system

Abstract

We provide the system. [Solution] An artificial intelligence device that learns different procedural rules and scrutinizes request information to verify its accuracy, A conversion means for automatically converting different data formats between multiple systems, A transmission means for transmitting the converted data to multiple information processing devices, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Due to differences in procedure rules and data formats among different information processing devices in an enterprise, it has been difficult to integrate in-house procedures. Since the "etiquette" of procedures is different for each system, employees have a great burden of understanding multiple different rules and appropriately inputting information, which has hindered efficient business operations. In such a situation, it is required to smooth the cooperation between systems within an enterprise and improve the efficiency of information management.

Means for Solving the Problems

[0005] To solve the above problems, this invention provides a system that allows an artificial intelligence device to learn different procedural rules and scrutinize request information to verify its accuracy. It also includes a conversion means for automatically converting different data formats between multiple information processing devices, and a transmission means for transmitting the converted data. This makes it possible to seamlessly execute different procedural rules, reduce the burden on employees, and achieve efficient information management.

[0006] An "artificial intelligence device" is a device that learns different procedural rules and has the function of scrutinizing requested information to verify its accuracy.

[0007] A "conversion means" is a means that has the function of automatically converting different data formats used by multiple information processing devices.

[0008] "Transmission means" refers to means for transmitting the converted data to multiple information processing devices.

[0009] A "notification method" is a means that has the function of requesting additional information if there is a shortage of information in the request.

[0010] A "result notification means" is a means of collecting responses from multiple systems and notifying the client of the processing results. [Brief explanation of the drawing]

[0011] [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, when an emotion engine is combined. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the 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.

[0015] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] This invention is a system designed to streamline procedures between multiple information processing devices within a company. The system receives request information from a user, an artificial intelligence device examines that information, and enables the automatic conversion and transmission of the data necessary for the procedure. The following describes a specific embodiment of this invention.

[0033] The server receives the request information from the user and passes it on to the artificial intelligence (AI) device. The AI ​​device analyzes the received information in detail and verifies the accuracy of the procedure. For example, it determines whether the new company name conforms to existing regulations. If any necessary information is missing during this process, the server notifies the user and requests that they provide the additional information.

[0034] Once all the necessary information is gathered, the artificial intelligence device converts the data to conform to the standards of multiple information processing devices. This conversion means that information suitable for each system with different formats can be generated. The converted data is then transmitted to the corresponding system via a server.

[0035] The server aggregates responses from each information processing device and notifies the user of the final processing result. This notification may include information on the completion of the procedure and any errors. By utilizing this result notification method, users can check the progress of each procedure in real time.

[0036] For example, if a user requests to change their company name to a "new company name," the server receives the request, and an artificial intelligence system verifies whether the "new company name" is legitimate. Once all the necessary information is gathered, a conversion tool is used to prepare the data in the appropriate format for the HR and financial systems, and then it is sent to each system. Upon completion of all processing, the server notifies the user of the success of the procedure. This model allows companies to integrate internal procedures quickly and accurately, optimizing human resources.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] The user enters and submits request information to the server. This request information includes details of changes to the company name and address.

[0040] Step 2:

[0041] When the server receives request information from a user, it immediately passes that information to the artificial intelligence device. Here, the received data is checked to ensure it is in the correct format, along with referencing customer information.

[0042] Step 3:

[0043] The artificial intelligence system scrutinizes the request information and checks whether each item conforms to the business standards. For example, in the case of an address change, it verifies that the postal code and city / town name are accurately entered.

[0044] Step 4:

[0045] If necessary information is missing or incomplete, the server will notify the user of the missing or incorrect information and request that they provide the additional information. The user will then review the requested information again and send the completed information back to the server.

[0046] Step 5:

[0047] The artificial intelligence device re-verifies the information, and if there are no deficiencies, converts the data into the format required by each information processing device for the procedure. Through the conversion means, the data is appropriately formatted for systems with different formats.

[0048] Step 6:

[0049] The server sends the transformed data via the API to each information processing device. Each device receives the data and performs internal processing. For example, this could involve changing the company name in the HR system or updating the address in the financial system.

[0050] Step 7:

[0051] The server checks whether each information processing device has completed its processing or if any errors have occurred, and receives the response. If all procedures are completed, the server notifies the user of the results. This notification will include information that the procedures were completed successfully and, if there were any problems, how to deal with them.

[0052] (Example 1)

[0053] 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."

[0054] The aim is to solve the problem of inefficient procedures between multiple information processing devices in companies, which lead to processing delays and errors. Another challenge is the heavy burden of manual conversion work when handling different data formats.

[0055] 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.

[0056] In this invention, the server includes a computing device that learns different operating procedures and analyzes request data to verify accuracy, a conversion means that automatically converts different data arrangements between multiple devices, and a transmission means that transfers the converted data to multiple information processing devices. This enables increased efficiency in procedures and automation of data conversion work.

[0057] A "calculation unit" is a device that learns different operating procedures and analyzes received request data to verify its accuracy.

[0058] A "conversion means" is a mechanism for automatically converting data formats between multiple devices with different data formats.

[0059] "Transmission means" refers to means for transferring converted data to multiple information processing devices.

[0060] A "verification method" is a method for requesting additional data based on a thorough examination of the requested data.

[0061] A "notification method" is a means of collecting responses from multiple information processing devices and reporting the final processing results to the client.

[0062] For this invention to be implemented, the server, terminal, and user must each fulfill their respective roles, and the entire system must function efficiently. The server first receives request data transmitted from the user via the terminal. This request data may relate to procedures such as registering a new company name within a company or format conversion.

[0063] The server transfers the received request data to an artificial intelligence (AI) device. This AI device possesses advanced computing capabilities, including generative AI models, and performs learning of different operational procedures and data analysis. Specific software includes natural language processing techniques and pattern matching algorithms. This allows for checking the accuracy and consistency of the data.

[0064] The artificial intelligence device sends notifications to the server as needed, prompting the user to provide additional information if the requested data is incomplete. This exchange is carried out quickly by the user entering the additional information from their terminal and resending it.

[0065] Once all the necessary information is gathered, the artificial intelligence device converts the data format. This conversion process automatically handles data conversion between multiple devices with different data structures, using conversion tools. For example, it can convert JSON data to CSV format and generate a data format compatible with a specific information processing device.

[0066] The generated data is transferred from the server to multiple information processing devices, where it is processed appropriately. The server then integrates the responses from each device and notifies the user of the final processing result. This notification may include confirmation of the procedure's completion as well as error information.

[0067] As a concrete example, consider a case where a user changes their company name to "New Company Name." The user sends a request from their terminal, and the server forwards the request to an artificial intelligence (AI) device. The AI ​​device verifies compliance with laws and regulations and notifies the user via the server of any missing information. In this case, an example of a prompt message might be, "Please begin the necessary procedures to register the new company name. Please ensure compliance with legal regulations and prepare and submit data for the HR and financial systems." This allows companies to integrate procedures efficiently and accurately and optimize resources.

[0068] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0069] Step 1:

[0070] The user uses a terminal to input the necessary request data for the procedure and sends it to the server. Specifically, the user enters the company name and related information into a form and clicks the "Submit" button. The entered data is sent to the server as output. At this point, the output is the raw data entered by the user.

[0071] Step 2:

[0072] The server temporarily holds the received request data and transfers it to the computing unit. The input is the raw data received from the user, and the output is the procedure for passing that data to the computing unit. Specifically, after the server confirms receipt of the data, it formats it into the appropriate format and transfers it. This transferred data becomes the input to the computing unit.

[0073] Step 3:

[0074] The computing unit uses a generation AI model to analyze the received data. Here, it verifies whether the "new company name" complies with legal regulations. The input is formatted request data, and the output is the analysis result. Specific operations include matching against a registered database and comparing against a blacklist. The analysis result outputs the verification of legitimacy.

[0075] Step 4:

[0076] The server receives the analysis results from the computing unit to verify that all the necessary information is available. The input is the analysis results, and the output is a pass / fail status indicating whether the information is sufficient. Specifically, based on the analysis results, if there is any missing information, the server prepares to send a notification to the user.

