system

Abstract

We provide the system. [Solution] A data acquisition method for collecting audio data and text data, A data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks, A management system for setting priorities for extracted events and tasks and managing their schedules, A notification means that provides notifications and alerts to users, Translation tools that support multilingual conversations through translation processing, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In recent years, with the rapid increase in individual digital information, efficient scheduling and task management have become difficult. Also, in information retrieval for obtaining important information, it is time-consuming to select relevant information, and there are many situations where communication in a foreign language becomes an obstacle. As a result, the problems that impede daily life and business are increasing. 【Means for Solving the Problems】 【0005】 This invention provides a data analysis means that collects audio and text data, analyzes the data using speech recognition and natural language processing, and extracts events and tasks, thereby streamlining schedule and task management. It also includes a management means for setting priorities for the extracted events and tasks, making user schedule management easier. Furthermore, by supporting multilingual conversations using a translation means, it facilitates communication in foreign languages ​​and improves user convenience. 【0006】 "Audio data" refers to data used to record or transmit audio in digital format. 【0007】 "Text data" refers to data used to record or transmit character information in a digital format. 【0008】 "Data acquisition means" refers to methods or functions for collecting information such as audio data and text data. 【0009】 "Speech recognition" is a technology that analyzes speech and converts it into text or other formats. 【0010】 "Natural language processing" is a technology that enables computers to understand and process human language. 【0011】 "Data analysis means" refers to a method or function for processing collected data and extracting useful information. 【0012】 An "event" is an item that represents a specific occurrence or activity. 【0013】 A "task" refers to the actions necessary to complete a specific action or task. 【0014】 "Management tools" refer to methods or functions for organizing, prioritizing, and scheduling events and tasks. 【0015】 "Notification means" refers to a method or function for conveying information and alerts to users. 【0016】 "Translation means" refers to a method or function for converting text or speech in one language into another language. 【0017】 "Information source" refers to the origin such as a database or website that provides information. 【0018】 "Information optimization means" refers to a method or function for evaluating the acquired information and presenting it in an optimal form for the user. 【Brief Description of Drawings】 【0019】 [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined. 【Modes for Carrying Out the Invention】 【0020】 Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0021】 First, the terms used in the following description will be explained. 【0022】 In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc. 【0023】 In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0024】 In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes. 【0025】 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). 【0026】 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." 【0027】 [First Embodiment] 【0028】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0029】 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. 【0030】 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). 【0031】 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. 【0032】 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. 【0033】 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. 【0034】 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. 【0035】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0036】 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. 【0037】 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. 【0038】 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. 【0039】 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". 【0040】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and communication in foreign languages, in order to improve the efficiency of users in their daily lives and business. 【0041】 This system functions through the interaction of the server, terminals, and users. The server collects and periodically monitors user emails and meeting audio data. This data is transferred to the terminals, where speech recognition technology is used to convert the audio data into text. The converted text is then analyzed on the server through natural language processing, and events and tasks are automatically extracted. 【0042】 On the device, tasks and events prioritized by the server are incorporated into the user's schedule. This schedule is updated in real time, and the user can check the progress of their schedule and tasks through the device and edit the content as needed. For example, when a user joins a meeting, important tasks and deadlines mentioned in that meeting are automatically recognized and added to the schedule. 【0043】 Furthermore, if a user needs information, they can send a request to their device via voice or text. The server processes this request and gathers relevant information from multiple sources. The device displays a list of information that has been evaluated for relevance and reliability, allowing the user to easily access the information they need. For example, in response to a request such as "Tell me about the latest market trends," relevant news and data will be displayed. 【0044】 Furthermore, to support communication with foreign language speakers, when voice input is received on the device, it is automatically translated into the specified language via a server. The translated result is output again as voice on the device, allowing users to converse smoothly with foreign language speakers. For example, Japanese input can be translated into English, supporting immediate understanding for the other party. 【0045】 This system combines speech recognition, natural language processing, data analysis, and translation technologies to solve many of the challenges users face and significantly improve their daily efficiency. 【0046】 The following describes the processing flow. 【0047】 Step 1: 【0048】 The server periodically collects user emails and meeting audio data. The collected data is temporarily stored and prepared for analysis. 【0049】 Step 2: 【0050】 The server sends the collected audio data to the terminal. The terminal uses speech recognition technology to convert the audio data into text data. The converted text is then sent back to the server. 【0051】 Step 3: 【0052】 The server receives text data and analyzes its content using natural language processing techniques. Through this analysis, tasks and events are extracted, and related information is organized. 【0053】 Step 4: 【0054】 The server prioritizes the extracted tasks and events. An algorithm is used to evaluate them based on importance and proximity of deadlines. 【0055】 Step 5: 【0056】 The server sends prioritized tasks to the device. The device automatically integrates these tasks into the user's calendar or task management application. 【0057】 Step 6: 【0058】 The device notifies the user of schedule updates. The user can check the schedule through the device and edit or delete task details as needed. 【0059】 Step 7: 【0060】 When a user searches for information, they send a request to their device via voice or text. 【0061】 Step 8: 【0062】 The server searches for relevant information from multiple sources based on the received request. It evaluates the relevance and reliability of the information and selects the most appropriate information. 【0063】 Step 9: 【0064】 The server sends optimized information to the terminal. The terminal displays the information on the user interface, making it easy for the user to access. 【0065】 Step 10: 【0066】 If a user wishes to converse in a foreign language, they input voice commands into the device. The device then uses voice recognition to convert the input into text and sends it to the server. 【0067】 Step 11: 【0068】 The server uses natural language processing and translation techniques to translate the input text into the specified language. The translation result is returned to the terminal. 【0069】 Step 12: 【0070】 The device converts the translated text into speech using speech synthesis technology and outputs it through the speaker. This allows users to have smooth conversations with foreign language speakers. 【0071】 (Example 1) 【0072】 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." 【0073】 Information overload has made it difficult for users to efficiently collect, organize, and utilize the information they need for their daily lives and businesses. Furthermore, the limited means of achieving smooth communication across multiple languages ​​is compromising user convenience. Therefore, there is a need to develop a system that effectively utilizes audio and text data to comprehensively support schedule management, information retrieval, and multilingual communication. 【0074】 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. 【0075】 In this invention, the server includes data acquisition means for collecting voice data and text data; data analysis means for converting voice data into text data using speech recognition technology, analyzing the data using natural language processing technology, and extracting events and tasks; and management means for setting priorities for the extracted events and tasks and managing an electronic schedule. This enables users to efficiently collect and organize necessary information, as well as facilitate communication across multiple languages. 【0076】 "Audio data" refers to data used to record and process audio in a digital format. 【0077】 "Text data" refers to data that represents information composed of characters. 【0078】 A "data acquisition method" is a system for collecting and recording specific information. 【0079】 "Speech recognition technology" is a technology that analyzes speech data and interprets it as a string of characters. 【0080】 "Natural language processing technology" is a technology that enables computers to understand and process human language. 【0081】 "Data analysis methods" are means for analyzing collected information and extracting useful information. 【0082】 An "event" refers to a specific, planned occurrence or activity. 【0083】 "Work" refers to a series of activities or tasks performed to achieve a certain objective. 【0084】 A "management tool" is a system for efficiently organizing plans and tasks and controlling their execution. 【0085】 A "notification method" is a mechanism for informing users of information or warnings. 【0086】 "Translation methods" are technologies that convert information in order to convey meaning between different languages. 【0087】 "Information retrieval methods" refer to methods of searching databases or the internet to identify necessary information. 【0088】 "Information optimization methods" are means of evaluating acquired information and selecting the most important and necessary content. 【0089】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and multilingual communication, in order to improve the efficiency of users in their daily lives and businesses. 【0090】 The server periodically collects communication data from users, such as emails and audio from meetings. This requires server equipment with high-performance processors, and the software utilizes database management systems and cloud infrastructure to efficiently process the data streams. In particular, speech recognition software (such as Google® Cloud Speech-to-Text API) is used to transcribe audio data. 【0091】 The terminal converts audio received from the server into text data and sends it to a natural language processing engine to extract events and tasks. Text analysis solutions (such as SpaCy or NLTK) are used for natural language processing, and the server uses this to prioritize tasks and manage schedules automatically. 【0092】 Through this system, users can always stay informed of their latest schedules and receive notifications. Furthermore, if they need information, users can send requests via voice or text to their devices, and the server processes these requests to gather relevant information from the internet and other digital sources. The web crawling technologies and information gathering solutions used in this process allow users to quickly access the information they need. 【0093】 Furthermore, to support communication in foreign languages, the system instantly translates voice input and outputs it as voice in the specified language. This uses a translation API (such as the Google Translate API). This system enables users to converse smoothly with people who speak different languages. 【0094】 For example, if a user asks, "Tell me more about next week's meeting," the system will analyze the data as text and the server will provide the necessary details. Another example of a prompt to the generative AI model is, "Convert the audio data to text and automatically update the schedule for the next three days." 【0095】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0096】 Step 1: 【0097】 The server collects audio and text data from the user's environment. When a user joins a meeting, their audio data is sent to the server in real time. The collected audio data is stored in a digital format. The input is audio data, and the output is stored digital audio data. The server stores data in a database to maintain readiness for speech recognition. 【0098】 Step 2: 【0099】 The terminal receives audio data transferred from the server and converts it into text data using speech recognition technology. This process uses a noise reduction filter to remove noise from the audio. The input is audio data, and the output is text data. Speech recognition software analyzes the audio waveform, converts the result into text, and returns it to the server. 【0100】 Step 3: 【0101】 The server analyzes text data provided by the terminal using natural language processing technology. It extracts event and task information from the text data. The input is text data, and the output is the extracted event and task information. The natural language processing engine understands the meaning of the text, identifies relevant information, and registers it in the database. 【0102】 Step 4: 【0103】 The terminal receives instructions from the server and automatically incorporates events and tasks into the user's schedule. The information is added to an electronic calendar and sorted according to priority settings. Input is extracted event and task information, and output is an updated schedule. Users can view changes in real time and make corrections as needed. 【0104】 Step 5: 【0105】 Users send requests via voice or text through their device if they need additional information. The server analyzes the user's request and gathers relevant information from multiple sources. The input is the user's request, and the output is a list of relevant information. The server uses web crawling technology to collect information and presents it to the device. 【0106】 Step 6: 【0107】 When a user requests multilingual communication, the device forwards the voice input to a translation system, translates it into the specified language, and outputs it as voice. The input is the user's voice data, and the output is the translated voice data. Automatic translation is performed via a translation API, enabling smooth conversation. 【0108】 (Application Example 1) 【0109】 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." 【0110】 In recent years, there has been a growing demand for efficient schedule management and information retrieval even while traveling. However, operating smartphones and other devices while on the move is not only burdensome for users, but also presents communication barriers, especially when using foreign languages. Therefore, there is a need to provide systems that allow users to efficiently obtain information in multiple languages ​​even while traveling. 【0111】 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. 【0112】 In this invention, the server includes data acquisition means for collecting voice data and text data, data analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and information provision means for providing schedule information and destination-related information to passengers of a moving vehicle via voice. This enables users to manage their schedules, obtain destination-related information in real time, and engage in smooth multilingual conversations even while on the move. 【0113】 A "data acquisition means for collecting voice and text data" is a device that collects voice and text information from passengers or terminals of a moving vehicle and transmits it to a server as basic data for analysis. 【0114】 "Data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks" refers to a technology that converts collected speech data into text and analyzes that text to automatically identify the user's schedule and important tasks. 【0115】 "A management system for prioritizing extracted events and tasks and managing schedules" refers to a process that evaluates the importance and deadlines of analyzed events and tasks, and then efficiently manages the user's schedule based on that evaluation. 【0116】 A "notification system that provides notifications and alerts to users" is a system that informs users in real time about the progress and updates of their schedules and tasks. 【0117】 A "translation method that supports multilingual dialogue through translation processing" is a technology that automatically translates speech or text into another language and delivers it to the user in order to support communication in a foreign language. 【0118】 "Information provision means for providing schedule information and destination-related information via voice to passengers in mobile vehicles" refers to a system that provides passengers in automobiles or other mobile vehicles with information about their next schedule and destination in real time via voice. 【0119】 The system implementing this invention is designed for operation within autonomous vehicles. Passengers can access the system via smartphones or terminals installed in the vehicle. The server is equipped with various software for data collection, speech recognition, natural language processing, information retrieval, and multilingual translation. Specifically, the server uses Google Cloud's speech recognition engine, natural language processing API, and translation API to perform data processing and calculations. 【0120】 Users interact with the system through voice input. When a passenger asks, "What's my next appointment?", the voice is collected by a data acquisition system and converted to text by speech recognition technology on a server. The text is then analyzed using natural language processing to extract relevant events and tasks, which are then notified to the terminal. Subsequently, a management system manages the schedule information and provides the results to the passenger via voice. 【0121】 Similarly, if a passenger requests information in a foreign language, the voice is translated on the server, and the translated information is provided in real time as needed. For example, if a passenger asks, "Where is the nearest gas station?", the terminal translates the voice from English into the specified language and provides, "The nearest gas station is 500 meters away." 