system

Abstract

Provide a system. 【Solution means】 Means for collecting enterprise information and storing it in an electronic knowledge base, Means for providing an interactive interface for receiving information requests from users, Means for generating an answer based on an information request using generation technology, Means for displaying the answer to the user, Means for periodically updating the knowledge base, Means for periodically collecting financial transaction-related data and incorporating it into the knowledge base, Means for generating an answer using generation technology in response to a financial-related information request from a user, A system including the above.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of the present invention is to solve the problem that employees cannot fully grasp information on various products and services provided within a company. As a result of the scattered information within the company, employees cannot obtain necessary information quickly and efficiently. This causes problems such as a decrease in work efficiency and underutilization of information.

Means for Solving the Problems

[0005] This invention provides a system equipped with the function of collecting internal company information and storing it in an electronic knowledge base. This system provides an interactive interface that accepts information requests from users and generates appropriate answers to questions using generation technology. The generated answers are presented to the user. Furthermore, the knowledge base is regularly updated, ensuring that the latest information is always available. This allows employees to quickly and easily obtain the necessary information, improving work efficiency.

[0006] "Internal company information" refers to the collection of all documents, data, policies, and procedures generated and stored within a company.

[0007] An "electronic knowledge base" is a system of information stored in digital format, designed to be easily searchable and accessible.

[0008] A "user" refers to an individual or group within a company who uses the system to search for information or ask questions.

[0009] An "information request" refers to a question or request that a user sends to a system in order to obtain specific information or an answer.

[0010] An "interactive interface" is a user interface for interaction between the user and the system, providing an environment in which questions and instructions can be entered in natural language.

[0011] "Generative technology" refers to techniques that use machine learning and natural language processing to automatically generate appropriate answers and information based on given data and questions.

[0012] "Knowledge base updating" refers to the process of integrating newly added information and modified data into the existing database to keep it constantly up-to-date. [Brief explanation of the drawing]

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

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

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

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

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

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

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

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

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

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

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

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

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

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

[0034] This invention is implemented as a system that effectively collects information within a company and allows employees to quickly obtain the information they need. The implementation of the invention includes the following elements:

[0035] First, the server periodically collects policies, procedures, and other relevant document data from internal corporate sources. Then, it stores the collected data in an electronic knowledge base and converts it into a format that can be understood by generation technologies. This ensures that the latest information is always available, allowing for a rapid response to user requests.

[0036] Next, the terminal provides an interactive interface accessible to employees. Here, employees can input questions in natural language to find specific company information. The interface is often implemented as a web browser or a dedicated application. In this way, employees can operate the system without needing technical knowledge.

[0037] Subsequently, when the user enters a question via the terminal, the server receives the question and uses generation technology to retrieve the appropriate data from the knowledge base. The generation technology analyzes the question, processes the most relevant information, generates an answer in natural language format, and sends it to the terminal via the server.

[0038] For example, if an employee asks, "What is the latest HR policy?", the server searches the knowledge base for the relevant document and generates a summary and detailed explanation of the policy using generation technology. This answer is displayed on the terminal, allowing the user to quickly understand the necessary information.

[0039] Furthermore, the knowledge base is regularly updated by the server. This ensures that the latest information is always stored, allowing users to access reliable information.

[0040] This invention aims to improve operational efficiency by centralizing internal company information and enabling employees to easily obtain the information they need.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server collects internal company information and stores it in an electronic knowledge base. It also processes each document and data to convert it into a format that can be understood by the generation technology.

[0044] Step 2:

[0045] The terminal displays an interactive interface accessible to the user, providing a text box for entering questions and a submit button.

[0046] Step 3:

[0047] Users input the information or questions they want to know in natural language and send them to the server by clicking the send button on their device.

[0048] Step 4:

[0049] The server passes the user's question received from the terminal to the generation technology, which analyzes the question content. It then performs advanced processing to search for relevant information from the knowledge base.

[0050] Step 5:

[0051] The generation technology generates appropriate answers based on the question and returns them to the server in natural language format. The server then organizes the answers and verifies their accuracy.

[0052] Step 6:

[0053] The terminal displays the answer retrieved from the server to the user. Related information and links are also provided to aid user understanding.

[0054] Step 7:

[0055] The server regularly updates its knowledge base, integrating new information and changed data to ensure that the most up-to-date information is always available.

[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] There is a need to provide a system that efficiently collects and manages vast amounts of information within a company, allowing employees to quickly and easily access the information they need. Traditional systems have the problem of being time-consuming to retrieve information and making it difficult to obtain the latest information.

[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 means for extracting information from data sources within a company and storing it in an electronic database, means for receiving information requests from users and providing an interactive interface that allows input in natural language, and means for analyzing user information requests using generation technology and generating responses based on those requests. This enables employees to efficiently acquire the information they need and to quickly access the latest and most accurate information.

[0061] "Internal corporate data sources" refer to locations where various types of information are stored, including systems and document management platforms operated within a company.

[0062] An "electronic database" refers to a collection of information organized in a digital format and arranged for efficient management and access.

[0063] "Users" refer to employees and staff who operate the company's information systems to search for and retrieve necessary information.

[0064] A "natural language-based interactive interface" refers to an interface that allows users to input questions and instructions into the system using everyday language, without requiring specialized knowledge.

[0065] "Generative technologies" are technical methods used to analyze data and generate responses to specific questions, and primarily include natural language processing and machine learning techniques.

[0066] "Means of generating responses" refers to the process of gathering relevant information based on information requests from users, utilizing generation technologies, and providing answers in an easily understandable format.

[0067] This invention provides a system for the efficient collection and management of information within a company, and for users to quickly access that information. Specific embodiments are described below.

[0068] First, the server collects data from internal corporate information sources. These sources include internal databases, document management systems, and other information management platforms. The server utilizes automated processes to periodically ingest this information into electronic databases. The collected information is converted into a format that is easily processed by generative AI models and stored in an accessible form.

[0069] Next, the terminal provides employees with an interface that allows them to input questions in natural language. This interface functions as a web browser or a dedicated application and does not require any special technical knowledge. Employees can easily input the information they want to know, for example, by asking questions such as, "Please tell me about the latest HR policy."

[0070] When a user enters a question via their device, the server receives the information and analyzes the question using generative technology. The generative AI model grasps the intent of the question and searches for relevant information in the database. Based on this information, the server generates a natural language answer and sends it to the device.

[0071] In this way, users can quickly receive the information they need, achieving efficient information retrieval. Through this process, employees can access the latest information with evidence, contributing to improved work efficiency.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The server periodically collects data from information sources within the company. It receives data from various sources as input and outputs data in a format suitable for the generated AI model. Specifically, it performs processes such as standardizing data formats, removing noise, and adding necessary metadata. This data is stored in an electronic database, making it available to other components.

[0075] Step 2:

[0076] The terminal provides employees with an interface that allows them to input questions in natural language. The input consists of prompt text entered by the user, and the output is that input sent to the server. The process involves a web browser or dedicated application receiving natural language input and passing it to the server.

[0077] Step 3:

[0078] The server analyzes questions received from terminals and retrieves relevant information from its knowledge base. Input consists of the user's question and data from an electronic database, while output is a generated answer. The server first uses a generative AI model to analyze the intent of the question and extract relevant keywords. Next, it retrieves information corresponding to these keywords and generates it in a user-friendly format.

[0079] Step 4:

[0080] The server sends the generated response to the terminal. The input is the generated response in natural language format, and the output is that response displayed on the terminal. In this step, data is transmitted from the server to the terminal, and the user can view the response on the screen.

[0081] Step 5:

[0082] The user reviews the answers obtained on the device and asks follow-up questions as needed. The information received by the user is used as input, and the next question prompt is formed as output. In this process, the user can evaluate the accuracy and applicability of the information and continue gathering information.

[0083] (Application Example 1)

[0084] 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."

[0085] In modern businesses, the sheer volume of information provided, especially regarding electronic payments which are frequently updated, makes it difficult for users to quickly and accurately obtain the information they need. Furthermore, users require immediate access to information such as past spending and upcoming payment amounts to understand their financial situation. There is a need for systems that can meet these needs.

[0086] 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.

[0087] In this invention, the server includes means for collecting corporate information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses based on information requests using generation technology. This enables users to quickly and accurately obtain information related to financial transactions.

[0088] "Corporate information" refers to a variety of data and documents that companies use for business operations and decision-making.

[0089] An "electronic knowledge base" is a data storage system that organizes and stores information in a digital format, enabling efficient retrieval and utilization.

[0090] "User" refers to an individual or organization that uses the system to request and receive information.

[0091] An "information request" refers to an inquiry or question that a user enters into a system seeking specific data or answers.

[0092] An "interactive interface" refers to a user interface that allows users to communicate with a system in two-way using natural language.

[0093] "Generative technology" refers to technology that automatically generates appropriate answers based on requested information.

[0094] "Financial transaction data" refers to all transaction information related to an individual's or organization's income, expenses, savings, etc.

[0095] The system of this invention is designed to efficiently collect corporate information and quickly provide financial data based on user requests. The server is responsible for collecting corporate information and financial transaction-related data and storing it in an electronic knowledge base. This information is mainly accumulated through a web server using Python and Django, and PostgreSQL is used as the database system for managing it.

[0096] The terminal provides an interactive interface that accepts information requests from users. The primary interface is a smartphone application utilizing React Native, allowing users to input questions in natural language through the application. This makes the system easily accessible to anyone, even without technical knowledge.

[0097] Information requests submitted by users in natural language are sent to the server. The server then uses a generative AI model to analyze the information and generate responses. The generative technologies primarily utilize natural language processing APIs from OpenAI® and Google®, which extract appropriate data in response to the user's request and generate responses in natural language format. The responses are then sent to the user's device, allowing the user to receive the information.

[0098] For example, if a user asks, "What is my total spending this month?", the system searches its knowledge base for the relevant data and generates the result using a generative AI model. A concise summary of the total spending is then displayed on the user's smartphone. This allows the user to quickly understand their financial situation. An example of a prompt used in this process is, "Based on the user's question, extract relevant financial data and provide an answer in natural language."

[0099] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0100] Step 1:

[0101] The server periodically collects corporate information and financial transaction-related data and stores it in an electronic knowledge base. As input, this data is obtained from various corporate sources, which the server organizes using the Django framework and stores in a PostgreSQL database. This process involves structuring the data content and converting it into an efficiently searchable format.

[0102] Step 2:

[0103] Users input information requests in natural language using an application on their smartphone. The input consists of user questions, which are received by a mobile application built with React Native. The application receives this text input and sends it to the server. This is the first step towards providing information tailored to the user's intent.

[0104] Step 3:

[0105] The server analyzes the information request received from the user and extracts relevant data from its knowledge base. The input includes the user's question text, which is then analyzed using a generative AI model, such as the OpenAI API. Based on the results, the server retrieves the corresponding data from a PostgreSQL database in preparation for the next step.