[0077] Step 5:

[0078] The server sends a notification to the user requesting additional information if any is missing. The input is the notification content based on the previous pass / fail decision, and the output is the notification message to the user. Specifically, a dialog box is displayed on the user's terminal requesting additional input. The user receives the notification, re-enters the necessary information, and submits it.

[0079] Step 6:

[0080] After confirming that all necessary information is available, the processing unit performs data conversion. The input is the complete request data, and the output is the converted data. Specifically, this involves format conversion from JSON to CSV. This ensures that the output data is adaptable to different data processing devices.

[0081] Step 7:

[0082] The server transfers the converted data to multiple information processing devices. The input is the converted data, and the output is the accurate data delivery to the multiple devices. Specific operations include monitoring and logging of data delivery.

[0083] Step 8:

[0084] The server collects processing responses from all information processing devices and notifies the user of the final processing result. The input is the response data from each device, and the output is the summarized processing result. Specifically, it sends a notification to the terminal, allowing the user to confirm the success or error information of the process. This notification enables the user to recognize the completion of the procedure.

[0085] (Application Example 1)

[0086] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0087] In today's information processing environment, different procedural norms and data formats exist across multiple information processing devices, making it difficult to manage and operate them uniformly. Furthermore, efficient and accurate management is required for information input and verification, but this is difficult to achieve with conventional systems. It is necessary to solve these problems and improve the efficiency and accuracy of information processing.

[0088] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0089] In this invention, the server includes an intelligent device that acquires different procedural norms, analyzes request information, and verifies its accuracy; a conversion means for automatically converting and managing different information formats between multiple information processing devices; and a means for inputting and verifying information via a portable electronic device or display device operated by the user. This enables improved efficiency and accuracy in information processing.

[0090] "Different procedural norms" refer to the individual standards and rules that various information processing devices and systems possess.

[0091] An "intelligent device that analyzes requested information and verifies its accuracy" is a device equipped with artificial intelligence that automatically analyzes input information and determines whether it should be processed appropriately.

[0092] A "conversion means for automatically converting and managing different information formats" is a means that has the function of appropriately converting and organizing information across diverse formats based on common standards.

[0093] "A user-operated portable electronic device or display device" refers to a portable electronic device used for inputting or checking information, such as a smartphone, tablet, or head-mounted display.

[0094] "Communication means for transmitting converted information" refers to means for transmitting information to a specific device or system after it has been appropriately converted.

[0095] A "signaling means for requesting supplementary information" is a means for sending a signal to notify the user if there is insufficient input information and to request additional information.

[0096] "Result presentation means for presenting results to the operator" refers to functions or devices that enable the display of information processing results to the user in an easily understandable manner.

[0097] To realize this invention, the server first receives the request information and provides it to the intelligent device. The intelligent device then analyzes the request information in detail, using, for example, a natural language processing library such as Python, and verifies its accuracy. If the analyzed information is deemed incomplete, the server notifies the user and requests the provision of any additional information.

[0098] After the information is confirmed to be complete, the server uses a conversion mechanism that automatically converts between different information formats. This conversion mechanism uses technologies such as REST APIs to format the information according to the requirements of each information processing device. The information thus prepared is then transmitted from the server to the multiple information processing devices as converted information.

[0099] Furthermore, responses from information processing devices acquired by the server are collected, and the intelligent device notifies the user of the success / failure result. Users can use smartphones, tablets, head-mounted displays, etc., to check the information transmission status and results in real time. As a specific example, when setting up a new device, request information such as "Install new server A01" is entered. The AI ​​analyzes this information and sends it to each system in the specified format, thereby centrally managing and streamlining multiple procedures.

[0100] As an example of a prompt message, the user can enter, "Please add a new server to the data center. The server name is 'Server A01'. Please proceed with the procedure, including the relevant network settings," which will allow the procedure to proceed smoothly. This invention efficiently manages procedures that span multiple systems and reduces the burden on the user.

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

[0102] Step 1:

[0103] The server receives request information sent by the user. This request information includes details about device setup and registration. The server prepares this information for transfer to the intelligent device. The input is the user's request data, and the output is the data converted into a format for parsing.

[0104] Step 2:

[0105] The intelligent device analyzes the received request information using a generative AI model. At this stage, it verifies the accuracy of the information and determines if there are any deficiencies. Natural language processing is used for the analysis to check the integrity of the data. The input is the request data formatted in step 1, and the output is the analysis result and any supplementary information that should be notified to the user as needed.

[0106] Step 3:

[0107] Based on the analysis results, the server sends a notification to the user requesting supplementary information. This notification is displayed on the user's device, prompting them to enter additional information. The input here is a request for supplementary information generated from the analysis results, and the output is the supplementary information request notification displayed on the device.

[0108] Step 4:

[0109] The user inputs the requested supplementary information on the terminal and sends it to the server. The server receives this information and resends it to the intelligent device. The input is the supplementary information newly provided by the user, and the output is data whose completeness has been confirmed.

[0110] Step 5:

[0111] Intelligent devices perform information format conversion using complete data. They convert and manage data in formats suitable for different information processing devices. The input is data that has been verified for completeness, and the output is data converted to a different system format.

[0112] Step 6:

[0113] The server transmits the converted data to each information processing device. The data is transmitted to the necessary systems using communication methods. The input is the converted data from the intelligent device, and the output is the data received by each destination device.

[0114] Step 7:

[0115] The server aggregates the results received from the information processing devices and notifies the user of the results via an intelligent device. The user can check the success or failure of the procedure through the terminal. The input is the response data from each information processing device, and the output is the result notification presented to the user.

[0116] 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.

[0117] This invention is a system that recognizes and takes into account user emotions during internal corporate procedures. The system receives request information from users and combines artificial intelligence and an emotion engine into the process, enabling efficient and human-centered responses. Specific embodiments of this invention are described below.

[0118] When a user submits request information to the server, the server immediately passes that information to the artificial intelligence (AI) device and the emotion engine. The AI ​​device scrutinizes the information and determines whether the procedure is appropriate. In parallel, the emotion engine analyzes the user's emotions and understands their emotional state at the time of submitting the request information. For example, if the user is nervous, the system can determine that appropriate information or explanations are needed.

[0119] When all the necessary information for the procedure is available, the emotion engine uses the analysis results to adjust how and when the notification system delivers additional information. For example, it can make notifications for missing information more discreet or gentler in its wording.

[0120] Subsequently, the artificial intelligence device converts the data to conform to the specifications of multiple information processing devices. At this stage, the analysis results of the emotion engine may influence processing priorities and the progression of procedures. The conversion process ensures the data is formatted accurately and transmitted to each information processing device via a server.

[0121] Once all processing is complete, the emotion engine selects the wording and method for notifying the requester of the results. For example, if it determines that the user is seeking reassurance upon successful completion of the request, the notification will be delivered using appropriate reassuring language. The server then communicates this information to the user, confirming that the procedure proceeded without any issues. This improves the user experience and is expected to lead to smoother business operations.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] The user enters and submits request information to the server. The interface is optimized to minimize the psychological burden of input, taking emotions into consideration.

[0125] Step 2:

[0126] As soon as the server receives the request information, the emotion engine analyzes the user's voice and visual elements to infer the user's emotional state. For example, the pitch and speed of the voice tone and the mouse speed during input are among the elements analyzed.

[0127] Step 3:

[0128] After the emotion engine analyzes the user's emotional state, it passes the results to the server, which then works with an artificial intelligence device to refine the information. If the emotion indicates anxiety, the server prioritizes informing the user that it understands the request.

[0129] Step 4:

[0130] The artificial intelligence system scrutinizes the request information and verifies that all necessary procedural information is present. If any information is missing, the server gently and appropriately notifies the user of the missing information and requests any additional information needed.

[0131] Step 5:

[0132] The artificial intelligence device converts data to match the format of multiple information processing devices. Based on the analysis results of the emotion engine, it may prioritize which system should begin processing the converted data.