【0122】 This system enhances passenger convenience by utilizing generative AI models to provide information in real time. Furthermore, users can easily obtain information using prompts. For example, by entering "Tell me the weather for the next three hours" as a prompt, the information can be obtained instantly. 【0123】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0124】 Step 1: 【0125】 The user provides voice input to a smartphone or in-car device. This voice input is collected in real time by a data acquisition system. The input data is saved as an audio file and sent to a server. 【0126】 Step 2: 【0127】 The server sends the received audio file to the speech recognition engine, where it converts the audio data into text data. This conversion provides the content of the audio in text format. This text serves as the basis for subsequent analysis. 【0128】 Step 3: 【0129】 The server analyzes text data using a natural language processing API to extract events and tasks from the text. This data analysis clearly understands user requests and demands. As a result of the analysis, information such as the next scheduled event or destination can be obtained. 【0130】 Step 4: 【0131】 The device uses a management system to manage the schedule, adding the analyzed information to the user's schedule. Newly added events and tasks are prioritized and notified to the user in real time. This notification is displayed on the device in both audio and text format. 【0132】 Step 5: 【0133】 When a user makes a request in a foreign language, the server uses translation tools to translate the text into the specified language. The translated text data is then converted into speech by a speech synthesis engine. This allows the user to receive the translation result in audio format. 【0134】 Step 6: 【0135】 The terminal provides users with translated information and schedule management information via voice output. This output allows users to check their schedules, obtain information about their destination, and communicate smoothly in foreign languages ​​while inside an autonomous vehicle. 【0136】 In this way, the series of processes are performed based on a generative AI model and are designed to directly respond to user requests through prompt messages. 【0137】 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. 【0138】 This invention integrates an emotion engine into an AI system that supports users' daily activities, recognizing user emotions and adjusting responses in real time. The system interacts with the server, terminal, and user interface, making the user experience more personalized and interactive. 【0139】 The server collects and periodically monitors voice and text data from users. The terminal uses speech recognition to convert voice data into text and sends it to the server. The server uses natural language processing technology to analyze the text data and automatically extract events and tasks. The information obtained from this analysis is used for the user's schedule and task management, and the server prioritizes these tasks before notifying the terminal. 【0140】 Furthermore, this system includes an emotion engine to detect user emotions. Audio and video data from the device are sent to the server, and the emotion engine analyzes the data to recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems, dynamically adjusting content and alerts according to the user's emotional state. 【0141】 For example, if the emotion engine detects that a user is stressed, the server will temporarily hide low-priority tasks and suppress less important notifications. On the other hand, if the user is relaxed, it can provide additional information. 【0142】 When a user needs information, they can request it via voice or text on their device. The server searches for relevant information and selects what to display, taking into account the user's emotional state. For example, if the emotion engine determines that the user is feeling down, information containing kind words and encouragement will be prioritized. 【0143】 Furthermore, if the user shows interest in a conversation in a foreign language, the system translates the user's voice input in real time, and if the emotion engine determines that the user's emotions are positive, it promotes communication by praising the content of the conversation. Thus, the dynamic optimization of the user experience by the emotion engine is a key feature of this system. 【0144】 The following describes the processing flow. 【0145】 Step 1: 【0146】 The server periodically collects voice and text data from users. This data is temporarily stored in storage and prepared for analysis. 【0147】 Step 2: 【0148】 The device uses speech recognition technology to convert the collected speech data into text. The converted text data is then sent to the server. 【0149】 Step 3: 【0150】 The server uses natural language processing to analyze the received text data and identify events and tasks. This analysis includes keyword extraction and contextual understanding. 【0151】 Step 4: 【0152】 The server applies an algorithm to prioritize the analyzed events and tasks. This creates a schedule based on the importance and deadline of each task. 【0153】 Step 5: 【0154】 The device automatically integrates prioritized tasks into the user's scheduling application. The user can view these tasks through the device and edit them as needed. 【0155】 Step 6: 【0156】 On the device, an emotion engine analyzes the user's voice and video data to evaluate the user's emotional state in real time. 【0157】 Step 7: 【0158】 The server receives information from the emotion engine and generates a response tailored to the user's emotional state. This allows notifications and alerts to be dynamically adjusted. 【0159】 Step 8: 【0160】 When a user searches for information, they enter a request into their device via voice or text. This request is then sent to the server. 【0161】 Step 9: 【0162】 The server searches for relevant information from multiple sources. The retrieved information is optimized according to sentiment evaluation. 【0163】 Step 10: 【0164】 The device will display optimized information in the user interface, allowing users to view information tailored to their emotions. 【0165】 Step 11: 【0166】 When a user engages in a conversation in a foreign language, the device receives voice input. The device uses speech recognition to convert the input into text and sends it to the server. 【0167】 Step 12: 【0168】 The server receives the text, translates it using natural language processing and translation technology, and sends the translated result back to the terminal, adjusting the tone of the conversation to take into account emotional state. 【0169】 Step 13: 【0170】 The device converts the obtained translated text into speech using speech synthesis and provides it to the user. This allows the user to continue communicating smoothly with foreign language speakers. 【0171】 (Example 2) 【0172】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0173】 In today's information-saturated society, providing information and managing tasks in a way that aligns with individual user needs and emotional states is challenging. Furthermore, in multilingual communication, accurately interpreting user emotions in real time and adjusting responses accordingly is difficult. These challenges must be addressed to make the user experience more personalized and effective. 【0174】 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. 【0175】 In this invention, the server includes input means for collecting voice and text data, analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and emotion recognition means for detecting the user's emotional state and dynamically adjusting the response. This enables the provision of information and task management tailored to the user's individual needs, as well as real-time multilingual communication support. 【0176】 "Audio data" refers to information that has been recorded and stored in digital format. 【0177】 "Text data" refers to information expressed as a string of characters, and is an element that makes up documents, messages, and other similar materials. 【0178】 "Input means" refers to a device or function that collects voice or text data and provides it to the system. 【0179】 "Speech recognition" is a technology that analyzes speech data and converts it into text. 【0180】 Natural language processing is a technology that enables computers to understand, analyze, and generate human language. 【0181】 "Analysis means" refers to a function or device that analyzes acquired data to extract information or structure. 【0182】 An "event" refers to a phenomenon or action that occurs under specific conditions or circumstances. 【0183】 "Work" refers to a series of steps or processes performed to achieve a specific objective. 【0184】 "Organizational tools" refer to functions or devices that prioritize and efficiently manage extracted events or tasks. 【0185】 A "notification means" is a function or device used to transmit important information or notifications to a user. 【0186】 "Translation methods" are technologies that convert information between different languages, enabling multilingual communication. 【0187】 "Emotion recognition means" refers to a function or device that analyzes and judges the user's emotional state and reflects it in the system's response. 【0188】 This invention provides an advanced AI system that supports users' daily activities, integrating an emotion engine to recognize user emotions in real time and adjust responses accordingly. This system interacts through a server, terminal, and user interface, making the user experience personal and interactive. 【0189】 The server provides functionality for collecting voice and text data from users. Voice data is acquired using the microphone built into devices such as smartphones and personal computers. The device uses speech recognition software, for example, a common speech recognition API, to convert the voice data into text. The text data is then sent to the server. The server analyzes the text data using natural language processing techniques and automatically extracts events and tasks. The software used may include open-source natural language processing libraries. 【0190】 Furthermore, the device sends audio and video data to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems and used to dynamically adjust content according to the user's emotional state. For example, if the emotion engine determines that the user is stressed, the server will hide low-priority tasks and suppress notifications. When the user is relaxed, additional information can be provided. 【0191】 When a user needs information, they make a request to their device via voice or text. The server searches for relevant information and selects it while considering emotional information. If the server determines that the user is feeling down, it will provide information that includes an encouraging message. For example, consider a request from a user saying, "Tell me my schedule and the weather for this week." The server uses natural language processing to analyze this request and presents schedule and weather information. Another example is a prompt that reads, "Explain how the emotion engine detects the user's emotions and generates an appropriate response when a user requests, 'Tell me today's news.'" 【0192】 Through this system, users can gain a richer, more personalized experience and communicate smoothly even in multilingual conversations. 【0193】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0194】 Step 1: 【0195】 The user inputs instructions into the terminal by voice. The terminal acquires this voice data through the microphone and converts it into text information using speech recognition software. Specifically, it uses a speech recognition API to analyze the voice waveform and generate corresponding text data. At this stage, the voice data is analyzed as input, and text data is obtained as output. 【0196】 Step 2: 【0197】 The terminal sends text data generated by speech recognition to the server. The server receives this text data and analyzes it using natural language processing techniques. Specifically, it applies a natural language processing library to extract keywords and understand the user's intent. The input is text data, and the output is extracted event and task information. 【0198】 Step 3: 【0199】 The server prioritizes events and task information based on the extracted data. This includes automatic scheduling that takes into account the importance and deadlines of tasks. The server uses a prioritization algorithm to organize each task and sort them in order of importance to the user. The input is event and task information, and the output is prioritized scheduling information. 【0200】 Step 4: 【0201】 The device creates and displays notifications to the user based on prioritized schedule information received from the server. Specifically, it uses the device's display and speech synthesis function to communicate task reminders and alerts to the user. This is done via a notification engine, allowing the user to receive high-priority tasks preferentially. The input is prioritized schedule information, and the output is notifications to the user. 【0202】 Step 5: 【0203】 The device provides audio and visual data to the server, which then analyzes it using an emotion engine. The emotion engine identifies the user's emotional state from the input data and adjusts its response in real time as needed. Specifically, it uses emotion recognition technology to analyze voice tone and facial expressions to determine how the user is feeling. The input is audio and visual data, and the output is the recognized emotional state. 【0204】 Step 6: 【0205】 The server adjusts the content of the information, selects an appropriate response, and sends it to the terminal based on the user's emotional state. For example, if the user is feeling anxious, the server will add an encouraging message to the information. The input is the user's emotional state and related information, and the output is the adjusted information and response. 【0206】 Step 7: 【0207】 When a user requires multilingual support, the device forwards its voice input to a server, which translates it in real time. Furthermore, when the emotion engine detects a positive emotion, the server generates a message containing praise and sends it back to the device to encourage the user. The input is multilingual voice data, and the output is translated text and an emotion-based response. 【0208】 (Application Example 2) 【0209】 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". 【0210】 In recent years, home assistants utilizing artificial intelligence technology have become widespread. However, conventional systems struggle to respond flexibly while considering user emotions, resulting in insufficient provision of optimal information and operational adjustments in response to changes in the user's emotions. Therefore, there is a need for technologies that make the user experience more personal and interactive. 【0211】 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. 【0212】 In this invention, the server includes information acquisition means for acquiring voice data and text data; analysis means for analyzing data using speech recognition and natural language processing and extracting operations and tasks; emotion recognition means for analyzing video and audio data and recognizing emotional states; and optimization means for optimizing and dynamically adjusting notification content and information provision according to the emotional state. This enables real-time recognition of the user's emotions, provision of information and entertainment tailored to those emotions, and changes in task priorities. 【0213】 "Information acquisition means for acquiring voice data and text data" refers to a function for collecting voice and text information from users using voice input devices, keyboards, etc. 【0214】 "Analysis means for analyzing data using speech recognition and natural language processing to extract operations and tasks" refers to a means for identifying and executing user instructions and requests using technologies to convert speech information into text and understand its content. 【0215】 "An emotion recognition method that analyzes video and audio data to recognize emotional states" is a technology that analyzes the user's emotional expressions from video and audio collected using cameras and microphones, and identifies their emotional state at any given time. 【0216】 "Optimization means that optimizes and dynamically adjusts notification content and information provision according to emotional state" refers to a function that selects and adjusts the most appropriate information and notifications to match the user's current emotions and presents them accordingly. 【0217】 To realize this invention, first, an information acquisition means for acquiring voice data and text data is employed. The terminal is equipped with a voice input device and a camera, and the data collected from these devices is transmitted to the server. The server uses speech recognition and natural language processing technology to analyze the data and activates an analysis means to identify and extract instructions and requests from the user. 【0218】 Emotion recognition incorporates algorithms that process video and audio data, recognizing the user's emotional state by analyzing their facial expressions and tone of voice. For this purpose, DeepAffects and other emotion analysis frameworks can be utilized. Based on these emotion recognition results, the server executes optimization measures to optimize the notification content and information provided according to the emotional state. For example, if the system recognizes that the user is stressed, it will provide content that promotes relaxation. 【0219】 As a concrete example of this invention, when a user says "I'm tired today" to their device upon returning home, the server can detect the user's stress and suggest, "Would you like to play some relaxing music today?" In this way, it becomes possible to optimize the user experience based on emotions. 【0220】 Furthermore, since the information provided is generated by a generative AI model, a dynamic and diverse approach is possible. An example of a prompt sentence to give instructions to this model is, "Please advise what kind of content should be provided when the user is tired." This allows for the provision of optimal content tailored to the user's emotions. 【0221】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0222】 Step 1: 【0223】 The device acquires user voice and video data via its microphone and camera. When the user speaks into the device, voice data is input, and the camera simultaneously captures video data. This data is temporarily stored for later processing. 【0224】 Step 2: 【0225】 The device uses speech recognition technology to convert acquired audio data into text. It analyzes the audio data using APIs such as the Google Cloud Speech-to-Text API and generates text data. This text data is then sent to the server as input for analyzing the user's intent. 【0226】 Step 3: 【0227】 The server uses natural language processing technology to analyze the received text data. A generative AI model is used for the analysis, extracting operations and tasks from the user's utterances. From the input text data, the server clarifies the user's intent and identifies the actions that should be performed. 【0228】 Step 4: 【0229】 The device sends video and audio data to the server for emotion recognition. The server uses DeepAffects or a similar emotion analysis framework to evaluate the user's emotional state. The analysis output generates data indicating the user's current emotions, which is used in the next step. 【0230】 Step 5: 【0231】 Based on the results of emotion recognition, the server optimizes the information and alerts provided according to the user's emotional state. Using a generative AI model and prompt statements, it determines what content is best for the user. For example, it selects generated content using the prompt statement "Advise what kind of content should be provided when the user is tired." 