system

Abstract

We provide the system. [Solution] An input means for receiving voice input or keyword input, A conversion means that converts the data received from the input means into text data, An analysis means for analyzing the aforementioned text data and identifying related documents, A registration means for registering the identified document in a recording device, Based on the aforementioned document, a time calculation means for calculating work time, A display means for displaying the document name and the work time on an output device, A system that includes this.

Description

【Technical Field】 , , 【0005】 【0001】 The technology of this disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In modern operations, as the operation content becomes more complex, it has become difficult to smoothly select an appropriate operation manual. Especially for operators with little experience, it takes time to determine which manual to select, resulting in a decrease in work efficiency. Also, the calculation of working hours is often done manually, leading to inaccuracies in work planning. 【Means for Solving the Problems】 【0005】 To solve this problem, the present invention provides a system that automatically selects an appropriate work manual from voice input or keyword input. The system receives voice or keywords from the user using an input means and converts the input into text data using a conversion means. Furthermore, it analyzes the text data using an analysis means and identifies the relevant document from a document database. The identified document is registered in a recording device by a registration means, and the work time is calculated through a time calculation means. Finally, the document name and work time are presented to the user by a display means. Through this series of automated processes, the user can quickly and accurately obtain the appropriate manual, and the accuracy of work planning is also improved. 【0006】 "Voice input" is a method of transmitting information or instructions to a system using voice. 【0007】 "Keyword input" is a method of conveying information to a system using specific words or phrases. 【0008】 "Input means" refers to a device or interface that receives data such as voice or text. 【0009】 "Conversion means" refers to a part of a system that has the function of converting audio data into text data. 【0010】 The "analysis means" is a module that analyzes received text data and identifies related documents and information. 【0011】 "Relevant documents" refer to manuals or guides that are relevant to a specific task or context, based on the analyzed data. 【0012】 "Registration means" refers to a function for saving identified information or documents to a recording device. 【0013】 "Time calculation means" refers to a process or device for predicting or calculating the required work time. 【0014】 "Display means" refers to devices or interfaces used to visually present information to a user. [Brief explanation of the drawing] 【0015】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0016】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0017】 First, the terms used in the following description will be explained. 【0018】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0019】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0020】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0021】 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). 【0022】 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." 【0023】 [First Embodiment] 【0024】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0025】 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. 【0026】 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). 【0027】 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. 【0028】 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. 【0029】 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. 【0030】 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. 【0031】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0032】 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. 【0033】 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. 【0034】 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. 【0035】 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". 【0036】 This invention provides a system that automates the selection of work manuals and the calculation of work time, and a specific embodiment thereof is shown below. The system mainly consists of a user terminal and a server. 【0037】 First, the user inputs the task details into the device using voice or keywords. For example, consider a case where the user voice-inputs "Troubleshooting XYZ model." This voice input is converted into text data using the device's speech recognition engine, and the text is sent to the server. 【0038】 The server analyzes the received text data using natural language processing techniques and searches and identifies relevant documents from the database. In this example, the server can identify the appropriate manual, "XYZ Model Troubleshooting Guide." 【0039】 The identified manual is registered in a dedicated sheet by the server. Furthermore, the server calculates the standard work time required for the task based on that manual and records it in the sheet. This calculated work time is performed using an algorithm based on historical data and industry standards. 【0040】 Finally, the terminal uses the information received from the server to display the identified manual name and estimated work time to the user. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour" on the user's screen. This display prepares the user to begin work immediately. 【0041】 Thus, the system of the present invention enables users to quickly select the manual required for a specific task and predict the necessary work time. This will improve work efficiency and provide a stable work environment that does not depend on the worker's experience. 【0042】 The following describes the processing flow. 【0043】 Step 1: 【0044】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might voice command "XYZ model troubleshooting" or enter the keyword "XYZ model troubleshooting". 【0045】 Step 2: 【0046】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0047】 Step 3: 【0048】 The terminal sends the converted text data to the server. The input text is in a format that the server can process. 【0049】 Step 4: 【0050】 The server processes the received text data using a natural language processing engine to analyze relevant keywords and context. Based on this analysis, it identifies appropriate documents and information. 【0051】 Step 5: 【0052】 Based on the analysis results, the server searches the document database for the most relevant manual and identifies it. For example, it might identify the "XYZ Model Troubleshooting Guide." 【0053】 Step 6: 【0054】 The server registers the identified manual in a dedicated sheet. Furthermore, it retrieves the standard working time associated with that manual from the database and calculates the working time. 【0055】 Step 7: 【0056】 Based on information sent from the server, the terminal displays the identified manual name and estimated work time on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated work time: 1 hour". 【0057】 This series of steps allows users to efficiently obtain the necessary information and quickly begin working. 【0058】 (Example 1) 【0059】 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." 【0060】 In conventional work processes, it was necessary to manually select materials for the task and calculate the required time individually, which resulted in time-consuming and labor-intensive work and decreased efficiency. Furthermore, the process relied on the experience of individual workers, making it difficult to standardize the work. 【0061】 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. 【0062】 In this invention, the server includes receiving means for receiving voice or keywords, conversion means for converting the information received from the receiving means into text information, and processing means for processing the text information and identifying related information materials. This makes it possible for users to easily identify the desired materials and obtain a standardized time estimate. 【0063】 "Receiving means" refers to devices or technologies for receiving audio or keywords. 【0064】 "Conversion means" refers to devices or technologies for converting received audio or keywords into textual information. 【0065】 "Processing means" refers to technology for processing textual information and identifying related information materials from databases, etc. 【0066】 "Registration means" refers to a device or method for registering identified information materials into an appropriate recording medium. 【0067】 "Time calculation means" refers to a device or method for calculating the time required for a task based on registered information and data. 【0068】 "Presentation means" refers to the technology or function for displaying the calculated required time and the names of the information materials on the output device. 【0069】 The system based on this invention automatically identifies materials for a task using voice or keyword input and calculates the time required. The system mainly consists of a terminal used by the user and a server that processes related data. 【0070】 Users begin using the service by entering voice or keywords into the device. In the case of voice input, the device uses a speech recognition engine to convert the voice into text. In this process, a commonly available API (Application Programming Interface) is used for the speech recognition engine. A specific example is a cloud service such as Google® Cloud Speech-to-Text. 【0071】 The converted text information is sent to a server via the internet. The server analyzes the text information using natural language processing technology and identifies relevant information from a database. This analysis can utilize tools such as the Google Cloud Natural Language API. The server then registers the identified information in a storage medium such as a database or spreadsheet, and calculates the time required based on this information. Historical data and industry-standard algorithms are used for the calculation. 【0072】 For example, if a user enters "XYZ model troubleshooting" into the terminal, the server will identify the relevant troubleshooting guide and calculate that the standard working time is 1 hour. As a result, the terminal will display "XYZ model troubleshooting guide - estimated working time: 1 hour," and the user can proceed with the work based on this information. 【0073】 Furthermore, an example of a prompt message would be for the user to input, "What steps are required to troubleshoot an XYZ model?". This invention allows the user to work efficiently and perform tasks with a consistent quality that is not dependent on experience. 【0074】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0075】 Step 1: 【0076】 The user performs an action by inputting voice or keywords into the device. For example, the user inputs "Troubleshooting XYZ model". The input voice is captured within the device and treated as data in audio format. 【0077】 Step 2: 【0078】 The terminal converts voice input into text information. This uses a speech recognition engine, specifically a common API or service (e.g., a speech recognition API). Once the voice input is converted into a string, the converted text information is output. 【0079】 Step 3: 【0080】 The terminal sends the converted character information to the server. Possible transmission methods include HTTP requests. The character information reaches the server and is treated as input data. 【0081】 Step 4: 【0082】 The server analyzes the received text information using natural language processing technology. Through this analysis, it searches the database for relevant information. The input data is text information, and the output is the identification of relevant information. 【0083】 Step 5: 【0084】 The server registers the identified information data into a recording medium. Database management systems or spreadsheets are used for this registration. The server registers the information data and its corresponding data, generating the information data as input data and the registration results as output data. 【0085】 Step 6: 【0086】 The server calculates the time required for the task based on the identified information data. This uses algorithms based on historical data and industry standards. The algorithm processes the information data as input data and outputs the time required as output data. 【0087】 Step 7: 【0088】 The terminal receives the results from the server and presents the user with the name of the information document and the estimated time required. The terminal displays the received data in a GUI and presents the results as final output in the format of "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour". 【0089】 By combining data input and output flows in this way at each step, users can efficiently obtain the information and time necessary for their work. 【0090】 (Application Example 1) 【0091】 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." 【0092】 In many workplaces, workers are required to quickly find the appropriate procedure manuals and accurately estimate the time required for each task. However, the current manual process of searching for procedure manuals and estimating time is time-consuming and hinders work efficiency. There is a need to develop a system that solves this problem and rapidly supplies work procedures to machines. 【0093】 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. 【0094】 In this invention, the server includes receiving means for receiving voice input or keyword input, conversion means for converting the data received from the receiving means into text information, and analysis means for analyzing the text information and identifying relevant materials. This enables workers to quickly obtain appropriate procedure manuals based on voice instructions and to accurately estimate work time. 【0095】 "Receiving means" refers to a function for receiving voice input or keyword input and transmitting it to the system. 【0096】 A "conversion means" is a function that receives voice input or keyword input and converts it into text information. 【0097】 "Analysis means" refers to a function for identifying related materials based on the converted text information. 【0098】 A "registration method" is a function for saving identified data to a storage device. 【0099】 A "time estimation method" is a function that calculates the time required for a task based on registered data. 【0100】 "Display means" refers to a function that visually displays to the user the name of the identified material and the estimated time required for its creation. 【0101】 A "supply means" is a function that obtains specific procedures based on voice instructions and provides that information to the device. 【0102】 The system for carrying out this invention has the function of effectively processing voice input and keyword input, identifying relevant materials, and estimating work time. The system consists of a terminal device equipped with a microphone for receiving voice as hardware, and a server for performing advanced processing. 【0103】 First, the user inputs their task details using voice or keywords via a terminal device. This voice input is converted into text using Google's Speech-to-Text API. The server analyzes the converted text using Python's Natural Language Toolkit (NLTK) and identifies relevant data from a MySQL® database. Once the data is identified, the server registers it in storage and then performs a time estimate based on the data. This time estimate is calculated using an algorithm based on historical data. 【0104】 Regarding display, the server visually displays the identified document name and estimated work time on the user's terminal device display. This allows the user to quickly obtain the necessary procedure manuals and plan their work. 【0105】 As a concrete example, consider a system used in a factory. A robot might request an assembly guide for product X via voice, and the guide would be instantly displayed along with an estimated completion time of one hour. Such a system would allow workers to work more efficiently. It would also be possible to input a prompt such as, "Please tell me the steps to predict the troubleshooting time for a new product," into the generating AI model. 【0106】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0107】 Step 1: 【0108】 The terminal receives voice or keyword input through the microphone. The user speaks "Assembly guide for product X" to input voice. The input voice data is acquired as digital voice data by the terminal's input module. 【0109】 Step 2: 【0110】 The device uses Google's Speech-to-Text API to convert the received audio data into text. The audio data is sent to the cloud, and the converted data is received. This data will be the text "Assembly Guide for Product X". 【0111】 Step 3: 【0112】 The server receives text information and performs analysis using Python's Natural Language Toolkit (NLTK). Text analysis is performed to extract relevant keywords. In this case, "Product X" and "Assembly Guide" are identified as important keywords. 