[0106] Step 4:

[0107] The server uses the extracted data to generate responses in natural language. Here, a generative AI model is utilized, constructing responses tailored to the purpose and use of the data as input. The output is a well-organized response text, which is a crucial element of this process.

[0108] Step 5:

[0109] The server sends the generated response to the device and displays it to the user. As output, the generated response is displayed on the user's smartphone via React Native. In this final step, the user can quickly obtain the desired information and use it to understand financial transactions.

[0110] 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.

[0111] This invention implements an internal information provision system that incorporates an emotion engine that recognizes user emotions. This system provides a more personalized user experience by dynamically adjusting the way information is provided based on the user's emotions.

[0112] First, the server collects internal company information and stores it in an electronic knowledge base. This ensures that various policies and procedures are always kept up-to-date. The server then converts this knowledge base data into a structured format that can be processed by generation technology.

[0113] Next, the device displays an interface for interacting with the user. This interface incorporates an emotion engine that analyzes user input and interactions to recognize emotions. This allows the device to determine the user's emotional state in real time.

[0114] The user requests information through the interface, and during this process, the emotion engine analyzes the user's tone of voice, input speed, and other behavioral patterns to infer the emotions the user is currently experiencing. This emotion information is passed to the generation technology and reflected in the generated response.

[0115] For example, if the system detects that a user is experiencing "dissatisfaction with the system," the server will generate a response using more descriptive and polite language to mitigate the reaction. Additionally, the terminal will adjust the interface layout and colors to provide a design that helps the user relax.

[0116] Furthermore, the server records the emotions detected by the emotion engine in a database and collects feedback. This feedback data is used to optimize the knowledge base and improve the user interface.

[0117] Thus, by implementing the present invention, users can not only receive information but also receive information that is tailored to their emotions at the time, thereby further improving work efficiency and reducing stress.

[0118] The following describes the processing flow.

[0119] Step 1:

[0120] The server periodically collects internal company information from various sources and stores it in an electronic knowledge base. The collected information is organized as structured data suitable for generation technologies and updated as needed.

[0121] Step 2:

[0122] The device provides users with an interactive interface that incorporates an emotion engine capable of recognizing the user's facial expressions and tone of voice. Through this interface, users can input questions in natural language.

[0123] Step 3:

[0124] The user inputs the information they want to know or their questions into an interactive interface and submits their inquiries. At this time, the emotion engine analyzes the user's emotions from the format of their input and the tone of their voice.

[0125] Step 4:

[0126] The server provides the user's question and sentiment data received from the terminal to the generation technology. The generation technology combines the question content and sentiment information to generate an answer that takes sentiment into consideration.

[0127] Step 5:

[0128] The device displays the generated response to the user. It reflects emotion-based feedback, adjusting the interface design and language tone to match the user's current emotional state.

[0129] Step 6:

[0130] The server records sentiment data and user feedback, which is used to optimize the knowledge base and user interface. This feedback is used to improve future interactions.

[0131] Step 7:

[0132] This entire process is regularly evaluated, and improvements and optimizations are made to the entire system. This makes it possible to increase user satisfaction and streamline business processes.

[0133] (Example 2)

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

[0135] Conventional information delivery systems provide uniform information without considering user emotions, making it difficult to personalize the user experience. This hinders effective information transmission and improves user satisfaction.

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

[0137] In this invention, the server includes means for collecting and storing information in a knowledge base, interactive display means for receiving information requests from users, and means for recognizing the user's emotions using emotion estimation technology. This enables real-time recognition of the user's emotions and the provision of appropriate information according to those emotions.

[0138] "Means of collecting information and storing it in a knowledge base" refers to the function of a system that automatically collects and stores internal and external data, making it available for use as organizational knowledge.

[0139] An "interactive display means for receiving information requests from users" is a mechanism that provides an interface for users to input the information they desire, thereby facilitating interaction between the user and the system.

[0140] "Means of recognizing a user's emotions using emotion estimation technology" refers to technologies that infer and understand a user's emotional state through voice analysis and behavioral pattern analysis.

[0141] "Means of generating responses using generative technology" refers to technologies that automatically construct appropriate responses based on acquired data and user sentiment.

[0142] "Means for saving emotion recognition results and optimizing the database" refers to the process of recording and managing data related to users' emotions and using feedback to improve the performance of the knowledge base and the overall system.

[0143] This invention is an emotion-responsive internal information provision system that dynamically recognizes user emotions and provides personalized information. A specific embodiment of this system is described below.

[0144] First, the server collects internal company information and stores it in a knowledge base. This information collection includes feedback data from each department and documents related to business processes. The server uses a database management system to structure this data and convert it into a format that can be used by the generated AI model.

[0145] Next, the device provides an interactive interface for direct user access. This interface incorporates emotion estimation technology that analyzes the user's voice tone, input speed, and operation patterns in real time to estimate their emotions. This makes it possible to accurately understand the user's emotional state.

[0146] The user submits an information request through this interactive interface. Upon receiving the request, sentiment estimation technology analyzes the user's emotions and sends that information to the server. The server uses a generative AI model to construct the optimal response based on the received sentiment data. In this process, the generative AI model utilizes pre-prepared information templates and feedback data to generate content that is most appropriate to the user's request and emotions.

[0147] For example, if a user expresses "concerns about the system," the server can generate a polite and considerate response such as, "Thank you for using the system. Please feel free to provide feedback if you have any complaints." Another example of a prompt in this process is, "How should a user provide information when they are dissatisfied with the system?"

[0148] Ultimately, the device not only presents the generated information to the user, but also adjusts the user interface's colors and layout according to the user's emotions, providing a stress-reducing environment. Furthermore, emotion estimation results and user feedback are stored on a server and used to optimize the knowledge base and improve the user interface.

[0149] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0150] Step 1:

[0151] The server collects internal and external information and stores it in a knowledge base. Input data includes emails, business reports, and feedback forms. The server uses text analysis techniques to convert this information into structured data, ultimately storing it in JSON format. This stored data becomes the output data used by the generative AI model.

[0152] Step 2:

[0153] The terminal displays an interactive interface that enables user interaction. Input methods include user voice input and text input. Built-in emotion estimation technology analyzes the user's voice tone and input speed to recognize the user's emotions in real time. This emotion data is output data sent to the server.

[0154] Step 3:

[0155] The server generates responses using a generative AI model based on user sentiment data received from the terminal. The input data consists of the sentiment score and the user's information request. The generative AI model uses the given input data as prompts and combines it with knowledge base data to generate responses that meet user needs. These responses become the output data.

[0156] Step 4:

[0157] The terminal receives responses from the server and displays them to the user. The input is the response received from the server, and the interface's colors and layout are adjusted according to the user's emotions. The final output is the information presented to the user, aiming to soothe their emotions and improve their satisfaction.

[0158] Step 5:

[0159] The server records the user's emotion estimation results and feedback on the response in a database. It collects user response behavior and additional feedback as input data and analyzes it to optimize system performance. The output of this process is used to optimize the knowledge base and generate responses in the future.

[0160] (Application Example 2)

[0161] 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".

[0162] When users seek information, a problem arises where services are standardized because their emotional state is not taken into consideration, resulting in a lack of improvement in the user experience. This issue is particularly concerning in physical stores, where it is feared that customer satisfaction will not improve. Therefore, it is necessary to develop a system that provides personalized services while taking into account the user's emotions.

[0163] 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.

[0164] In this invention, the server includes means for collecting internal company information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses to information requests using generation technology. This makes it possible to recognize the user's emotions and dynamically adjust the service based on their emotional state.

[0165] "Internal company information" refers to various data, documents, and information generated or used within an organization.

[0166] A "knowledge base" is an electronic database used to systematically store and manage collected company information.

[0167] "User" refers to an individual or group that uses the system to search for or request information.

[0168] An "interactive interface" is a user interface that allows users and systems to exchange information with each other.

[0169] "Generative technology" refers to technology used to automatically generate appropriate answers in response to user information requests.

[0170] "Emotional analysis technology" is a technology that analyzes a user's voice, facial expressions, etc., and recognizes their emotional state in real time.

[0171] A "display device" is a hardware device used by users to provide information or services.

[0172] "Dynamically adjusting services" means changing the content and format of the information and services provided in real time based on the user's emotional state and requests.

[0173] One embodiment of this invention involves first using a server system to collect internal company information and store it in an electronic knowledge base. The server periodically updates this knowledge base to maintain the latest information. The information within the knowledge base is provided to the generation technology as structured data.

[0174] The terminal displays an interface for interacting with the user. This interface incorporates emotion analysis technology, recognizing the user's emotional state in real time by analyzing their input and tone of voice. The user's emotional information is then reflected in the service, which is dynamically adjusted using generation technology.

[0175] The hardware uses display devices that capture and display information, such as smart glasses. The software employs machine learning frameworks like TENSORFLOW® and PyTorch for sentiment analysis, and React Native is used to build the user interface.

[0176] As a concrete example, when a customer is choosing a product in a physical store, if smart glasses detect that the customer is "confused" based on their facial expression and tone of voice, the glasses' display will show a message asking the customer if they are unsure and explaining the product details. In this way, the service received by the user is personalized, and customer satisfaction improves.

[0177] Examples of prompts include, "How should I assist this customer who seems confused?" or "How can I reassure a customer who is feeling stressed?"

[0178] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0179] Step 1:

[0180] The server collects internal company information and stores it in a knowledge base. In this process, various data from within the organization is sent to the server and stored in an electronic database. The input consists of various internal documents and data, and the output is structured data as a knowledge base. The server performs data processing to classify, organize, and store the data.

[0181] Step 2:

[0182] The terminal displays an interactive interface that accepts information requests from the user. At this stage, the user requests information from the terminal via voice or text. The input is the user's information request, and the output is request data that is parsed by the system. The interface captures the user's input and forwards it to the server.

[0183] Step 3:

[0184] The server uses emotion analysis technology to analyze the user's emotions from their voice tone and input speed. This analysis reveals the user's emotional state. The input is the user's voice or text data, and the output is a label indicating their emotional state. A machine learning model processes this data to recognize emotions.

[0185] Step 4:

[0186] The generation technology generates responses that meet information requests based on the user's emotional state. The generated responses reflect emotional nuances. The input consists of emotional information and relevant information drawn from a knowledge base, while the output is a personalized response. The generation AI model processes prompts, selecting and constructing appropriate words.

[0187] Step 5:

[0188] The terminal presents the generated response to the user. The display format and wording are adjusted appropriately according to the user's emotional state. The input is the generated response, and the output is information presented through an adjusted user interface. The display device visualizes the response in the most optimal way for the user.

[0189] Step 6:

[0190] The server collects user feedback and uses it to optimize the knowledge base. The feedback data is then used to further improve the system. Input is user feedback information, and output is an updated knowledge base and improved answer generation algorithms. The feedback is analyzed, and the overall system performance is adjusted accordingly.

[0191] 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.

[0192] 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.

[0193] 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.