【0232】 Step 6: 【0233】 The device presents optimized notifications and information received from the server to the user. Processed content is presented to the user visually or audibly, improving the user experience. This ensures that services are tailored to the user's emotions. 【0234】 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. 【0235】 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. 【0236】 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. 【0237】 [Second Embodiment] 【0238】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0239】 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. 【0240】 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). 【0241】 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. 【0242】 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. 【0243】 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). 【0244】 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. 【0245】 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. 【0246】 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. 【0247】 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. 【0248】 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. 【0249】 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". 【0250】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and communication in foreign languages, in order to improve the efficiency of users in their daily lives and business. 【0251】 This system functions through the interaction of the server, terminals, and users. The server collects and periodically monitors user emails and meeting audio data. This data is transferred to the terminals, where speech recognition technology is used to convert the audio data into text. The converted text is then analyzed on the server through natural language processing, and events and tasks are automatically extracted. 【0252】 On the device, tasks and events prioritized by the server are incorporated into the user's schedule. This schedule is updated in real time, and the user can check the progress of their schedule and tasks through the device and edit the content as needed. For example, when a user joins a meeting, important tasks and deadlines mentioned in that meeting are automatically recognized and added to the schedule. 【0253】 Furthermore, if a user needs information, they can send a request to their device via voice or text. The server processes this request and gathers relevant information from multiple sources. The device displays a list of information that has been evaluated for relevance and reliability, allowing the user to easily access the information they need. For example, in response to a request such as "Tell me about the latest market trends," relevant news and data will be displayed. 【0254】 Furthermore, to support communication with foreign language speakers, when voice input is received on the device, it is automatically translated into the specified language via a server. The translated result is output again as voice on the device, allowing users to converse smoothly with foreign language speakers. For example, Japanese input can be translated into English, supporting immediate understanding for the other party. 【0255】 This system combines speech recognition, natural language processing, data analysis, and translation technologies to solve many of the challenges users face and significantly improve their daily efficiency. 【0256】 The following describes the processing flow. 【0257】 Step 1: 【0258】 The server periodically collects user emails and meeting audio data. The collected data is temporarily stored and prepared for analysis. 【0259】 Step 2: 【0260】 The server sends the collected audio data to the terminal. The terminal uses speech recognition technology to convert the audio data into text data. The converted text is then sent back to the server. 【0261】 Step 3: 【0262】 The server receives text data and analyzes its content using natural language processing techniques. Through this analysis, tasks and events are extracted, and related information is organized. 【0263】 Step 4: 【0264】 The server prioritizes the extracted tasks and events. An algorithm is used to evaluate them based on importance and proximity of deadlines. 【0265】 Step 5: 【0266】 The server sends prioritized tasks to the device. The device automatically integrates these tasks into the user's calendar or task management application. 【0267】 Step 6: 【0268】 The device notifies the user of schedule updates. The user can check the schedule through the device and edit or delete task details as needed. 【0269】 Step 7: 【0270】 When a user searches for information, they send a request to their device via voice or text. 【0271】 Step 8: 【0272】 The server searches for relevant information from multiple sources based on the received request. It evaluates the relevance and reliability of the information and selects the most appropriate information. 【0273】 Step 9: 【0274】 The server sends optimized information to the terminal. The terminal displays the information on the user interface, making it easy for the user to access. 【0275】 Step 10: 【0276】 If a user wishes to converse in a foreign language, they input voice commands into the device. The device then uses voice recognition to convert the input into text and sends it to the server. 【0277】 Step 11: 【0278】 The server uses natural language processing and translation techniques to translate the input text into the specified language. The translation result is returned to the terminal. 【0279】 Step 12: 【0280】 The device converts the translated text into speech using speech synthesis technology and outputs it through the speaker. This allows users to have smooth conversations with foreign language speakers. 【0281】 (Example 1) 【0282】 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." 【0283】 Information overload has made it difficult for users to efficiently collect, organize, and utilize the information they need for their daily lives and businesses. Furthermore, the limited means of achieving smooth communication across multiple languages ​​is compromising user convenience. Therefore, there is a need to develop a system that effectively utilizes audio and text data to comprehensively support schedule management, information retrieval, and multilingual communication. 【0284】 The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0285】 In this invention, the server includes data acquisition means for collecting voice data and text data, data analysis means for converting voice data into text data using voice recognition technology, analyzing the data using natural language processing technology, and extracting events and tasks, and management means for setting priorities for the extracted events and tasks and performing electronic schedule management. Thereby, not only can the user efficiently collect and organize necessary information, but also can smoothly communicate among multiple languages. 【0286】 "Voice data" is data for recording and processing voices in digital format. 【0287】 "Text data" is data for expressing information composed of characters. 【0288】 "Data acquisition means" is a mechanism for collecting and recording specific information. 【0289】 "Voice recognition technology" is a technology for analyzing voice data and interpreting it as a character string. 【0290】 "Natural language processing technology" is a technology for enabling a computer to understand and process human language. 【0291】 "Data analysis means" is a means for analyzing the collected information and extracting useful information. 【0292】 "Event" refers to a specific planned event or activity. 【0293】 "Task" refers to a series of activities or tasks performed to achieve a certain purpose. 【0294】 A "management tool" is a system for efficiently organizing plans and tasks and controlling their execution. 【0295】 A "notification method" is a mechanism for informing users of information or warnings. 【0296】 "Translation methods" are technologies that convert information in order to convey meaning between different languages. 【0297】 "Information retrieval methods" refer to methods of searching databases or the internet to identify necessary information. 【0298】 "Information optimization methods" are means of evaluating acquired information and selecting the most important and necessary content. 【0299】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and multilingual communication, in order to improve the efficiency of users in their daily lives and businesses. 【0300】 The server periodically collects communication data from users, such as emails and meeting audio. This requires server equipment with high-performance processors, and the software utilizes database management systems and cloud infrastructure to efficiently process the data streams. In particular, speech recognition software (such as Google Cloud Speech-to-Text API) is used to transcribe audio data. 【0301】 The terminal converts audio received from the server into text data and sends it to a natural language processing engine to extract events and tasks. Text analysis solutions (such as SpaCy or NLTK) are used for natural language processing, and the server uses this to prioritize tasks and manage schedules automatically. 【0302】 Users can always keep track of the latest schedule and receive notifications through this system. Furthermore, when information is needed, users can send requests to the terminal in voice or text, and the server will process it and collect relevant information from the Internet or other digital information sources. With the Web crawling technology and information collection solutions used at this time, users can quickly access the information they need. 【0303】 Also, to assist in communication in foreign languages, voice input is immediately translated and voice output is performed in the specified language. For this, a translation API (such as the Google Translate API) is used. With this system, users can smoothly communicate with people who speak different languages. 【0304】 As a specific example, when a user asks "Tell me more about next week's meeting", the system analyzes the data as text and the server provides the necessary details. Also, as an example of a prompt sentence for a generative AI model, "Convert voice data to text and automatically update the schedule for the next three days." can be cited. 【0305】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0306】 Step 1: 【0307】 The server collects voice data and text data from the user's environment. When the user participates in a meeting, the voice data is sent to the server in real time. The collected voice data is stored in digital format. The input is voice data and the output is the stored digital voice data. The server accumulates data in the database to maintain a state where voice recognition is ready. 【0308】 Step 2: 【0309】 The terminal receives audio data transferred from the server and converts it into text data using speech recognition technology. This process uses a noise reduction filter to remove noise from the audio. The input is audio data, and the output is text data. Speech recognition software analyzes the audio waveform, converts the result into text, and returns it to the server. 【0310】 Step 3: 【0311】 The server analyzes text data provided by the terminal using natural language processing technology. It extracts event and task information from the text data. The input is text data, and the output is the extracted event and task information. The natural language processing engine understands the meaning of the text, identifies relevant information, and registers it in the database. 【0312】 Step 4: 【0313】 The terminal receives instructions from the server and automatically incorporates events and tasks into the user's schedule. The information is added to an electronic calendar and sorted according to priority settings. Input is extracted event and task information, and output is an updated schedule. Users can view changes in real time and make corrections as needed. 【0314】 Step 5: 【0315】 Users send requests via voice or text through their device if they need additional information. The server analyzes the user's request and gathers relevant information from multiple sources. The input is the user's request, and the output is a list of relevant information. The server uses web crawling technology to collect information and presents it to the device. 【0316】 Step 6: 【0317】 When a user requests multilingual communication, the device forwards the voice input to a translation system, translates it into the specified language, and outputs it as voice. The input is the user's voice data, and the output is the translated voice data. Automatic translation is performed via a translation API, enabling smooth conversation. 【0318】 (Application Example 1) 【0319】 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." 【0320】 In recent years, there has been a growing demand for efficient schedule management and information retrieval even while traveling. However, operating smartphones and other devices while on the move is not only burdensome for users, but also presents communication barriers, especially when using foreign languages. Therefore, there is a need to provide systems that allow users to efficiently obtain information in multiple languages ​​even while traveling. 【0321】 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. 【0322】 In this invention, the server includes data acquisition means for collecting voice data and text data, data analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and information provision means for providing schedule information and destination-related information to passengers of a moving vehicle via voice. This enables users to manage their schedules, obtain destination-related information in real time, and engage in smooth multilingual conversations even while on the move. 【0323】 A "data acquisition means for collecting voice and text data" is a device that collects voice and text information from passengers or terminals of a moving vehicle and transmits it to a server as basic data for analysis. 【0324】 "Data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks" refers to a technology that converts collected speech data into text and analyzes that text to automatically identify the user's schedule and important tasks. 【0325】 "A management system for prioritizing extracted events and tasks and managing schedules" refers to a process that evaluates the importance and deadlines of analyzed events and tasks, and then efficiently manages the user's schedule based on that evaluation. 【0326】 A "notification system that provides notifications and alerts to users" is a system that informs users in real time about the progress and updates of their schedules and tasks. 【0327】 A "translation method that supports multilingual dialogue through translation processing" is a technology that automatically translates speech or text into another language and delivers it to the user in order to support communication in a foreign language. 【0328】 "Information provision means for providing schedule information and destination-related information via voice to passengers in mobile vehicles" refers to a system that provides passengers in automobiles or other mobile vehicles with information about their next schedule and destination in real time via voice. 【0329】 The system implementing this invention is designed for operation within autonomous vehicles. Passengers can access the system via smartphones or terminals installed in the vehicle. The server is equipped with various software for data collection, speech recognition, natural language processing, information retrieval, and multilingual translation. Specifically, the server uses Google Cloud's speech recognition engine, natural language processing API, and translation API to perform data processing and calculations. 【0330】 Users interact with the system through voice input. When a passenger asks, "What's my next appointment?", the voice is collected by a data acquisition system and converted to text by speech recognition technology on a server. The text is then analyzed using natural language processing to extract relevant events and tasks, which are then notified to the terminal. Subsequently, a management system manages the schedule information and provides the results to the passenger via voice. 【0331】 Similarly, if a passenger requests information in a foreign language, the voice is translated on the server, and the translated information is provided in real time as needed. For example, if a passenger asks, "Where is the nearest gas station?", the terminal translates the voice from English into the specified language and provides, "The nearest gas station is 500 meters away." 【0332】 This system enhances passenger convenience by utilizing generative AI models to provide information in real time. Furthermore, users can easily obtain information using prompts. For example, by entering "Tell me the weather for the next three hours" as a prompt, the information can be obtained instantly. 【0333】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0334】 Step 1: 【0335】 The user provides voice input to a smartphone or in-car device. This voice input is collected in real time by a data acquisition system. The input data is saved as an audio file and sent to a server. 【0336】 Step 2: 【0337】 The server sends the received audio file to the speech recognition engine, where it converts the audio data into text data. This conversion provides the content of the audio in text format. This text serves as the basis for subsequent analysis. 【0338】 Step 3: 【0339】 The server analyzes text data using a natural language processing API to extract events and tasks from the text. This data analysis clearly understands user requests and demands. As a result of the analysis, information such as the next scheduled event or destination can be obtained. 【0340】 Step 4: 【0341】 The device uses a management system to manage the schedule, adding the analyzed information to the user's schedule. Newly added events and tasks are prioritized and notified to the user in real time. This notification is displayed on the device in both audio and text format. 【0342】 Step 5: 【0343】 When a user makes a request in a foreign language, the server uses translation tools to translate the text into the specified language. The translated text data is then converted into speech by a speech synthesis engine. This allows the user to receive the translation result in audio format. 【0344】 Step 6: 【0345】 The terminal provides users with translated information and schedule management information via voice output. This output allows users to check their schedules, obtain information about their destination, and communicate smoothly in foreign languages ​​while inside an autonomous vehicle. 【0346】 In this way, the series of processes are performed based on a generative AI model and are designed to directly respond to user requests through prompt messages. 【0347】 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. 【0348】 This invention integrates an emotion engine into an AI system that supports users' daily activities, recognizing user emotions and adjusting responses in real time. The system interacts with the server, terminal, and user interface, making the user experience more personalized and interactive. 【0349】 The server collects and periodically monitors voice and text data from users. The terminal uses speech recognition to convert voice data into text and sends it to the server. The server uses natural language processing technology to analyze the text data and automatically extract events and tasks. The information obtained from this analysis is used for the user's schedule and task management, and the server prioritizes these tasks before notifying the terminal. 