【0113】 Step 4: 【0114】 The server queries the MySQL database and searches for relevant documents based on the analyzed keywords. It retrieves document data corresponding to "Assembly Guide for Product X" from the database. 【0115】 Step 5: 【0116】 The server registers the acquired data into storage. The registration process ensures that the data is stored in a way that associates it with a specific user session. 【0117】 Step 6: 【0118】 The server calculates the work time based on the data. Using historical data and defined standard time data, it calculates an estimated time to complete the work, resulting in a time of "1 hour" as an example. 【0119】 Step 7: 【0120】 The server sends the estimated work time and identified document name to the user's terminal. The terminal interface displays "Product X Assembly Guide - Estimated Work Time: 1 hour" to the user. This information prepares the user to execute the work plan. 【0121】 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. 【0122】 This invention not only automates the selection of work manuals and the calculation of work time, but also provides a system for providing more appropriate responses based on the user's emotional state. This system mainly consists of a user terminal, a server, and an emotion engine. 【0123】 The user inputs their work details into the terminal using voice or keywords. If the input is voice, it is converted into text data by the terminal's speech recognition engine. The converted text data is sent to a server and analyzed using natural language processing technology. The server searches its database for and identifies relevant work manuals. Simultaneously, the terminal or server analyzes the user's emotions using an emotion engine. This analysis is derived from data such as the tone of voice and input, word choices, and facial recognition. 【0124】 Based on the user's emotional state detected by the emotion engine, the server can adjust how the work manual is presented. For example, if the user is stressed, the server will be configured to present a more concise and easy-to-understand explanation. It can also provide additional support information to help alleviate tension. Furthermore, the emotion analysis results influence the prediction of work time. If the server determines that the user is feeling fatigued, it may estimate a longer work time than usual. 【0125】 The server's final identified manual and estimated work time are sent to the terminal and presented to the user. For example, the user's screen might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotion-aware)." This allows the user to obtain information tailored to their emotional state, enabling them to work efficiently and with less stress. 【0126】 Thus, the system of the present invention allows users to receive intelligent support that goes beyond ordinary work assistance, which will result in improved work efficiency and worker satisfaction. 【0127】 The following describes the processing flow. 【0128】 Step 1: 【0129】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might give the voice command "Troubleshooting for XYZ models." 【0130】 Step 2: 【0131】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0132】 Step 3: 【0133】 The terminal sends the entered text data to the server. The information is sent in a format necessary for the server to begin processing. 【0134】 Step 4: 【0135】 The server analyzes the received text data using a natural language processing engine to identify relevant keywords and context. Based on the analysis results, it searches the database for and identifies the most relevant document. 【0136】 Step 5: 【0137】 The server uses an emotion engine to analyze the user's emotions. This analysis infers the emotional state from factors such as tone of voice, language choice, and the speed and intensity of the words used. 【0138】 Step 6: 【0139】 The server takes the sentiment analysis results into account and adjusts how relevant documents are presented. For example, if it determines that the user is experiencing stress, it adjusts the presentation of documents to be concise and easy to understand. 【0140】 Step 7: 【0141】 The server also adjusts its work time estimates based on emotion analysis. If the user is feeling fatigued or stressed, it calculates a more generous work time. 【0142】 Step 8: 【0143】 The server then sends the identified document name and adjusted work time to the terminal. 【0144】 Step 9: 【0145】 The terminal displays information received from the server on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotions considered)." This allows the user to receive support tailored to their emotional state, enabling more efficient work. 【0146】 (Example 2) 【0147】 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." 【0148】 Conventional systems had the problem of not being able to take into account the emotional state of the user when selecting work instructions and estimating work time, resulting in ineffective work support. Furthermore, they could not improve work efficiency in accordance with the user's stress level or fatigue level, potentially lowering worker satisfaction. 【0149】 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. 【0150】 In this invention, the server includes a receiving means for receiving voice input or keyword input, a conversion means for converting data from the receiving means into text format, and a discrimination means for analyzing the text format data and identifying related documents. This makes it possible to analyze the user's emotional state, adjust the method of presenting work instructions based on the analysis results, and accurately calculate work time. 【0151】 A "receiving means" is an element that has the function of accepting voice input or keyword input from the user. 【0152】 A "conversion means" is an element that has the function of converting received audio or keyword data into text format. 【0153】 A "discrimination means" is an element that analyzes converted text data and has the function of identifying related documents. 【0154】 A "recording means" is an element that has the function of registering a specific document in an information recording device. 【0155】 A "time calculation means" is an element that has the function of calculating work time based on a specified document. 【0156】 A "state analysis means" is an element that has the function of analyzing the user's emotional state. 【0157】 A "modification mechanism" is an element that has the function of adjusting the presentation method based on the analyzed emotional state. 【0158】 "Display means" refers to an element that has the function of displaying the name of the specified document and the calculated work time on a display device. 【0159】 To implement this invention, a user terminal, a server, and an emotion analysis engine are used. The user inputs the task details via voice or keywords through the terminal. In this case, the terminal uses a speech recognition engine to convert the voice into text format and sends the data to the server. A commonly known speech recognition API can be used as the speech recognition engine. 【0160】 The server analyzes the received text data using a generative AI model to identify relevant documents. This generative AI model may utilize, for example, a model employing natural language processing technology. Documents are searched within a database, and multiple documents may be identified as needed. 【0161】 Simultaneously, an emotion analysis engine is used to analyze the user's emotional state. For example, emotions are detected by voice tone, word selection in text, and, in some cases, by using the device's camera. Based on these analysis results, the server adjusts the format and content of the documents presented to the user. 【0162】 The server calculates the time required for a task, taking into account the results of an emotion analysis. For example, if it determines that the user is experiencing high levels of stress, the server will adjust the task time to be extended. This ensures that the user receives support best suited to their situation. Finally, this information is sent to the terminal and presented to the user. 【0163】 As a concrete example, consider a scenario where a user enters the prompt "Create agenda for the next meeting." The server identifies the relevant document and, through sentiment analysis, assesses that the user is feeling slightly fatigued. Therefore, the server sends a document to the terminal, along with a simpler agenda template, indicating a work time of "2 hours," and displays it as "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)." 【0164】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0165】 Step 1: 【0166】 The user inputs their task details into the terminal using voice or keywords. The input data, either voice or text, is sent to the terminal. The terminal receives this input and, in the case of voice input, uses a speech recognition engine to convert the voice into text data. The output is then generated as text data and sent to the server. 【0167】 Step 2: 【0168】 The server receives text data sent from the terminal. The input text data is analyzed by a generative AI model. The server extracts relevant keywords and uses those keywords to search the document database. The output is a list of relevant documents. 【0169】 Step 3: 【0170】 The server uses an emotion analysis engine to analyze the user's emotional state from their input voice or text tone, word selection, or facial recognition data. Input includes voice tone and text data. The analysis determines the user's emotional state, and the resulting output is emotion analysis data. 【0171】 Step 4: 【0172】 The server adjusts how relevant documents are presented based on the analyzed emotional state data. If the user is experiencing stress, the server selects more concise and easier-to-understand documents. The input includes emotional analysis data and a list of relevant documents, and the output is the adjusted documents. 【0173】 Step 5: 【0174】 The server calculates the work time, taking into account the results of the emotion analysis. If the analyzed emotional state indicates that the user is experiencing fatigue or stress, it estimates a longer work time than usual. The input includes the emotional state and related document data, and the output is the estimated work time. 【0175】 Step 6: 【0176】 The server sends the final document name, the adjusted document, and the estimated work time to the terminal. The user's terminal receives this data and displays it to the user. Specifically, the output might show information like "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)" on the screen. 【0177】 (Application Example 2) 【0178】 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". 【0179】 In modern industrial settings, problems frequently occur when workers operate robots, often leading to stress and fatigue during troubleshooting. Even in such situations, providing prompt and appropriate support to improve work efficiency is crucial. Furthermore, support that considers the emotional state of workers is necessary to enhance worker satisfaction. 【0180】 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. 【0181】 In this invention, the server includes a device for receiving voice input or keyword input, a conversion device for converting the information received from the device into text information, and an emotion analysis device for analyzing the user's emotional state. This makes it possible to provide prompt, emotionally sensitive, and appropriate support information even when the worker is experiencing stress or fatigue. 【0182】 "Voice input" refers to a format of information or instructions that a user can communicate to a system through their voice. 【0183】 "Keyword input" refers to a format in which users provide information to the system using a specific string of characters. 【0184】 "Device" refers to a hardware component used to perform a specific function. 【0185】 "Text information" refers to information that has been formalized as a string of characters and converted into a form that can be processed by a computer. 【0186】 A "conversion device" refers to a device used to convert data in one format to data in another format. 【0187】 An "analysis device" refers to a device used to analyze data and extract useful information from it. 【0188】 "Information" refers to the knowledge and data obtained from a specific database to meet the user's needs. 【0189】 A "storage device" refers to a device that has the function of holding data or information. 【0190】 A "registration device" refers to a device used to store specific data in a storage device or recording device. 【0191】 "Activity time" refers to the estimated time required for a particular task or operation. 【0192】 A "time estimation device" refers to a device used to predict the time required for a specific task. 【0193】 An "output device" refers to a device used to present data or information to a user. 【0194】 A "display device" refers to a device that presents information to a user visually. 【0195】 "Emotional state" refers to the state that expresses the user's psychological situation or mood. 【0196】 An "emotion analysis device" refers to a device that analyzes a user's emotional state and processes that information. 【0197】 A "regulating device" refers to a device used to change the output or operation of a system to conform to a certain standard. 【0198】 This invention provides a support system for work sites, and in particular, a system that realizes intelligent work support based on the emotional state of the user. This system mainly consists of a user terminal, a server, and an emotion analysis engine. 【0199】 When users encounter problems in factories or industrial settings, they use a terminal to input information via voice or keywords. The terminal uses a speech recognition engine to convert this input into text. The converted text information is sent to a server, which uses natural language processing techniques to analyze it and identify relevant documents from its database. 【0200】 Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. This emotion analysis engine determines emotions from factors such as voice tone, word choice, and input patterns. For example, if the user is experiencing stress, the system adjusts to provide a concise and easy-to-understand explanation. This adjustment is performed by an adjustment device. 【0201】 The server also estimates the activity time, taking into account the user's emotional state, along with the relevant manual, and sends it to the terminal. This allows the user to receive the manual best suited to their emotional state and perform their tasks with optimal efficiency. 【0202】 As a concrete example, consider a situation where a worker is having trouble removing a robot part during factory line work. The worker inputs "Tell me how to remove the part" into the terminal using voice commands, and the system presents a "part removal guide." Furthermore, if it senses the worker is stressed, it also provides additional messages such as, "It's okay even if this is your first time replacing a part; the procedure is simple." 【0203】 An example of a prompt message for a generating AI model is: "Please tell me how to provide a simple procedure and reassuring message to a worker who is under stress while replacing a robot part." 【0204】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0205】 Step 1: 【0206】 The terminal receives voice input or keyword input from the user. This input is converted into text information through a speech recognition engine. In this step, the input is the user's voice or keywords, and the output is text information. The speech recognition engine obtains the output by analyzing the waveform data of the input voice and converting it into a sequence of phonemes or words. 【0207】 Step 2: 【0208】 The server uses natural language processing techniques to analyze text information received from the terminal. This analysis searches the database for and identifies relevant documents. The input for this step is text information, and the output is the identifiers and links of the relevant documents. Natural language processing includes data processing such as morphological analysis and keyword extraction. 【0209】 Step 3: 【0210】 The server uses an emotion analysis engine to analyze the user's emotional state from text information. The input for this step is the user's text information, and the output is the determined emotional state (e.g., stress, fatigue, relief, etc.). Emotional features are extracted from the input's word choices and writing style, and these are used to determine the emotional state based on a statistical model. 【0211】 Step 4: 【0212】 The server adjusts the content and presentation method of the documents presented based on the analyzed emotional state, and sends this information to the terminal. The input for this step is the relevant documents and emotional state, and the output is the adjusted documents. Adjustments to the presentation method include simplifying the text and adding supplementary information. 