[0194] [Second Embodiment]

[0195] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0196] 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.

[0197] 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).

[0198] 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.

[0199] 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.

[0200] 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).

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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.

[0206] 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".

[0207] This invention is implemented as a system that effectively collects information within a company and allows employees to quickly obtain the information they need. The implementation of the invention includes the following elements:

[0208] First, the server periodically collects policies, procedures, and other relevant document data from internal corporate sources. Then, it stores the collected data in an electronic knowledge base and converts it into a format that can be understood by generation technologies. This ensures that the latest information is always available, allowing for a rapid response to user requests.

[0209] Next, the terminal provides an interactive interface accessible to employees. Here, employees can input questions in natural language to find specific company information. The interface is often implemented as a web browser or a dedicated application. In this way, employees can operate the system without needing technical knowledge.

[0210] Subsequently, when the user enters a question via the terminal, the server receives the question and uses generation technology to retrieve the appropriate data from the knowledge base. The generation technology analyzes the question, processes the most relevant information, generates an answer in natural language format, and sends it to the terminal via the server.

[0211] For example, if an employee asks, "What is the latest HR policy?", the server searches the knowledge base for the relevant document and generates a summary and detailed explanation of the policy using generation technology. This answer is displayed on the terminal, allowing the user to quickly understand the necessary information.

[0212] Furthermore, the knowledge base is regularly updated by the server. This ensures that the latest information is always stored, allowing users to access reliable information.

[0213] This invention aims to improve operational efficiency by centralizing internal company information and enabling employees to easily obtain the information they need.

[0214] The following describes the processing flow.

[0215] Step 1:

[0216] The server collects internal company information and stores it in an electronic knowledge base. It also processes each document and data to convert it into a format that can be understood by the generation technology.

[0217] Step 2:

[0218] The terminal displays an interactive interface accessible to the user, providing a text box for entering questions and a submit button.

[0219] Step 3:

[0220] Users input the information or questions they want to know in natural language and send them to the server by clicking the send button on their device.

[0221] Step 4:

[0222] The server passes the user's question received from the terminal to the generation technology, which analyzes the question content. It then performs advanced processing to search for relevant information from the knowledge base.

[0223] Step 5:

[0224] The generation technology generates appropriate answers based on the question and returns them to the server in natural language format. The server then organizes the answers and verifies their accuracy.

[0225] Step 6:

[0226] The terminal displays the answer retrieved from the server to the user. Related information and links are also provided to aid user understanding.

[0227] Step 7:

[0228] The server regularly updates its knowledge base, integrating new information and changed data to ensure that the most up-to-date information is always available.

[0229] (Example 1)

[0230] 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."

[0231] There is a need to provide a system that efficiently collects and manages vast amounts of information within a company, allowing employees to quickly and easily access the information they need. Traditional systems have the problem of being time-consuming to retrieve information and making it difficult to obtain the latest information.

[0232] 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.

[0233] In this invention, the server includes means for extracting information from data sources within a company and storing it in an electronic database, means for receiving information requests from users and providing an interactive interface that allows input in natural language, and means for analyzing user information requests using generation technology and generating responses based on those requests. This enables employees to efficiently acquire the information they need and to quickly access the latest and most accurate information.

[0234] "Internal corporate data sources" refer to locations where various types of information are stored, including systems and document management platforms operated within a company.

[0235] An "electronic database" refers to a collection of information organized in a digital format and arranged for efficient management and access.

[0236] "Users" refer to employees and staff who operate the company's information systems to search for and retrieve necessary information.

[0237] A "natural language-based interactive interface" refers to an interface that allows users to input questions and instructions into the system using everyday language, without requiring specialized knowledge.

[0238] "Generative technologies" are technical methods used to analyze data and generate responses to specific questions, and primarily include natural language processing and machine learning techniques.

[0239] "Means of generating responses" refers to the process of gathering relevant information based on information requests from users, utilizing generation technologies, and providing answers in an easily understandable format.

[0240] This invention provides a system for the efficient collection and management of information within a company, and for users to quickly access that information. Specific embodiments are described below.

[0241] First, the server collects data from internal corporate information sources. These sources include internal databases, document management systems, and other information management platforms. The server utilizes automated processes to periodically ingest this information into electronic databases. The collected information is converted into a format that is easily processed by generative AI models and stored in an accessible form.

[0242] Next, the terminal provides employees with an interface that allows them to input questions in natural language. This interface functions as a web browser or a dedicated application and does not require any special technical knowledge. Employees can easily input the information they want to know, for example, by asking questions such as, "Please tell me about the latest HR policy."

[0243] When a user enters a question via their device, the server receives the information and analyzes the question using generative technology. The generative AI model grasps the intent of the question and searches for relevant information in the database. Based on this information, the server generates a natural language answer and sends it to the device.

[0244] In this way, users can quickly receive the information they need, achieving efficient information retrieval. Through this process, employees can access the latest information with evidence, contributing to improved work efficiency.

[0245] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0246] Step 1:

[0247] The server periodically collects data from information sources within the company. It receives data from various sources as input and outputs data in a format suitable for the generated AI model. Specifically, it performs processes such as standardizing data formats, removing noise, and adding necessary metadata. This data is stored in an electronic database, making it available to other components.

[0248] Step 2:

[0249] The terminal provides employees with an interface that allows them to input questions in natural language. The input consists of prompt text entered by the user, and the output is that input sent to the server. In essence, a web browser or dedicated application receives the natural language input and passes it to the server.

[0250] Step 3:

[0251] The server analyzes questions received from terminals and retrieves relevant information from its knowledge base. Input consists of the user's question and data from an electronic database, while output is a generated answer. The server first uses a generative AI model to analyze the intent of the question and extract relevant keywords. Next, it retrieves information corresponding to these keywords and generates it in a user-friendly format.

[0252] Step 4:

[0253] The server sends the generated response to the terminal. The input is the generated response in natural language format, and the output is the response displayed on the terminal. In this step, data is transmitted from the server to the terminal, and the user can view the response on the screen.

[0254] Step 5:

[0255] The user reviews the answers obtained on the device and asks follow-up questions as needed. The information received by the user is used as input, and the next question prompt is formed as output. In this process, the user can evaluate the accuracy and applicability of the information and continue gathering information.

[0256] (Application Example 1)

[0257] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] In modern businesses, the sheer volume of information provided, especially regarding electronic payments which are frequently updated, makes it difficult for users to quickly and accurately obtain the information they need. Furthermore, users require immediate access to information such as past spending and upcoming payment amounts to understand their financial situation. There is a need for systems that can meet these needs.

[0259] 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.

[0260] In this invention, the server includes means for collecting corporate information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses based on information requests using generation technology. This enables users to quickly and accurately obtain information related to financial transactions.

[0261] "Corporate information" refers to a variety of data and documents that companies use for business operations and decision-making.

[0262] An "electronic knowledge base" is a data storage system that organizes and stores information in a digital format, enabling efficient retrieval and utilization.

[0263] "User" refers to an individual or organization that uses the system to request and receive information.

[0264] An "information request" refers to an inquiry or question that a user enters into a system seeking specific data or answers.

[0265] An "interactive interface" refers to a user interface that allows users to communicate with a system in two-way using natural language.

[0266] "Generative technology" refers to technology that automatically generates appropriate answers based on requested information.

[0267] "Financial transaction data" refers to all transaction information related to an individual's or organization's income, expenses, savings, etc.

[0268] The system of this invention is designed to efficiently collect corporate information and quickly provide financial data based on user requests. The server is responsible for collecting corporate information and financial transaction-related data and storing it in an electronic knowledge base. This information is mainly accumulated through a web server using Python and Django, and PostgreSQL is used as the database system for managing it.

[0269] The terminal provides an interactive interface that accepts information requests from users. The primary interface is a smartphone application utilizing React Native, allowing users to input questions in natural language through the application. This makes the system easily accessible to anyone, even without technical knowledge.

[0270] The user submits an information request in natural language, which is then sent to the server. The server uses a generative AI model to analyze the information and generate a response. The generative technology primarily uses OpenAI and Google's natural language processing APIs to extract appropriate data in response to the user's request and generate a response in natural language format. The response is then sent to the user's device, allowing the user to receive the information.

[0271] For example, if a user asks, "What is my total spending this month?", the system searches its knowledge base for the relevant data and generates the result using a generative AI model. A concise summary of the total spending is then displayed on the user's smartphone. This allows the user to quickly understand their financial situation. An example of a prompt used in this process is, "Based on the user's question, extract relevant financial data and provide an answer in natural language."

[0272] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0273] Step 1:

[0274] The server periodically collects corporate information and financial transaction-related data and stores it in an electronic knowledge base. As input, this data is obtained from various corporate sources, which the server organizes using the Django framework and stores in a PostgreSQL database. This process involves structuring the data content and converting it into an efficiently searchable format.

[0275] Step 2:

[0276] Users input information requests in natural language using an application on their smartphone. The input consists of user questions, which are received by a mobile application built with React Native. The application receives this text input and sends it to the server. This is the first step towards providing information tailored to the user's intent.

[0277] Step 3:

[0278] The server analyzes the information request received from the user and extracts relevant data from the knowledge base. As input, it includes the user's question text, and uses a generative AI model, such as the OpenAI API, to analyze the question. Based on the result, the server retrieves the corresponding data from the PostgreSQL database in preparation for the processing in the next step.

[0279] Step 4:

[0280] The server uses the extracted data to generate an answer in natural language. Here, it utilizes a generative AI model to construct an answer according to the purpose and application using the data as input. As output, a sorted answer text is generated, which is an important element of this process.

[0281] Step 5:

[0282] The server transmits the generated answer to the terminal and displays it to the user. As output, the generated answer is displayed on the user's smartphone through React Native. In this final step, the user can quickly obtain the desired information and can use it to grasp financial transactions.

[0283] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0284] In the present invention, an in-company information providing system incorporating an emotion engine for recognizing the user's emotion is implemented. This system provides a more personalized user experience by dynamically adjusting the information providing method based on the user's emotion.

[0285] First, the server collects in-house information and stores it in an electronic knowledge base. As a result, various policies and procedure manuals are always maintained in the latest state. The server converts the data in this knowledge base into a structured format that the generation technology can process.

[0286] Next, the terminal displays an interface for interacting with the user. An emotion engine is incorporated into this interface, and it is possible to analyze the user's input and interaction to recognize emotions. Thereby, the user's emotional state can be judged in real time.

[0287] The user requests information through the interface. At this time, the emotion engine analyzes the tone of the user's voice, input speed, and other behavioral patterns to infer the emotions the user is currently experiencing. This emotion information is passed to the generation technology and reflected in the generated answer.

[0288] As a specific example, when it is detected that the user has an emotion of "dissatisfaction with the system", the server generates an answer using more explanatory and polite language in order to soothe the reaction. Also, the terminal adjusts the layout and color of the interface to provide a design that allows the user to relax.