【0350】 Furthermore, this system includes an emotion engine to detect user emotions. Audio and video data from the device are sent to the server, and the emotion engine analyzes the data to recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems, dynamically adjusting content and alerts according to the user's emotional state. 【0351】 For example, if the emotion engine detects that a user is stressed, the server will temporarily hide low-priority tasks and suppress less important notifications. On the other hand, if the user is relaxed, it can provide additional information. 【0352】 When a user needs information, they can request it via voice or text on their device. The server searches for relevant information and selects what to display, taking into account the user's emotional state. For example, if the emotion engine determines that the user is feeling down, information containing kind words and encouragement will be prioritized. 【0353】 Furthermore, if the user shows interest in a conversation in a foreign language, the system translates the user's voice input in real time, and if the emotion engine determines that the user's emotions are positive, it promotes communication by praising the content of the conversation. Thus, the dynamic optimization of the user experience by the emotion engine is a key feature of this system. 【0354】 The following describes the processing flow. 【0355】 Step 1: 【0356】 The server periodically collects voice and text data from users. This data is temporarily stored in storage and prepared for analysis. 【0357】 Step 2: 【0358】 The device uses speech recognition technology to convert the collected speech data into text. The converted text data is then sent to the server. 【0359】 Step 3: 【0360】 The server uses natural language processing to analyze the received text data and identify events and tasks. This analysis includes keyword extraction and contextual understanding. 【0361】 Step 4: 【0362】 The server applies an algorithm to prioritize the analyzed events and tasks. This creates a schedule based on the importance and deadline of each task. 【0363】 Step 5: 【0364】 The device automatically integrates prioritized tasks into the user's scheduling application. The user can view these tasks through the device and edit them as needed. 【0365】 Step 6: 【0366】 On the device, an emotion engine analyzes the user's voice and video data to evaluate the user's emotional state in real time. 【0367】 Step 7: 【0368】 The server receives information from the emotion engine and generates a response tailored to the user's emotional state. This allows notifications and alerts to be dynamically adjusted. 【0369】 Step 8: 【0370】 When a user searches for information, they enter a request into their device via voice or text. This request is then sent to the server. 【0371】 Step 9: 【0372】 The server searches for relevant information from multiple sources. The retrieved information is optimized according to sentiment evaluation. 【0373】 Step 10: 【0374】 The device will display optimized information in the user interface, allowing users to view information tailored to their emotions. 【0375】 Step 11: 【0376】 When a user engages in a conversation in a foreign language, the device receives voice input. The device uses speech recognition to convert the input into text and sends it to the server. 【0377】 Step 12: 【0378】 The server receives the text, translates it using natural language processing and translation technology, and sends the translated result back to the terminal, adjusting the tone of the conversation to take into account emotional state. 【0379】 Step 13: 【0380】 The device converts the obtained translated text into speech using speech synthesis and provides it to the user. This allows the user to continue communicating smoothly with foreign language speakers. 【0381】 (Example 2) 【0382】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0383】 In today's information-saturated society, providing information and managing tasks in a way that aligns with individual user needs and emotional states is challenging. Furthermore, in multilingual communication, accurately interpreting user emotions in real time and adjusting responses accordingly is difficult. These challenges must be addressed to make the user experience more personalized and effective. 【0384】 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. 【0385】 In this invention, the server includes input means for collecting voice and text data, analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and emotion recognition means for detecting the user's emotional state and dynamically adjusting the response. This enables the provision of information and task management tailored to the user's individual needs, as well as real-time multilingual communication support. 【0386】 "Audio data" refers to information that has been recorded and stored in digital format. 【0387】 "Text data" refers to information expressed as a string of characters, and is an element that makes up documents, messages, and other similar materials. 【0388】 "Input means" refers to a device or function that collects voice or text data and provides it to the system. 【0389】 "Speech recognition" is a technology that analyzes speech data and converts it into text. 【0390】 Natural language processing is a technology that enables computers to understand, analyze, and generate human language. 【0391】 "Analysis means" refers to a function or device that analyzes acquired data to extract information or structure. 【0392】 An "event" refers to a phenomenon or action that occurs under specific conditions or circumstances. 【0393】 "Work" refers to a series of steps or processes performed to achieve a specific objective. 【0394】 "Organizational tools" refer to functions or devices that prioritize and efficiently manage extracted events or tasks. 【0395】 A "notification means" is a function or device used to transmit important information or notifications to a user. 【0396】 "Translation methods" are technologies that convert information between different languages, enabling multilingual communication. 【0397】 "Emotion recognition means" refers to a function or device that analyzes and judges the user's emotional state and reflects it in the system's response. 【0398】 This invention provides an advanced AI system that supports users' daily activities, integrating an emotion engine to recognize user emotions in real time and adjust responses accordingly. This system interacts through a server, terminal, and user interface, making the user experience personal and interactive. 【0399】 The server provides functionality for collecting voice and text data from users. Voice data is acquired using the microphone built into devices such as smartphones and personal computers. The device uses speech recognition software, for example, a common speech recognition API, to convert the voice data into text. The text data is then sent to the server. The server analyzes the text data using natural language processing techniques and automatically extracts events and tasks. The software used may include open-source natural language processing libraries. 【0400】 Furthermore, the device sends audio and video data to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems and used to dynamically adjust content according to the user's emotional state. For example, if the emotion engine determines that the user is stressed, the server will hide low-priority tasks and suppress notifications. When the user is relaxed, additional information can be provided. 【0401】 When a user needs information, they make a request to their device via voice or text. The server searches for relevant information and selects it while considering emotional information. If the server determines that the user is feeling down, it will provide information that includes an encouraging message. For example, consider a request from a user saying, "Tell me my schedule and the weather for this week." The server uses natural language processing to analyze this request and presents schedule and weather information. Another example is a prompt that reads, "Explain how the emotion engine detects the user's emotions and generates an appropriate response when a user requests, 'Tell me today's news.'" 【0402】 Through this system, users can gain a richer, more personalized experience and communicate smoothly even in multilingual conversations. 【0403】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0404】 Step 1: 【0405】 The user inputs instructions into the terminal by voice. The terminal acquires this voice data through the microphone and converts it into text information using speech recognition software. Specifically, it uses a speech recognition API to analyze the voice waveform and generate corresponding text data. At this stage, the voice data is analyzed as input, and text data is obtained as output. 【0406】 Step 2: 【0407】 The terminal sends text data generated by speech recognition to the server. The server receives this text data and analyzes it using natural language processing techniques. Specifically, it applies a natural language processing library to extract keywords and understand the user's intent. The input is text data, and the output is extracted event and task information. 【0408】 Step 3: 【0409】 The server prioritizes events and task information based on the extracted data. This includes automatic scheduling that takes into account the importance and deadlines of tasks. The server uses a prioritization algorithm to organize each task and sort them in order of importance to the user. The input is event and task information, and the output is prioritized scheduling information. 【0410】 Step 4: 【0411】 The device creates and displays notifications to the user based on prioritized schedule information received from the server. Specifically, it uses the device's display and speech synthesis function to communicate task reminders and alerts to the user. This is done via a notification engine, allowing the user to receive high-priority tasks preferentially. The input is prioritized schedule information, and the output is notifications to the user. 【0412】 Step 5: 【0413】 The device provides audio and visual data to the server, which then analyzes it using an emotion engine. The emotion engine identifies the user's emotional state from the input data and adjusts its response in real time as needed. Specifically, it uses emotion recognition technology to analyze voice tone and facial expressions to determine how the user is feeling. The input is audio and visual data, and the output is the recognized emotional state. 【0414】 Step 6: 【0415】 The server adjusts the content of the information, selects an appropriate response, and sends it to the terminal based on the user's emotional state. For example, if the user is feeling anxious, the server will add an encouraging message to the information. The input is the user's emotional state and related information, and the output is the adjusted information and response. 【0416】 Step 7: 【0417】 When a user requires multilingual support, the device forwards its voice input to a server, which translates it in real time. Furthermore, when the emotion engine detects a positive emotion, the server generates a message containing praise and sends it back to the device to encourage the user. The input is multilingual voice data, and the output is translated text and an emotion-based response. 【0418】 (Application Example 2) 【0419】 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." 【0420】 In recent years, home assistants utilizing artificial intelligence technology have become widespread. However, conventional systems struggle to respond flexibly while considering user emotions, resulting in insufficient provision of optimal information and operational adjustments in response to changes in the user's emotions. Therefore, there is a need for technologies that make the user experience more personal and interactive. 【0421】 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. 【0422】 In this invention, the server includes information acquisition means for acquiring voice data and text data; analysis means for analyzing data using speech recognition and natural language processing and extracting operations and tasks; emotion recognition means for analyzing video and audio data and recognizing emotional states; and optimization means for optimizing and dynamically adjusting notification content and information provision according to the emotional state. This enables real-time recognition of the user's emotions, provision of information and entertainment tailored to those emotions, and changes in task priorities. 【0423】 "Information acquisition means for acquiring voice data and text data" refers to a function for collecting voice and text information from users using voice input devices, keyboards, etc. 【0424】 "Analysis means for analyzing data using speech recognition and natural language processing to extract operations and tasks" refers to a means for identifying and executing user instructions and requests using technologies to convert speech information into text and understand its content. 【0425】 "An emotion recognition method that analyzes video and audio data to recognize emotional states" is a technology that analyzes the user's emotional expressions from video and audio collected using cameras and microphones, and identifies their emotional state at any given time. 【0426】 "Optimization means that optimizes and dynamically adjusts notification content and information provision according to emotional state" refers to a function that selects and adjusts the most appropriate information and notifications to match the user's current emotions and presents them accordingly. 【0427】 To realize this invention, first, an information acquisition means for acquiring voice data and text data is employed. The terminal is equipped with a voice input device and a camera, and the data collected from these devices is transmitted to the server. The server uses speech recognition and natural language processing technology to analyze the data and activates an analysis means to identify and extract instructions and requests from the user. 【0428】 Emotion recognition incorporates algorithms that process video and audio data, recognizing the user's emotional state by analyzing their facial expressions and tone of voice. For this purpose, DeepAffects and other emotion analysis frameworks can be utilized. Based on these emotion recognition results, the server executes optimization measures to optimize the notification content and information provided according to the emotional state. For example, if the system recognizes that the user is stressed, it will provide content that promotes relaxation. 【0429】 As a concrete example of this invention, when a user says "I'm tired today" to their device upon returning home, the server can detect the user's stress and suggest, "Would you like to play some relaxing music today?" In this way, it becomes possible to optimize the user experience based on emotions. 【0430】 Furthermore, since the information provided is generated by a generative AI model, a dynamic and diverse approach is possible. An example of a prompt sentence to give instructions to this model is, "Please advise what kind of content should be provided when the user is tired." This allows for the provision of optimal content tailored to the user's emotions. 【0431】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0432】 Step 1: 【0433】 The device acquires user voice and video data via its microphone and camera. When the user speaks into the device, voice data is input, and the camera simultaneously captures video data. This data is temporarily stored for later processing. 【0434】 Step 2: 【0435】 The device uses speech recognition technology to convert acquired audio data into text. It analyzes the audio data using APIs such as the Google Cloud Speech-to-Text API and generates text data. This text data is then sent to the server as input for analyzing the user's intent. 【0436】 Step 3: 【0437】 The server uses natural language processing technology to analyze the received text data. A generative AI model is used for the analysis, extracting operations and tasks from the user's utterances. From the input text data, the server clarifies the user's intent and identifies the actions that should be performed. 【0438】 Step 4: 【0439】 The device sends video and audio data to the server for emotion recognition. The server uses DeepAffects or a similar emotion analysis framework to evaluate the user's emotional state. The analysis output generates data indicating the user's current emotions, which is used in the next step. 【0440】 Step 5: 【0441】 Based on the results of emotion recognition, the server optimizes the information and alerts provided according to the user's emotional state. Using a generative AI model and prompt statements, it determines what content is best for the user. For example, it selects generated content using the prompt statement "Advise what kind of content should be provided when the user is tired." 【0442】 Step 6: 【0443】 The device presents optimized notifications and information received from the server to the user. Processed content is presented to the user visually or audibly, improving the user experience. This ensures that services are tailored to the user's emotions. 【0444】 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. 【0445】 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. 【0446】 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. 【0447】 [Third Embodiment] 【0448】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0449】 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. 【0450】 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). 【0451】 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. 【0452】 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. 【0453】 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). 【0454】 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. 【0455】 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. 【0456】 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. 【0457】 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. 【0458】 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. 【0459】 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". 【0460】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and communication in foreign languages, in order to improve the efficiency of users in their daily lives and business. 【0461】 This system functions through the interaction of the server, terminals, and users. The server collects and periodically monitors user emails and meeting audio data. This data is transferred to the terminals, where speech recognition technology is used to convert the audio data into text. The converted text is then analyzed on the server through natural language processing, and events and tasks are automatically extracted. 【0462】 On the device, tasks and events prioritized by the server are incorporated into the user's schedule. This schedule is updated in real time, and the user can check the progress of their schedule and tasks through the device and edit the content as needed. For example, when a user joins a meeting, important tasks and deadlines mentioned in that meeting are automatically recognized and added to the schedule. 【0463】 Furthermore, if a user needs information, they can send a request to their device via voice or text. The server processes this request and gathers relevant information from multiple sources. The device displays a list of information that has been evaluated for relevance and reliability, allowing the user to easily access the information they need. For example, in response to a request such as "Tell me about the latest market trends," relevant news and data will be displayed. 