【0213】 Step 5: 【0214】 The terminal presents the user with documents and activity times sent from the server. The input for this step is the adjusted document and activity time information, while the output is information that the user can visually confirm on the screen. The terminal assists in conveying information to the user through haptic feedback and voice guidance. 【0215】 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. 【0216】 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. 【0217】 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. 【0218】 [Second Embodiment] 【0219】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0220】 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. 【0221】 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). 【0222】 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. 【0223】 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. 【0224】 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). 【0225】 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. 【0226】 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. 【0227】 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. 【0228】 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. 【0229】 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. 【0230】 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". 【0231】 This invention provides a system that automates the selection of work manuals and the calculation of work time, and a specific embodiment thereof is shown below. The system mainly consists of a user terminal and a server. 【0232】 First, the user inputs the task details into the device using voice or keywords. For example, consider a case where the user voice-inputs "Troubleshooting XYZ model." This voice input is converted into text data using the device's speech recognition engine, and the text is sent to the server. 【0233】 The server analyzes the received text data using natural language processing techniques and searches and identifies relevant documents from the database. In this example, the server can identify the appropriate manual, "XYZ Model Troubleshooting Guide." 【0234】 The identified manual is registered in a dedicated sheet by the server. Furthermore, the server calculates the standard work time required for the task based on that manual and records it in the sheet. This calculated work time is performed using an algorithm based on historical data and industry standards. 【0235】 Finally, the terminal uses the information received from the server to display the identified manual name and estimated work time to the user. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour" on the user's screen. This display prepares the user to begin work immediately. 【0236】 Thus, the system of the present invention enables users to quickly select the manual required for a specific task and predict the necessary work time. This will improve work efficiency and provide a stable work environment that does not depend on the worker's experience. 【0237】 The following describes the processing flow. 【0238】 Step 1: 【0239】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might voice command "XYZ model troubleshooting" or enter the keyword "XYZ model troubleshooting". 【0240】 Step 2: 【0241】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0242】 Step 3: 【0243】 The terminal sends the converted text data to the server. The input text is in a format that the server can process. 【0244】 Step 4: 【0245】 The server processes the received text data using a natural language processing engine to analyze relevant keywords and context. Based on this analysis, it identifies appropriate documents and information. 【0246】 Step 5: 【0247】 Based on the analysis results, the server searches the document database for the most relevant manual and identifies it. For example, it might identify the "XYZ Model Troubleshooting Guide." 【0248】 Step 6: 【0249】 The server registers the identified manual in a dedicated sheet. Furthermore, it retrieves the standard working time associated with that manual from the database and calculates the working time. 【0250】 Step 7: 【0251】 Based on information sent from the server, the terminal displays the identified manual name and estimated work time on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated work time: 1 hour". 【0252】 This series of steps allows users to efficiently obtain the necessary information and quickly begin working. 【0253】 (Example 1) 【0254】 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." 【0255】 In conventional work processes, it was necessary to manually select materials for the task and calculate the required time individually, which resulted in time-consuming and labor-intensive work and decreased efficiency. Furthermore, the process relied on the experience of individual workers, making it difficult to standardize the work. 【0256】 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. 【0257】 In this invention, the server includes receiving means for receiving voice or keywords, conversion means for converting the information received from the receiving means into text information, and processing means for processing the text information and identifying related information materials. This makes it possible for users to easily identify the desired materials and obtain a standardized time estimate. 【0258】 "Receiving means" refers to devices or technologies for receiving audio or keywords. 【0259】 "Conversion means" refers to devices or technologies for converting received audio or keywords into textual information. 【0260】 "Processing means" refers to technology for processing textual information and identifying related information materials from databases, etc. 【0261】 "Registration means" refers to a device or method for registering identified information materials into an appropriate recording medium. 【0262】 "Time calculation means" refers to a device or method for calculating the time required for a task based on registered information and data. 【0263】 "Presentation means" refers to the technology or function for displaying the calculated required time and the names of the information materials on the output device. 【0264】 The system based on this invention automatically identifies materials for a task using voice or keyword input and calculates the time required. The system mainly consists of a terminal used by the user and a server that processes related data. 【0265】 Users begin using the service by entering voice or keywords into the device. In the case of voice input, the device uses a speech recognition engine to convert the voice into text. In this process, a commonly available API (Application Programming Interface) is used for the speech recognition engine. A specific example is a cloud service such as Google Cloud Speech-to-Text. 【0266】 The converted text information is sent to a server via the internet. The server analyzes the text information using natural language processing technology and identifies relevant information from a database. This analysis can utilize tools such as the Google Cloud Natural Language API. The server then registers the identified information in a storage medium such as a database or spreadsheet, and calculates the time required based on this information. Historical data and industry-standard algorithms are used for the calculation. 【0267】 For example, if a user enters "XYZ model troubleshooting" into the terminal, the server will identify the relevant troubleshooting guide and calculate that the standard working time is 1 hour. As a result, the terminal will display "XYZ model troubleshooting guide - estimated working time: 1 hour," and the user can proceed with the work based on this information. 【0268】 Furthermore, an example of a prompt message would be for the user to input, "What steps are required to troubleshoot an XYZ model?". This invention allows the user to work efficiently and perform tasks with a consistent quality that is not dependent on experience. 【0269】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0270】 Step 1: 【0271】 The user performs an action by inputting voice or keywords into the device. For example, the user inputs "Troubleshooting XYZ model". The input voice is captured within the device and treated as data in audio format. 【0272】 Step 2: 【0273】 The terminal converts voice input into text information. This uses a speech recognition engine, specifically a common API or service (e.g., a speech recognition API). Once the voice input is converted into a string, the converted text information is output. 【0274】 Step 3: 【0275】 The terminal sends the converted character information to the server. Possible transmission methods include HTTP requests. The character information reaches the server and is treated as input data. 【0276】 Step 4: 【0277】 The server analyzes the received text information using natural language processing technology. Through this analysis, it searches the database for relevant information. The input data is text information, and the output is the identification of relevant information. 【0278】 Step 5: 【0279】 The server registers the specified information materials on a recording medium. A database management system or a spreadsheet is used for this registration. The server registers the data corresponding to the information materials, and generates the information materials as input data and the registration result as output data. 【0280】 Step 6: 【0281】 Based on the specified information materials, the server calculates the required time for the work. An algorithm based on past data or industry standards is used for this. The algorithm processes the information materials as input data and obtains the required time as output data. 【0282】 Step 7: 【0283】 The terminal receives the result from the server and presents the information material name and the required time to the user. The terminal displays the received data on the GUI and presents the result in a format such as "XYZ Model Troubleshooting Guide - Predicted Working Time: 1 hour" as the final output. 【0284】 By combining the input and output flows of data in this way at each step, the user can efficiently obtain the information and time required for the work. 【0285】 (Application Example 1) 【0286】 Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0287】 At many sites, it is required that workers quickly find the appropriate procedure manual and estimate the accurate working time. However, the manual search for procedure manuals and time estimation in the past has taken time and has been a factor that impairs the work efficiency. The development of a system that solves this problem and quickly supplies the work procedures to the machine is required. 【0288】 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. 【0289】 In this invention, the server includes receiving means for receiving voice input or keyword input, conversion means for converting the data received from the receiving means into text information, and analysis means for analyzing the text information and identifying relevant materials. This enables workers to quickly obtain appropriate procedure manuals based on voice instructions and to accurately estimate work time. 【0290】 "Receiving means" refers to a function for receiving voice input or keyword input and transmitting it to the system. 【0291】 A "conversion means" is a function that receives voice input or keyword input and converts it into text information. 【0292】 "Analysis means" refers to a function for identifying related materials based on the converted text information. 【0293】 A "registration method" is a function for saving identified data to a storage device. 【0294】 A "time estimation method" is a function that calculates the time required for a task based on registered data. 【0295】 "Display means" refers to a function that visually displays to the user the name of the identified material and the estimated time required for its creation. 【0296】 A "supply means" is a function that obtains specific procedures based on voice instructions and provides that information to the device. 【0297】 The system for carrying out this invention has the function of effectively processing voice input and keyword input, identifying relevant materials, and estimating work time. The system consists of a terminal device equipped with a microphone for receiving voice as hardware, and a server for performing advanced processing. 【0298】 First, the user inputs their task details using voice or keywords via a terminal device. This voice input is converted into text using Google's Speech-to-Text API. The server analyzes the converted text using Python's Natural Language Toolkit (NLTK) to identify relevant data from a MySQL database. Once the data is identified, the server registers it in storage and then performs a time estimate based on the data. This time estimate is calculated using an algorithm based on historical data. 【0299】 Regarding display, the server visually displays the identified document name and estimated work time on the user's terminal device display. This allows the user to quickly obtain the necessary procedure manuals and plan their work. 【0300】 As a concrete example, consider a system used in a factory. A robot might request an assembly guide for product X via voice, and the guide would be instantly displayed along with an estimated completion time of one hour. Such a system would allow workers to work more efficiently. It would also be possible to input a prompt such as, "Please tell me the steps to predict the troubleshooting time for a new product," into the generating AI model. 【0301】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0302】 Step 1: 【0303】 The terminal receives voice or keyword input through the microphone. The user speaks "Assembly guide for product X" to input voice. The input voice data is acquired as digital voice data by the terminal's input module. 【0304】 Step 2: 【0305】 The terminal uses Google's Speech-to-Text API to convert the received voice data into character information. The voice data is sent to the cloud, and the data converted as text is received. This data becomes the text "Assembly Guide for Product X". 【0306】 Step 3: 【0307】 The server receives the text information and performs analysis using Python's Natural Language Toolkit (NLTK). Text analysis is performed to extract relevant keywords. In this case, "Product X" and "Assembly Guide" are obtained as important keywords. 【0308】 Step 4: 【0309】 The server queries the MySQL database and searches for relevant materials based on the analyzed keywords. Material data corresponding to the "Assembly Guide for Product X" is retrieved from within the database. 【0310】 Step 5: 【0311】 The server registers the retrieved material data in the storage device. Through the registration process, the material data is stored in a form associated with a specific user session. 【0312】 Step 6: 【0313】 The server calculates the working time based on the material data. Using past history data and defined standard time data, the estimated time to complete the work is calculated, and for example, a time of "1 hour" is obtained. 【0314】 Step 7: 【0315】 The server sends the estimated work time and identified document name to the user's terminal. The terminal interface displays "Product X Assembly Guide - Estimated Work Time: 1 hour" to the user. This information prepares the user to execute the work plan. 【0316】 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. 【0317】 This invention not only automates the selection of work manuals and the calculation of work time, but also provides a system for providing more appropriate responses based on the user's emotional state. This system mainly consists of a user terminal, a server, and an emotion engine. 【0318】 The user inputs their work details into the terminal using voice or keywords. If the input is voice, it is converted into text data by the terminal's speech recognition engine. The converted text data is sent to a server and analyzed using natural language processing technology. The server searches its database for and identifies relevant work manuals. Simultaneously, the terminal or server analyzes the user's emotions using an emotion engine. This analysis is derived from data such as the tone of voice and input, word choices, and facial recognition. 【0319】 Based on the user's emotional state detected by the emotion engine, the server can adjust how the work manual is presented. For example, if the user is stressed, the server will be configured to present a more concise and easy-to-understand explanation. It can also provide additional support information to help alleviate tension. Furthermore, the emotion analysis results influence the prediction of work time. If the server determines that the user is feeling fatigued, it may estimate a longer work time than usual. 【0320】 The server's final identified manual and estimated work time are sent to the terminal and presented to the user. For example, the user's screen might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotion-aware)." This allows the user to obtain information tailored to their emotional state, enabling them to work efficiently and with less stress. 