[0289] Furthermore, the server records the emotions detected by the emotion engine in the database and accumulates feedback. This feedback data is used for optimizing the knowledge base and improving the user interface.

[0290] In this way, by implementing the present invention, the user can not only receive information but also receive information provision that conforms to their emotions at each moment, making it possible to further improve work efficiency and reduce stress.

[0291] The following describes the processing flow.

[0292] Step 1:

[0293] The server periodically collects internal company information from various sources and stores it in an electronic knowledge base. The collected information is organized as structured data suitable for generation technologies and updated as needed.

[0294] Step 2:

[0295] The device provides users with an interactive interface that incorporates an emotion engine capable of recognizing the user's facial expressions and tone of voice. Through this interface, users can input questions in natural language.

[0296] Step 3:

[0297] The user inputs the information they want to know or their questions into an interactive interface and submits their inquiries. At this time, the emotion engine analyzes the user's emotions from the format of their input and the tone of their voice.

[0298] Step 4:

[0299] The server provides the user's question and sentiment data received from the terminal to the generation technology. The generation technology combines the question content and sentiment information to generate an answer that takes sentiment into consideration.

[0300] Step 5:

[0301] The device displays the generated response to the user. It reflects emotion-based feedback, adjusting the interface design and language tone to match the user's current emotional state.

[0302] Step 6:

[0303] The server records sentiment data and user feedback, which is used to optimize the knowledge base and user interface. This feedback is used to improve future interactions.

[0304] Step 7:

[0305] The entire process is periodically evaluated, and the overall system is improved and optimized. This makes it possible to enhance user satisfaction and streamline business processes.

[0306] (Example 2)

[0307] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0308] Conventional information provision systems have a problem in that it is difficult to individualize the user experience and to improve effective information transmission and user satisfaction because they provide uniform information without considering the user's feelings.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0310] In this invention, the server includes means for collecting information and storing it in a knowledge base, interactive display means for receiving an information request from a user, and means for recognizing the user's feelings using emotion estimation technology. This makes it possible to recognize the user's feelings in real time and provide appropriate information according to the feelings.

[0311] The "means for collecting information and storing it in a knowledge base" is a function of a system that automatically collects and stores data inside and outside the company and makes it available for use as organizational knowledge.

[0312] The "interactive display means for receiving an information request from a user" is a mechanism that provides an interface for inputting the information desired by the user and promotes interaction between the user and the system.

[0313] The "means for recognizing the user's feelings using emotion estimation technology" is a technology for inferring and understanding the user's emotional state through voice analysis and analysis of behavioral patterns.

[0314] "Means of generating responses using generative technology" refers to technologies that automatically construct appropriate responses based on acquired data and user sentiment.

[0315] "Means for saving emotion recognition results and optimizing the database" refers to the process of recording and managing data related to users' emotions and using feedback to improve the performance of the knowledge base and the overall system.

[0316] This invention is an emotion-responsive internal information provision system that dynamically recognizes user emotions and provides personalized information. A specific embodiment of this system is described below.

[0317] First, the server collects internal company information and stores it in a knowledge base. This information collection includes feedback data from each department and documents related to business processes. The server uses a database management system to structure this data and convert it into a format that can be used by the generating AI model.

[0318] Next, the device provides an interactive interface for direct user access. This interface incorporates emotion estimation technology that analyzes the user's voice tone, input speed, and operation patterns in real time to estimate their emotions. This makes it possible to accurately understand the user's emotional state.

[0319] The user submits an information request through this interactive interface. Upon receiving the request, sentiment estimation technology analyzes the user's emotions and sends that information to the server. The server uses a generative AI model to construct the optimal response based on the received sentiment data. In this process, the generative AI model utilizes pre-prepared information templates and feedback data to generate content that is most appropriate to the user's request and emotions.

[0320] For example, if a user expresses "concerns about the system," the server can generate a polite and considerate response such as, "Thank you for using the system. Please feel free to provide feedback if you have any complaints." Another example of a prompt in this process is, "How should a user provide information when they are dissatisfied with the system?"

[0321] Ultimately, the device not only presents the generated information to the user, but also adjusts the user interface's colors and layout according to the user's emotions, providing a stress-reducing environment. Furthermore, emotion estimation results and user feedback are stored on a server and used to optimize the knowledge base and improve the user interface.

[0322] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0323] Step 1:

[0324] The server collects internal and external information and stores it in a knowledge base. Input data includes emails, business reports, and feedback forms. The server uses text analysis techniques to convert this information into structured data, ultimately storing it in JSON format. This stored data becomes the output data used by the generative AI model.

[0325] Step 2:

[0326] The terminal displays an interactive interface that enables user interaction. Input methods include user voice input and text input. Built-in emotion estimation technology analyzes the user's voice tone and input speed to recognize the user's emotions in real time. This emotion data is output data sent to the server.

[0327] Step 3:

[0328] The server generates responses using a generative AI model based on user sentiment data received from the terminal. The input data consists of the sentiment score and the user's information request. The generative AI model uses the given input data as prompts and combines it with knowledge base data to generate responses that meet user needs. These responses become the output data.

[0329] Step 4:

[0330] The terminal receives responses from the server and displays them to the user. The input is the response received from the server, and the interface's colors and layout are adjusted according to the user's emotions. The final output is the information presented to the user, aiming to soothe their emotions and improve their satisfaction.

[0331] Step 5:

[0332] The server records the user's emotion estimation results and feedback on the response in a database. It collects user response behavior and additional feedback as input data and analyzes it to optimize system performance. The output of this process is used to optimize the knowledge base and generate responses in the future.

[0333] (Application Example 2)

[0334] 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."

[0335] When users seek information, a problem arises where services are standardized because their emotional state is not taken into consideration, resulting in a lack of improvement in the user experience. This issue is particularly concerning in physical stores, where it is feared that customer satisfaction will not improve. Therefore, it is necessary to develop a system that provides personalized services while taking into account the user's emotions.

[0336] 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.

[0337] In this invention, the server includes means for collecting internal company information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses to information requests using generation technology. This makes it possible to recognize the user's emotions and dynamically adjust the service based on their emotional state.

[0338] "Internal company information" refers to various data, documents, and information generated or used within an organization.

[0339] A "knowledge base" is an electronic database used to systematically store and manage collected company information.

[0340] "User" refers to an individual or group that uses the system to search for or request information.

[0341] An "interactive interface" is a user interface that allows users and systems to exchange information with each other.

[0342] "Generative technology" refers to technology used to automatically generate appropriate answers in response to user information requests.

[0343] "Emotional analysis technology" is a technology that analyzes a user's voice, facial expressions, etc., and recognizes their emotional state in real time.

[0344] A "display device" is a hardware device used by users to provide information or services.

[0345] "Dynamically adjusting services" means changing the content and format of the information and services provided in real time based on the user's emotional state and requests.

[0346] One embodiment of this invention involves first using a server system to collect internal company information and store it in an electronic knowledge base. The server periodically updates this knowledge base to maintain the latest information. The information within the knowledge base is provided to the generation technology as structured data.

[0347] The terminal displays an interface for interacting with the user. This interface incorporates emotion analysis technology, recognizing the user's emotional state in real time by analyzing their input and tone of voice. The user's emotional information is then reflected in the service, which is dynamically adjusted using generation technology.

[0348] In terms of hardware, a display device that captures and displays information is used, specifically such as smart glasses. For software, machine learning frameworks such as TensorFlow and PyTorch are used for sentiment analysis, and React Native is used to build the user interface.

[0349] As a concrete example, when a customer is choosing a product in a physical store, if smart glasses detect that the customer is "confused" based on their facial expression and tone of voice, the glasses' display will show a message asking the customer if they are unsure and explaining the product details. In this way, the service received by the user is personalized, and customer satisfaction improves.

[0350] Examples of prompts include, "How should I assist this customer who seems confused?" or "How can I reassure a customer who is feeling stressed?"

[0351] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0352] Step 1:

[0353] The server collects internal company information and stores it in a knowledge base. In this process, various data from within the organization is sent to the server and stored in an electronic database. The input consists of various internal documents and data, and the output is structured data as a knowledge base. The server performs data processing to classify, organize, and store the data.

[0354] Step 2:

[0355] The terminal displays an interactive interface that accepts information requests from the user. At this stage, the user requests information from the terminal via voice or text. The input is the user's information request, and the output is request data that is parsed by the system. The interface captures the user's input and forwards it to the server.

[0356] Step 3:

[0357] The server uses emotion analysis technology to analyze the user's emotions from their voice tone and input speed. This analysis reveals the user's emotional state. The input is the user's voice or text data, and the output is a label indicating their emotional state. A machine learning model processes this data to recognize emotions.

[0358] Step 4:

[0359] The generation technology generates responses that meet information requests based on the user's emotional state. The generated responses reflect emotional nuances. The input consists of emotional information and relevant information drawn from a knowledge base, while the output is a personalized response. The generation AI model processes prompts, selecting and constructing appropriate words.

[0360] Step 5:

[0361] The terminal presents the generated response to the user. The display format and wording are adjusted appropriately according to the user's emotional state. The input is the generated response, and the output is information presented through an adjusted user interface. The display device visualizes the response in the most optimal way for the user.

[0362] Step 6:

[0363] The server collects user feedback and uses it to optimize the knowledge base. The feedback data is then used to further improve the system. Input is user feedback information, and output is an updated knowledge base and improved answer generation algorithms. The feedback is analyzed, and the overall system performance is adjusted accordingly.

[0364] 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.

[0365] 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.

[0366] 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.

[0367] [Third Embodiment]

[0368] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0369] 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.

[0370] 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).

[0371] 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.

[0372] 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.

[0373] 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).

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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.

[0379] 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".

[0380] This invention is implemented as a system that effectively collects information within a company and allows employees to quickly obtain the information they need. The implementation of the invention includes the following elements:

[0381] First, the server periodically collects policies, procedures, and other relevant document data from internal corporate sources. Then, it stores the collected data in an electronic knowledge base and converts it into a format that can be understood by generation technologies. This ensures that the latest information is always available, allowing for a rapid response to user requests.

[0382] Next, the terminal provides an interactive interface accessible to employees. Here, employees can input questions in natural language to find specific company information. The interface is often implemented as a web browser or a dedicated application. In this way, employees can operate the system without needing technical knowledge.

[0383] Subsequently, when the user enters a question via the terminal, the server receives the question and uses generation technology to retrieve the appropriate data from the knowledge base. The generation technology analyzes the question, processes the most relevant information, generates an answer in natural language format, and sends it to the terminal via the server.

[0384] For example, if an employee asks, "What is the latest HR policy?", the server searches the knowledge base for the relevant document and generates a summary and detailed explanation of the policy using generation technology. This answer is displayed on the terminal, allowing the user to quickly understand the necessary information.

[0385] Furthermore, the knowledge base is regularly updated by the server. This ensures that the latest information is always stored, allowing users to access reliable information.

[0386] This invention aims to improve operational efficiency by centralizing internal company information and enabling employees to easily obtain the information they need.