【0464】 Furthermore, to support communication with foreign language speakers, when voice input is received on the device, it is automatically translated into the specified language via a server. The translated result is output again as voice on the device, allowing users to converse smoothly with foreign language speakers. For example, Japanese input can be translated into English, supporting immediate understanding for the other party. 【0465】 This system combines speech recognition, natural language processing, data analysis, and translation technologies to solve many of the challenges users face and significantly improve their daily efficiency. 【0466】 The following describes the processing flow. 【0467】 Step 1: 【0468】 The server periodically collects user emails and meeting audio data. The collected data is temporarily stored and prepared for analysis. 【0469】 Step 2: 【0470】 The server sends the collected audio data to the terminal. The terminal uses speech recognition technology to convert the audio data into text data. The converted text is then sent back to the server. 【0471】 Step 3: 【0472】 The server receives text data and analyzes its content using natural language processing techniques. Through this analysis, tasks and events are extracted, and related information is organized. 【0473】 Step 4: 【0474】 The server prioritizes the extracted tasks and events. An algorithm is used to evaluate them based on importance and proximity of deadlines. 【0475】 Step 5: 【0476】 The server sends prioritized tasks to the device. The device automatically integrates these tasks into the user's calendar or task management application. 【0477】 Step 6: 【0478】 The device notifies the user of schedule updates. The user can check the schedule through the device and edit or delete task details as needed. 【0479】 Step 7: 【0480】 When a user searches for information, they send a request to their device via voice or text. 【0481】 Step 8: 【0482】 The server searches for relevant information from multiple sources based on the received request. It evaluates the relevance and reliability of the information and selects the most appropriate information. 【0483】 Step 9: 【0484】 The server sends optimized information to the terminal. The terminal displays the information on the user interface, making it easy for the user to access. 【0485】 Step 10: 【0486】 If a user wishes to converse in a foreign language, they input voice commands into the device. The device then uses voice recognition to convert the input into text and sends it to the server. 【0487】 Step 11: 【0488】 The server uses natural language processing and translation techniques to translate the input text into the specified language. The translation result is returned to the terminal. 【0489】 Step 12: 【0490】 The device converts the translated text into speech using speech synthesis technology and outputs it through the speaker. This allows users to have smooth conversations with foreign language speakers. 【0491】 (Example 1) 【0492】 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." 【0493】 Information overload has made it difficult for users to efficiently collect, organize, and utilize the information they need for their daily lives and businesses. Furthermore, the limited means of achieving smooth communication across multiple languages ​​is compromising user convenience. Therefore, there is a need to develop a system that effectively utilizes audio and text data to comprehensively support schedule management, information retrieval, and multilingual communication. 【0494】 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. 【0495】 In this invention, the server includes data acquisition means for collecting voice data and text data; data analysis means for converting voice data into text data using speech recognition technology, analyzing the data using natural language processing technology, and extracting events and tasks; and management means for setting priorities for the extracted events and tasks and managing an electronic schedule. This enables users to efficiently collect and organize necessary information, as well as facilitate communication across multiple languages. 【0496】 "Audio data" refers to data used to record and process audio in a digital format. 【0497】 "Text data" refers to data that represents information composed of characters. 【0498】 A "data acquisition method" is a system for collecting and recording specific information. 【0499】 "Speech recognition technology" is a technology that analyzes speech data and interprets it as a string of characters. 【0500】 "Natural language processing technology" is a technology that enables computers to understand and process human language. 【0501】 "Data analysis methods" are means for analyzing collected information and extracting useful information. 【0502】 An "event" refers to a specific, planned occurrence or activity. 【0503】 "Work" refers to a series of activities or tasks performed to achieve a certain objective. 【0504】 A "management tool" is a system for efficiently organizing plans and tasks and controlling their execution. 【0505】 A "notification method" is a mechanism for informing users of information or warnings. 【0506】 "Translation methods" are technologies that convert information in order to convey meaning between different languages. 【0507】 "Information retrieval methods" refer to methods of searching databases or the internet to identify necessary information. 【0508】 "Information optimization methods" are means of evaluating acquired information and selecting the most important and necessary content. 【0509】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and multilingual communication, in order to improve the efficiency of users in their daily lives and businesses. 【0510】 The server periodically collects communication data from users, such as emails and meeting audio. This requires server equipment with high-performance processors, and the software utilizes database management systems and cloud infrastructure to efficiently process the data streams. In particular, speech recognition software (such as Google Cloud Speech-to-Text API) is used to transcribe audio data. 【0511】 The terminal converts audio received from the server into text data and sends it to a natural language processing engine to extract events and tasks. Text analysis solutions (such as SpaCy or NLTK) are used for natural language processing, and the server uses this to prioritize tasks and manage schedules automatically. 【0512】 Through this system, users can always stay informed of their latest schedules and receive notifications. Furthermore, if they need information, users can send requests via voice or text to their devices, and the server processes these requests to gather relevant information from the internet and other digital sources. The web crawling technologies and information gathering solutions used in this process allow users to quickly access the information they need. 【0513】 Furthermore, to support communication in foreign languages, the system instantly translates voice input and outputs it as voice in the specified language. This uses a translation API (such as the Google Translate API). This system enables users to converse smoothly with people who speak different languages. 【0514】 For example, if a user asks, "Tell me more about next week's meeting," the system will analyze the data as text and the server will provide the necessary details. Another example of a prompt to the generative AI model is, "Convert the audio data to text and automatically update the schedule for the next three days." 【0515】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0516】 Step 1: 【0517】 The server collects audio and text data from the user's environment. When a user joins a meeting, their audio data is sent to the server in real time. The collected audio data is stored in a digital format. The input is audio data, and the output is stored digital audio data. The server stores data in a database to maintain readiness for speech recognition. 【0518】 Step 2: 【0519】 The terminal receives audio data transferred from the server and converts it into text data using speech recognition technology. This process uses a noise reduction filter to remove noise from the audio. The input is audio data, and the output is text data. Speech recognition software analyzes the audio waveform, converts the result into text, and returns it to the server. 【0520】 Step 3: 【0521】 The server analyzes text data provided by the terminal using natural language processing technology. It extracts event and task information from the text data. The input is text data, and the output is the extracted event and task information. The natural language processing engine understands the meaning of the text, identifies relevant information, and registers it in the database. 【0522】 Step 4: 【0523】 The terminal receives instructions from the server and automatically incorporates events and tasks into the user's schedule. The information is added to an electronic calendar and sorted according to priority settings. Input is extracted event and task information, and output is an updated schedule. Users can view changes in real time and make corrections as needed. 【0524】 Step 5: 【0525】 Users send requests via voice or text through their device if they need additional information. The server analyzes the user's request and gathers relevant information from multiple sources. The input is the user's request, and the output is a list of relevant information. The server uses web crawling technology to collect information and presents it to the device. 【0526】 Step 6: 【0527】 When a user requests multilingual communication, the device forwards the voice input to a translation system, translates it into the specified language, and outputs it as voice. The input is the user's voice data, and the output is the translated voice data. Automatic translation is performed via a translation API, enabling smooth conversation. 【0528】 (Application Example 1) 【0529】 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." 【0530】 In recent years, there has been a growing demand for efficient schedule management and information retrieval even while traveling. However, operating smartphones and other devices while on the move is not only burdensome for users, but also presents communication barriers, especially when using foreign languages. Therefore, there is a need to provide systems that allow users to efficiently obtain information in multiple languages ​​even while traveling. 【0531】 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. 【0532】 In this invention, the server includes data acquisition means for collecting voice data and text data, data analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and information provision means for providing schedule information and destination-related information to passengers of a moving vehicle via voice. This enables users to manage their schedules, obtain destination-related information in real time, and engage in smooth multilingual conversations even while on the move. 【0533】 A "data acquisition means for collecting voice and text data" is a device that collects voice and text information from passengers or terminals of a moving vehicle and transmits it to a server as basic data for analysis. 【0534】 "Data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks" refers to a technology that converts collected speech data into text and analyzes that text to automatically identify the user's schedule and important tasks. 【0535】 "A management system for prioritizing extracted events and tasks and managing schedules" refers to a process that evaluates the importance and deadlines of analyzed events and tasks, and then efficiently manages the user's schedule based on that evaluation. 【0536】 A "notification system that provides notifications and alerts to users" is a system that informs users in real time about the progress and updates of their schedules and tasks. 【0537】 A "translation method that supports multilingual dialogue through translation processing" is a technology that automatically translates speech or text into another language and delivers it to the user in order to support communication in a foreign language. 【0538】 "Information provision means for providing schedule information and destination-related information via voice to passengers in mobile vehicles" refers to a system that provides passengers in automobiles or other mobile vehicles with information about their next schedule and destination in real time via voice. 【0539】 The system implementing this invention is designed for operation within autonomous vehicles. Passengers can access the system via smartphones or terminals installed in the vehicle. The server is equipped with various software for data collection, speech recognition, natural language processing, information retrieval, and multilingual translation. Specifically, the server uses Google Cloud's speech recognition engine, natural language processing API, and translation API to perform data processing and calculations. 【0540】 Users interact with the system through voice input. When a passenger asks, "What's my next appointment?", the voice is collected by a data acquisition system and converted to text by speech recognition technology on a server. The text is then analyzed using natural language processing to extract relevant events and tasks, which are then notified to the terminal. Subsequently, a management system manages the schedule information and provides the results to the passenger via voice. 【0541】 Similarly, if a passenger requests information in a foreign language, the voice is translated on the server, and the translated information is provided in real time as needed. For example, if a passenger asks, "Where is the nearest gas station?", the terminal translates the voice from English into the specified language and provides, "The nearest gas station is 500 meters away." 【0542】 This system enhances passenger convenience by utilizing generative AI models to provide information in real time. Furthermore, users can easily obtain information using prompts. For example, by entering "Tell me the weather for the next three hours" as a prompt, the information can be obtained instantly. 【0543】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0544】 Step 1: 【0545】 The user provides voice input to a smartphone or in-car device. This voice input is collected in real time by a data acquisition system. The input data is saved as an audio file and sent to a server. 【0546】 Step 2: 【0547】 The server sends the received audio file to the speech recognition engine, where it converts the audio data into text data. This conversion provides the content of the audio in text format. This text serves as the basis for subsequent analysis. 【0548】 Step 3: 【0549】 The server analyzes text data using a natural language processing API to extract events and tasks from the text. This data analysis clearly understands user requests and demands. As a result of the analysis, information such as the next scheduled event or destination can be obtained. 【0550】 Step 4: 【0551】 The device uses a management system to manage the schedule, adding the analyzed information to the user's schedule. Newly added events and tasks are prioritized and notified to the user in real time. This notification is displayed on the device in both audio and text format. 【0552】 Step 5: 【0553】 When a user makes a request in a foreign language, the server uses translation tools to translate the text into the specified language. The translated text data is then converted into speech by a speech synthesis engine. This allows the user to receive the translation result in audio format. 【0554】 Step 6: 【0555】 The terminal provides users with translated information and schedule management information via voice output. This output allows users to check their schedules, obtain information about their destination, and communicate smoothly in foreign languages ​​while inside an autonomous vehicle. 【0556】 In this way, the series of processes are performed based on a generative AI model and are designed to directly respond to user requests through prompt messages. 【0557】 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. 【0558】 This invention integrates an emotion engine into an AI system that supports users' daily activities, recognizing user emotions and adjusting responses in real time. The system interacts with the server, terminal, and user interface, making the user experience more personalized and interactive. 【0559】 The server collects and periodically monitors voice and text data from users. The terminal uses speech recognition to convert voice data into text and sends it to the server. The server uses natural language processing technology to analyze the text data and automatically extract events and tasks. The information obtained from this analysis is used for the user's schedule and task management, and the server prioritizes these tasks before notifying the terminal. 【0560】 Furthermore, this system includes an emotion engine to detect user emotions. Audio and video data from the device are sent to the server, and the emotion engine analyzes the data to recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems, dynamically adjusting content and alerts according to the user's emotional state. 【0561】 For example, if the emotion engine detects that a user is stressed, the server will temporarily hide low-priority tasks and suppress less important notifications. On the other hand, if the user is relaxed, it can provide additional information. 【0562】 When a user needs information, they can request it via voice or text on their device. The server searches for relevant information and selects what to display, taking into account the user's emotional state. For example, if the emotion engine determines that the user is feeling down, information containing kind words and encouragement will be prioritized. 【0563】 Furthermore, if the user shows interest in a conversation in a foreign language, the system translates the user's voice input in real time, and if the emotion engine determines that the user's emotions are positive, it promotes communication by praising the content of the conversation. Thus, the dynamic optimization of the user experience by the emotion engine is a key feature of this system. 【0564】 The following describes the processing flow. 【0565】 Step 1: 【0566】 The server periodically collects voice and text data from users. This data is temporarily stored in storage and prepared for analysis. 【0567】 Step 2: 【0568】 The device uses speech recognition technology to convert the collected speech data into text. The converted text data is then sent to the server. 【0569】 Step 3: 【0570】 The server uses natural language processing to analyze the received text data and identify events and tasks. This analysis includes keyword extraction and contextual understanding. 【0571】 Step 4: 【0572】 The server applies an algorithm to prioritize the analyzed events and tasks. This creates a schedule based on the importance and deadline of each task. 【0573】 Step 5: 【0574】 The device automatically integrates prioritized tasks into the user's scheduling application. The user can view these tasks through the device and edit them as needed. 【0575】 Step 6: 【0576】 On the device, an emotion engine analyzes the user's voice and video data to evaluate the user's emotional state in real time. 【0577】 Step 7: 【0578】 The server receives information from the emotion engine and generates a response tailored to the user's emotional state. This allows notifications and alerts to be dynamically adjusted. 【0579】 Step 8: 【0580】 When a user searches for information, they enter a request into their device via voice or text. This request is then sent to the server. 