【0321】 Thus, the system of the present invention allows users to receive intelligent support that goes beyond ordinary work assistance, which will result in improved work efficiency and worker satisfaction. 【0322】 The following describes the processing flow. 【0323】 Step 1: 【0324】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might give the voice command "Troubleshooting for XYZ models." 【0325】 Step 2: 【0326】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0327】 Step 3: 【0328】 The terminal sends the entered text data to the server. The information is sent in a format necessary for the server to begin processing. 【0329】 Step 4: 【0330】 The server analyzes the received text data using a natural language processing engine to identify relevant keywords and context. Based on the analysis results, it searches the database for and identifies the most relevant document. 【0331】 Step 5: 【0332】 The server uses an emotion engine to analyze the user's emotions. This analysis infers the emotional state from factors such as tone of voice, language choice, and the speed and intensity of the words used. 【0333】 Step 6: 【0334】 The server takes the sentiment analysis results into account and adjusts how relevant documents are presented. For example, if it determines that the user is experiencing stress, it adjusts the presentation of documents to be concise and easy to understand. 【0335】 Step 7: 【0336】 The server also adjusts its work time estimates based on emotion analysis. If the user is feeling fatigued or stressed, it calculates a more generous work time. 【0337】 Step 8: 【0338】 The server then sends the identified document name and adjusted work time to the terminal. 【0339】 Step 9: 【0340】 The terminal displays information received from the server on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotions considered)." This allows the user to receive support tailored to their emotional state, enabling more efficient work. 【0341】 (Example 2) 【0342】 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". 【0343】 Conventional systems had the problem of not being able to take into account the emotional state of the user when selecting work instructions and estimating work time, resulting in ineffective work support. Furthermore, they could not improve work efficiency in accordance with the user's stress level or fatigue level, potentially lowering worker satisfaction. 【0344】 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. 【0345】 In this invention, the server includes a receiving means for receiving voice input or keyword input, a conversion means for converting data from the receiving means into text format, and a discrimination means for analyzing the text format data and identifying related documents. This makes it possible to analyze the user's emotional state, adjust the method of presenting work instructions based on the analysis results, and accurately calculate work time. 【0346】 A "receiving means" is an element that has the function of accepting voice input or keyword input from the user. 【0347】 A "conversion means" is an element that has the function of converting received audio or keyword data into text format. 【0348】 A "discrimination means" is an element that analyzes converted text data and has the function of identifying related documents. 【0349】 A "recording means" is an element that has the function of registering a specific document in an information recording device. 【0350】 A "time calculation means" is an element that has the function of calculating work time based on a specified document. 【0351】 A "state analysis means" is an element that has the function of analyzing the user's emotional state. 【0352】 A "modification mechanism" is an element that has the function of adjusting the presentation method based on the analyzed emotional state. 【0353】 "Display means" refers to an element that has the function of displaying the name of the specified document and the calculated work time on a display device. 【0354】 To implement this invention, a user terminal, a server, and an emotion analysis engine are used. The user inputs the task details via voice or keywords through the terminal. In this case, the terminal uses a speech recognition engine to convert the voice into text format and sends the data to the server. A commonly known speech recognition API can be used as the speech recognition engine. 【0355】 The server analyzes the received text data using a generative AI model to identify relevant documents. This generative AI model may utilize, for example, a model employing natural language processing technology. Documents are searched within a database, and multiple documents may be identified as needed. 【0356】 Simultaneously, an emotion analysis engine is used to analyze the user's emotional state. For example, emotions are detected by voice tone, word selection in text, and, in some cases, by using the device's camera. Based on these analysis results, the server adjusts the format and content of the documents presented to the user. 【0357】 The server calculates the time required for a task, taking into account the results of an emotion analysis. For example, if it determines that the user is experiencing high levels of stress, the server will adjust the task time to be extended. This ensures that the user receives support best suited to their situation. Finally, this information is sent to the terminal and presented to the user. 【0358】 As a concrete example, consider a scenario where a user enters the prompt "Create agenda for the next meeting." The server identifies the relevant document and, through sentiment analysis, assesses that the user is feeling slightly fatigued. Therefore, the server sends a document to the terminal, along with a simpler agenda template, indicating a work time of "2 hours," and displays it as "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)." 【0359】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0360】 Step 1: 【0361】 The user inputs their task details into the terminal using voice or keywords. The input data, either voice or text, is sent to the terminal. The terminal receives this input and, in the case of voice input, uses a speech recognition engine to convert the voice into text data. The output is then generated as text data and sent to the server. 【0362】 Step 2: 【0363】 The server receives text data sent from the terminal. The input text data is analyzed by a generative AI model. The server extracts relevant keywords and uses those keywords to search the document database. The output is a list of relevant documents. 【0364】 Step 3: 【0365】 The server uses an emotion analysis engine to analyze the user's emotional state from their input voice or text tone, word selection, or facial recognition data. Input includes voice tone and text data. The analysis determines the user's emotional state, and the resulting output is emotion analysis data. 【0366】 Step 4: 【0367】 The server adjusts how relevant documents are presented based on the analyzed emotional state data. If the user is experiencing stress, the server selects more concise and easier-to-understand documents. The input includes emotional analysis data and a list of relevant documents, and the output is the adjusted documents. 【0368】 Step 5: 【0369】 The server calculates the work time, taking into account the results of the emotion analysis. If the analyzed emotional state indicates that the user is experiencing fatigue or stress, it estimates a longer work time than usual. The input includes the emotional state and related document data, and the output is the estimated work time. 【0370】 Step 6: 【0371】 The server sends the final document name, the adjusted document, and the estimated work time to the terminal. The user's terminal receives this data and displays it to the user. Specifically, the output might show information like "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)" on the screen. 【0372】 (Application Example 2) 【0373】 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." 【0374】 In modern industrial settings, problems frequently occur when workers operate robots, often leading to stress and fatigue during troubleshooting. Even in such situations, providing prompt and appropriate support to improve work efficiency is crucial. Furthermore, support that considers the emotional state of workers is necessary to enhance worker satisfaction. 【0375】 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. 【0376】 In this invention, the server includes a device for receiving voice input or keyword input, a conversion device for converting the information received from the device into text information, and an emotion analysis device for analyzing the user's emotional state. This makes it possible to provide prompt, emotionally sensitive, and appropriate support information even when the worker is experiencing stress or fatigue. 【0377】 "Voice input" refers to a format of information or instructions that a user can communicate to a system through their voice. 【0378】 "Keyword input" refers to a format in which users provide information to the system using a specific string of characters. 【0379】 "Device" refers to a hardware component used to perform a specific function. 【0380】 "Text information" refers to information that has been formalized as a string of characters and converted into a form that can be processed by a computer. 【0381】 A "conversion device" refers to a device used to convert data in one format to data in another format. 【0382】 An "analysis device" refers to a device used to analyze data and extract useful information from it. 【0383】 "Information" refers to the knowledge and data obtained from a specific database to meet the user's needs. 【0384】 A "storage device" refers to a device that has the function of holding data or information. 【0385】 A "registration device" refers to a device used to store specific data in a storage device or recording device. 【0386】 "Activity time" refers to the estimated time required for a particular task or operation. 【0387】 A "time estimation device" refers to a device used to predict the time required for a specific task. 【0388】 An "output device" refers to a device used to present data or information to a user. 【0389】 A "display device" refers to a device that presents information to a user visually. 【0390】 "Emotional state" refers to the state that expresses the user's psychological situation or mood. 【0391】 An "emotion analysis device" refers to a device that analyzes a user's emotional state and processes that information. 【0392】 A "regulating device" refers to a device used to change the output or operation of a system to conform to a certain standard. 【0393】 This invention provides a support system for work sites, and in particular, a system that realizes intelligent work support based on the emotional state of the user. This system mainly consists of a user terminal, a server, and an emotion analysis engine. 【0394】 When users encounter problems in factories or industrial settings, they use a terminal to input information via voice or keywords. The terminal uses a speech recognition engine to convert this input into text. The converted text information is sent to a server, which uses natural language processing techniques to analyze it and identify relevant documents from its database. 【0395】 Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. This emotion analysis engine determines emotions from factors such as voice tone, word choice, and input patterns. For example, if the user is experiencing stress, the system adjusts to provide a concise and easy-to-understand explanation. This adjustment is performed by an adjustment device. 【0396】 The server also estimates the activity time, taking into account the user's emotional state, along with the relevant manual, and sends it to the terminal. This allows the user to receive the manual best suited to their emotional state and perform their tasks with optimal efficiency. 【0397】 As a concrete example, consider a situation where a worker is having trouble removing a robot part during factory line work. The worker inputs "Tell me how to remove the part" into the terminal using voice commands, and the system presents a "part removal guide." Furthermore, if it senses the worker is stressed, it also provides additional messages such as, "It's okay even if this is your first time replacing a part; the procedure is simple." 【0398】 An example of a prompt message for a generating AI model is: "Please tell me how to provide a simple procedure and reassuring message to a worker who is under stress while replacing a robot part." 【0399】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0400】 Step 1: 【0401】 The terminal receives voice input or keyword input from the user. This input is converted into text information through a speech recognition engine. In this step, the input is the user's voice or keywords, and the output is text information. The speech recognition engine obtains the output by analyzing the waveform data of the input voice and converting it into a sequence of phonemes or words. 【0402】 Step 2: 【0403】 The server uses natural language processing techniques to analyze text information received from the terminal. This analysis searches the database for and identifies relevant documents. The input for this step is text information, and the output is the identifiers and links of the relevant documents. Natural language processing includes data processing such as morphological analysis and keyword extraction. 【0404】 Step 3: 【0405】 The server uses an emotion analysis engine to analyze the user's emotional state from text information. The input for this step is the user's text information, and the output is the determined emotional state (e.g., stress, fatigue, relief, etc.). Emotional features are extracted from the input's word choices and writing style, and these are used to determine the emotional state based on a statistical model. 【0406】 Step 4: 【0407】 The server adjusts the content and presentation method of the documents presented based on the analyzed emotional state, and sends this information to the terminal. The input for this step is the relevant documents and emotional state, and the output is the adjusted documents. Adjustments to the presentation method include simplifying the text and adding supplementary information. 【0408】 Step 5: 【0409】 The terminal presents the user with documents and activity times sent from the server. The input for this step is the adjusted document and activity time information, while the output is information that the user can visually confirm on the screen. The terminal assists in conveying information to the user through haptic feedback and voice guidance. 【0410】 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. 【0411】 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. 【0412】 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. 【0413】 [Third Embodiment] 【0414】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0415】 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. 【0416】 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). 【0417】 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. 【0418】 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. 【0419】 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). 【0420】 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. 【0421】 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. 【0422】 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. 【0423】 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. 【0424】 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. 【0425】 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". 【0426】 This invention provides a system that automates the selection of work manuals and the calculation of work time, and a specific embodiment thereof is shown below. The system mainly consists of a user terminal and a server. 【0427】 First, the user inputs the task details into the device using voice or keywords. For example, consider a case where the user voice-inputs "Troubleshooting XYZ model." This voice input is converted into text data using the device's speech recognition engine, and the text is sent to the server. 【0428】 The server analyzes the received text data using natural language processing techniques and searches and identifies relevant documents from the database. In this example, the server can identify the appropriate manual, "XYZ Model Troubleshooting Guide." 【0429】 The identified manual is registered in a dedicated sheet by the server. Furthermore, the server calculates the standard work time required for the task based on that manual and records it in the sheet. This calculated work time is performed using an algorithm based on historical data and industry standards. 【0430】 Finally, the terminal uses the information received from the server to display the identified manual name and estimated work time to the user. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour" on the user's screen. This display prepares the user to begin work immediately. 【0431】 Thus, the system of the present invention enables users to quickly select the manual required for a specific task and predict the necessary work time. This will improve work efficiency and provide a stable work environment that does not depend on the worker's experience. 