[0133] Step 6:

[0134] The server sends the converted data to each information processing device. Depending on the results of the emotion engine, the greeting and message sent may be adjusted.

[0135] Step 7:

[0136] Each information processing unit notifies the server when processing is complete, and the server receives the results. If the emotion engine recognizes dissatisfaction or anxiety, the result notification system communicates the situation to the user in reassuring terms.

[0137] Step 8:

[0138] The server notifies the user that the procedure is complete. At this time, the sentiment engine selects the best words. Efforts are made to enhance the user experience with a positive message that emphasizes the success of the procedure.

[0139] (Example 2)

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

[0141] In corporate procedures, there is a problem where the user experience is insufficient and the smooth progress of business is hindered when processes are carried out mechanically without considering the user's feelings. Furthermore, there is the issue of inefficiency in procedures between multiple systems with different information formats.

[0142] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0143] In this invention, the server includes artificial intelligence means for scrutinizing request information and determining whether the procedure is appropriate, emotion recognition means for analyzing the user's emotional state, notification adjustment means for adjusting notification content based on the analyzed emotion information, data conversion means for automatically converting different data formats, and data transmission means for transmitting the converted information to multiple information processing means. This enables emotion-based user interaction, making the procedure more efficient and human-centered.

[0144] "Artificial intelligence means" refers to a technological element that has the function of analyzing request information and determining the appropriateness of the procedure.

[0145] "Emotion recognition means" refers to a technological element that analyzes the emotional state from the user's request information and extracts that state.

[0146] A "notification adjustment mechanism" is a technological element that has the function of adjusting the content and method of notifications sent to the user based on analyzed emotional information.

[0147] A "data conversion means" is a technical element that has the function of automatically converting data formats used between different information processing systems to ensure compatibility.

[0148] A "data transmission means" is a technical element that has the function of transmitting converted information to multiple information processing devices.

[0149] This invention is a system that recognizes user emotions in corporate procedures, making the process more effective and humane. Specifically, it uses a server that receives requests, artificial intelligence means, emotion recognition means, notification adjustment means, data conversion means, and data transmission means. The server first passes the request information sent by the user to the artificial intelligence means, which analyzes the request information and determines the appropriateness of the procedure. Next, the emotion recognition means analyzes the user's emotional state from the request information. Based on this, the notification adjustment means determines the appropriate notification method and content. For example, if the user is feeling anxious or tense, a gentler expression may be used. In addition, the data conversion means converts the information into a format that can be easily accepted by other information processing devices as needed, and the data transmission means is responsible for actually transmitting that information.

[0150] Specifically, the system's software elements include generative AI models for text analysis and natural language processing. For example, it employs sentiment recognition algorithms to identify emotions within text and natural language generation engines to generate appropriate tones. Data exchange is efficiently handled through REST APIs and message queues.

[0151] As a concrete example, consider a scenario where a user is in the process of purchasing a new product. The server, using its emotion recognition system, determines that the user is feeling anxious and creates a notification that takes this into consideration, thereby reducing the user's anxiety. An example of a prompt message in this case might be: "Create a reassuring notification message for users who are feeling anxious about the product purchase process."

[0152] The introduction of such systems is expected to make internal corporate procedures more efficient and emotionally sensitive, thereby improving the user experience.

[0153] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0154] Step 1:

[0155] The user sends request information regarding internal company procedures to the server. The server receives the request information and provides this data as input to an artificial intelligence system. The request information includes the type of procedure and related details.

[0156] Step 2:

[0157] The server uses artificial intelligence to analyze the received request information and determine whether the procedure is appropriate. The analysis utilizes a generative AI model to scrutinize the accuracy and completeness of the information. The output of this step is a report evaluating the appropriateness of the procedure.

[0158] Step 3:

[0159] The server passes the request information to the emotion recognition system. The emotion recognition system receives input data from the request information to analyze emotions. This analysis uses a natural language processing algorithm to understand the user's emotional state. The output is an emotion analysis report.

[0160] Step 4:

[0161] The server uses notification adjustment mechanisms to adjust the content of notifications sent to the user based on the sentiment analysis report. Specifically, if the user is stressed, the tone of the notification message is softened, and the information is presented in a gentler manner. The input for this step is the sentiment analysis report, and the output is the adjusted notification message.

[0162] Step 5:

[0163] The server uses data conversion means to convert procedural information into a format that can be easily handled by other systems. This ensures data compatibility between different information processing systems. The input is procedural information, and the output is the converted data format.

[0164] Step 6:

[0165] The server uses a data transmission mechanism to send the converted data to various information processing devices. These devices are systems that support the procedures. After transmission, an operation is performed to verify that the data is processed correctly by the other systems.

[0166] Step 7:

[0167] The server uses emotion recognition to notify the client with appropriate language based on the processing results. It generates messages that reflect the client's emotional state, such as using reassuring language upon success. The input is the processing result, and the output is the adjusted final notification message.

[0168] (Application Example 2)

[0169] 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 device 14 will be referred to as the "terminal."

[0170] In modern information processing, improving usability is paramount, and there is a growing need for responses that take emotions into consideration. However, conventional systems have struggled to provide appropriate information and notifications that respond to user emotions, often resulting in mechanical and one-sided responses. Therefore, the challenge is to reduce the stress users experience and achieve more human-centered responses.

[0171] 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.

[0172] In this invention, the server includes an information processing device that learns different procedural rules and scrutinizes request information to verify its accuracy, an emotion estimation means that recognizes and analyzes the emotions of the requester, and a data formatting means that automatically converts different data formats between multiple systems. This enables the provision of appropriate information and notifications that take into account the user's emotions.

[0173] An "information processing device" is a device that learns different procedural rules and has the function of scrutinizing requested information and verifying its accuracy.

[0174] "Emotion estimation methods" are means for recognizing and analyzing the emotions of a client.

[0175] A "data formatting method" is a means for automatically converting different data formats between multiple systems.

[0176] "Communication means" refers to a means for transmitting converted data to multiple information processing devices.

[0177] An "information presentation method" is a means of notifying information in an appropriate manner to the recipient, based on the analysis results of an emotion estimation method.

[0178] A "results reporting means" is a means for aggregating responses from multiple information processing devices and notifying the client of the processing results in an expression appropriate to the analysis results of the emotion estimation means.

[0179] The system that realizes this invention is primarily server-centered and functions by combining multiple means. The server consists of an information processing device, emotion estimation means, data formatting means, communication means, information presentation means, and result reporting means.

[0180] First, the user's request information is sent to the server. The information processing device receives this request information and verifies its accuracy according to procedural rules. A typical server or cloud-based processing system is used to do this.

[0181] Next, the emotion estimation system acquires the user's voice and video data and recognizes and analyzes their emotions. This system utilizes OpenCV and speech analysis technologies, and, if necessary, platforms such as IBM Watson® Tone Analyzer are used. The analyzed emotion information is then used in other parts of the system.

[0182] Subsequently, a data formatting tool automatically converts the data into different formats. This conversion uses APIs and software libraries for data format conversion. Then, the converted data is sent to other processing systems using a communication tool.

[0183] The information presentation system adjusts the content and expression of its responses to the user based on the analysis results obtained from the emotion estimation system. This enables more appropriate responses that take the user's emotions into consideration. Specifically, it uses generative AI models such as "GPT-4 (registered trademark)" to conduct text-based communication.

[0184] Furthermore, the results reporting means aggregates responses from other information processing devices and notifies the user of the final processing result. In this process, too, a prompt message is constructed that adjusts the expression and timing of the content based on the sentiment estimation results.

[0185] For example, if a user is feeling stressed, the emotion estimation tool detects this, and the information presentation tool generates a message such as, "Please take some time to relax today." In this way, a more reassuring response can be provided to the user. As an example of a prompt, by instructing the system to "Suggest appropriate responses if the user is feeling stressed," specific countermeasures will be generated.

[0186] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0187] Step 1:

[0188] The server receives request information from users. The input is the request information sent by the user from their terminal, and the output is the storage and initial confirmation of that information. Specifically, the server records the request details in the database and prepares this information for the next processing step.