[0387] The following describes the processing flow.

[0388] Step 1:

[0389] The server collects internal company information and stores it in an electronic knowledge base. It also processes each document and data to convert it into a format that can be understood by the generation technology.

[0390] Step 2:

[0391] The terminal displays an interactive interface accessible to the user, providing a text box for entering questions and a submit button.

[0392] Step 3:

[0393] Users input the information or questions they want to know in natural language and send them to the server by clicking the send button on their device.

[0394] Step 4:

[0395] The server passes the user's question received from the terminal to the generation technology, which analyzes the question content. It then performs advanced processing to search for relevant information from the knowledge base.

[0396] Step 5:

[0397] The generation technology generates appropriate answers based on the question and returns them to the server in natural language format. The server then organizes the answers and verifies their accuracy.

[0398] Step 6:

[0399] The terminal displays the answer retrieved from the server to the user. Related information and links are also provided to aid user understanding.

[0400] Step 7:

[0401] The server regularly updates its knowledge base, integrating new information and changed data to ensure that the most up-to-date information is always available.

[0402] (Example 1)

[0403] 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."

[0404] There is a need to provide a system that efficiently collects and manages vast amounts of information within a company, allowing employees to quickly and easily access the information they need. Traditional systems have the problem of being time-consuming to retrieve information and making it difficult to obtain the latest information.

[0405] 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.

[0406] In this invention, the server includes means for extracting information from data sources within a company and storing it in an electronic database, means for receiving information requests from users and providing an interactive interface that allows input in natural language, and means for analyzing user information requests using generation technology and generating responses based on those requests. This enables employees to efficiently acquire the information they need and to quickly access the latest and most accurate information.

[0407] "Internal corporate data sources" refer to locations where various types of information are stored, including systems and document management platforms operated within a company.

[0408] An "electronic database" refers to a collection of information organized in a digital format and arranged for efficient management and access.

[0409] "Users" refer to employees and staff who operate the company's information systems to search for and retrieve necessary information.

[0410] A "natural language-based interactive interface" refers to an interface that allows users to input questions and instructions into the system using everyday language, without requiring specialized knowledge.

[0411] "Generative technologies" are technical methods used to analyze data and generate responses to specific questions, and primarily include natural language processing and machine learning techniques.

[0412] "Means of generating responses" refers to the process of gathering relevant information based on information requests from users, utilizing generation technologies, and providing answers in an easily understandable format.

[0413] This invention provides a system for the efficient collection and management of information within a company, and for users to quickly access that information. Specific embodiments are described below.

[0414] First, the server collects data from internal corporate information sources. These sources include internal databases, document management systems, and other information management platforms. The server utilizes automated processes to periodically ingest this information into electronic databases. The collected information is converted into a format that is easily processed by generative AI models and stored in an accessible form.

[0415] Next, the terminal provides employees with an interface that allows them to input questions in natural language. This interface functions as a web browser or a dedicated application and does not require any special technical knowledge. Employees can easily input the information they want to know, for example, by asking questions such as, "Please tell me about the latest HR policy."

[0416] When a user enters a question via their device, the server receives the information and analyzes the question using generative technology. The generative AI model grasps the intent of the question and searches for relevant information in the database. Based on this information, the server generates a natural language answer and sends it to the device.

[0417] In this way, users can quickly receive the information they need, achieving efficient information retrieval. Through this process, employees can access the latest information with evidence, contributing to improved work efficiency.

[0418] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0419] Step 1:

[0420] The server periodically collects data from information sources within the company. It receives data from various sources as input and outputs data in a format suitable for the generated AI model. Specifically, it performs processes such as standardizing data formats, removing noise, and adding necessary metadata. This data is stored in an electronic database, making it available to other components.

[0421] Step 2:

[0422] The terminal provides employees with an interface that allows them to input questions in natural language. The input consists of prompt text entered by the user, and the output is that input sent to the server. In essence, a web browser or dedicated application receives the natural language input and passes it to the server.

[0423] Step 3:

[0424] The server analyzes questions received from terminals and retrieves relevant information from its knowledge base. Input consists of the user's question and data from an electronic database, while output is a generated answer. The server first uses a generative AI model to analyze the intent of the question and extract relevant keywords. Next, it retrieves information corresponding to these keywords and generates it in a user-friendly format.

[0425] Step 4:

[0426] The server sends the generated response to the terminal. The input is the generated response in natural language format, and the output is the response displayed on the terminal. In this step, data is transmitted from the server to the terminal, and the user can view the response on the screen.

[0427] Step 5:

[0428] The user reviews the answers obtained on the device and asks follow-up questions as needed. The information received by the user is used as input, and the next question prompt is formed as output. In this process, the user can evaluate the accuracy and applicability of the information and continue gathering information.

[0429] (Application Example 1)

[0430] 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."

[0431] In modern businesses, the sheer volume of information provided, especially regarding electronic payments which are frequently updated, makes it difficult for users to quickly and accurately obtain the information they need. Furthermore, users require immediate access to information such as past spending and upcoming payment amounts to understand their financial situation. There is a need for systems that can meet these needs.

[0432] 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.

[0433] In this invention, the server includes means for collecting corporate information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses based on information requests using generation technology. This enables users to quickly and accurately obtain information related to financial transactions.

[0434] "Corporate information" refers to a variety of data and documents that companies use for business operations and decision-making.

[0435] An "electronic knowledge base" is a data storage system that organizes and stores information in a digital format, enabling efficient retrieval and utilization.

[0436] "User" refers to an individual or organization that uses the system to request and receive information.

[0437] An "information request" refers to an inquiry or question that a user enters into a system seeking specific data or answers.

[0438] An "interactive interface" refers to a user interface that allows users to communicate with a system in two-way using natural language.

[0439] "Generative technology" refers to technology that automatically generates appropriate answers based on requested information.

[0440] "Financial transaction data" refers to all transaction information related to an individual's or organization's income, expenses, savings, etc.

[0441] The system of this invention is designed to efficiently collect corporate information and quickly provide financial data based on user requests. The server is responsible for collecting corporate information and financial transaction-related data and storing it in an electronic knowledge base. This information is mainly accumulated through a web server using Python and Django, and PostgreSQL is used as the database system for managing it.

[0442] The terminal provides an interactive interface that accepts information requests from users. The primary interface is a smartphone application utilizing React Native, allowing users to input questions in natural language through the application. This makes the system easily accessible to anyone, even without technical knowledge.

[0443] The user submits an information request in natural language, which is then sent to the server. The server uses a generative AI model to analyze the information and generate a response. The generative technology primarily uses OpenAI and Google's natural language processing APIs to extract appropriate data in response to the user's request and generate a response in natural language format. The response is then sent to the user's device, allowing the user to receive the information.

[0444] For example, if a user asks, "What is my total spending this month?", the system searches its knowledge base for the relevant data and generates the result using a generative AI model. A concise summary of the total spending is then displayed on the user's smartphone. This allows the user to quickly understand their financial situation. An example of a prompt used in this process is, "Based on the user's question, extract relevant financial data and provide an answer in natural language."

[0445] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0446] Step 1:

[0447] The server periodically collects corporate information and financial transaction-related data and stores it in an electronic knowledge base. As input, this data is obtained from various corporate sources, which the server organizes using the Django framework and stores in a PostgreSQL database. This process involves structuring the data content and converting it into an efficiently searchable format.

[0448] Step 2:

[0449] Users input information requests in natural language using an application on their smartphone. The input consists of user questions, which are received by a mobile application built with React Native. The application receives this text input and sends it to the server. This is the first step towards providing information tailored to the user's intent.

[0450] Step 3:

[0451] The server analyzes the information request received from the user and extracts relevant data from its knowledge base. The input includes the user's question text, which is then analyzed using a generative AI model, such as the OpenAI API. Based on the results, the server retrieves the corresponding data from a PostgreSQL database in preparation for the next step.

[0452] Step 4:

[0453] The server uses the extracted data to generate responses in natural language. Here, a generative AI model is utilized, constructing responses tailored to the purpose and use of the data as input. The output is a well-organized response text, which is a crucial element of this process.

[0454] Step 5:

[0455] The server sends the generated response to the device and displays it to the user. As output, the generated response is displayed on the user's smartphone via React Native. In this final step, the user can quickly obtain the desired information and use it to understand financial transactions.

[0456] 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.

[0457] This invention implements an internal information provision system that incorporates an emotion engine that recognizes user emotions. This system provides a more personalized user experience by dynamically adjusting the way information is provided based on the user's emotions.

[0458] First, the server collects internal company information and stores it in an electronic knowledge base. This ensures that various policies and procedures are always kept up-to-date. The server then converts this knowledge base data into a structured format that can be processed by generation technology.

[0459] Next, the device displays an interface for interacting with the user. This interface incorporates an emotion engine that analyzes user input and interactions to recognize emotions. This allows the device to determine the user's emotional state in real time.

[0460] The user requests information through the interface, and during this process, the emotion engine analyzes the user's tone of voice, input speed, and other behavioral patterns to infer the emotions the user is currently experiencing. This emotion information is then passed to the generation technology and reflected in the generated response.

[0461] For example, if the system detects that a user is experiencing "dissatisfaction with the system," the server will generate a response using more descriptive and polite language to mitigate the reaction. The terminal will also adjust the interface layout and colors to provide a relaxing design for the user.

[0462] Furthermore, the server records the emotions detected by the emotion engine in a database and collects feedback. This feedback data is used to optimize the knowledge base and improve the user interface.

[0463] Thus, by implementing the present invention, users can not only receive information but also receive information that is tailored to their emotions at the time, thereby further improving work efficiency and reducing stress.

[0464] The following describes the processing flow.

[0465] Step 1:

[0466] The server periodically collects internal company information from various sources and stores it in an electronic knowledge base. The collected information is organized as structured data suitable for generation technologies and updated as needed.

[0467] Step 2:

[0468] The device provides users with an interactive interface that incorporates an emotion engine capable of recognizing the user's facial expressions and tone of voice. Through this interface, users can input questions in natural language.

[0469] Step 3:

[0470] Users input the information they want to know or their questions into an interactive interface and submit their inquiries. At this time, the emotion engine analyzes the user's emotions from the format of their input and the tone of their voice.

[0471] Step 4:

[0472] The server provides the user's question and sentiment data received from the terminal to the generation technology. The generation technology combines the question content and sentiment information to generate an answer that takes sentiment into consideration.

[0473] Step 5:

[0474] The device displays the generated response to the user. It reflects emotion-based feedback, adjusting the interface design and language tone to match the user's current emotional state.

[0475] Step 6:

[0476] The server records sentiment data and user feedback, which is used to optimize the knowledge base and user interface. This feedback is then used to improve future interactions.

[0477] Step 7:

[0478] This entire process is regularly evaluated, and improvements and optimizations are made to the entire system. This makes it possible to increase user satisfaction and streamline business processes.

[0479] (Example 2)

[0480] 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."