【0432】 The following describes the processing flow. 【0433】 Step 1: 【0434】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might voice command "XYZ model troubleshooting" or enter the keyword "XYZ model troubleshooting". 【0435】 Step 2: 【0436】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0437】 Step 3: 【0438】 The terminal sends the converted text data to the server. The input text is in a format that the server can process. 【0439】 Step 4: 【0440】 The server processes the received text data using a natural language processing engine to analyze relevant keywords and context. Based on this analysis, it identifies appropriate documents and information. 【0441】 Step 5: 【0442】 Based on the analysis results, the server searches the document database for the most relevant manual and identifies it. For example, it might identify the "XYZ Model Troubleshooting Guide." 【0443】 Step 6: 【0444】 The server registers the identified manual in a dedicated sheet. Furthermore, it retrieves the standard working time associated with that manual from the database and calculates the working time. 【0445】 Step 7: 【0446】 Based on information sent from the server, the terminal displays the identified manual name and estimated work time on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated work time: 1 hour". 【0447】 This series of steps allows users to efficiently obtain the necessary information and quickly begin working. 【0448】 (Example 1) 【0449】 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." 【0450】 In conventional work processes, it was necessary to manually select materials for the task and calculate the required time individually, which resulted in time-consuming and labor-intensive work and decreased efficiency. Furthermore, the process relied on the experience of individual workers, making it difficult to standardize the work. 【0451】 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. 【0452】 In this invention, the server includes receiving means for receiving voice or keywords, conversion means for converting the information received from the receiving means into text information, and processing means for processing the text information and identifying related information materials. This makes it possible for users to easily identify the desired materials and obtain a standardized time estimate. 【0453】 "Receiving means" refers to devices or technologies for receiving audio or keywords. 【0454】 "Conversion means" refers to devices or technologies for converting received audio or keywords into textual information. 【0455】 "Processing means" refers to technology for processing textual information and identifying related information materials from databases, etc. 【0456】 "Registration means" refers to a device or method for registering identified information materials into an appropriate recording medium. 【0457】 "Time calculation means" refers to a device or method for calculating the time required for a task based on registered information and data. 【0458】 "Presentation means" refers to the technology or function for displaying the calculated required time and the names of the information materials on the output device. 【0459】 The system based on this invention automatically identifies materials for a task using voice or keyword input and calculates the time required. The system mainly consists of a terminal used by the user and a server that processes related data. 【0460】 Users begin using the service by entering voice or keywords into the device. In the case of voice input, the device uses a speech recognition engine to convert the voice into text. In this process, a commonly available API (Application Programming Interface) is used for the speech recognition engine. A specific example is a cloud service such as Google Cloud Speech-to-Text. 【0461】 The converted text information is sent to a server via the internet. The server analyzes the text information using natural language processing technology and identifies relevant information from a database. This analysis can utilize tools such as the Google Cloud Natural Language API. The server then registers the identified information in a storage medium such as a database or spreadsheet, and calculates the time required based on this information. Historical data and industry-standard algorithms are used for the calculation. 【0462】 For example, if a user enters "XYZ model troubleshooting" into the terminal, the server will identify the relevant troubleshooting guide and calculate that the standard working time is 1 hour. As a result, the terminal will display "XYZ model troubleshooting guide - estimated working time: 1 hour," and the user can proceed with the work based on this information. 【0463】 Furthermore, an example of a prompt message would be for the user to input, "What steps are required to troubleshoot an XYZ model?". This invention allows the user to work efficiently and perform tasks with a consistent quality that is not dependent on experience. 【0464】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0465】 Step 1: 【0466】 The user performs an action by inputting voice or keywords into the device. For example, the user inputs "Troubleshooting XYZ model". The input voice is captured within the device and treated as data in audio format. 【0467】 Step 2: 【0468】 The terminal converts voice input into text information. This uses a speech recognition engine, specifically a common API or service (e.g., a speech recognition API). Once the voice input is converted into a string, the converted text information is output. 【0469】 Step 3: 【0470】 The terminal sends the converted character information to the server. Possible transmission methods include HTTP requests. The character information reaches the server and is treated as input data. 【0471】 Step 4: 【0472】 The server analyzes the received text information using natural language processing technology. Through this analysis, it searches the database for relevant information. The input data is text information, and the output is the identification of relevant information. 【0473】 Step 5: 【0474】 The server registers the identified information data into a recording medium. Database management systems or spreadsheets are used for this registration. The server registers the information data and its corresponding data, generating the information data as input data and the registration results as output data. 【0475】 Step 6: 【0476】 The server calculates the time required for the task based on the identified information data. This uses algorithms based on historical data and industry standards. The algorithm processes the information data as input data and outputs the time required as output data. 【0477】 Step 7: 【0478】 The terminal receives the results from the server and presents the user with the name of the information document and the estimated time required. The terminal displays the received data in a GUI and presents the results as final output in the format of "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour". 【0479】 By combining data input and output flows in this way at each step, users can efficiently obtain the information and time necessary for their work. 【0480】 (Application Example 1) 【0481】 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." 【0482】 In many workplaces, workers are required to quickly find the appropriate procedure manuals and accurately estimate the time required for each task. However, the current manual process of searching for procedure manuals and estimating time is time-consuming and hinders work efficiency. There is a need to develop a system that solves this problem and rapidly supplies work procedures to machines. 【0483】 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. 【0484】 In this invention, the server includes receiving means for receiving voice input or keyword input, conversion means for converting the data received from the receiving means into text information, and analysis means for analyzing the text information and identifying relevant materials. This enables workers to quickly obtain appropriate procedure manuals based on voice instructions and to accurately estimate work time. 【0485】 "Receiving means" refers to a function for receiving voice input or keyword input and transmitting it to the system. 【0486】 A "conversion means" is a function that receives voice input or keyword input and converts it into text information. 【0487】 "Analysis means" refers to a function for identifying related materials based on the converted text information. 【0488】 A "registration method" is a function for saving identified data to a storage device. 【0489】 A "time estimation method" is a function that calculates the time required for a task based on registered data. 【0490】 "Display means" refers to a function that visually displays to the user the name of the identified material and the estimated time required for its creation. 【0491】 A "supply means" is a function that obtains specific procedures based on voice instructions and provides that information to the device. 【0492】 The system for carrying out this invention has the function of effectively processing voice input and keyword input, identifying relevant materials, and estimating work time. The system consists of a terminal device equipped with a microphone for receiving voice as hardware, and a server for performing advanced processing. 【0493】 First, the user inputs their task details using voice or keywords via a terminal device. This voice input is converted into text using Google's Speech-to-Text API. The server analyzes the converted text using Python's Natural Language Toolkit (NLTK) to identify relevant data from a MySQL database. Once the data is identified, the server registers it in storage and then performs a time estimate based on the data. This time estimate is calculated using an algorithm based on historical data. 【0494】 Regarding display, the server visually displays the identified document name and estimated work time on the user's terminal device display. This allows the user to quickly obtain the necessary procedure manuals and plan their work. 【0495】 As a concrete example, consider a system used in a factory. A robot might request an assembly guide for product X via voice, and the guide would be instantly displayed along with an estimated completion time of one hour. Such a system would allow workers to work more efficiently. It would also be possible to input a prompt such as, "Please tell me the steps to predict the troubleshooting time for a new product," into the generating AI model. 【0496】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0497】 Step 1: 【0498】 The terminal receives voice or keyword input through the microphone. The user speaks "Assembly guide for product X" to input voice. The input voice data is acquired as digital voice data by the terminal's input module. 【0499】 Step 2: 【0500】 The device uses Google's Speech-to-Text API to convert the received audio data into text. The audio data is sent to the cloud, and the converted data is received. This data will be the text "Assembly Guide for Product X". 【0501】 Step 3: 【0502】 The server receives text information and performs analysis using Python's Natural Language Toolkit (NLTK). Text analysis is performed to extract relevant keywords. In this case, "Product X" and "Assembly Guide" are identified as important keywords. 【0503】 Step 4: 【0504】 The server queries the MySQL database and searches for relevant documents based on the analyzed keywords. It retrieves document data corresponding to "Assembly Guide for Product X" from the database. 【0505】 Step 5: 【0506】 The server registers the acquired data into storage. The registration process ensures that the data is stored in a way that associates it with a specific user session. 【0507】 Step 6: 【0508】 The server calculates the work time based on the data. Using historical data and defined standard time data, it calculates an estimated time to complete the work, resulting in a time of "1 hour" as an example. 【0509】 Step 7: 【0510】 The server sends the estimated work time and identified document name to the user's terminal. The terminal interface displays "Product X Assembly Guide - Estimated Work Time: 1 hour" to the user. This information prepares the user to execute the work plan. 【0511】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0512】 This invention not only automates the selection of work manuals and the calculation of work time, but also provides a system for providing more appropriate responses based on the user's emotional state. This system mainly consists of a user terminal, a server, and an emotion engine. 【0513】 The user inputs their work details into the terminal using voice or keywords. If the input is voice, it is converted into text data by the terminal's speech recognition engine. The converted text data is sent to a server and analyzed using natural language processing technology. The server searches its database for and identifies relevant work manuals. Simultaneously, the terminal or server analyzes the user's emotions using an emotion engine. This analysis is derived from data such as the tone of voice and input, word choices, and facial recognition. 【0514】 Based on the user's emotional state detected by the emotion engine, the server can adjust how the work manual is presented. For example, if the user is stressed, the server will be configured to present a more concise and easy-to-understand explanation. It can also provide additional support information to help alleviate tension. Furthermore, the emotion analysis results influence the prediction of work time. If the server determines that the user is feeling fatigued, it may estimate a longer work time than usual. 【0515】 The server's final identified manual and estimated work time are sent to the terminal and presented to the user. For example, the user's screen might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotion-aware)." This allows the user to obtain information tailored to their emotional state, enabling them to work efficiently and with less stress. 【0516】 Thus, the system of the present invention allows users to receive intelligent support that goes beyond ordinary work assistance, which will result in improved work efficiency and worker satisfaction. 【0517】 The following describes the processing flow. 【0518】 Step 1: 【0519】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might give the voice command "Troubleshooting for XYZ models." 【0520】 Step 2: 【0521】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0522】 Step 3: 【0523】 The terminal sends the entered text data to the server. The information is sent in a format necessary for the server to begin processing. 【0524】 Step 4: 【0525】 The server analyzes the received text data using a natural language processing engine to identify relevant keywords and context. Based on the analysis results, it searches the database for and identifies the most relevant document. 【0526】 Step 5: 【0527】 The server uses an emotion engine to analyze the user's emotions. This analysis infers the emotional state from factors such as tone of voice, language choice, and the speed and intensity of the words used. 【0528】 Step 6: 【0529】 The server takes the sentiment analysis results into account and adjusts how relevant documents are presented. For example, if it determines that the user is experiencing stress, it adjusts the presentation of documents to be concise and easy to understand. 【0530】 Step 7: 【0531】 The server also adjusts its work time estimates based on emotion analysis. If the user is feeling fatigued or stressed, it calculates a more generous work time. 【0532】 Step 8: 【0533】 The server then sends the identified document name and adjusted work time to the terminal. 【0534】 Step 9: 【0535】 The terminal displays information received from the server on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotions considered)." This allows the user to receive support tailored to their emotional state, enabling more efficient work. 【0536】 (Example 2) 【0537】 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." 【0538】 Conventional systems had the problem of not being able to take into account the emotional state of the user when selecting work instructions and estimating work time, resulting in ineffective work support. Furthermore, they could not improve work efficiency in accordance with the user's stress level or fatigue level, potentially lowering worker satisfaction. 【0539】 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. 【0540】 In this invention, the server includes a receiving means for receiving voice input or keyword input, a conversion means for converting data from the receiving means into text format, and a discrimination means for analyzing the text format data and identifying related documents. This makes it possible to analyze the user's emotional state, adjust the method of presenting work instructions based on the analysis results, and accurately calculate work time. 【0541】 A "receiving means" is an element that has the function of accepting voice input or keyword input from the user. 