[0189] Step 2:

[0190] The server uses an information processing device to examine the received request information. The input is the request information saved in step 1, and the output is the result of the judgment on whether the request conforms to the procedural rules and any necessary corrections. Here, the accuracy of the request content and the completeness of the required information are confirmed by comparing it with a pre-trained procedural rule database.

[0191] Step 3:

[0192] The server analyzes the user's emotions using emotion estimation tools. It receives user audio and video data as input and outputs the results of the emotion analysis. Specifically, it utilizes tools such as "IBM Watson Tone Analyzer" to estimate the emotional state based on the user's tone and facial expressions and generates evaluation results.

[0193] Step 4:

[0194] The server automatically converts different data formats using data formatting tools. The input consists of request information and analysis results, while the output is data converted to a format suitable for different systems. Specifically, it converts the data to the required format via an API and prepares it for transmission to each system.

[0195] Step 5:

[0196] The server transmits the converted data to the information processing device using a communication method. The input is the converted data obtained in step 4, and the output allows each information processing device to receive the processing results. Here, a communication protocol is used to transfer the data to the appropriate destination.

[0197] Step 6:

[0198] The server uses information presentation tools to notify the user in a way that is appropriate to their sentiment analysis results. The input is the sentiment analysis results and processing results, and the output is the notification content for the user. A generative AI model such as "GPT-4" is used to create a message based on the prompt and send it to the user.

[0199] Step 7:

[0200] The server notifies the user of the aggregated processing results using a results reporting mechanism. Inputs are responses from each information processing device and sentiment analysis results, while output is the final result notification to the user. The notification uses polite language tailored to the user's emotions, and is designed to make the processing results easy for the user to understand.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] [Second Embodiment]

[0205] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0206] 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.

[0207] 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).

[0208] 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.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] 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".

[0217] This invention is a system designed to streamline procedures between multiple information processing devices within a company. The system receives request information from a user, an artificial intelligence device examines that information, and enables the automatic conversion and transmission of the data necessary for the procedure. The following describes a specific embodiment of this invention.

[0218] The server receives the request information from the user and passes it on to the artificial intelligence (AI) device. The AI ​​device analyzes the received information in detail and verifies the accuracy of the procedure. For example, it determines whether the new company name conforms to existing regulations. If any necessary information is missing during this process, the server notifies the user and requests that they provide the additional information.

[0219] Once all the necessary information is gathered, the artificial intelligence device converts the data to conform to the standards of multiple information processing devices. This conversion means that information suitable for each system with different formats can be generated. The converted data is then transmitted to the corresponding system via a server.

[0220] The server aggregates responses from each information processing device and notifies the user of the final processing result. This notification may include information on the completion of the procedure and any errors. By utilizing this result notification method, users can check the progress of each procedure in real time.

[0221] For example, if a user requests to change their company name to a "new company name," the server receives the request, and an artificial intelligence system verifies whether the "new company name" is legitimate. Once all the necessary information is gathered, a conversion tool is used to prepare the data in the appropriate format for the HR and financial systems, and then it is sent to each system. Upon completion of all processing, the server notifies the user of the success of the procedure. This model allows companies to integrate internal procedures quickly and accurately, optimizing human resources.

[0222] The following describes the processing flow.

[0223] Step 1:

[0224] The user enters and submits request information to the server. This request information includes details of changes to the company name and address.

[0225] Step 2:

[0226] When the server receives request information from a user, it immediately passes that information to the artificial intelligence device. Here, the received data is checked to ensure it is in the correct format, along with referencing customer information.

[0227] Step 3:

[0228] The artificial intelligence system scrutinizes the request information and checks whether each item conforms to the business standards. For example, in the case of an address change, it verifies that the postal code and city / town name are accurately entered.

[0229] Step 4:

[0230] If necessary information is missing or incomplete, the server will notify the user of the missing or incorrect information and request that they provide the additional information. The user will then review the requested information again and send the completed information back to the server.

[0231] Step 5:

[0232] The artificial intelligence device re-verifies the information, and if there are no deficiencies, converts the data into the format required by each information processing device for the procedure. Through the conversion means, the data is appropriately formatted for systems with different formats.

[0233] Step 6:

[0234] The server sends the transformed data via the API to each information processing device. Each device receives the data and performs internal processing. For example, this could involve changing the company name in the HR system or updating the address in the financial system.

[0235] Step 7:

[0236] The server checks whether each information processing device has completed its processing or if any errors have occurred, and receives the response. If all procedures are completed, the server notifies the user of the results. This notification will include information that the procedures were completed successfully and, if there were any problems, how to deal with them.

[0237] (Example 1)

[0238] 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."

[0239] The aim is to solve the problem of inefficient procedures between multiple information processing devices in companies, which lead to processing delays and errors. Another challenge is the heavy burden of manual conversion work when handling different data formats.

[0240] 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.

[0241] In this invention, the server includes a computing device that learns different operating procedures and analyzes request data to verify accuracy, a conversion means that automatically converts different data arrangements between multiple devices, and a transmission means that transfers the converted data to multiple information processing devices. This enables increased efficiency in procedures and automation of data conversion work.

[0242] A "calculation unit" is a device that learns different operating procedures and analyzes received request data to verify its accuracy.

[0243] A "conversion means" is a mechanism for automatically converting data formats between multiple devices with different data formats.

[0244] "Transmission means" refers to means for transferring converted data to multiple information processing devices.

[0245] A "verification method" is a method for requesting additional data based on a thorough examination of the requested data.

[0246] A "notification method" is a means of collecting responses from multiple information processing devices and reporting the final processing results to the client.

[0247] For this invention to be implemented, the server, terminal, and user must each fulfill their respective roles, and the entire system must function efficiently. The server first receives request data transmitted from the user via the terminal. This request data may relate to procedures such as registering a new company name within a company or format conversion.

[0248] The server transfers the received request data to an artificial intelligence (AI) device. This AI device possesses advanced computing capabilities, including generative AI models, and performs learning of different operational procedures and data analysis. Specific software includes natural language processing techniques and pattern matching algorithms. This allows for checking the accuracy and consistency of the data.

[0249] The artificial intelligence device sends notifications to the server as needed, prompting the user to provide additional information if the requested data is incomplete. This exchange is carried out quickly by the user entering the additional information from their terminal and resending it.

[0250] Once all the necessary information is gathered, the artificial intelligence device converts the data format. This conversion process automatically handles data conversion between multiple devices with different data structures, using conversion tools. For example, it can convert JSON data to CSV format and generate a data format compatible with a specific information processing device.

[0251] The generated data is transferred from the server to multiple information processing devices, where it is processed appropriately. The server then integrates the responses from each device and notifies the user of the final processing result. This notification may include confirmation of the procedure's completion as well as error information.

[0252] As a concrete example, consider a case where a user changes their company name to "New Company Name." The user sends a request from their terminal, and the server forwards the request to an artificial intelligence (AI) device. The AI ​​device verifies compliance with laws and regulations and notifies the user via the server of any missing information. In this case, an example of a prompt message might be, "Please begin the necessary procedures to register the new company name. Please ensure compliance with legal regulations and prepare and submit data for the HR and financial systems." This allows companies to integrate procedures efficiently and accurately and optimize resources.

[0253] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0254] Step 1:

[0255] The user uses a terminal to input the necessary request data for the procedure and sends it to the server. Specifically, the user enters the company name and related information into a form and clicks the "Submit" button. The entered data is sent to the server as output. At this point, the output is the raw data entered by the user.

[0256] Step 2:

[0257] The server temporarily holds the received request data and transfers it to the computing unit. The input is the raw data received from the user, and the output is the procedure for passing that data to the computing unit. Specifically, after the server confirms receipt of the data, it formats it into the appropriate format and transfers it. This transferred data becomes the input to the computing unit.

[0258] Step 3:

[0259] The computing unit uses a generation AI model to analyze the received data. Here, it verifies whether the "new company name" complies with legal regulations. The input is formatted request data, and the output is the analysis result. Specific operations include matching against a registered database and comparing against a blacklist. The analysis result outputs the verification of legitimacy.