[0481] Conventional information delivery systems provide uniform information without considering user emotions, making it difficult to personalize the user experience and hindering effective information transmission and improved user satisfaction.

[0482] 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.

[0483] In this invention, the server includes means for collecting and storing information in a knowledge base, interactive display means for receiving information requests from users, and means for recognizing the user's emotions using emotion estimation technology. This enables real-time recognition of the user's emotions and the provision of appropriate information according to those emotions.

[0484] "Means of collecting information and storing it in a knowledge base" refers to the function of a system that automatically collects and stores internal and external data, making it available for use as organizational knowledge.

[0485] An "interactive display means for receiving information requests from users" is a mechanism that provides an interface for users to input the information they desire, thereby facilitating interaction between the user and the system.

[0486] "Means of recognizing a user's emotions using emotion estimation technology" refers to technologies that infer and understand a user's emotional state through voice analysis and behavioral pattern analysis.

[0487] "Means of generating responses using generative technology" refers to technologies that automatically construct appropriate responses based on acquired data and user sentiment.

[0488] "Means for saving emotion recognition results and optimizing the database" refers to the process of recording and managing data related to users' emotions and using feedback to improve the performance of the knowledge base and the overall system.

[0489] This invention is an emotion-responsive internal information provision system that dynamically recognizes user emotions and provides personalized information. A specific embodiment of this system will be described here.

[0490] First, the server collects internal company information and stores it in a knowledge base. This information collection includes feedback data from each department and documents related to business processes. The server uses a database management system to structure this data and convert it into a format that can be used by the generating AI model.

[0491] Next, the device provides an interactive interface for direct user access. This interface incorporates emotion estimation technology that analyzes the user's voice tone, input speed, and operation patterns in real time to estimate their emotions. This makes it possible to accurately understand the user's emotional state.

[0492] The user submits an information request through this interactive interface. Upon receiving the request, sentiment estimation technology analyzes the user's emotions and sends that information to the server. The server uses a generative AI model to construct the optimal response based on the received sentiment data. In this process, the generative AI model utilizes pre-prepared information templates and feedback data to generate content that is most appropriate to the user's request and emotions.

[0493] For example, if a user expresses "concerns about the system," the server can generate a polite and considerate response such as, "Thank you for using the system. Please feel free to provide feedback if you have any complaints." Another example of a prompt in this process is, "How should a user provide information when they are dissatisfied with the system?"

[0494] Ultimately, the device not only presents the generated information to the user, but also adjusts the user interface's colors and layout according to the user's emotions, providing a stress-reducing environment. Furthermore, emotion estimation results and user feedback are stored on a server and used to optimize the knowledge base and improve the user interface.

[0495] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0496] Step 1:

[0497] The server collects internal and external information and stores it in a knowledge base. Input data includes emails, business reports, and feedback forms. The server uses text analysis techniques to convert this information into structured data, ultimately storing it in JSON format. This stored data becomes the output data used by the generative AI model.

[0498] Step 2:

[0499] The terminal displays an interactive interface that enables user interaction. Input methods include user voice input and text input. Built-in emotion estimation technology analyzes the user's voice tone and input speed to recognize the user's emotions in real time. This emotion data is output data sent to the server.

[0500] Step 3:

[0501] The server generates responses using a generative AI model based on user sentiment data received from the terminal. The input data consists of the sentiment score and the user's information request. The generative AI model uses the given input data as prompts and combines it with knowledge base data to generate responses that meet user needs. These responses become the output data.

[0502] Step 4:

[0503] The terminal receives responses from the server and displays them to the user. The input is the response received from the server, and the interface's colors and layout are adjusted according to the user's emotions. The final output is the information presented to the user, aiming to soothe their emotions and improve their satisfaction.

[0504] Step 5:

[0505] The server records the user's emotion estimation results and feedback on the response in a database. It collects user response behavior and additional feedback as input data and analyzes it to optimize system performance. The output of this process is used to optimize the knowledge base and generate responses in the future.

[0506] (Application Example 2)

[0507] 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."

[0508] When users seek information, a problem arises where services are standardized because their emotional state is not taken into consideration, resulting in a lack of improvement in the user experience. This issue is particularly concerning in physical stores, where it is feared that customer satisfaction will not improve. Therefore, it is necessary to develop a system that provides personalized services while taking into account the user's emotions.

[0509] 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.

[0510] In this invention, the server includes means for collecting internal company information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses to information requests using generation technology. This makes it possible to recognize the user's emotions and dynamically adjust the service based on their emotional state.

[0511] "Internal company information" refers to various data, documents, and information generated or used within an organization.

[0512] A "knowledge base" is an electronic database used to systematically store and manage collected company information.

[0513] "User" refers to an individual or group that uses the system to search for or request information.

[0514] An "interactive interface" is a user interface that allows users and systems to exchange information with each other.

[0515] "Generative technology" refers to technology used to automatically generate appropriate answers in response to user information requests.

[0516] "Emotional analysis technology" is a technology that analyzes a user's voice, facial expressions, etc., and recognizes their emotional state in real time.

[0517] A "display device" is a hardware device used by users to provide information or services.

[0518] "Dynamically adjusting services" means changing the content and format of the information and services provided in real time based on the user's emotional state and requests.

[0519] One embodiment of this invention involves first using a server system to collect internal company information and store it in an electronic knowledge base. The server periodically updates this knowledge base to maintain the latest information. The information within the knowledge base is provided to the generation technology as structured data.

[0520] The terminal displays an interface for interacting with the user. This interface incorporates emotion analysis technology, recognizing the user's emotional state in real time by analyzing their input and tone of voice. The user's emotional information is then reflected in the service, which is dynamically adjusted using generation technology.

[0521] In terms of hardware, a display device that captures and displays information is used, specifically such as smart glasses. For software, machine learning frameworks such as TensorFlow and PyTorch are used for sentiment analysis, and React Native is used to build the user interface.

[0522] As a concrete example, when a customer is choosing a product in a physical store, if smart glasses detect that the customer is "confused" based on their facial expression and tone of voice, the glasses' display will show a message asking the customer if they are unsure and explaining the product details. In this way, the service received by the user is personalized, and customer satisfaction improves.

[0523] Examples of prompts include, "How should I best assist this customer who seems confused?" or "How can I reassure a customer who is feeling stressed?"

[0524] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0525] Step 1:

[0526] The server collects internal company information and stores it in a knowledge base. In this process, various data from within the organization is sent to the server and stored in an electronic database. The input consists of various internal documents and data, and the output is structured data as a knowledge base. The server performs data processing to classify, organize, and store the data.

[0527] Step 2:

[0528] The terminal displays an interactive interface that accepts information requests from the user. At this stage, the user requests information from the terminal via voice or text. The input is the user's information request, and the output is request data that is parsed by the system. The interface captures the user's input and forwards it to the server.

[0529] Step 3:

[0530] The server uses emotion analysis technology to analyze the user's emotions from their voice tone and input speed. This analysis reveals the user's emotional state. The input is the user's voice or text data, and the output is a label indicating their emotional state. A machine learning model processes this data to recognize emotions.

[0531] Step 4:

[0532] The generation technology generates responses that meet information requests based on the user's emotional state. The generated responses reflect emotional nuances. The input consists of emotional information and relevant information drawn from a knowledge base, while the output is a personalized response. The generation AI model processes prompts, selecting and constructing appropriate words.

[0533] Step 5:

[0534] The terminal presents the generated response to the user. The display format and wording are adjusted appropriately according to the user's emotional state. The input is the generated response, and the output is information presented through an adjusted user interface. The display device visualizes the response in the most optimal way for the user.

[0535] Step 6:

[0536] The server collects user feedback and uses it to optimize the knowledge base. The feedback data is then used to further improve the system. Input is user feedback information, and output is an updated knowledge base and improved answer generation algorithms. The feedback is analyzed, and the overall system performance is adjusted accordingly.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] [Fourth Embodiment]

[0541] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0542] 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.

[0543] 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).

[0544] 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.

[0545] 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.

[0546] 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).

[0547] 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.

[0548] 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.

[0549] 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.

[0550] 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.

[0551] 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.

[0552] 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.

[0553] 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".

[0554] This invention is implemented as a system that effectively collects information within a company and allows employees to quickly obtain the information they need. The implementation of the invention includes the following elements:

[0555] First, the server periodically collects policies, procedures, and other relevant document data from internal corporate sources. Then, it stores the collected data in an electronic knowledge base and converts it into a format that can be understood by generation technologies. This ensures that the latest information is always available, allowing for a rapid response to user requests.

[0556] Next, the terminal provides an interactive interface accessible to employees. Here, employees can input questions in natural language to find specific company information. The interface is often implemented as a web browser or a dedicated application. In this way, employees can operate the system without needing technical knowledge.

[0557] Subsequently, when the user enters a question via the terminal, the server receives the question and uses generation technology to retrieve the appropriate data from the knowledge base. The generation technology analyzes the question, processes the most relevant information, generates an answer in natural language format, and sends it to the terminal via the server.

[0558] For example, if an employee asks, "What is the latest HR policy?", the server searches the knowledge base for the relevant document and generates a summary and detailed explanation of the policy using generation technology. This answer is displayed on the terminal, allowing the user to quickly understand the necessary information.

[0559] Furthermore, the knowledge base is regularly updated by the server. This ensures that the latest information is always stored, allowing users to access reliable information.

[0560] This invention aims to improve operational efficiency by centralizing internal company information and enabling employees to easily obtain the information they need.

[0561] The following describes the processing flow.

[0562] Step 1:

[0563] The server collects internal company information and stores it in an electronic knowledge base. It also processes each document and data to convert it into a format that can be understood by the generation technology.

[0564] Step 2:

[0565] The terminal displays an interactive interface accessible to the user, providing a text box for entering questions and a submit button.

[0566] Step 3:

[0567] Users input the information or questions they want to know in natural language and send them to the server by clicking the send button on their device.

[0568] Step 4:

[0569] The server passes the user's question received from the terminal to the generation technology, which analyzes the question content. It then performs advanced processing to search for relevant information from the knowledge base.

[0570] Step 5:

[0571] The generation technology generates appropriate answers based on the question and returns them to the server in natural language format. The server then organizes the answers and verifies their accuracy.

[0572] Step 6:

[0573] The terminal displays the answer retrieved from the server to the user. Related information and links are also provided to aid user understanding.

[0574] Step 7:

[0575] The server regularly updates its knowledge base, integrating new information and changed data to ensure that the most up-to-date information is always available.

[0576] (Example 1)

[0577] 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".

[0578] There is a need to provide a system that efficiently collects and manages vast amounts of information within a company, allowing employees to quickly and easily access the information they need. Traditional systems have the problem of being time-consuming to retrieve information and making it difficult to obtain the latest information.

[0579] 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.

[0580] In this invention, the server includes means for extracting information from data sources within a company and storing it in an electronic database, means for receiving information requests from users and providing an interactive interface that allows input in natural language, and means for analyzing user information requests using generation technology and generating responses based on those requests. This enables employees to efficiently acquire the information they need and to quickly access the latest and most accurate information.