【0542】 A "conversion means" is an element that has the function of converting received audio or keyword data into text format. 【0543】 A "discrimination means" is an element that analyzes converted text data and has the function of identifying related documents. 【0544】 A "recording means" is an element that has the function of registering a specific document in an information recording device. 【0545】 A "time calculation means" is an element that has the function of calculating work time based on a specified document. 【0546】 A "state analysis means" is an element that has the function of analyzing the user's emotional state. 【0547】 A "modification mechanism" is an element that has the function of adjusting the presentation method based on the analyzed emotional state. 【0548】 "Display means" refers to an element that has the function of displaying the name of the specified document and the calculated work time on a display device. 【0549】 To implement this invention, a user terminal, a server, and an emotion analysis engine are used. The user inputs the task details via voice or keywords through the terminal. In this case, the terminal uses a speech recognition engine to convert the voice into text format and sends the data to the server. A commonly known speech recognition API can be used as the speech recognition engine. 【0550】 The server analyzes the received text data using a generative AI model to identify relevant documents. This generative AI model may utilize, for example, a model employing natural language processing technology. Documents are searched within a database, and multiple documents may be identified as needed. 【0551】 Simultaneously, an emotion analysis engine is used to analyze the user's emotional state. For example, emotions are detected by voice tone, word selection in text, and, in some cases, by using the device's camera. Based on these analysis results, the server adjusts the format and content of the documents presented to the user. 【0552】 The server calculates the time required for a task, taking into account the results of an emotion analysis. For example, if it determines that the user is experiencing high levels of stress, the server will adjust the task time to be extended. This ensures that the user receives support best suited to their situation. Finally, this information is sent to the terminal and presented to the user. 【0553】 As a concrete example, consider a scenario where a user enters the prompt "Create agenda for the next meeting." The server identifies the relevant document and, through sentiment analysis, assesses that the user is feeling slightly fatigued. Therefore, the server sends a document to the terminal, along with a simpler agenda template, indicating a work time of "2 hours," and displays it as "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)." 【0554】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0555】 Step 1: 【0556】 The user inputs their task details into the terminal using voice or keywords. The input data, either voice or text, is sent to the terminal. The terminal receives this input and, in the case of voice input, uses a speech recognition engine to convert the voice into text data. The output is then generated as text data and sent to the server. 【0557】 Step 2: 【0558】 The server receives text data sent from the terminal. The input text data is analyzed by a generative AI model. The server extracts relevant keywords and uses those keywords to search the document database. The output is a list of relevant documents. 【0559】 Step 3: 【0560】 The server uses an emotion analysis engine to analyze the user's emotional state from their input voice or text tone, word selection, or facial recognition data. Input includes voice tone and text data. The analysis determines the user's emotional state, and the resulting output is emotion analysis data. 【0561】 Step 4: 【0562】 The server adjusts how relevant documents are presented based on the analyzed emotional state data. If the user is experiencing stress, the server selects more concise and easier-to-understand documents. The input includes emotional analysis data and a list of relevant documents, and the output is the adjusted documents. 【0563】 Step 5: 【0564】 The server calculates the work time, taking into account the results of the emotion analysis. If the analyzed emotional state indicates that the user is experiencing fatigue or stress, it estimates a longer work time than usual. The input includes the emotional state and related document data, and the output is the estimated work time. 【0565】 Step 6: 【0566】 The server sends the final document name, the adjusted document, and the estimated work time to the terminal. The user's terminal receives this data and displays it to the user. Specifically, the output might show information like "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)" on the screen. 【0567】 (Application Example 2) 【0568】 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." 【0569】 In modern industrial settings, problems frequently occur when workers operate robots, often leading to stress and fatigue during troubleshooting. Even in such situations, providing prompt and appropriate support to improve work efficiency is crucial. Furthermore, support that considers the emotional state of workers is necessary to enhance worker satisfaction. 【0570】 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. 【0571】 In this invention, the server includes a device for receiving voice input or keyword input, a conversion device for converting the information received from the device into text information, and an emotion analysis device for analyzing the user's emotional state. This makes it possible to provide prompt, emotionally sensitive, and appropriate support information even when the worker is experiencing stress or fatigue. 【0572】 "Voice input" refers to a format of information or instructions that a user can communicate to a system through their voice. 【0573】 "Keyword input" refers to a format in which users provide information to the system using a specific string of characters. 【0574】 "Device" refers to a hardware component used to perform a specific function. 【0575】 "Text information" refers to information that has been formalized as a string of characters and converted into a form that can be processed by a computer. 【0576】 A "conversion device" refers to a device used to convert data in one format to data in another format. 【0577】 An "analysis device" refers to a device used to analyze data and extract useful information from it. 【0578】 "Information" refers to the knowledge and data obtained from a specific database to meet the user's needs. 【0579】 A "storage device" refers to a device that has the function of holding data or information. 【0580】 A "registration device" refers to a device used to store specific data in a storage device or recording device. 【0581】 "Activity time" refers to the estimated time required for a particular task or operation. 【0582】 A "time estimation device" refers to a device used to predict the time required for a specific task. 【0583】 An "output device" refers to a device used to present data or information to a user. 【0584】 A "display device" refers to a device that presents information to a user visually. 【0585】 "Emotional state" refers to the state that expresses the user's psychological situation or mood. 【0586】 An "emotion analysis device" refers to a device that analyzes a user's emotional state and processes that information. 【0587】 A "regulating device" refers to a device used to change the output or operation of a system to conform to a certain standard. 【0588】 This invention provides a support system for work sites, and in particular, a system that realizes intelligent work support based on the emotional state of the user. This system mainly consists of a user terminal, a server, and an emotion analysis engine. 【0589】 When users encounter problems in factories or industrial settings, they use a terminal to input information via voice or keywords. The terminal uses a speech recognition engine to convert this input into text. The converted text information is sent to a server, which uses natural language processing techniques to analyze it and identify relevant documents from its database. 【0590】 Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. This emotion analysis engine determines emotions from factors such as voice tone, word choice, and input patterns. For example, if the user is experiencing stress, the system adjusts to provide a concise and easy-to-understand explanation. This adjustment is performed by an adjustment device. 【0591】 The server also estimates the activity time, taking into account the user's emotional state, along with the relevant manual, and sends it to the terminal. This allows the user to receive the manual best suited to their emotional state and perform their tasks with optimal efficiency. 【0592】 As a concrete example, consider a situation where a worker is having trouble removing a robot part during factory line work. The worker inputs "Tell me how to remove the part" into the terminal using voice commands, and the system presents a "part removal guide." Furthermore, if it senses the worker is stressed, it also provides additional messages such as, "It's okay even if this is your first time replacing a part; the procedure is simple." 【0593】 An example of a prompt message for a generating AI model is: "Please tell me how to provide a simple procedure and reassuring message to a worker who is under stress while replacing a robot part." 【0594】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0595】 Step 1: 【0596】 The terminal receives voice input or keyword input from the user. This input is converted into text information through a speech recognition engine. In this step, the input is the user's voice or keywords, and the output is text information. The speech recognition engine obtains the output by analyzing the waveform data of the input voice and converting it into a sequence of phonemes or words. 【0597】 Step 2: 【0598】 The server uses natural language processing techniques to analyze text information received from the terminal. This analysis searches the database for and identifies relevant documents. The input for this step is text information, and the output is the identifiers and links of the relevant documents. Natural language processing includes data processing such as morphological analysis and keyword extraction. 【0599】 Step 3: 【0600】 The server uses an emotion analysis engine to analyze the user's emotional state from text information. The input for this step is the user's text information, and the output is the determined emotional state (e.g., stress, fatigue, relief, etc.). Emotional features are extracted from the input's word choices and writing style, and these are used to determine the emotional state based on a statistical model. 【0601】 Step 4: 【0602】 The server adjusts the content and presentation method of the documents presented based on the analyzed emotional state, and sends this information to the terminal. The input for this step is the relevant documents and emotional state, and the output is the adjusted documents. Adjustments to the presentation method include simplifying the text and adding supplementary information. 【0603】 Step 5: 【0604】 The terminal presents the user with documents and activity times sent from the server. The input for this step is the adjusted document and activity time information, while the output is information that the user can visually confirm on the screen. The terminal assists in conveying information to the user through haptic feedback and voice guidance. 【0605】 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. 【0606】 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. 【0607】 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. 【0608】 [Fourth Embodiment] 【0609】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0610】 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. 【0611】 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). 【0612】 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. 【0613】 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. 【0614】 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). 【0615】 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. 【0616】 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. 【0617】 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. 【0618】 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. 【0619】 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. 【0620】 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. 【0621】 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". 【0622】 This invention provides a system that automates the selection of work manuals and the calculation of work time, and a specific embodiment thereof is shown below. The system mainly consists of a user terminal and a server. 【0623】 First, the user inputs the task details into the device using voice or keywords. For example, consider a case where the user voice-inputs "Troubleshooting XYZ model." This voice input is converted into text data using the device's speech recognition engine, and the text is sent to the server. 【0624】 The server analyzes the received text data using natural language processing techniques and searches and identifies relevant documents from the database. In this example, the server can identify the appropriate manual, "XYZ Model Troubleshooting Guide." 【0625】 The identified manual is registered in a dedicated sheet by the server. Furthermore, the server calculates the standard work time required for the task based on that manual and records it in the sheet. This calculated work time is performed using an algorithm based on historical data and industry standards. 【0626】 Finally, the terminal uses the information received from the server to display the identified manual name and estimated work time to the user. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour" on the user's screen. This display prepares the user to begin work immediately. 【0627】 Thus, the system of the present invention enables users to quickly select the manual required for a specific task and predict the necessary work time. This will improve work efficiency and provide a stable work environment that does not depend on the worker's experience. 【0628】 The following describes the processing flow. 【0629】 Step 1: 【0630】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might voice command "XYZ model troubleshooting" or enter the keyword "XYZ model troubleshooting". 【0631】 Step 2: 【0632】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0633】 Step 3: 【0634】 The terminal sends the converted text data to the server. The input text is in a format that the server can process. 【0635】 Step 4: 【0636】 The server processes the received text data using a natural language processing engine to analyze relevant keywords and context. Based on this analysis, it identifies appropriate documents and information. 【0637】 Step 5: 【0638】 Based on the analysis results, the server searches the document database for the most relevant manual and identifies it. For example, it might identify the "XYZ Model Troubleshooting Guide." 【0639】 Step 6: 【0640】 The server registers the identified manual in a dedicated sheet. Furthermore, it retrieves the standard working time associated with that manual from the database and calculates the working time. 【0641】 Step 7: 【0642】 Based on information sent from the server, the terminal displays the identified manual name and estimated work time on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated work time: 1 hour". 【0643】 This series of steps allows users to efficiently obtain the necessary information and quickly begin working. 【0644】 (Example 1) 【0645】 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". 【0646】 In conventional work processes, it was necessary to manually select materials for the task and calculate the required time individually, which resulted in time-consuming and labor-intensive work and decreased efficiency. Furthermore, the process relied on the experience of individual workers, making it difficult to standardize the work. 【0647】 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. 【0648】 In this invention, the server includes receiving means for receiving voice or keywords, conversion means for converting the information received from the receiving means into text information, and processing means for processing the text information and identifying related information materials. This makes it possible for users to easily identify the desired materials and obtain a standardized time estimate. 【0649】 "Receiving means" refers to devices or technologies for receiving audio or keywords. 【0650】 "Conversion means" refers to devices or technologies for converting received audio or keywords into textual information. 【0651】 "Processing means" refers to technology for processing textual information and identifying related information materials from databases, etc. 【0652】 "Registration means" refers to a device or method for registering identified information materials into an appropriate recording medium. 