【0581】 Step 9: 【0582】 The server searches for relevant information from multiple sources. The retrieved information is optimized according to sentiment evaluation. 【0583】 Step 10: 【0584】 The device will display optimized information in the user interface, allowing users to view information tailored to their emotions. 【0585】 Step 11: 【0586】 When a user engages in a conversation in a foreign language, the device receives voice input. The device uses speech recognition to convert the input into text and sends it to the server. 【0587】 Step 12: 【0588】 The server receives the text, translates it using natural language processing and translation technology, and sends the translated result back to the terminal, adjusting the tone of the conversation to take into account emotional state. 【0589】 Step 13: 【0590】 The device converts the obtained translated text into speech using speech synthesis and provides it to the user. This allows the user to continue communicating smoothly with foreign language speakers. 【0591】 (Example 2) 【0592】 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." 【0593】 In today's information-saturated society, providing information and managing tasks in a way that aligns with individual user needs and emotional states is challenging. Furthermore, in multilingual communication, accurately interpreting user emotions in real time and adjusting responses accordingly is difficult. These challenges must be addressed to make the user experience more personalized and effective. 【0594】 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. 【0595】 In this invention, the server includes input means for collecting voice and text data, analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and emotion recognition means for detecting the user's emotional state and dynamically adjusting the response. This enables the provision of information and task management tailored to the user's individual needs, as well as real-time multilingual communication support. 【0596】 "Audio data" refers to information that has been recorded and stored in digital format. 【0597】 "Text data" refers to information expressed as a string of characters, and is an element that makes up documents, messages, and other similar materials. 【0598】 "Input means" refers to a device or function that collects voice or text data and provides it to the system. 【0599】 "Speech recognition" is a technology that analyzes speech data and converts it into text. 【0600】 Natural language processing is a technology that enables computers to understand, analyze, and generate human language. 【0601】 "Analysis means" refers to a function or device that analyzes acquired data to extract information or structure. 【0602】 An "event" refers to a phenomenon or action that occurs under specific conditions or circumstances. 【0603】 "Work" refers to a series of steps or processes performed to achieve a specific objective. 【0604】 "Organizational tools" refer to functions or devices that prioritize and efficiently manage extracted events or tasks. 【0605】 A "notification means" is a function or device used to transmit important information or notifications to a user. 【0606】 "Translation methods" are technologies that convert information between different languages, enabling multilingual communication. 【0607】 "Emotion recognition means" refers to a function or device that analyzes and judges the user's emotional state and reflects it in the system's response. 【0608】 This invention provides an advanced AI system that supports users' daily activities, integrating an emotion engine to recognize user emotions in real time and adjust responses accordingly. This system interacts through a server, terminal, and user interface, making the user experience personal and interactive. 【0609】 The server provides functionality for collecting voice and text data from users. Voice data is acquired using the microphone built into devices such as smartphones and personal computers. The device uses speech recognition software, for example, a common speech recognition API, to convert the voice data into text. The text data is then sent to the server. The server analyzes the text data using natural language processing techniques and automatically extracts events and tasks. The software used may include open-source natural language processing libraries. 【0610】 Furthermore, the device sends audio and video data to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems and used to dynamically adjust content according to the user's emotional state. For example, if the emotion engine determines that the user is stressed, the server will hide low-priority tasks and suppress notifications. When the user is relaxed, additional information can be provided. 【0611】 When a user needs information, they make a request to their device via voice or text. The server searches for relevant information and selects it while considering emotional information. If the server determines that the user is feeling down, it will provide information that includes an encouraging message. For example, consider a request from a user saying, "Tell me my schedule and the weather for this week." The server uses natural language processing to analyze this request and presents schedule and weather information. Another example is a prompt that reads, "Explain how the emotion engine detects the user's emotions and generates an appropriate response when a user requests, 'Tell me today's news.'" 【0612】 Through this system, users can gain a richer, more personalized experience and communicate smoothly even in multilingual conversations. 【0613】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0614】 Step 1: 【0615】 The user inputs instructions into the terminal by voice. The terminal acquires this voice data through the microphone and converts it into text information using speech recognition software. Specifically, it uses a speech recognition API to analyze the voice waveform and generate corresponding text data. At this stage, the voice data is analyzed as input, and text data is obtained as output. 【0616】 Step 2: 【0617】 The terminal sends text data generated by speech recognition to the server. The server receives this text data and analyzes it using natural language processing techniques. Specifically, it applies a natural language processing library to extract keywords and understand the user's intent. The input is text data, and the output is extracted event and task information. 【0618】 Step 3: 【0619】 The server prioritizes events and task information based on the extracted data. This includes automatic scheduling that takes into account the importance and deadlines of tasks. The server uses a prioritization algorithm to organize each task and sort them in order of importance to the user. The input is event and task information, and the output is prioritized scheduling information. 【0620】 Step 4: 【0621】 The device creates and displays notifications to the user based on prioritized schedule information received from the server. Specifically, it uses the device's display and speech synthesis function to communicate task reminders and alerts to the user. This is done via a notification engine, allowing the user to receive high-priority tasks preferentially. The input is prioritized schedule information, and the output is notifications to the user. 【0622】 Step 5: 【0623】 The device provides audio and visual data to the server, which then analyzes it using an emotion engine. The emotion engine identifies the user's emotional state from the input data and adjusts its response in real time as needed. Specifically, it uses emotion recognition technology to analyze voice tone and facial expressions to determine how the user is feeling. The input is audio and visual data, and the output is the recognized emotional state. 【0624】 Step 6: 【0625】 The server adjusts the content of the information, selects an appropriate response, and sends it to the terminal based on the user's emotional state. For example, if the user is feeling anxious, the server will add an encouraging message to the information. The input is the user's emotional state and related information, and the output is the adjusted information and response. 【0626】 Step 7: 【0627】 When a user requires multilingual support, the device forwards its voice input to a server, which translates it in real time. Furthermore, when the emotion engine detects a positive emotion, the server generates a message containing praise and sends it back to the device to encourage the user. The input is multilingual voice data, and the output is translated text and an emotion-based response. 【0628】 (Application Example 2) 【0629】 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." 【0630】 In recent years, home assistants utilizing artificial intelligence technology have become widespread. However, conventional systems struggle to respond flexibly while considering user emotions, resulting in insufficient provision of optimal information and operational adjustments in response to changes in the user's emotions. Therefore, there is a need for technologies that make the user experience more personal and interactive. 【0631】 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. 【0632】 In this invention, the server includes information acquisition means for acquiring voice data and text data; analysis means for analyzing data using speech recognition and natural language processing and extracting operations and tasks; emotion recognition means for analyzing video and audio data and recognizing emotional states; and optimization means for optimizing and dynamically adjusting notification content and information provision according to the emotional state. This enables real-time recognition of the user's emotions, provision of information and entertainment tailored to those emotions, and changes in task priorities. 【0633】 "Information acquisition means for acquiring voice data and text data" refers to a function for collecting voice and text information from users using voice input devices, keyboards, etc. 【0634】 "Analysis means for analyzing data using speech recognition and natural language processing to extract operations and tasks" refers to a means for identifying and executing user instructions and requests using technologies to convert speech information into text and understand its content. 【0635】 "An emotion recognition method that analyzes video and audio data to recognize emotional states" is a technology that analyzes the user's emotional expressions from video and audio collected using cameras and microphones, and identifies their emotional state at any given time. 【0636】 "Optimization means that optimizes and dynamically adjusts notification content and information provision according to emotional state" refers to a function that selects and adjusts the most appropriate information and notifications to match the user's current emotions and presents them accordingly. 【0637】 To realize this invention, first, an information acquisition means for acquiring voice data and text data is employed. The terminal is equipped with a voice input device and a camera, and the data collected from these devices is transmitted to the server. The server uses speech recognition and natural language processing technology to analyze the data and activates an analysis means to identify and extract instructions and requests from the user. 【0638】 Emotion recognition incorporates algorithms that process video and audio data, recognizing the user's emotional state by analyzing their facial expressions and tone of voice. For this purpose, DeepAffects and other emotion analysis frameworks can be utilized. Based on these emotion recognition results, the server executes optimization measures to optimize the notification content and information provided according to the emotional state. For example, if the system recognizes that the user is stressed, it will provide content that promotes relaxation. 【0639】 As a concrete example of this invention, when a user says "I'm tired today" to their device upon returning home, the server can detect the user's stress and suggest, "Would you like to play some relaxing music today?" In this way, it becomes possible to optimize the user experience based on emotions. 【0640】 Furthermore, since the information provided is generated by a generative AI model, a dynamic and diverse approach is possible. An example of a prompt sentence to give instructions to this model is, "Please advise what kind of content should be provided when the user is tired." This allows for the provision of optimal content tailored to the user's emotions. 【0641】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0642】 Step 1: 【0643】 The device acquires user voice and video data via its microphone and camera. When the user speaks into the device, voice data is input, and the camera simultaneously captures video data. This data is temporarily stored for later processing. 【0644】 Step 2: 【0645】 The device uses speech recognition technology to convert acquired audio data into text. It analyzes the audio data using APIs such as the Google Cloud Speech-to-Text API and generates text data. This text data is then sent to the server as input for analyzing the user's intent. 【0646】 Step 3: 【0647】 The server uses natural language processing technology to analyze the received text data. A generative AI model is used for the analysis, extracting operations and tasks from the user's utterances. From the input text data, the server clarifies the user's intent and identifies the actions that should be performed. 【0648】 Step 4: 【0649】 The device sends video and audio data to the server for emotion recognition. The server uses DeepAffects or a similar emotion analysis framework to evaluate the user's emotional state. The analysis output generates data indicating the user's current emotions, which is used in the next step. 【0650】 Step 5: 【0651】 Based on the results of emotion recognition, the server optimizes the information and alerts provided according to the user's emotional state. Using a generative AI model and prompt statements, it determines what content is best for the user. For example, it selects generated content using the prompt statement "Advise what kind of content should be provided when the user is tired." 【0652】 Step 6: 【0653】 The device presents optimized notifications and information received from the server to the user. Processed content is presented to the user visually or audibly, improving the user experience. This ensures that services are tailored to the user's emotions. 【0654】 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. 【0655】 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. 【0656】 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. 【0657】 [Fourth Embodiment] 【0658】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0659】 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. 【0660】 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). 【0661】 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. 【0662】 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. 【0663】 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). 【0664】 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. 【0665】 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. 【0666】 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. 【0667】 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. 【0668】 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. 【0669】 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. 【0670】 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". 【0671】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and communication in foreign languages, in order to improve the efficiency of users in their daily lives and business. 【0672】 This system functions through the interaction of the server, terminals, and users. The server collects and periodically monitors user emails and meeting audio data. This data is transferred to the terminals, where speech recognition technology is used to convert the audio data into text. The converted text is then analyzed on the server through natural language processing, and events and tasks are automatically extracted. 【0673】 On the device, tasks and events prioritized by the server are incorporated into the user's schedule. This schedule is updated in real time, and the user can check the progress of their schedule and tasks through the device and edit the content as needed. For example, when a user joins a meeting, important tasks and deadlines mentioned in that meeting are automatically recognized and added to the schedule. 【0674】 Furthermore, if a user needs information, they can send a request to their device via voice or text. The server processes this request and gathers relevant information from multiple sources. The device displays a list of information that has been evaluated for relevance and reliability, allowing the user to easily access the information they need. For example, in response to a request such as "Tell me about the latest market trends," relevant news and data will be displayed. 【0675】 Furthermore, to support communication with foreign language speakers, when voice input is received on the device, it is automatically translated into the specified language via a server. The translated result is output again as voice on the device, allowing users to converse smoothly with foreign language speakers. For example, Japanese input can be translated into English, supporting immediate understanding for the other party. 【0676】 This system combines speech recognition, natural language processing, data analysis, and translation technologies to solve many of the challenges users face and significantly improve their daily efficiency. 【0677】 The following describes the processing flow. 【0678】 Step 1: 【0679】 The server periodically collects user emails and meeting audio data. The collected data is temporarily stored and prepared for analysis. 【0680】 Step 2: 【0681】 The server sends the collected audio data to the terminal. The terminal uses speech recognition technology to convert the audio data into text data. The converted text is then sent back to the server. 【0682】 Step 3: 【0683】 The server receives text data and analyzes its content using natural language processing techniques. Through this analysis, tasks and events are extracted, and related information is organized. 【0684】 Step 4: 【0685】 The server prioritizes the extracted tasks and events. An algorithm is used to evaluate them based on importance and proximity of deadlines. 【0686】 Step 5: 【0687】 The server sends prioritized tasks to the device. The device automatically integrates these tasks into the user's calendar or task management application. 【0688】 Step 6: 【0689】 The device notifies the user of schedule updates. The user can check the schedule through the device and edit or delete task details as needed. 【0690】 Step 7: 【0691】 When a user searches for information, they send a request to their device via voice or text. 【0692】 Step 8: 【0693】 The server searches for relevant information from multiple sources based on the received request. It evaluates the relevance and reliability of the information and selects the most appropriate information. 【0694】 Step 9: 【0695】 The server sends optimized information to the terminal. The terminal displays the information on the user interface, making it easy for the user to access. 【0696】 Step 10: 【0697】 If a user wishes to converse in a foreign language, they input voice commands into the device. The device then uses voice recognition to convert the input into text and sends it to the server. 【0698】 Step 11: 【0699】 The server uses natural language processing and translation techniques to translate the input text into the specified language. The translation result is returned to the terminal. 