[0581] "Internal corporate data sources" refer to locations where various types of information are stored, including systems and document management platforms operated within a company.

[0582] An "electronic database" refers to a collection of information organized in a digital format and arranged for efficient management and access.

[0583] "Users" refer to employees and staff who operate the company's information systems to search for and retrieve necessary information.

[0584] A "natural language-based interactive interface" refers to an interface that allows users to input questions and instructions into the system using everyday language, without requiring specialized knowledge.

[0585] "Generative technologies" are technical methods used to analyze data and generate responses to specific questions, and primarily include natural language processing and machine learning techniques.

[0586] "Means of generating responses" refers to the process of gathering relevant information based on information requests from users, utilizing generation technologies, and providing answers in an easily understandable format.

[0587] This invention provides a system for the efficient collection and management of information within a company, and for users to quickly access that information. Specific embodiments are described below.

[0588] First, the server collects data from internal corporate information sources. These sources include internal databases, document management systems, and other information management platforms. The server utilizes automated processes to periodically ingest this information into electronic databases. The collected information is converted into a format that is easily processed by generative AI models and stored in an accessible form.

[0589] Next, the terminal provides employees with an interface that allows them to input questions in natural language. This interface functions as a web browser or a dedicated application and does not require any special technical knowledge. Employees can easily input the information they want to know, for example, by asking questions such as, "Please tell me about the latest HR policy."

[0590] When a user enters a question via their device, the server receives the information and analyzes the question using generative technology. The generative AI model grasps the intent of the question and searches for relevant information in the database. Based on this information, the server generates a natural language answer and sends it to the device.

[0591] In this way, users can quickly receive the information they need, achieving efficient information retrieval. Through this process, employees can access the latest information with evidence, contributing to improved work efficiency.

[0592] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0593] Step 1:

[0594] The server periodically collects data from information sources within the company. It receives data from various sources as input and outputs data in a format suitable for the generated AI model. Specifically, it performs processes such as standardizing data formats, removing noise, and adding necessary metadata. This data is stored in an electronic database, making it available to other components.

[0595] Step 2:

[0596] The terminal provides employees with an interface that allows them to input questions in natural language. The input consists of prompt text entered by the user, and the output is that input sent to the server. In essence, a web browser or dedicated application receives the natural language input and passes it to the server.

[0597] Step 3:

[0598] The server analyzes questions received from terminals and retrieves relevant information from its knowledge base. Input consists of the user's question and data from an electronic database, while output is a generated answer. The server first uses a generative AI model to analyze the intent of the question and extract relevant keywords. Next, it retrieves information corresponding to these keywords and generates it in a user-friendly format.

[0599] Step 4:

[0600] The server sends the generated response to the terminal. The input is the generated response in natural language format, and the output is the response displayed on the terminal. In this step, data is transmitted from the server to the terminal, and the user can view the response on the screen.

[0601] Step 5:

[0602] The user reviews the answers obtained on the device and asks follow-up questions as needed. The information received by the user is used as input, and the next question prompt is formed as output. In this process, the user can evaluate the accuracy and applicability of the information and continue gathering information.

[0603] (Application Example 1)

[0604] 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".

[0605] In modern businesses, the sheer volume of information provided, especially regarding electronic payments which are frequently updated, makes it difficult for users to quickly and accurately obtain the information they need. Furthermore, users require immediate access to information such as past spending and upcoming payment amounts to understand their financial situation. There is a need for systems that can meet these needs.

[0606] 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.

[0607] In this invention, the server includes means for collecting corporate information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses based on information requests using generation technology. This enables users to quickly and accurately obtain information related to financial transactions.

[0608] "Corporate information" refers to a variety of data and documents that companies use for business operations and decision-making.

[0609] An "electronic knowledge base" is a data storage system that organizes and stores information in a digital format, enabling efficient retrieval and utilization.

[0610] "User" refers to an individual or organization that uses the system to request and receive information.

[0611] An "information request" refers to an inquiry or question that a user enters into a system seeking specific data or answers.

[0612] An "interactive interface" refers to a user interface that allows users to communicate with a system in two-way using natural language.

[0613] "Generative technology" refers to technology that automatically generates appropriate answers based on requested information.

[0614] "Financial transaction data" refers to all transaction information related to an individual's or organization's income, expenses, savings, etc.

[0615] The system of this invention is designed to efficiently collect corporate information and quickly provide financial data based on user requests. The server is responsible for collecting corporate information and financial transaction-related data and storing it in an electronic knowledge base. This information is mainly accumulated through a web server using Python and Django, and PostgreSQL is used as the database system for managing it.

[0616] The terminal provides an interactive interface that accepts information requests from users. The primary interface is a smartphone application utilizing React Native, allowing users to input questions in natural language through the application. This makes the system easily accessible to anyone, even without technical knowledge.

[0617] The user submits an information request in natural language, which is then sent to the server. The server uses a generative AI model to analyze the information and generate a response. The generative technology primarily uses OpenAI and Google's natural language processing APIs to extract appropriate data in response to the user's request and generate a response in natural language format. The response is then sent to the user's device, allowing the user to receive the information.

[0618] For example, if a user asks, "What is my total spending this month?", the system searches its knowledge base for the relevant data and generates the result using a generative AI model. A concise summary of the total spending is then displayed on the user's smartphone. This allows the user to quickly understand their financial situation. An example of a prompt used in this process is, "Based on the user's question, extract relevant financial data and provide an answer in natural language."

[0619] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0620] Step 1:

[0621] The server periodically collects corporate information and financial transaction-related data and stores it in an electronic knowledge base. As input, this data is obtained from various corporate sources, which the server organizes using the Django framework and stores in a PostgreSQL database. This process involves structuring the data content and converting it into an efficiently searchable format.

[0622] Step 2:

[0623] Users input information requests in natural language using an application on their smartphone. The input consists of user questions, which are received by a mobile application built with React Native. The application receives this text input and sends it to the server. This is the first step towards providing information tailored to the user's intent.

[0624] Step 3:

[0625] The server analyzes the information request received from the user and extracts relevant data from its knowledge base. The input includes the user's question text, which is then analyzed using a generative AI model, such as the OpenAI API. Based on the results, the server retrieves the corresponding data from a PostgreSQL database in preparation for the next step.

[0626] Step 4:

[0627] The server uses the extracted data to generate responses in natural language. Here, a generative AI model is utilized, constructing responses tailored to the purpose and use of the data as input. The output is a well-organized response text, which is a crucial element of this process.

[0628] Step 5:

[0629] The server sends the generated response to the device and displays it to the user. As output, the generated response is displayed on the user's smartphone via React Native. In this final step, the user can quickly obtain the desired information and use it to understand financial transactions.

[0630] 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.

[0631] This invention implements an internal information provision system that incorporates an emotion engine that recognizes user emotions. This system provides a more personalized user experience by dynamically adjusting the way information is provided based on the user's emotions.

[0632] First, the server collects internal company information and stores it in an electronic knowledge base. This ensures that various policies and procedures are always kept up-to-date. The server then converts this knowledge base data into a structured format that can be processed by generation technology.

[0633] Next, the device displays an interface for interacting with the user. This interface incorporates an emotion engine that analyzes user input and interactions to recognize emotions. This allows the device to determine the user's emotional state in real time.

[0634] The user requests information through the interface, and during this process, the emotion engine analyzes the user's tone of voice, input speed, and other behavioral patterns to infer the emotions the user is currently experiencing. This emotion information is then passed to the generation technology and reflected in the generated response.

[0635] For example, if the system detects that a user is experiencing "dissatisfaction with the system," the server will generate a response using more descriptive and polite language to mitigate the reaction. The terminal will also adjust the interface layout and colors to provide a relaxing design for the user.

[0636] Furthermore, the server records the emotions detected by the emotion engine in a database and collects feedback. This feedback data is used to optimize the knowledge base and improve the user interface.

[0637] Thus, by implementing the present invention, users can not only receive information but also receive information that is tailored to their emotions at the time, thereby further improving work efficiency and reducing stress.

[0638] The following describes the processing flow.

[0639] Step 1:

[0640] The server periodically collects internal company information from various sources and stores it in an electronic knowledge base. The collected information is organized as structured data suitable for generation technologies and updated as needed.

[0641] Step 2:

[0642] The device provides users with an interactive interface that incorporates an emotion engine capable of recognizing the user's facial expressions and tone of voice. Through this interface, users can input questions in natural language.

[0643] Step 3:

[0644] Users input the information they want to know or their questions into an interactive interface and submit their inquiries. At this time, the emotion engine analyzes the user's emotions from the format of their input and the tone of their voice.

[0645] Step 4:

[0646] The server provides the user's question and sentiment data received from the terminal to the generation technology. The generation technology combines the question content and sentiment information to generate an answer that takes sentiment into consideration.

[0647] Step 5:

[0648] The device displays the generated response to the user. It reflects emotion-based feedback, adjusting the interface design and language tone to match the user's current emotional state.

[0649] Step 6:

[0650] The server records sentiment data and user feedback, which is used to optimize the knowledge base and user interface. This feedback is then used to improve future interactions.

[0651] Step 7:

[0652] This entire process is regularly evaluated, and improvements and optimizations are made to the entire system. This makes it possible to increase user satisfaction and streamline business processes.

[0653] (Example 2)

[0654] 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".

[0655] Conventional information delivery systems provide uniform information without considering user emotions, making it difficult to personalize the user experience and hindering effective information transmission and improved user satisfaction.

[0656] 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.

[0657] In this invention, the server includes means for collecting and storing information in a knowledge base, interactive display means for receiving information requests from users, and means for recognizing the user's emotions using emotion estimation technology. This enables real-time recognition of the user's emotions and the provision of appropriate information according to those emotions.

[0658] "Means of collecting information and storing it in a knowledge base" refers to the function of a system that automatically collects and stores internal and external data, making it available for use as organizational knowledge.

[0659] An "interactive display means for receiving information requests from users" is a mechanism that provides an interface for users to input the information they desire, thereby facilitating interaction between the user and the system.

[0660] "Means of recognizing a user's emotions using emotion estimation technology" refers to technologies that infer and understand a user's emotional state through voice analysis and behavioral pattern analysis.

[0661] "Means of generating responses using generative technology" refers to technologies that automatically construct appropriate responses based on acquired data and user sentiment.

[0662] "Means for saving emotion recognition results and optimizing the database" refers to the process of recording and managing data related to users' emotions and using feedback to improve the performance of the knowledge base and the overall system.

[0663] This invention is an emotion-responsive internal information provision system that dynamically recognizes user emotions and provides personalized information. A specific embodiment of this system will be described here.

[0664] First, the server collects internal company information and stores it in a knowledge base. This information collection includes feedback data from each department and documents related to business processes. The server uses a database management system to structure this data and convert it into a format that can be used by the generating AI model.

