly and emotionally sensitive responses.

[0806] Step 6:

[0807] The device displays the adjusted response text on the smart glasses' display. The input is the adjusted response text, and the output is presented visually or audibly. This allows the user to receive accurate answers to their questions.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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."

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0829] The following is further disclosed regarding the embodiments described above.

[0830] (Claim 1)

[0831] An input method for entering questions regarding weddings, funerals, and other ceremonial occasions,

[0832] A generation means that analyzes the input question and generates an appropriate answer,

[0833] A presentation means for presenting the generated answer and related information to the user,

[0834] A means of arranging goods and services based on the relevant information presented,

[0835] A system that includes this.

[0836] (Claim 2)

[0837] The system according to claim 1, further comprising means for analyzing the input question in natural language.

[0838] (Claim 3)

[0839] The system according to claim 1, characterized in that the arrangement means further comprises means for securely processing payments.

[0840] "Example 1"

[0841] (Claim 1)

[0842] A communication means for receiving questions from users and transferring the input information to a processing device,

[0843] A generation means that analyzes the transmitted information and generates an appropriate answer using generation AI technology,

[0844] A presentation means that presents the generated answers and related information to the user's terminal and provides choices visually or audibly,

[0845] A management system for managing arrangements to provide services or products based on the presented options,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising analytical means for analyzing intent using natural language processing technology based on an input question and deriving an accurate answer.

[0849] (Claim 3)

[0850] The system according to claim 1, characterized in that the management means has a function to manage electronic transactions in order to guarantee secure transactions.

[0851] "Application Example 1"

[0852] (Claim 1)

[0853] An input method for entering questions regarding weddings, funerals, and other ceremonial occasions,

[0854] A generation means that analyzes the input question and generates an appropriate answer,

[0855] A presentation means for presenting the generated answer and related information to the user,

[0856] A means of making arrangements for meals and other items based on the relevant information presented,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, further comprising means for analyzing the input question in natural language and providing options suitable for common use cases.

[0860] (Claim 3)

[0861] The system according to claim 1, characterized in that the ordering means further comprises means for automating and securely processing order procedures.

[0862] "Example 2 of combining an emotion engine"

[0863] (Claim 1)

[0864] A terminal for entering questions about weddings, funerals, and other ceremonial occasions,

[0865] A generation means that analyzes the input question using natural language processing technology and generates an appropriate answer,

[0866] An emotion adjustment mechanism that adjusts the generated response according to the user's emotional state,

[0867] A presentation method for presenting adjusted answers and related information to the user,

[0868] A means of arranging goods and services based on the relevant information presented,

[0869] A system that includes this.

[0870] (Claim 2)

[0871] The system according to claim 1, characterized by comprising a generative AI model for analyzing an input question and generating a corresponding answer.

[0872] (Claim 3)

[0873] The system according to claim 1, further comprising emotion recognition means for detecting the user's voice and facial expressions and identifying emotions based thereon.

[0874] "Application example 2 of combining emotional engines"

[0875] (Claim 1)

[0876] An operating environment where you can input questions about weddings, funerals, and other ceremonial occasions,

[0877] A processing means that analyzes the input question and generates appropriate information,

[0878] A display means for presenting generated information and related information to the user,

[0879] A means of making adjustments to goods and services based on the displayed relevant information,

[0880] An emotion recognition means that analyzes the user's emotional state and adjusts the tone and format of the information presented,

[0881] A system that includes this.

[0882] (Claim 2)

[0883] The system according to claim 1, further comprising a process for analyzing the input question in natural language.

[0884] (Claim 3)

[0885] The system according to claim 1, wherein the adjustment means further comprises a procedure for securely processing payments. [Explanation of symbols]

[0886] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for entering questions regarding weddings, funerals, and other ceremonial occasions, A generation means that analyzes the input question and generates an appropriate answer, A presentation means for presenting the generated answer and related information to the user, A means of arranging goods and services based on the relevant information presented, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the input question in natural language.

3. The system according to claim 1, characterized in that the arrangement means further comprises means for securely processing payments.

Images