【0700】 Step 12: 【0701】 The device converts the translated text into speech using speech synthesis technology and outputs it through the speaker. This allows users to have smooth conversations with foreign language speakers. 【0702】 (Example 1) 【0703】 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". 【0704】 Information overload has made it difficult for users to efficiently collect, organize, and utilize the information they need for their daily lives and businesses. Furthermore, the limited means of achieving smooth communication across multiple languages ​​is compromising user convenience. Therefore, there is a need to develop a system that effectively utilizes audio and text data to comprehensively support schedule management, information retrieval, and multilingual communication. 【0705】 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. 【0706】 In this invention, the server includes data acquisition means for collecting voice data and text data; data analysis means for converting voice data into text data using speech recognition technology, analyzing the data using natural language processing technology, and extracting events and tasks; and management means for setting priorities for the extracted events and tasks and managing an electronic schedule. This enables users to efficiently collect and organize necessary information, as well as facilitate communication across multiple languages. 【0707】 "Audio data" refers to data used to record and process audio in a digital format. 【0708】 "Text data" refers to data that represents information composed of characters. 【0709】 A "data acquisition method" is a system for collecting and recording specific information. 【0710】 "Speech recognition technology" is a technology that analyzes speech data and interprets it as a string of characters. 【0711】 "Natural language processing technology" is a technology that enables computers to understand and process human language. 【0712】 "Data analysis methods" are means for analyzing collected information and extracting useful information. 【0713】 An "event" refers to a specific, planned occurrence or activity. 【0714】 "Work" refers to a series of activities or tasks performed to achieve a certain objective. 【0715】 A "management tool" is a system for efficiently organizing plans and tasks and controlling their execution. 【0716】 A "notification method" is a mechanism for informing users of information or warnings. 【0717】 "Translation methods" are technologies that convert information in order to convey meaning between different languages. 【0718】 "Information retrieval methods" refer to methods of searching databases or the internet to identify necessary information. 【0719】 "Information optimization methods" are means of evaluating acquired information and selecting the most important and necessary content. 【0720】 This invention is a system that utilizes voice and text data to support schedule management, information retrieval, and multilingual communication, in order to improve the efficiency of users in their daily lives and businesses. 【0721】 The server periodically collects communication data from users, such as emails and meeting audio. This requires server equipment with high-performance processors, and the software utilizes database management systems and cloud infrastructure to efficiently process the data streams. In particular, speech recognition software (such as Google Cloud Speech-to-Text API) is used to transcribe audio data. 【0722】 The terminal converts audio received from the server into text data and sends it to a natural language processing engine to extract events and tasks. Text analysis solutions (such as SpaCy or NLTK) are used for natural language processing, and the server uses this to prioritize tasks and manage schedules automatically. 【0723】 Through this system, users can always stay informed of their latest schedules and receive notifications. Furthermore, if they need information, users can send requests via voice or text to their devices, and the server processes these requests to gather relevant information from the internet and other digital sources. The web crawling technologies and information gathering solutions used in this process allow users to quickly access the information they need. 【0724】 Furthermore, to support communication in foreign languages, the system instantly translates voice input and outputs it as voice in the specified language. This uses a translation API (such as the Google Translate API). This system enables users to converse smoothly with people who speak different languages. 【0725】 For example, if a user asks, "Tell me more about next week's meeting," the system will analyze the data as text and the server will provide the necessary details. Another example of a prompt to the generative AI model is, "Convert the audio data to text and automatically update the schedule for the next three days." 【0726】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0727】 Step 1: 【0728】 The server collects audio and text data from the user's environment. When a user joins a meeting, their audio data is sent to the server in real time. The collected audio data is stored in a digital format. The input is audio data, and the output is stored digital audio data. The server stores data in a database to maintain readiness for speech recognition. 【0729】 Step 2: 【0730】 The terminal receives audio data transferred from the server and converts it into text data using speech recognition technology. This process uses a noise reduction filter to remove noise from the audio. The input is audio data, and the output is text data. Speech recognition software analyzes the audio waveform, converts the result into text, and returns it to the server. 【0731】 Step 3: 【0732】 The server analyzes text data provided by the terminal using natural language processing technology. It extracts event and task information from the text data. The input is text data, and the output is the extracted event and task information. The natural language processing engine understands the meaning of the text, identifies relevant information, and registers it in the database. 【0733】 Step 4: 【0734】 The terminal receives instructions from the server and automatically incorporates events and tasks into the user's schedule. The information is added to an electronic calendar and sorted according to priority settings. Input is extracted event and task information, and output is an updated schedule. Users can view changes in real time and make corrections as needed. 【0735】 Step 5: 【0736】 Users send requests via voice or text through their device if they need additional information. The server analyzes the user's request and gathers relevant information from multiple sources. The input is the user's request, and the output is a list of relevant information. The server uses web crawling technology to collect information and presents it to the device. 【0737】 Step 6: 【0738】 When a user requests multilingual communication, the device forwards the voice input to a translation system, translates it into the specified language, and outputs it as voice. The input is the user's voice data, and the output is the translated voice data. Automatic translation is performed via a translation API, enabling smooth conversation. 【0739】 (Application Example 1) 【0740】 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". 【0741】 In recent years, there has been a growing demand for efficient schedule management and information retrieval even while traveling. However, operating smartphones and other devices while on the move is not only burdensome for users, but also presents communication barriers, especially when using foreign languages. Therefore, there is a need to provide systems that allow users to efficiently obtain information in multiple languages ​​even while traveling. 【0742】 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. 【0743】 In this invention, the server includes data acquisition means for collecting voice data and text data, data analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and information provision means for providing schedule information and destination-related information to passengers of a moving vehicle via voice. This enables users to manage their schedules, obtain destination-related information in real time, and engage in smooth multilingual conversations even while on the move. 【0744】 A "data acquisition means for collecting voice and text data" is a device that collects voice and text information from passengers or terminals of a moving vehicle and transmits it to a server as basic data for analysis. 【0745】 "Data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks" refers to a technology that converts collected speech data into text and analyzes that text to automatically identify the user's schedule and important tasks. 【0746】 "A management system for prioritizing extracted events and tasks and managing schedules" refers to a process that evaluates the importance and deadlines of analyzed events and tasks, and then efficiently manages the user's schedule based on that evaluation. 【0747】 A "notification system that provides notifications and alerts to users" is a system that informs users in real time about the progress and updates of their schedules and tasks. 【0748】 A "translation method that supports multilingual dialogue through translation processing" is a technology that automatically translates speech or text into another language and delivers it to the user in order to support communication in a foreign language. 【0749】 "Information provision means for providing schedule information and destination-related information via voice to passengers in mobile vehicles" refers to a system that provides passengers in automobiles or other mobile vehicles with information about their next schedule and destination in real time via voice. 【0750】 The system implementing this invention is designed for operation within autonomous vehicles. Passengers can access the system via smartphones or terminals installed in the vehicle. The server is equipped with various software for data collection, speech recognition, natural language processing, information retrieval, and multilingual translation. Specifically, the server uses Google Cloud's speech recognition engine, natural language processing API, and translation API to perform data processing and calculations. 【0751】 Users interact with the system through voice input. When a passenger asks, "What's my next appointment?", the voice is collected by a data acquisition system and converted to text by speech recognition technology on a server. The text is then analyzed using natural language processing to extract relevant events and tasks, which are then notified to the terminal. Subsequently, a management system manages the schedule information and provides the results to the passenger via voice. 【0752】 Similarly, if a passenger requests information in a foreign language, the voice is translated on the server, and the translated information is provided in real time as needed. For example, if a passenger asks, "Where is the nearest gas station?", the terminal translates the voice from English into the specified language and provides, "The nearest gas station is 500 meters away." 【0753】 This system enhances passenger convenience by utilizing generative AI models to provide information in real time. Furthermore, users can easily obtain information using prompts. For example, by entering "Tell me the weather for the next three hours" as a prompt, the information can be obtained instantly. 【0754】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0755】 Step 1: 【0756】 The user provides voice input to a smartphone or in-car device. This voice input is collected in real time by a data acquisition system. The input data is saved as an audio file and sent to a server. 【0757】 Step 2: 【0758】 The server sends the received audio file to the speech recognition engine, where it converts the audio data into text data. This conversion provides the content of the audio in text format. This text serves as the basis for subsequent analysis. 【0759】 Step 3: 【0760】 The server analyzes text data using a natural language processing API to extract events and tasks from the text. This data analysis clearly understands user requests and demands. As a result of the analysis, information such as the next scheduled event or destination can be obtained. 【0761】 Step 4: 【0762】 The device uses a management system to manage the schedule, adding the analyzed information to the user's schedule. Newly added events and tasks are prioritized and notified to the user in real time. This notification is displayed on the device in both audio and text format. 【0763】 Step 5: 【0764】 When a user makes a request in a foreign language, the server uses translation tools to translate the text into the specified language. The translated text data is then converted into speech by a speech synthesis engine. This allows the user to receive the translation result in audio format. 【0765】 Step 6: 【0766】 The terminal provides users with translated information and schedule management information via voice output. This output allows users to check their schedules, obtain information about their destination, and communicate smoothly in foreign languages ​​while inside an autonomous vehicle. 【0767】 In this way, the series of processes are performed based on a generative AI model and are designed to directly respond to user requests through prompt messages. 【0768】 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. 【0769】 This invention integrates an emotion engine into an AI system that supports users' daily activities, recognizing user emotions and adjusting responses in real time. The system interacts with the server, terminal, and user interface, making the user experience more personalized and interactive. 【0770】 The server collects and periodically monitors voice and text data from users. The terminal uses speech recognition to convert voice data into text and sends it to the server. The server uses natural language processing technology to analyze the text data and automatically extract events and tasks. The information obtained from this analysis is used for the user's schedule and task management, and the server prioritizes these tasks before notifying the terminal. 【0771】 Furthermore, this system includes an emotion engine to detect user emotions. Audio and video data from the device are sent to the server, and the emotion engine analyzes the data to recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems, dynamically adjusting content and alerts according to the user's emotional state. 【0772】 For example, if the emotion engine detects that a user is stressed, the server will temporarily hide low-priority tasks and suppress less important notifications. On the other hand, if the user is relaxed, it can provide additional information. 【0773】 When a user needs information, they can request it via voice or text on their device. The server searches for relevant information and selects what to display, taking into account the user's emotional state. For example, if the emotion engine determines that the user is feeling down, information containing kind words and encouragement will be prioritized. 【0774】 Furthermore, if the user shows interest in a conversation in a foreign language, the system translates the user's voice input in real time, and if the emotion engine determines that the user's emotions are positive, it promotes communication by praising the content of the conversation. Thus, the dynamic optimization of the user experience by the emotion engine is a key feature of this system. 【0775】 The following describes the processing flow. 【0776】 Step 1: 【0777】 The server periodically collects voice and text data from users. This data is temporarily stored in storage and prepared for analysis. 【0778】 Step 2: 【0779】 The device uses speech recognition technology to convert the collected speech data into text. The converted text data is then sent to the server. 【0780】 Step 3: 【0781】 The server uses natural language processing to analyze the received text data and identify events and tasks. This analysis includes keyword extraction and contextual understanding. 【0782】 Step 4: 【0783】 The server applies an algorithm to prioritize the analyzed events and tasks. This creates a schedule based on the importance and deadline of each task. 【0784】 Step 5: 【0785】 The device automatically integrates prioritized tasks into the user's scheduling application. The user can view these tasks through the device and edit them as needed. 【0786】 Step 6: 【0787】 On the device, an emotion engine analyzes the user's voice and video data to evaluate the user's emotional state in real time. 【0788】 Step 7: 【0789】 The server receives information from the emotion engine and generates a response tailored to the user's emotional state. This allows notifications and alerts to be dynamically adjusted. 【0790】 Step 8: 【0791】 When a user searches for information, they enter a request into their device via voice or text. This request is then sent to the server. 【0792】 Step 9: 【0793】 The server searches for relevant information from multiple sources. The retrieved information is optimized according to sentiment evaluation. 【0794】 Step 10: 【0795】 The device will display optimized information in the user interface, allowing users to view information tailored to their emotions. 【0796】 Step 11: 【0797】 When a user engages in a conversation in a foreign language, the device receives voice input. The device uses speech recognition to convert the input into text and sends it to the server. 【0798】 Step 12: 【0799】 The server receives the text, translates it using natural language processing and translation technology, and sends the translated result back to the terminal, adjusting the tone of the conversation to take into account emotional state. 【0800】 Step 13: 【0801】 The device converts the obtained translated text into speech using speech synthesis and provides it to the user. This allows the user to continue communicating smoothly with foreign language speakers. 【0802】 (Example 2) 【0803】 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". 【0804】 In today's information-saturated society, providing information and managing tasks in a way that aligns with individual user needs and emotional states is challenging. Furthermore, in multilingual communication, accurately interpreting user emotions in real time and adjusting responses accordingly is difficult. These challenges must be addressed to make the user experience more personalized and effective. 【0805】 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. 【0806】 In this invention, the server includes input means for collecting voice and text data, analysis means for analyzing the data using speech recognition and natural language processing to extract events and tasks, and emotion recognition means for detecting the user's emotional state and dynamically adjusting the response. This enables the provision of information and task management tailored to the user's individual needs, as well as real-time multilingual communication support. 【0807】 "Audio data" refers to information that has been recorded and stored in digital format. 【0808】 "Text data" refers to information expressed as a string of characters, and is an element that makes up documents, messages, and other similar materials. 【0809】 "Input means" refers to a device or function that collects voice or text data and provides it to the system. 【0810】 "Speech recognition" is a technology that analyzes speech data and converts it into text. 【0811】 Natural language processing is a technology that enables computers to understand, analyze, and generate human language. 