[0665] Next, the device provides an interactive interface for direct user access. This interface incorporates emotion estimation technology that analyzes the user's voice tone, input speed, and operation patterns in real time to estimate their emotions. This makes it possible to accurately understand the user's emotional state.

[0666] The user submits an information request through this interactive interface. Upon receiving the request, sentiment estimation technology analyzes the user's emotions and sends that information to the server. The server uses a generative AI model to construct the optimal response based on the received sentiment data. In this process, the generative AI model utilizes pre-prepared information templates and feedback data to generate content that is most appropriate to the user's request and emotions.

[0667] For example, if a user expresses "concerns about the system," the server can generate a polite and considerate response such as, "Thank you for using the system. Please feel free to provide feedback if you have any complaints." Another example of a prompt in this process is, "How should a user provide information when they are dissatisfied with the system?"

[0668] Ultimately, the device not only presents the generated information to the user, but also adjusts the user interface's colors and layout according to the user's emotions, providing a stress-reducing environment. Furthermore, emotion estimation results and user feedback are stored on a server and used to optimize the knowledge base and improve the user interface.

[0669] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0670] Step 1:

[0671] The server collects internal and external information and stores it in a knowledge base. Input data includes emails, business reports, and feedback forms. The server uses text analysis techniques to convert this information into structured data, ultimately storing it in JSON format. This stored data becomes the output data used by the generative AI model.

[0672] Step 2:

[0673] The terminal displays an interactive interface that enables user interaction. Input methods include user voice input and text input. Built-in emotion estimation technology analyzes the user's voice tone and input speed to recognize the user's emotions in real time. This emotion data is output data sent to the server.

[0674] Step 3:

[0675] The server generates responses using a generative AI model based on user sentiment data received from the terminal. The input data consists of the sentiment score and the user's information request. The generative AI model uses the given input data as prompts and combines it with knowledge base data to generate responses that meet user needs. These responses become the output data.

[0676] Step 4:

[0677] The terminal receives responses from the server and displays them to the user. The input is the response received from the server, and the interface's colors and layout are adjusted according to the user's emotions. The final output is the information presented to the user, aiming to soothe their emotions and improve their satisfaction.

[0678] Step 5:

[0679] The server records the user's emotion estimation results and feedback on the response in a database. It collects user response behavior and additional feedback as input data and analyzes it to optimize system performance. The output of this process is used to optimize the knowledge base and generate responses in the future.

[0680] (Application Example 2)

[0681] 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".

[0682] When users seek information, a problem arises where services are standardized because their emotional state is not taken into consideration, resulting in a lack of improvement in the user experience. This issue is particularly concerning in physical stores, where it is feared that customer satisfaction will not improve. Therefore, it is necessary to develop a system that provides personalized services while taking into account the user's emotions.

[0683] 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.

[0684] In this invention, the server includes means for collecting internal company information and storing it in an electronic knowledge base, means for providing an interactive interface for receiving information requests from users, and means for generating responses to information requests using generation technology. This makes it possible to recognize the user's emotions and dynamically adjust the service based on their emotional state.

[0685] "Internal company information" refers to various data, documents, and information generated or used within an organization.

[0686] A "knowledge base" is an electronic database used to systematically store and manage collected company information.

[0687] "User" refers to an individual or group that uses the system to search for or request information.

[0688] An "interactive interface" is a user interface that allows users and systems to exchange information with each other.

[0689] "Generative technology" refers to technology used to automatically generate appropriate answers in response to user information requests.

[0690] "Emotional analysis technology" is a technology that analyzes a user's voice, facial expressions, etc., and recognizes their emotional state in real time.

[0691] A "display device" is a hardware device used by users to provide information or services.

[0692] "Dynamically adjusting services" means changing the content and format of the information and services provided in real time based on the user's emotional state and requests.

[0693] One embodiment of this invention involves first using a server system to collect internal company information and store it in an electronic knowledge base. The server periodically updates this knowledge base to maintain the latest information. The information within the knowledge base is provided to the generation technology as structured data.

[0694] The terminal displays an interface for interacting with the user. This interface incorporates emotion analysis technology, recognizing the user's emotional state in real time by analyzing their input and tone of voice. The user's emotional information is then reflected in the service, which is dynamically adjusted using generation technology.

[0695] In terms of hardware, a display device that captures and displays information is used, specifically such as smart glasses. For software, machine learning frameworks such as TensorFlow and PyTorch are used for sentiment analysis, and React Native is used to build the user interface.

[0696] As a concrete example, when a customer is choosing a product in a physical store, if smart glasses detect that the customer is "confused" based on their facial expression and tone of voice, the glasses' display will show a message asking the customer if they are unsure and explaining the product details. In this way, the service received by the user is personalized, and customer satisfaction improves.

[0697] Examples of prompts include, "How should I best assist this customer who seems confused?" or "How can I reassure a customer who is feeling stressed?"

[0698] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0699] Step 1:

[0700] The server collects internal company information and stores it in a knowledge base. In this process, various data from within the organization is sent to the server and stored in an electronic database. The input consists of various internal documents and data, and the output is structured data as a knowledge base. The server performs data processing to classify, organize, and store the data.

[0701] Step 2:

[0702] The terminal displays an interactive interface that accepts information requests from the user. At this stage, the user requests information from the terminal via voice or text. The input is the user's information request, and the output is request data that is parsed by the system. The interface captures the user's input and forwards it to the server.

[0703] Step 3:

[0704] The server uses emotion analysis technology to analyze the user's emotions from their voice tone and input speed. This analysis reveals the user's emotional state. The input is the user's voice or text data, and the output is a label indicating their emotional state. A machine learning model processes this data to recognize emotions.

[0705] Step 4:

[0706] The generation technology generates responses that meet information requests based on the user's emotional state. The generated responses reflect emotional nuances. The input consists of emotional information and relevant information drawn from a knowledge base, while the output is a personalized response. The generation AI model processes prompts, selecting and constructing appropriate words.

[0707] Step 5:

[0708] The terminal presents the generated response to the user. The display format and wording are adjusted appropriately according to the user's emotional state. The input is the generated response, and the output is information presented through an adjusted user interface. The display device visualizes the response in the most optimal way for the user.

[0709] Step 6:

[0710] The server collects user feedback and uses it to optimize the knowledge base. The feedback data is then used to further improve the system. Input is user feedback information, and output is an updated knowledge base and improved answer generation algorithms. The feedback is analyzed, and the overall system performance is adjusted accordingly.

[0711] 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.

[0712] 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.

[0713] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0714] 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.

[0715] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0716] 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.

[0717] 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.

[0718] 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.

[0719] 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."

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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.

[0729] 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.

[0730] 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.

[0731] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0732] The following is further disclosed regarding the embodiments described above.

[0733] (Claim 1)

[0734] A means of collecting internal company information and storing it in an electronic knowledge base,

[0735] A means of providing an interactive interface that accepts information requests from users,

[0736] A means for generating answers to information requests using generation technology,

[0737] A means of presenting the aforementioned answer to the user,

[0738] Methods for regularly updating the knowledge base,

[0739] A system that includes this.

[0740] (Claim 2)

[0741] The system according to claim 1, comprising means for providing the aforementioned internal company information as structured data to a generation technology.

[0742] (Claim 3)

[0743] The system according to claim 1, comprising means for collecting user feedback and optimizing the knowledge base.

[0744] "Example 1"

[0745] (Claim 1)

[0746] A means of extracting information from data sources within a company and storing it in an electronic database,

[0747] A means of receiving information requests from users and providing an interactive interface that allows input in natural language,

[0748] A means for analyzing a user's information request using generation technology and generating a response based on that request,

[0749] A means of providing the generated response to the user,

[0750] A means of regularly updating the database and maintaining the most reliable and up-to-date information,

[0751] A system that includes this.

[0752] (Claim 2)

[0753] The system according to claim 1, comprising means for converting the aforementioned data into a unified format and preparing it so that it can be easily processed by the generation technology.

[0754] (Claim 3)

[0755] The system according to claim 1, comprising means for aggregating user feedback and using the results to effectively improve the database.

[0756] "Application Example 1"

[0757] (Claim 1)

[0758] Means for collecting corporate information and storing it in an electronic knowledge base,

[0759] A means of providing an interactive interface that accepts information requests from users,

[0760] A means for generating responses based on information requests using generation technology,

[0761] A means of displaying the aforementioned answer to the user,

[0762] Means for regularly updating the knowledge base,

[0763] A means of regularly collecting financial transaction-related data and incorporating it into a knowledge base,

[0764] A means of generating responses using generation technology in response to financial information requests from users,

[0765] A system that includes this.

[0766] (Claim 2)

[0767] The system according to claim 1, comprising means for providing the aforementioned information as structured data to a generation technology.

[0768] (Claim 3)

[0769] The system according to claim 1, comprising means for collecting user feedback and optimizing the knowledge base.

[0770] "Example 2 of combining an emotion engine"

[0771] (Claim 1)

[0772] Means for collecting information and storing it in a knowledge base,

[0773] An interactive display means for receiving information requests from users,

[0774] A means of recognizing the user's emotions using emotion estimation technology,

[0775] Means for generating a response using generation technology, taking the aforementioned emotions into consideration,

[0776] A means of adjusting the aforementioned response and presenting it to the user,

[0777] A means for saving emotion recognition results and optimizing the database,

[0778] A system that includes this.

[0779] (Claim 2)

[0780] The system according to claim 1, comprising means for providing internal company information as structured data to a generation technology.

[0781] (Claim 3)

[0782] The system according to claim 1, comprising means for collecting user feedback and optimizing the knowledge base.

[0783] "Application example 2 when combining with an emotional engine"

[0784] (Claim 1)

[0785] A means of collecting internal company information and storing it in an electronic knowledge base,

[0786] A means of providing an interactive interface that accepts information requests from users,

[0787] A means for generating answers to information requests using generation technology,

[0788] A means of presenting the aforementioned answer to the user,

[0789] Means for regularly updating the knowledge base,

[0790] A means for dynamically adjusting services based on the user's emotional state, using a display device that incorporates emotion analysis technology to recognize the user's emotions,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, comprising means for providing the aforementioned internal company information as structured data to a generation technology.

[0794] (Claim 3)

[0795] The system according to claim 1, comprising means for collecting user feedback and optimizing the knowledge base. [Explanation of Symbols]

[0796] 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. Means for collecting corporate information and storing it in an electronic knowledge base, A means of providing an interactive interface that accepts information requests from users, A means for generating responses based on information requests using generation technology, A means of displaying the aforementioned answer to the user, Means for regularly updating the knowledge base, A means of regularly collecting financial transaction-related data and incorporating it into a knowledge base, A means of generating responses using generation technology in response to financial information requests from users, A system that includes this.

2. The system according to claim 1, comprising means for providing the aforementioned information as structured data to a generation technology.

3. The system according to claim 1, comprising means for collecting user feedback and optimizing the knowledge base.

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