【0653】 "Time calculation means" refers to a device or method for calculating the time required for a task based on registered information and data. 【0654】 "Presentation means" refers to the technology or function for displaying the calculated required time and the names of the information materials on the output device. 【0655】 The system based on this invention automatically identifies materials for a task using voice or keyword input and calculates the time required. The system mainly consists of a terminal used by the user and a server that processes related data. 【0656】 Users begin using the service by entering voice or keywords into the device. In the case of voice input, the device uses a speech recognition engine to convert the voice into text. In this process, a commonly available API (Application Programming Interface) is used for the speech recognition engine. A specific example is a cloud service such as Google Cloud Speech-to-Text. 【0657】 The converted text information is sent to a server via the internet. The server analyzes the text information using natural language processing technology and identifies relevant information from a database. This analysis can utilize tools such as the Google Cloud Natural Language API. The server then registers the identified information in a storage medium such as a database or spreadsheet, and calculates the time required based on this information. Historical data and industry-standard algorithms are used for the calculation. 【0658】 For example, if a user enters "XYZ model troubleshooting" into the terminal, the server will identify the relevant troubleshooting guide and calculate that the standard working time is 1 hour. As a result, the terminal will display "XYZ model troubleshooting guide - estimated working time: 1 hour," and the user can proceed with the work based on this information. 【0659】 Furthermore, an example of a prompt message would be for the user to input, "What steps are required to troubleshoot an XYZ model?". This invention allows the user to work efficiently and perform tasks with a consistent quality that is not dependent on experience. 【0660】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0661】 Step 1: 【0662】 The user performs an action by inputting voice or keywords into the device. For example, the user inputs "Troubleshooting XYZ model". The input voice is captured within the device and treated as data in audio format. 【0663】 Step 2: 【0664】 The terminal converts voice input into text information. This uses a speech recognition engine, specifically a common API or service (e.g., a speech recognition API). Once the voice input is converted into a string, the converted text information is output. 【0665】 Step 3: 【0666】 The terminal sends the converted character information to the server. Possible transmission methods include HTTP requests. The character information reaches the server and is treated as input data. 【0667】 Step 4: 【0668】 The server analyzes the received text information using natural language processing technology. Through this analysis, it searches the database for relevant information. The input data is text information, and the output is the identification of relevant information. 【0669】 Step 5: 【0670】 The server registers the identified information data into a recording medium. Database management systems or spreadsheets are used for this registration. The server registers the information data and its corresponding data, generating the information data as input data and the registration results as output data. 【0671】 Step 6: 【0672】 The server calculates the time required for the task based on the identified information data. This uses algorithms based on historical data and industry standards. The algorithm processes the information data as input data and outputs the time required as output data. 【0673】 Step 7: 【0674】 The terminal receives the results from the server and presents the user with the name of the information document and the estimated time required. The terminal displays the received data in a GUI and presents the results as final output in the format of "XYZ Model Troubleshooting Guide - Estimated Work Time: 1 hour". 【0675】 By combining data input and output flows in this way at each step, users can efficiently obtain the information and time necessary for their work. 【0676】 (Application Example 1) 【0677】 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". 【0678】 In many workplaces, workers are required to quickly find the appropriate procedure manuals and accurately estimate the time required for each task. However, the current manual process of searching for procedure manuals and estimating time is time-consuming and hinders work efficiency. There is a need to develop a system that solves this problem and rapidly supplies work procedures to machines. 【0679】 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. 【0680】 In this invention, the server includes receiving means for receiving voice input or keyword input, conversion means for converting the data received from the receiving means into text information, and analysis means for analyzing the text information and identifying relevant materials. This enables workers to quickly obtain appropriate procedure manuals based on voice instructions and to accurately estimate work time. 【0681】 "Receiving means" refers to a function for receiving voice input or keyword input and transmitting it to the system. 【0682】 A "conversion means" is a function that receives voice input or keyword input and converts it into text information. 【0683】 "Analysis means" refers to a function for identifying related materials based on the converted text information. 【0684】 A "registration method" is a function for saving identified data to a storage device. 【0685】 A "time estimation method" is a function that calculates the time required for a task based on registered data. 【0686】 "Display means" refers to a function that visually displays to the user the name of the identified material and the estimated time required for its creation. 【0687】 A "supply means" is a function that obtains specific procedures based on voice instructions and provides that information to the device. 【0688】 The system for carrying out this invention has the function of effectively processing voice input and keyword input, identifying relevant materials, and estimating work time. The system consists of a terminal device equipped with a microphone for receiving voice as hardware, and a server for performing advanced processing. 【0689】 First, the user inputs their task details using voice or keywords via a terminal device. This voice input is converted into text using Google's Speech-to-Text API. The server analyzes the converted text using Python's Natural Language Toolkit (NLTK) to identify relevant data from a MySQL database. Once the data is identified, the server registers it in storage and then performs a time estimate based on the data. This time estimate is calculated using an algorithm based on historical data. 【0690】 Regarding display, the server visually displays the identified document name and estimated work time on the user's terminal device display. This allows the user to quickly obtain the necessary procedure manuals and plan their work. 【0691】 As a concrete example, consider a system used in a factory. A robot might request an assembly guide for product X via voice, and the guide would be instantly displayed along with an estimated completion time of one hour. Such a system would allow workers to work more efficiently. It would also be possible to input a prompt such as, "Please tell me the steps to predict the troubleshooting time for a new product," into the generating AI model. 【0692】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0693】 Step 1: 【0694】 The terminal receives voice or keyword input through the microphone. The user speaks "Assembly guide for product X" to input voice. The input voice data is acquired as digital voice data by the terminal's input module. 【0695】 Step 2: 【0696】 The device uses Google's Speech-to-Text API to convert the received audio data into text. The audio data is sent to the cloud, and the converted data is received. This data will be the text "Assembly Guide for Product X". 【0697】 Step 3: 【0698】 The server receives text information and performs analysis using Python's Natural Language Toolkit (NLTK). Text analysis is performed to extract relevant keywords. In this case, "Product X" and "Assembly Guide" are identified as important keywords. 【0699】 Step 4: 【0700】 The server queries the MySQL database and searches for relevant documents based on the analyzed keywords. It retrieves document data corresponding to "Assembly Guide for Product X" from the database. 【0701】 Step 5: 【0702】 The server registers the acquired data into storage. The registration process ensures that the data is stored in a way that associates it with a specific user session. 【0703】 Step 6: 【0704】 The server calculates the work time based on the data. Using historical data and defined standard time data, it calculates an estimated time to complete the work, resulting in a time of "1 hour" as an example. 【0705】 Step 7: 【0706】 The server sends the estimated work time and identified document name to the user's terminal. The terminal interface displays "Product X Assembly Guide - Estimated Work Time: 1 hour" to the user. This information prepares the user to execute the work plan. 【0707】 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. 【0708】 This invention not only automates the selection of work manuals and the calculation of work time, but also provides a system for providing more appropriate responses based on the user's emotional state. This system mainly consists of a user terminal, a server, and an emotion engine. 【0709】 The user inputs their work details into the terminal using voice or keywords. If the input is voice, it is converted into text data by the terminal's speech recognition engine. The converted text data is sent to a server and analyzed using natural language processing technology. The server searches its database for and identifies relevant work manuals. Simultaneously, the terminal or server analyzes the user's emotions using an emotion engine. This analysis is derived from data such as the tone of voice and input, word choices, and facial recognition. 【0710】 Based on the user's emotional state detected by the emotion engine, the server can adjust how the work manual is presented. For example, if the user is stressed, the server will be configured to present a more concise and easy-to-understand explanation. It can also provide additional support information to help alleviate tension. Furthermore, the emotion analysis results influence the prediction of work time. If the server determines that the user is feeling fatigued, it may estimate a longer work time than usual. 【0711】 The server's final identified manual and estimated work time are sent to the terminal and presented to the user. For example, the user's screen might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotion-aware)." This allows the user to obtain information tailored to their emotional state, enabling them to work efficiently and with less stress. 【0712】 Thus, the system of the present invention allows users to receive intelligent support that goes beyond ordinary work assistance, which will result in improved work efficiency and worker satisfaction. 【0713】 The following describes the processing flow. 【0714】 Step 1: 【0715】 The user can give voice commands to the device or enter keywords using the keyboard. For example, the user might give the voice command "Troubleshooting for XYZ models." 【0716】 Step 2: 【0717】 When voice input is received, the device uses a speech recognition engine to convert the voice data into text data. For example, the voice "Troubleshooting XYZ models" is converted to the text "Troubleshooting XYZ models". 【0718】 Step 3: 【0719】 The terminal sends the entered text data to the server. The information is sent in a format necessary for the server to begin processing. 【0720】 Step 4: 【0721】 The server analyzes the received text data using a natural language processing engine to identify relevant keywords and context. Based on the analysis results, it searches the database for and identifies the most relevant document. 【0722】 Step 5: 【0723】 The server uses an emotion engine to analyze the user's emotions. This analysis infers the emotional state from factors such as tone of voice, language choice, and the speed and intensity of the words used. 【0724】 Step 6: 【0725】 The server takes the sentiment analysis results into account and adjusts how relevant documents are presented. For example, if it determines that the user is experiencing stress, it adjusts the presentation of documents to be concise and easy to understand. 【0726】 Step 7: 【0727】 The server also adjusts its work time estimates based on emotion analysis. If the user is feeling fatigued or stressed, it calculates a more generous work time. 【0728】 Step 8: 【0729】 The server then sends the identified document name and adjusted work time to the terminal. 【0730】 Step 9: 【0731】 The terminal displays information received from the server on the user's screen. For example, it might display "XYZ Model Troubleshooting Guide - Estimated Work Time: 1.5 hours (emotions considered)." This allows the user to receive support tailored to their emotional state, enabling more efficient work. 【0732】 (Example 2) 【0733】 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". 【0734】 Conventional systems had the problem of not being able to take into account the emotional state of the user when selecting work instructions and estimating work time, resulting in ineffective work support. Furthermore, they could not improve work efficiency in accordance with the user's stress level or fatigue level, potentially lowering worker satisfaction. 【0735】 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. 【0736】 In this invention, the server includes a receiving means for receiving voice input or keyword input, a conversion means for converting data from the receiving means into text format, and a discrimination means for analyzing the text format data and identifying related documents. This makes it possible to analyze the user's emotional state, adjust the method of presenting work instructions based on the analysis results, and accurately calculate work time. 【0737】 A "receiving means" is an element that has the function of accepting voice input or keyword input from the user. 【0738】 A "conversion means" is an element that has the function of converting received audio or keyword data into text format. 【0739】 A "discrimination means" is an element that analyzes converted text data and has the function of identifying related documents. 【0740】 A "recording means" is an element that has the function of registering a specific document in an information recording device. 【0741】 A "time calculation means" is an element that has the function of calculating work time based on a specified document. 【0742】 A "state analysis means" is an element that has the function of analyzing the user's emotional state. 【0743】 A "modification mechanism" is an element that has the function of adjusting the presentation method based on the analyzed emotional state. 【0744】 "Display means" refers to an element that has the function of displaying the name of the specified document and the calculated work time on a display device. 【0745】 To implement this invention, a user terminal, a server, and an emotion analysis engine are used. The user inputs the task details via voice or keywords through the terminal. In this case, the terminal uses a speech recognition engine to convert the voice into text format and sends the data to the server. A commonly known speech recognition API can be used as the speech recognition engine. 【0746】 The server analyzes the received text data using a generative AI model to identify relevant documents. This generative AI model may utilize, for example, a model employing natural language processing technology. Documents are searched within a database, and multiple documents may be identified as needed. 【0747】 Simultaneously, an emotion analysis engine is used to analyze the user's emotional state. For example, emotions are detected by voice tone, word selection in text, and, in some cases, by using the device's camera. Based on these analysis results, the server adjusts the format and content of the documents presented to the user. 【0748】 The server calculates the time required for a task, taking into account the results of an emotion analysis. For example, if it determines that the user is experiencing high levels of stress, the server will adjust the task time to be extended. This ensures that the user receives support best suited to their situation. Finally, this information is sent to the terminal and presented to the user. 