【0812】 "Analysis means" refers to a function or device that analyzes acquired data to extract information or structure. 【0813】 An "event" refers to a phenomenon or action that occurs under specific conditions or circumstances. 【0814】 "Work" refers to a series of steps or processes performed to achieve a specific objective. 【0815】 "Organizational tools" refer to functions or devices that prioritize and efficiently manage extracted events or tasks. 【0816】 A "notification means" is a function or device used to transmit important information or notifications to a user. 【0817】 "Translation methods" are technologies that convert information between different languages, enabling multilingual communication. 【0818】 "Emotion recognition means" refers to a function or device that analyzes and judges the user's emotional state and reflects it in the system's response. 【0819】 This invention provides an advanced AI system that supports users' daily activities, integrating an emotion engine to recognize user emotions in real time and adjust responses accordingly. This system interacts through a server, terminal, and user interface, making the user experience personal and interactive. 【0820】 The server provides functionality for collecting voice and text data from users. Voice data is acquired using the microphone built into devices such as smartphones and personal computers. The device uses speech recognition software, for example, a common speech recognition API, to convert the voice data into text. The text data is then sent to the server. The server analyzes the text data using natural language processing techniques and automatically extracts events and tasks. The software used may include open-source natural language processing libraries. 【0821】 Furthermore, the device sends audio and video data to the server. The server uses an emotion engine to analyze this data and recognize the user's emotional state. This emotional information is reflected in the schedule management and notification systems and used to dynamically adjust content according to the user's emotional state. For example, if the emotion engine determines that the user is stressed, the server will hide low-priority tasks and suppress notifications. When the user is relaxed, additional information can be provided. 【0822】 When a user needs information, they make a request to their device via voice or text. The server searches for relevant information and selects it while considering emotional information. If the server determines that the user is feeling down, it will provide information that includes an encouraging message. For example, consider a request from a user saying, "Tell me my schedule and the weather for this week." The server uses natural language processing to analyze this request and presents schedule and weather information. Another example is a prompt that reads, "Explain how the emotion engine detects the user's emotions and generates an appropriate response when a user requests, 'Tell me today's news.'" 【0823】 Through this system, users can gain a richer, more personalized experience and communicate smoothly even in multilingual conversations. 【0824】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0825】 Step 1: 【0826】 The user inputs instructions into the terminal by voice. The terminal acquires this voice data through the microphone and converts it into text information using speech recognition software. Specifically, it uses a speech recognition API to analyze the voice waveform and generate corresponding text data. At this stage, the voice data is analyzed as input, and text data is obtained as output. 【0827】 Step 2: 【0828】 The terminal sends text data generated by speech recognition to the server. The server receives this text data and analyzes it using natural language processing techniques. Specifically, it applies a natural language processing library to extract keywords and understand the user's intent. The input is text data, and the output is extracted event and task information. 【0829】 Step 3: 【0830】 The server prioritizes events and task information based on the extracted data. This includes automatic scheduling that takes into account the importance and deadlines of tasks. The server uses a prioritization algorithm to organize each task and sort them in order of importance to the user. The input is event and task information, and the output is prioritized scheduling information. 【0831】 Step 4: 【0832】 The device creates and displays notifications to the user based on prioritized schedule information received from the server. Specifically, it uses the device's display and speech synthesis function to communicate task reminders and alerts to the user. This is done via a notification engine, allowing the user to receive high-priority tasks preferentially. The input is prioritized schedule information, and the output is notifications to the user. 【0833】 Step 5: 【0834】 The device provides audio and visual data to the server, which then analyzes it using an emotion engine. The emotion engine identifies the user's emotional state from the input data and adjusts its response in real time as needed. Specifically, it uses emotion recognition technology to analyze voice tone and facial expressions to determine how the user is feeling. The input is audio and visual data, and the output is the recognized emotional state. 【0835】 Step 6: 【0836】 The server adjusts the content of the information, selects an appropriate response, and sends it to the terminal based on the user's emotional state. For example, if the user is feeling anxious, the server will add an encouraging message to the information. The input is the user's emotional state and related information, and the output is the adjusted information and response. 【0837】 Step 7: 【0838】 When a user requires multilingual support, the device forwards its voice input to a server, which translates it in real time. Furthermore, when the emotion engine detects a positive emotion, the server generates a message containing praise and sends it back to the device to encourage the user. The input is multilingual voice data, and the output is translated text and an emotion-based response. 【0839】 (Application Example 2) 【0840】 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". 【0841】 In recent years, home assistants utilizing artificial intelligence technology have become widespread. However, conventional systems struggle to respond flexibly while considering user emotions, resulting in insufficient provision of optimal information and operational adjustments in response to changes in the user's emotions. Therefore, there is a need for technologies that make the user experience more personal and interactive. 【0842】 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. 【0843】 In this invention, the server includes information acquisition means for acquiring voice data and text data; analysis means for analyzing data using speech recognition and natural language processing and extracting operations and tasks; emotion recognition means for analyzing video and audio data and recognizing emotional states; and optimization means for optimizing and dynamically adjusting notification content and information provision according to the emotional state. This enables real-time recognition of the user's emotions, provision of information and entertainment tailored to those emotions, and changes in task priorities. 【0844】 "Information acquisition means for acquiring voice data and text data" refers to a function for collecting voice and text information from users using voice input devices, keyboards, etc. 【0845】 "Analysis means for analyzing data using speech recognition and natural language processing to extract operations and tasks" refers to a means for identifying and executing user instructions and requests using technologies to convert speech information into text and understand its content. 【0846】 "An emotion recognition method that analyzes video and audio data to recognize emotional states" is a technology that analyzes the user's emotional expressions from video and audio collected using cameras and microphones, and identifies their emotional state at any given time. 【0847】 "Optimization means that optimizes and dynamically adjusts notification content and information provision according to emotional state" refers to a function that selects and adjusts the most appropriate information and notifications to match the user's current emotions and presents them accordingly. 【0848】 To realize this invention, first, an information acquisition means for acquiring voice data and text data is employed. The terminal is equipped with a voice input device and a camera, and the data collected from these devices is transmitted to the server. The server uses speech recognition and natural language processing technology to analyze the data and activates an analysis means to identify and extract instructions and requests from the user. 【0849】 Emotion recognition incorporates algorithms that process video and audio data, recognizing the user's emotional state by analyzing their facial expressions and tone of voice. For this purpose, DeepAffects and other emotion analysis frameworks can be utilized. Based on these emotion recognition results, the server executes optimization measures to optimize the notification content and information provided according to the emotional state. For example, if the system recognizes that the user is stressed, it will provide content that promotes relaxation. 【0850】 As a concrete example of this invention, when a user says "I'm tired today" to their device upon returning home, the server can detect the user's stress and suggest, "Would you like to play some relaxing music today?" In this way, it becomes possible to optimize the user experience based on emotions. 【0851】 Furthermore, since the information provided is generated by a generative AI model, a dynamic and diverse approach is possible. An example of a prompt sentence to give instructions to this model is, "Please advise what kind of content should be provided when the user is tired." This allows for the provision of optimal content tailored to the user's emotions. 【0852】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0853】 Step 1: 【0854】 The device acquires user voice and video data via its microphone and camera. When the user speaks into the device, voice data is input, and the camera simultaneously captures video data. This data is temporarily stored for later processing. 【0855】 Step 2: 【0856】 The device uses speech recognition technology to convert acquired audio data into text. It analyzes the audio data using APIs such as the Google Cloud Speech-to-Text API and generates text data. This text data is then sent to the server as input for analyzing the user's intent. 【0857】 Step 3: 【0858】 The server uses natural language processing technology to analyze the received text data. A generative AI model is used for the analysis, extracting operations and tasks from the user's utterances. From the input text data, the server clarifies the user's intent and identifies the actions that should be performed. 【0859】 Step 4: 【0860】 The device sends video and audio data to the server for emotion recognition. The server uses DeepAffects or a similar emotion analysis framework to evaluate the user's emotional state. The analysis output generates data indicating the user's current emotions, which is used in the next step. 【0861】 Step 5: 【0862】 Based on the results of emotion recognition, the server optimizes the information and alerts provided according to the user's emotional state. Using a generative AI model and prompt statements, it determines what content is best for the user. For example, it selects generated content using the prompt statement "Advise what kind of content should be provided when the user is tired." 【0863】 Step 6: 【0864】 The device presents optimized notifications and information received from the server to the user. Processed content is presented to the user visually or audibly, improving the user experience. This ensures that services are tailored to the user's emotions. 【0865】 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. 【0866】 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. 【0867】 In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0868】 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. 【0869】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0870】 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. 【0871】 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. 【0872】 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. 【0873】 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." 【0874】 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. 【0875】 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. 【0876】 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. 【0877】 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. 【0878】 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. 【0879】 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. 【0880】 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. 【0881】 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. 【0882】 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. 【0883】 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. 【0884】 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. 【0885】 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. 【0886】 The following is further disclosed regarding the embodiments described above. 【0887】 (Claim 1) 【0888】 A data acquisition method for collecting audio data and text data, 【0889】 A data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks, 【0890】 A management system for setting priorities for extracted events and tasks and managing their schedules, 【0891】 A notification means that provides notifications and alerts to users, 【0892】 Translation tools that support multilingual conversations through translation processing, 【0893】 A system that includes this. 【0894】 (Claim 2) 【0895】 The system according to claim 1, comprising a search means for receiving a voice request and searching for and obtaining relevant information from multiple sources. 【0896】 (Claim 3) 【0897】 The system according to claim 1, comprising information optimization means for evaluating the relevance and reliability of acquired information and presenting the most appropriate information to the user. 【0898】 "Example 1" 【0899】 (Claim 1) 【0900】 A data acquisition means for collecting audio data and text data, 【0901】 A data analysis means that converts speech data into text data using speech recognition technology, analyzes the data using natural language processing technology, and extracts events and tasks. 【0902】 A management system for setting priorities for extracted events and tasks and managing them electronically in a schedule, 【0903】 A notification means for providing notifications and alerts through the user's terminal device, 【0904】 Translation methods to support multilingual conversations using translation processing technology, 【0905】 A system that includes this. 【0906】 (Claim 2) 【0907】 The system according to claim 1, which is an information retrieval means for receiving a voice request and searching for and obtaining related information from multiple sources. 【0908】 (Claim 3) 【0909】 The system according to claim 1, which includes an information optimization means for evaluating the relevance and reliability of acquired information and for presenting the most suitable information to the user. 【0910】 "Application Example 1" 【0911】 (Claim 1) 【0912】 A data acquisition method for collecting audio data and text data, 【0913】 A data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks, 【0914】 A management system for setting priorities for extracted events and tasks and managing their schedules, 【0915】 A notification means that provides notifications and alerts to users, 【0916】 A translation tool that supports multilingual dialogue through translation processing, 【0917】 An information provision method that provides schedule information and destination-related information to passengers of mobile vehicles via voice, 【0918】 A system that includes this. 【0919】 (Claim 2) 【0920】 The system according to claim 1, comprising a search means for receiving a voice request and searching for and obtaining relevant information from multiple sources. 【0921】 (Claim 3) 【0922】 The system according to claim 1, comprising information optimization means for evaluating the relevance and reliability of acquired information and presenting the most appropriate information to the user. 【0923】 "Example 2 of combining an emotion engine" 【0924】 (Claim 1) 【0925】 An input means for collecting audio data and text data, 【0926】 An analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks, 【0927】 A means of organizing extracted events and tasks by setting priorities and managing schedules, 【0928】 A notification means that provides notifications and warnings to users, 【0929】 Translation tools that support multilingual conversations through translation processing, 【0930】 An emotion recognition means that detects the user's emotional state and dynamically adjusts the response, 【0931】 A system that includes this. 【0932】 (Claim 2) 【0933】 The system according to claim 1, which includes a search means for receiving a voice request and searching for and obtaining relevant information from multiple sources. 【0934】 (Claim 3) 【0935】 The system according to claim 1, which is an information selection means that evaluates the relevance and reliability of acquired information and presents the most suitable information to the user. 【0936】 "Application example 2 when combining with an emotional engine" 【0937】 (Claim 1) 【0938】 Information acquisition means for acquiring audio data and text data, 【0939】 An analysis means that analyzes data using speech recognition and natural language processing and extracts operations and tasks, 【0940】 A management system for prioritizing extracted operations and tasks and managing schedules, 【0941】 A notification means that provides notifications and warnings to users, 【0942】 Translation tools that support conversations in diverse languages ​​through the translation process, 【0943】 An emotion recognition means that analyzes video and audio data to recognize emotional states, 【0944】 An optimization method that dynamically adjusts and optimizes the content of notifications and information provided according to the emotional state, 【0945】 A system that includes this. 【0946】 (Claim 2) 【0947】 The system according to claim 1, which includes a search means for receiving a voice request and searching for and obtaining relevant information from multiple sources. 【0948】 (Claim 3) 【0949】 The information adaptation means according to claim 1, which evaluates the relevance and reliability of acquired information and provides optimal information to the user. [Explanation of Symbols] 【0950】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] A data acquisition method for collecting audio data and text data, A data analysis means that analyzes data using speech recognition and natural language processing to extract events and tasks, A management system for setting priorities for extracted events and tasks and managing their schedules, A notification means that provides notifications and alerts to users, Translation tools that support multilingual conversations through translation processing, A system that includes this. [Claim 2] The system according to claim 1, comprising a search means for receiving a voice request and searching for and obtaining relevant information from multiple sources. [Claim 3] The system according to claim 1, comprising information optimization means for evaluating the relevance and reliability of acquired information and presenting the most appropriate information to the user.

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