[0260] Step 4:

[0261] The server receives the analysis results from the computing unit to verify that all the necessary information is available. The input is the analysis results, and the output is a pass / fail status indicating whether the information is sufficient. Specifically, based on the analysis results, if there is any missing information, the server prepares to send a notification to the user.

[0262] Step 5:

[0263] The server sends a notification to the user requesting additional information if any is missing. The input is the notification content based on the previous pass / fail decision, and the output is the notification message to the user. Specifically, a dialog box is displayed on the user's terminal requesting additional input. The user receives the notification, re-enters the necessary information, and submits it.

[0264] Step 6:

[0265] After confirming that all necessary information is available, the processing unit performs data conversion. The input is the complete request data, and the output is the converted data. Specifically, this involves format conversion from JSON to CSV. This ensures that the output data is adaptable to different data processing devices.

[0266] Step 7:

[0267] The server transfers the converted data to multiple information processing devices. The input is the converted data, and the output is the accurate data delivery to the multiple devices. Specific operations include monitoring and logging of data delivery.

[0268] Step 8:

[0269] The server collects processing responses from all information processing devices and notifies the user of the final processing result. The input is the response data from each device, and the output is the summarized processing result. Specifically, it sends a notification to the terminal, allowing the user to confirm the success or error information of the process. This notification enables the user to recognize the completion of the procedure.

[0270] (Application Example 1)

[0271] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0272] In today's information processing environment, different procedural norms and data formats exist across multiple information processing devices, making it difficult to manage and operate them uniformly. Furthermore, efficient and accurate management is required for information input and verification, but this is difficult to achieve with conventional systems. It is necessary to solve these problems and improve the efficiency and accuracy of information processing.

[0273] 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.

[0274] In this invention, the server includes an intelligent device that acquires different procedural norms, analyzes request information, and verifies its accuracy; a conversion means for automatically converting and managing different information formats between multiple information processing devices; and a means for inputting and verifying information via a portable electronic device or display device operated by the user. This enables improved efficiency and accuracy in information processing.

[0275] "Different procedural norms" refer to the individual standards and rules that various information processing devices and systems possess.

[0276] An "intelligent device that analyzes requested information and verifies its accuracy" is a device equipped with artificial intelligence that automatically analyzes input information and determines whether it should be processed appropriately.

[0277] A "conversion means for automatically converting and managing different information formats" is a means that has the function of appropriately converting and organizing information across diverse formats based on common standards.

[0278] "A user-operated portable electronic device or display device" refers to a portable electronic device used for inputting or checking information, such as a smartphone, tablet, or head-mounted display.

[0279] "Communication means for transmitting converted information" refers to means for transmitting information to a specific device or system after it has been appropriately converted.

[0280] A "signaling means for requesting supplementary information" is a means for sending a signal to notify the user if there is insufficient input information and to request additional information.

[0281] "Result presentation means for presenting results to the operator" refers to functions or devices that enable the display of information processing results to the user in an easily understandable manner.

[0282] To realize this invention, the server first receives the request information and provides it to the intelligent device. The intelligent device then analyzes the request information in detail, using, for example, a natural language processing library such as Python, and verifies its accuracy. If the analyzed information is deemed incomplete, the server notifies the user and requests the provision of any additional information.

[0283] After the information is confirmed to be complete, the server uses a conversion mechanism that automatically converts between different information formats. This conversion mechanism uses technologies such as REST APIs to format the information according to the requirements of each information processing device. The information thus prepared is then transmitted from the server to the multiple information processing devices as converted information.

[0284] Furthermore, the response from the information processing device acquired by the server is collected, and the intelligent device notifies the user of the success / failure result. The user can utilize a smartphone, tablet, head-mounted display, etc. to confirm the information transmission status and result in real time. As a specific example, when setting up a new device, request information such as "Install new server A01" is input. The AI analyzes this information and transmits it in the format specified for each system, thereby centrally managing and streamlining multiple procedures.

[0285] As an example of the prompt sentence, when the user inputs "Please add a new server to the data center. The server name is 'Server A01'. Please proceed with the procedure including the related network settings.", the procedure proceeds smoothly. This invention efficiently manages procedures spanning multiple systems and reduces the burden on the user.

[0286] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0287] Step 1:

[0288] The server receives the request information transmitted from the user. This request information includes content related to device setup and registration. The server prepares to transfer this information to the intelligent device. The input is the user's request data, and the output is converted into a format for analyzing it.

[0289] Step 2:

[0290] The intelligent device analyzes the received request information using the generated AI model. At this stage, the accuracy of the information is confirmed, and it is determined whether there are any deficiencies. Natural language processing is used for analysis to check the data consistency. The input is the request data formatted in Step 1, and the output is the analysis result and, if necessary, complementary information to be notified to the user is generated.

[0291] Step 3:

[0292] Based on the analysis results, the server sends a notification to the user requesting supplementary information. This notification is displayed on the user's device, prompting them to enter additional information. The input here is a request for supplementary information generated from the analysis results, and the output is the supplementary information request notification displayed on the device.

[0293] Step 4:

[0294] The user inputs the requested supplementary information on the terminal and sends it to the server. The server receives this information and resends it to the intelligent device. The input is the supplementary information newly provided by the user, and the output is data whose completeness has been confirmed.

[0295] Step 5:

[0296] Intelligent devices perform information format conversion using complete data. They convert and manage data in formats suitable for different information processing devices. The input is data that has been verified for completeness, and the output is data converted to a different system format.

[0297] Step 6:

[0298] The server transmits the converted data to each information processing device. The data is transmitted to the necessary systems using communication methods. The input is the converted data from the intelligent device, and the output is the data received by each destination device.

[0299] Step 7:

[0300] The server aggregates the results received from the information processing devices and notifies the user of the results via an intelligent device. The user can check the success or failure of the procedure through the terminal. The input is the response data from each information processing device, and the output is the result notification presented to the user.

[0301] 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.

[0302] This invention is a system that recognizes and takes into account user emotions during internal corporate procedures. The system receives request information from users and combines artificial intelligence and an emotion engine into the process, enabling efficient and human-centered responses. Specific embodiments of this invention are described below.

[0303] When a user submits request information to the server, the server immediately passes that information to the artificial intelligence (AI) device and the emotion engine. The AI ​​device scrutinizes the information and determines whether the procedure is appropriate. In parallel, the emotion engine analyzes the user's emotions and understands their emotional state at the time of submitting the request information. For example, if the user is nervous, the system can determine that appropriate information or explanations are needed.

[0304] When all the necessary information for the procedure is available, the emotion engine uses the analysis results to adjust how and when the notification system delivers additional information. For example, it can make notifications for missing information more discreet or gentler in its wording.

[0305] Subsequently, the artificial intelligence device converts the data to conform to the specifications of multiple information processing devices. At this stage, the analysis results of the emotion engine may influence processing priorities and the progression of procedures. The conversion process ensures the data is formatted accurately and transmitted to each information processing device via a server.

[0306] Once all the processing is completed, the emotion engine selects the expressions and means for notifying the requester of the processing results. For example, when the request is successful and it is determined that the user is seeking a sense of security, the notification will be made with an expression that gives a corresponding sense of security. The server conveys the content to the user and confirms that the procedure has proceeded without problems. This can improve the user experience and enable smooth progress of the business.

[0307] The following explains the process flow.

[0308] Step 1:

[0309] The user inputs and sends the request information for the procedure to the server. The interface is optimized so that the operation during input does not cause a psychological burden as an influencing factor of emotion.

[0310] Step 2:

[0311] When the server receives the request information, at the same time, the emotion engine analyzes the user's voice and visual elements and infers the user's emotional state. For example, the height and speed of the voice tone, the mouse speed during input, etc. are the analysis targets.

[0312] Step 3:

[0313] After the emotion engine analyzes the user's emotional state, it passes the result to the server and collaborates with the artificial intelligence device to scrutinize the information. If the emotion indicates uneasiness, the server preferentially conveys to the user that it has grasped the content of the request.