【0749】 As a concrete example, consider a scenario where a user enters the prompt "Create agenda for the next meeting." The server identifies the relevant document and, through sentiment analysis, assesses that the user is feeling slightly fatigued. Therefore, the server sends a document to the terminal, along with a simpler agenda template, indicating a work time of "2 hours," and displays it as "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)." 【0750】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0751】 Step 1: 【0752】 The user inputs their task details into the terminal using voice or keywords. The input data, either voice or text, is sent to the terminal. The terminal receives this input and, in the case of voice input, uses a speech recognition engine to convert the voice into text data. The output is then generated as text data and sent to the server. 【0753】 Step 2: 【0754】 The server receives text data sent from the terminal. The input text data is analyzed by a generative AI model. The server extracts relevant keywords and uses those keywords to search the document database. The output is a list of relevant documents. 【0755】 Step 3: 【0756】 The server uses an emotion analysis engine to analyze the user's emotional state from their input voice or text tone, word selection, or facial recognition data. Input includes voice tone and text data. The analysis determines the user's emotional state, and the resulting output is emotion analysis data. 【0757】 Step 4: 【0758】 The server adjusts how relevant documents are presented based on the analyzed emotional state data. If the user is experiencing stress, the server selects more concise and easier-to-understand documents. The input includes emotional analysis data and a list of relevant documents, and the output is the adjusted documents. 【0759】 Step 5: 【0760】 The server calculates the work time, taking into account the results of the emotion analysis. If the analyzed emotional state indicates that the user is experiencing fatigue or stress, it estimates a longer work time than usual. The input includes the emotional state and related document data, and the output is the estimated work time. 【0761】 Step 6: 【0762】 The server sends the final document name, the adjusted document, and the estimated work time to the terminal. The user's terminal receives this data and displays it to the user. Specifically, the output might show information like "Agenda Creation Guide - Estimated Work Time: 2 hours (Sentiment Considered)" on the screen. 【0763】 (Application Example 2) 【0764】 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". 【0765】 In modern industrial settings, problems frequently occur when workers operate robots, often leading to stress and fatigue during troubleshooting. Even in such situations, providing prompt and appropriate support to improve work efficiency is crucial. Furthermore, support that considers the emotional state of workers is necessary to enhance worker satisfaction. 【0766】 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. 【0767】 In this invention, the server includes a device for receiving voice input or keyword input, a conversion device for converting the information received from the device into text information, and an emotion analysis device for analyzing the user's emotional state. This makes it possible to provide prompt, emotionally sensitive, and appropriate support information even when the worker is experiencing stress or fatigue. 【0768】 "Voice input" refers to a format of information or instructions that a user can communicate to a system through their voice. 【0769】 "Keyword input" refers to a format in which users provide information to the system using a specific string of characters. 【0770】 "Device" refers to a hardware component used to perform a specific function. 【0771】 "Text information" refers to information that has been formalized as a string of characters and converted into a form that can be processed by a computer. 【0772】 A "conversion device" refers to a device used to convert data in one format to data in another format. 【0773】 An "analysis device" refers to a device used to analyze data and extract useful information from it. 【0774】 "Information" refers to the knowledge and data obtained from a specific database to meet the user's needs. 【0775】 A "storage device" refers to a device that has the function of holding data or information. 【0776】 A "registration device" refers to a device used to store specific data in a storage device or recording device. 【0777】 "Activity time" refers to the estimated time required for a particular task or operation. 【0778】 A "time estimation device" refers to a device used to predict the time required for a specific task. 【0779】 An "output device" refers to a device used to present data or information to a user. 【0780】 A "display device" refers to a device that presents information to a user visually. 【0781】 "Emotional state" refers to the state that expresses the user's psychological situation or mood. 【0782】 An "emotion analysis device" refers to a device that analyzes a user's emotional state and processes that information. 【0783】 A "regulating device" refers to a device used to change the output or operation of a system to conform to a certain standard. 【0784】 This invention provides a support system for work sites, and in particular, a system that realizes intelligent work support based on the emotional state of the user. This system mainly consists of a user terminal, a server, and an emotion analysis engine. 【0785】 When users encounter problems in factories or industrial settings, they use a terminal to input information via voice or keywords. The terminal uses a speech recognition engine to convert this input into text. The converted text information is sent to a server, which uses natural language processing techniques to analyze it and identify relevant documents from its database. 【0786】 Furthermore, the server uses an emotion analysis engine to analyze the user's emotional state. This emotion analysis engine determines emotions from factors such as voice tone, word choice, and input patterns. For example, if the user is experiencing stress, the system adjusts to provide a concise and easy-to-understand explanation. This adjustment is performed by an adjustment device. 【0787】 The server also estimates the activity time, taking into account the user's emotional state, along with the relevant manual, and sends it to the terminal. This allows the user to receive the manual best suited to their emotional state and perform their tasks with optimal efficiency. 【0788】 As a concrete example, consider a situation where a worker is having trouble removing a robot part during factory line work. The worker inputs "Tell me how to remove the part" into the terminal using voice commands, and the system presents a "part removal guide." Furthermore, if it senses the worker is stressed, it also provides additional messages such as, "It's okay even if this is your first time replacing a part; the procedure is simple." 【0789】 An example of a prompt message for a generating AI model is: "Please tell me how to provide a simple procedure and reassuring message to a worker who is under stress while replacing a robot part." 【0790】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0791】 Step 1: 【0792】 The terminal receives voice input or keyword input from the user. This input is converted into text information through a speech recognition engine. In this step, the input is the user's voice or keywords, and the output is text information. The speech recognition engine obtains the output by analyzing the waveform data of the input voice and converting it into a sequence of phonemes or words. 【0793】 Step 2: 【0794】 The server uses natural language processing techniques to analyze text information received from the terminal. This analysis searches the database for and identifies relevant documents. The input for this step is text information, and the output is the identifiers and links of the relevant documents. Natural language processing includes data processing such as morphological analysis and keyword extraction. 【0795】 Step 3: 【0796】 The server uses an emotion analysis engine to analyze the user's emotional state from text information. The input for this step is the user's text information, and the output is the determined emotional state (e.g., stress, fatigue, relief, etc.). Emotional features are extracted from the input's word choices and writing style, and these are used to determine the emotional state based on a statistical model. 【0797】 Step 4: 【0798】 The server adjusts the content and presentation method of the documents presented based on the analyzed emotional state, and sends this information to the terminal. The input for this step is the relevant documents and emotional state, and the output is the adjusted documents. Adjustments to the presentation method include simplifying the text and adding supplementary information. 【0799】 Step 5: 【0800】 The terminal presents the user with documents and activity times sent from the server. The input for this step is the adjusted document and activity time information, while the output is information that the user can visually confirm on the screen. The terminal assists in conveying information to the user through haptic feedback and voice guidance. 【0801】 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. 【0802】 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. 【0803】 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. 【0804】 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. 【0805】 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. 【0806】 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. 【0807】 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. 【0808】 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. 【0809】 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." 【0810】 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. 【0811】 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. 【0812】 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. 【0813】 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. 【0814】 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. 【0815】 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. 【0816】 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. 【0817】 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. 【0818】 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. 【0819】 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. 【0820】 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. 【0821】 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. 【0822】 The following is further disclosed regarding the embodiments described above. 【0823】 (Claim 1) 【0824】 An input means for receiving voice input or keyword input, 【0825】 A conversion means that converts the data received from the input means into text data, 【0826】 An analysis means for analyzing the aforementioned text data and identifying related documents, 【0827】 A registration means for registering the identified document in a recording device, 【0828】 Based on the aforementioned document, a time calculation means for calculating work time, 【0829】 A display means for displaying the document name and the work time on an output device, 【0830】 A system that includes this. 【0831】 (Claim 2) 【0832】 The system according to claim 1, which uses a speech recognition engine to convert the speech input into text data. 【0833】 (Claim 3) 【0834】 The system according to claim 1, wherein the analysis means searches a document database using natural language processing technology and identifies relevant documents. 【0835】 "Example 1" 【0836】 (Claim 1) 【0837】 A receiving means for receiving voice or keywords, 【0838】 A conversion means that converts the information received from the receiving means into character information, 【0839】 Processing means for processing the aforementioned character information and identifying related information materials, 【0840】 A registration means for registering the identified information materials on a recording medium, 【0841】 A time calculation means for calculating the time required for the work based on the aforementioned information materials, 【0842】 A display means for displaying the name of the information material and the required time on the output device, 【0843】 A system that includes this. 【0844】 (Claim 2) 【0845】 The system according to claim 1, wherein a speech recognition device is used to convert the speech into text information. 【0846】 (Claim 3) 【0847】 The system according to claim 1, wherein the processing means searches an information data database using natural language processing technology and identifies relevant information data. 【0848】 "Application Example 1" 【0849】 (Claim 1) 【0850】 A receiving means for receiving voice input or keyword input, 【0851】 A conversion means that converts the data received from the receiving means into character information, 【0852】 An analysis means for analyzing the aforementioned textual information and identifying related materials, 【0853】 A registration means for registering the identified material in a storage device, 【0854】 Based on the above-mentioned materials, a time estimation means for calculating work time, 【0855】 A display means for displaying the aforementioned document name and the aforementioned work time on a display device, 【0856】 A supply means that obtains specific procedures based on voice instructions and supplies information to the device, 【0857】 A mechanism that includes this. 【0858】 (Claim 2) 【0859】 The mechanism according to claim 1, which uses a speech recognition device to convert the speech input into text information. 【0860】 (Claim 3) 【0861】 The mechanism according to claim 1, wherein the analysis means searches a data database using language processing technology and identifies relevant data. 【0862】 "Example 2 of combining an emotion engine" 【0863】 (Claim 1) 【0864】 A receiving means for receiving voice input or keyword input, 【0865】 A conversion means for converting data from the receiving means into text format, 【0866】 A discrimination means for analyzing the aforementioned text format data and identifying related documents, 【0867】 A recording means for registering the identified document in an information recording device, 【0868】 A time calculation means for calculating work time based on the aforementioned document, 【0869】 A state analysis method for analyzing the user's emotional state, 【0870】 An adjustment means for adjusting the presentation method based on the aforementioned emotional state, 【0871】 A display means for showing the document name and the work time on a display device, 【0872】 A system that includes this. 【0873】 (Claim 2) 【0874】 The system according to claim 1, which uses speech recognition technology to convert the speech input into text format. 【0875】 (Claim 3) 【0876】 The system according to claim 1, wherein the discrimination means searches a document information base using natural language processing technology and identifies related documents. 【0877】 "Application example 2 when combining with an emotional engine" 【0878】 (Claim 1) 【0879】 A device that receives voice input or keyword input, 【0880】 A conversion device that converts information received from the aforementioned device into text information, 【0881】 An analysis device that analyzes the aforementioned text information and identifies related information, 【0882】 A registration device for registering the identified information in a storage device, 【0883】 A time estimation device that calculates activity time based on the aforementioned information, 【0884】 A display device that displays the aforementioned information name and the aforementioned activity time on an output device, 【0885】 An emotion analysis device that analyzes the emotional state of the user, 【0886】 An adjustment device that adjusts the method of presenting the information based on the aforementioned emotional state, 【0887】 A system that includes this. 【0888】 (Claim 2) 【0889】 The system according to claim 1, which uses a speech recognition device to convert the speech input into text information. 【0890】 (Claim 3) 【0891】 The system according to claim 1, wherein the analysis device searches a document database using natural language processing technology and identifies relevant information. [Explanation of symbols] 【0892】 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] An input means for receiving voice input or keyword input, A conversion means that converts the data received from the input means into text data, An analysis means for analyzing the aforementioned text data and identifying related documents, A registration means for registering the identified document in a recording device, Based on the aforementioned document, a time calculation means for calculating work time, A display means for displaying the document name and the work time on an output device, A system that includes this. [Claim 2] The system according to claim 1, which uses a speech recognition engine to convert the speech input into text data. [Claim 3] The system according to claim 1, wherein the analysis means searches a document database using natural language processing technology and identifies relevant documents.

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