[0314] Step 4:

[0315] The artificial intelligence device scrutinizes the request information and checks whether all the necessary procedure information is available. If information is missing, the server gently and appropriately notifies the user of the missing information and requests the necessary additional information.

[0316] Step 5:

[0317] The artificial intelligence device converts data to match the format of multiple information processing devices. Based on the analysis results of the emotion engine, it may prioritize which system should begin processing the converted data.

[0318] Step 6:

[0319] The server sends the converted data to each information processing device. Depending on the results of the emotion engine, the greeting and message sent may be adjusted.

[0320] Step 7:

[0321] Each information processing unit notifies the server when processing is complete, and the server receives the results. If the emotion engine recognizes dissatisfaction or anxiety, the result notification system communicates the situation to the user in reassuring terms.

[0322] Step 8:

[0323] The server notifies the user that the procedure is complete. At this time, the sentiment engine selects the best words. Efforts are made to enhance the user experience with a positive message that emphasizes the success of the procedure.

[0324] (Example 2)

[0325] 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".

[0326] In corporate procedures, there is a problem where the user experience is insufficient and the smooth progress of business is hindered when processes are carried out mechanically without considering the user's feelings. Furthermore, there is the issue of inefficiency in procedures between multiple systems with different information formats.

[0327] 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.

[0328] In this invention, the server includes artificial intelligence means for scrutinizing request information and determining whether the procedure is appropriate, emotion recognition means for analyzing the user's emotional state, notification adjustment means for adjusting notification content based on the analyzed emotion information, data conversion means for automatically converting different data formats, and data transmission means for transmitting the converted information to multiple information processing means. This enables emotion-based user interaction, making the procedure more efficient and human-centered.

[0329] "Artificial intelligence means" refers to a technological element that has the function of analyzing request information and determining the appropriateness of the procedure.

[0330] "Emotion recognition means" refers to a technological element that analyzes the emotional state from the user's request information and extracts that state.

[0331] A "notification adjustment mechanism" is a technological element that has the function of adjusting the content and method of notifications sent to the user based on analyzed emotional information.

[0332] A "data conversion means" is a technical element that has the function of automatically converting data formats used between different information processing systems to ensure compatibility.

[0333] A "data transmission means" is a technical element that has the function of transmitting converted information to multiple information processing devices.

[0334] This invention is a system that recognizes user emotions in corporate procedures, making the process more effective and humane. Specifically, it uses a server that receives requests, artificial intelligence means, emotion recognition means, notification adjustment means, data conversion means, and data transmission means. The server first passes the request information sent by the user to the artificial intelligence means, which analyzes the request information and determines the appropriateness of the procedure. Next, the emotion recognition means analyzes the user's emotional state from the request information. Based on this, the notification adjustment means determines the appropriate notification method and content. For example, if the user is feeling anxious or tense, a gentler expression may be used. In addition, the data conversion means converts the information into a format that can be easily accepted by other information processing devices as needed, and the data transmission means is responsible for actually transmitting that information.

[0335] Specifically, the system's software elements include generative AI models for text analysis and natural language processing. For example, it employs sentiment recognition algorithms to identify emotions within text and natural language generation engines to generate appropriate tones. Data exchange is efficiently handled through REST APIs and message queues.

[0336] As a concrete example, consider a scenario where a user is in the process of purchasing a new product. The server, using its emotion recognition system, determines that the user is feeling anxious and creates a notification that takes this into consideration, thereby reducing the user's anxiety. An example of a prompt message in this case might be: "Create a reassuring notification message for users who are feeling anxious about the product purchase process."

[0337] The introduction of such systems is expected to make internal corporate procedures more efficient and emotionally sensitive, thereby improving the user experience.

[0338] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0339] Step 1:

[0340] The user sends request information regarding internal company procedures to the server. The server receives the request information and provides this data as input to an artificial intelligence system. The request information includes the type of procedure and related details.

[0341] Step 2:

[0342] The server uses artificial intelligence to analyze the received request information and determine whether the procedure is appropriate. The analysis utilizes a generative AI model to scrutinize the accuracy and completeness of the information. The output of this step is a report evaluating the appropriateness of the procedure.

[0343] Step 3:

[0344] The server passes the request information to the emotion recognition system. The emotion recognition system receives input data from the request information to analyze emotions. This analysis uses a natural language processing algorithm to understand the user's emotional state. The output is an emotion analysis report.

[0345] Step 4:

[0346] The server uses notification adjustment mechanisms to adjust the content of notifications sent to the user based on the sentiment analysis report. Specifically, if the user is stressed, the tone of the notification message is softened, and the information is presented in a gentler manner. The input for this step is the sentiment analysis report, and the output is the adjusted notification message.

[0347] Step 5:

[0348] The server uses data conversion means to convert procedural information into a format that can be easily handled by other systems. This ensures data compatibility between different information processing systems. The input is procedural information, and the output is the converted data format.

[0349] Step 6:

[0350] The server uses a data transmission mechanism to send the converted data to various information processing devices. These devices are systems that support the procedures. After transmission, an operation is performed to verify that the data is processed correctly by the other systems.

[0351] Step 7:

[0352] The server uses emotion recognition to notify the client with appropriate language based on the processing results. It generates messages that reflect the client's emotional state, such as using reassuring language upon success. The input is the processing result, and the output is the adjusted final notification message.

[0353] (Application Example 2)

[0354] 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."

[0355] In modern information processing, improving usability is paramount, and there is a growing need for responses that take emotions into consideration. However, conventional systems have struggled to provide appropriate information and notifications that respond to user emotions, often resulting in mechanical and one-sided responses. Therefore, the challenge is to reduce the stress users experience and achieve more human-centered responses.

[0356] 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.

[0357] In this invention, the server includes an information processing device that learns different procedural rules and scrutinizes request information to verify its accuracy, an emotion estimation means that recognizes and analyzes the emotions of the requester, and a data formatting means that automatically converts different data formats between multiple systems. This enables the provision of appropriate information and notifications that take into account the user's emotions.

[0358] An "information processing device" is a device that learns different procedural rules and has the function of scrutinizing requested information and verifying its accuracy.

[0359] "Emotion estimation methods" are means for recognizing and analyzing the emotions of a client.

[0360] A "data formatting method" is a means for automatically converting different data formats between multiple systems.

[0361] "Communication means" refers to a means for transmitting converted data to multiple information processing devices.

[0362] An "information presentation method" is a means of notifying information in an appropriate manner to the recipient, based on the analysis results of an emotion estimation method.

[0363] A "results reporting means" is a means for aggregating responses from multiple information processing devices and notifying the client of the processing results in an expression appropriate to the analysis results of the emotion estimation means.

[0364] The system that realizes this invention is primarily server-centered and functions by combining multiple means. The server consists of an information processing device, emotion estimation means, data formatting means, communication means, information presentation means, and result reporting means.

[0365] First, the user's request information is sent to the server. The information processing device receives this request information and verifies its accuracy according to procedural rules. A typical server or cloud-based processing system is used to do this.

[0366] Next, the emotion estimation system acquires the user's voice and video data and recognizes and analyzes their emotions. This system utilizes OpenCV and speech analysis technologies, and platforms such as IBM Watson Tone Analyzer are used as needed. The analyzed emotion information is then used in other parts of the system.

[0367] Subsequently, a data formatting tool automatically converts the data into different formats. This conversion uses APIs and software libraries for data format conversion. Then, the converted data is sent to other processing systems using a communication tool.

[0368] The information presentation system adjusts the content and expression of its responses to the user based on the analysis results obtained from the emotion estimation system. This enables more appropriate responses that take the user's emotions into consideration. Specifically, it uses generative AI models such as "GPT-4" to conduct text-based communication.

[0369] Furthermore, the results reporting means aggregates responses from other information processing devices and notifies the user of the final processing result. In this process, too, a prompt message is constructed that adjusts the expression and timing of the content based on the sentiment estimation results.

[0370] For example, if a user is feeling stressed, the emotion estimation tool detects this, and the information presentation tool generates a message such as, "Please take some time to relax today." In this way, a more reassuring response can be provided to the user. As an example of a prompt, by instructing the system to "Suggest appropriate responses if the user is feeling stressed," specific countermeasures will be generated.

[0371] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0372] Step 1:

[0373] The server receives request information from users. The input is the request information sent by the user from their terminal, and the output is the storage and initial confirmation of that information. Specifically, the server records the request details in the database and prepares this information for the next processing step.

[0374] Step 2:

[0375] The server uses an information processing device to examine the received request information. The input is the request information saved in step 1, and the output is the result of the judgment on whether the request conforms to the procedural rules and any necessary corrections. Here, the accuracy of the request content and the completeness of the required information are confirmed by comparing it with a pre-trained procedural rule database.

[0376] Step 3:

[0377] The server analyzes the user's emotions using emotion estimation tools. It receives user audio and video data as input and outputs the results of the emotion analysis. Specifically, it utilizes tools such as "IBM Watson Tone Analyzer" to estimate the emotional state based on the user's tone and facial expressions and generates evaluation results.

[0378] Step 4:

[0379] The server automatically converts different data formats using data formatting tools. The input consists of request information and analysis results, while the output is data converted to a format suitable for different systems. Specifically, it converts the data to the required format via an API and prepares it for transmission to each system.

[0380] Step 5:

[0381] The server transmits the converted data to the information processing device using a communication method. The input is the converted data obtained in step 4, and the output allows each information processing device to receive the processing results. Here, a communication protocol is used to transfer the data to the appropriate destination.

[0382] Step 6:

[0383] The server uses information presentation tools to notify the user in a way that is appropriate to their sentiment analysis results. The input is the sentiment analysis results and processing results, and the output is the notification content for the user. A generative AI model such as "GPT-4" is used to create a message based on the prompt and send it to the user.

[0384] Step 7:

[0385] The server notifies the user of the aggregated processing results using a results reporting mechanism. Inputs are responses from each information processing device and sentiment analysis results, while output is the final result notification to the user. The notification uses polite language tailored to the user's emotions, and is designed to make the processing results easy for the user to understand.

[0386] 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.

[0387] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0388] 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.

[0389] [Third Embodiment]

[0390] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0391] 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.

[0392] 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).

[0393] 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.

[0394] 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.

[0395] 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).

[0396] 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.

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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".

[0402] This invention is a system designed to streamline procedures between multiple information processing devices within a company. The system receives request information from a user, an artificial intelligence device examines that information, and enables the automatic conversion and transmission of the data necessary for the procedure. The following describes a specific embodiment of this invention.

[0403] The server receives the request information from the user and passes it on to the artificial intelligence (AI) device. The AI ​​device analyzes the received information in detail and verifies the accuracy of the procedure. For example, it determines whether the new company name conforms to existing regulations. If any necessary information is missing during this process, the server notifies the user and requests that they provide the additional information.

[0404] Once all the necessary information is gathered, the artificial intelligence device converts the data to conform to the standards of multiple information processing devices. This conversion means that information suitable for each system with different formats can be generated. The converted data is then transmitted to the corresponding system via a server.

[0405] The server aggregates responses from each information processing device and notifies the user of the final processing result. This notification may include information on the completion of the procedure and any errors. By utilizing this result notification method, users can check the progress of each procedure in real time.

[0406] For example, if a user requests to change their company name to a "new company name," the server receives the request, and an artificial intelligence system verifies whether the "new company name" is legitimate. Once all the necessary information is gathered, a conversion tool is used to prepare the data in the appropriate format for the HR and financial systems, and then it is sent to each system. Upon completion of all processing, the server notifies the user of the success of the procedure. This model allows companies to integrate internal procedures quickly and accurately, optimizing human resources.

[0407] The following describes the processing flow.

[0408] Step 1:

[0409] The user enters and submits request information to the server. This request information includes details of changes to the company name and address.

[0410] Step 2:

[0411] When the server receives request information from a user, it immediately passes that information to the artificial intelligence device. Here, the received data is checked to ensure it is in the correct format, along with referencing customer information.

[0412] Step 3:

[0413] The artificial intelligence system scrutinizes the request information and checks whether each item conforms to the business standards. For example, in the case of an address change, it verifies that the postal code and city / town name are accurately entered.

[0414] Step 4:

[0415] If necessary information is missing or incomplete, the server will notify the user of the missing or incorrect information and request that they provide the additional information. The user will then review the requested information again and send the completed information back to the server.

[0416] Step 5:

[0417] The artificial intelligence device re-verifies the information, and if there are no deficiencies, converts the data into the format required by each information processing device for the procedure. Through the conversion means, the data is appropriately formatted for systems with different formats.

[0418] Step 6:

[0419] The server sends the transformed data via the API to each information processing device. Each device receives the data and performs internal processing. For example, this could involve changing the company name in the HR system or updating the address in the financial system.

[0420] Step 7:

[0421] The server checks whether each information processing device has completed its processing or if any errors have occurred, and receives the response. If all procedures are completed, the server notifies the user of the results. This notification will include information that the procedures were completed successfully and, if there were any problems, how to deal with them.

[0422] (Example 1)

[0423] 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."

[0424] The aim is to solve the problem of inefficient procedures between multiple information processing devices in companies, which lead to processing delays and errors. Another challenge is the heavy burden of manual conversion work when handling different data formats.

[0425] 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.

[0426] In this invention, the server includes a computing device that learns different operating procedures and analyzes request data to verify accuracy, a conversion means that automatically converts different data arrangements between multiple devices, and a transmission means that transfers the converted data to multiple information processing devices. This enables increased efficiency in procedures and automation of data conversion work.

[0427] A "calculation unit" is a device that learns different operating procedures and analyzes received request data to verify its accuracy.

[0428] A "conversion means" is a mechanism for automatically converting data formats between multiple devices with different data formats.

[0429] "Transmission means" refers to means for transferring converted data to multiple information processing devices.

[0430] A "verification method" is a method for requesting additional data based on a thorough examination of the requested data.

[0431] A "notification method" is a means of collecting responses from multiple information processing devices and reporting the final processing results to the client.

[0432] For this invention to be implemented, the server, terminal, and user must each fulfill their respective roles, and the entire system must function efficiently. The server first receives request data transmitted from the user via the terminal. This request data may relate to procedures such as registering a new company name within a company or format conversion.

[0433] The server transfers the received request data to an artificial intelligence (AI) device. This AI device possesses advanced computing capabilities, including generative AI models, and performs learning of different operational procedures and data analysis. Specific software includes natural language processing techniques and pattern matching algorithms. This allows for checking the accuracy and consistency of the data.

[0434] The artificial intelligence device sends notifications to the server as needed, prompting the user to provide additional information if the requested data is incomplete. This exchange is carried out quickly by the user entering the additional information from their terminal and resending it.

[0435] Once all the necessary information is gathered, the artificial intelligence device converts the data format. This conversion process automatically handles data conversion between multiple devices with different data structures, using conversion tools. For example, it can convert JSON data to CSV format and generate a data format compatible with a specific information processing device.

[0436] The generated data is transferred from the server to multiple information processing devices, where it is processed appropriately. The server then integrates the responses from each device and notifies the user of the final processing result. This notification may include confirmation of the procedure's completion as well as error information.

[0437] As a concrete example, consider a case where a user changes their company name to "New Company Name." The user sends a request from their terminal, and the server forwards the request to an artificial intelligence (AI) device. The AI ​​device verifies compliance with laws and regulations and notifies the user via the server of any missing information. In this case, an example of a prompt message might be, "Please begin the necessary procedures to register the new company name. Please ensure compliance with legal regulations and prepare and submit data for the HR and financial systems." This allows companies to integrate procedures efficiently and accurately and optimize resources.

[0438] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0439] Step 1:

[0440] The user uses a terminal to input the necessary request data for the procedure and sends it to the server. Specifically, the user enters the company name and related information into a form and clicks the "Submit" button. The entered data is sent to the server as output. At this point, the output is the raw data entered by the user.

[0441] Step 2:

[0442] The server temporarily holds the received request data and transfers it to the computing unit. The input is the raw data received from the user, and the output is the procedure for passing that data to the computing unit. Specifically, after the server confirms receipt of the data, it formats it into the appropriate format and transfers it. This transferred data becomes the input to the computing unit.

[0443] Step 3:

[0444] The computing unit uses a generation AI model to analyze the received data. Here, it verifies whether the "new company name" complies with legal regulations. The input is formatted request data, and the output is the analysis result. Specific operations include matching against a registered database and comparing against a blacklist. The analysis result outputs the verification of legitimacy.

[0445] Step 4:

[0446] The server receives the analysis results from the computing unit to verify that all the necessary information is available. The input is the analysis results, and the output is a pass / fail status indicating whether the information is sufficient. Specifically, based on the analysis results, if there is any missing information, the server prepares to send a notification to the user.

[0447] Step 5:

[0448] The server sends a notification to the user requesting additional information if any is missing. The input is the notification content based on the previous pass / fail decision, and the output is the notification message to the user. Specifically, a dialog box is displayed on the user's terminal requesting additional input. The user receives the notification, re-enters the necessary information, and submits it.

[0449] Step 6:

[0450] After confirming that all necessary information is available, the processing unit performs data conversion. The input is the complete request data, and the output is the converted data. Specifically, this involves format conversion from JSON to CSV. This ensures that the output data is adaptable to different data processing devices.

[0451] Step 7:

[0452] The server transfers the converted data to multiple information processing devices. The input is the converted data, and the output is the accurate data delivery to the multiple devices. Specific operations include monitoring and logging of data delivery.

[0453] Step 8:

[0454] The server collects processing responses from all information processing devices and notifies the user of the final processing result. The input is the response data from each device, and the output is the summarized processing result. Specifically, it sends a notification to the terminal, allowing the user to confirm the success or error information of the process. This notification enables the user to recognize the completion of the procedure.

[0455] (Application Example 1)

[0456] 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."

[0457] In today's information processing environment, different procedural norms and data formats exist across multiple information processing devices, making it difficult to manage and operate them uniformly. Furthermore, efficient and accurate management is required for information input and verification, but this is difficult to achieve with conventional systems. It is necessary to solve these problems and improve the efficiency and accuracy of information processing.

[0458] 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.

[0459] In this invention, the server includes an intelligent device that acquires different procedural norms, analyzes request information, and verifies its accuracy; a conversion means for automatically converting and managing different information formats between multiple information processing devices; and a means for inputting and verifying information via a portable electronic device or display device operated by the user. This enables improved efficiency and accuracy in information processing.

[0460] "Different procedural norms" refer to the individual standards and rules that various information processing devices and systems possess.

[0461] An "intelligent device that analyzes requested information and verifies its accuracy" is a device equipped with artificial intelligence that automatically analyzes input information and determines whether it should be processed appropriately.

[0462] A "conversion means for automatically converting and managing different information formats" is a means that has the function of appropriately converting and organizing information across diverse formats based on common standards.

[0463] "A user-operated portable electronic device or display device" refers to a portable electronic device used for inputting or checking information, such as a smartphone, tablet, or head-mounted display.

[0464] "Communication means for transmitting converted information" refers to means for transmitting information to a specific device or system after it has been appropriately converted.

[0465] A "signaling means for requesting supplementary information" is a means for sending a signal to notify the user if there is insufficient input information and to request additional information.

[0466] "Result presentation means for presenting results to the operator" refers to functions or devices that enable the display of information processing results to the user in an easily understandable manner.

[0467] To realize this invention, the server first receives the request information and provides it to the intelligent device. The intelligent device then analyzes the request information in detail, using, for example, a natural language processing library such as Python, and verifies its accuracy. If the analyzed information is deemed incomplete, the server notifies the user and requests the provision of any additional information.

[0468] After the information is confirmed to be complete, the server uses a conversion mechanism that automatically converts between different information formats. This conversion mechanism uses technologies such as REST APIs to format the information according to the requirements of each information processing device. The information thus prepared is then transmitted from the server to the multiple information processing devices as converted information.

[0469] Furthermore, responses from information processing devices acquired by the server are collected, and the intelligent device notifies the user of the success / failure result. Users can use smartphones, tablets, head-mounted displays, etc., to check the information transmission status and results in real time. As a specific example, when setting up a new device, request information such as "Install new server A01" is entered. The AI ​​analyzes this information and sends it to each system in the specified format, thereby centrally managing and streamlining multiple procedures.

[0470] As an example of a prompt message, the user can enter, "Please add a new server to the data center. The server name is 'Server A01'. Please proceed with the procedure, including the relevant network settings," which will allow the procedure to proceed smoothly. This invention efficiently manages procedures that span multiple systems and reduces the burden on the user.

[0471] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0472] Step 1:

[0473] The server receives request information sent by the user. This request information includes details about device setup and registration. The server prepares this information for transfer to the intelligent device. The input is the user's request data, and the output is the data converted into a format for parsing.

[0474] Step 2:

[0475] The intelligent device analyzes the received request information using a generative AI model. At this stage, it verifies the accuracy of the information and determines if there are any deficiencies. Natural language processing is used for the analysis to check the integrity of the data. The input is the request data formatted in step 1, and the output is the analysis result and any supplementary information that should be notified to the user as needed.

[0476] Step 3:

[0477] Based on the analysis results, the server sends a notification to the user requesting supplementary information. This notification is displayed on the user's device, prompting them to enter additional information. The input here is a request for supplementary information generated from the analysis results, and the output is the supplementary information request notification displayed on the device.

[0478] Step 4:

[0479] The user inputs the requested supplementary information on the terminal and sends it to the server. The server receives this information and resends it to the intelligent device. The input is the supplementary information newly provided by the user, and the output is data whose completeness has been confirmed.

[0480] Step 5:

[0481] Intelligent devices perform information format conversion using complete data. They convert and manage data in formats suitable for different information processing devices. The input is data that has been verified for completeness, and the output is data converted to a different system format.

[0482] Step 6:

[0483] The server transmits the converted data to each information processing device. The data is transmitted to the necessary systems using communication methods. The input is the converted data from the intelligent device, and the output is the data received by each destination device.

[0484] Step 7:

[0485] The server aggregates the results received from the information processing devices and notifies the user of the results via an intelligent device. The user can check the success or failure of the procedure through the terminal. The input is the response data from each information processing device, and the output is the result notification presented to the user.

[0486] 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.

[0487] This invention is a system that recognizes and takes into account user emotions during internal corporate procedures. The system receives request information from users and combines artificial intelligence and an emotion engine into the process, enabling efficient and human-centered responses. Specific embodiments of this invention are described below.

[0488] When a user submits request information to the server, the server immediately passes that information to the artificial intelligence (AI) device and the emotion engine. The AI ​​device scrutinizes the information and determines whether the procedure is appropriate. In parallel, the emotion engine analyzes the user's emotions and understands their emotional state at the time of submitting the request information. For example, if the user is nervous, the system can determine that appropriate information or explanations are needed.

[0489] When all the necessary information for the procedure is available, the emotion engine uses the analysis results to adjust how and when the notification system delivers additional information. For example, it can make notifications for missing information more discreet or gentler in its wording.

[0490] Subsequently, the artificial intelligence device converts the data to conform to the specifications of multiple information processing devices. At this stage, the analysis results of the emotion engine may influence processing priorities and the progression of procedures. The conversion process ensures the data is formatted accurately and transmitted to each information processing device via a server.

[0491] Once all processing is complete, the emotion engine selects the wording and method for notifying the requester of the results. For example, if it determines that the user is seeking reassurance upon successful completion of the request, the notification will be delivered using appropriate reassuring language. The server then communicates this information to the user, confirming that the procedure proceeded without any issues. This improves the user experience and is expected to lead to smoother business operations.

[0492] The following describes the processing flow.

[0493] Step 1:

[0494] The user enters and submits request information to the server. The interface is optimized to minimize the psychological burden of input, taking emotions into consideration.

[0495] Step 2:

[0496] As soon as the server receives the request information, the emotion engine analyzes the user's voice and visual elements to infer the user's emotional state. For example, the pitch and speed of the voice tone and the mouse speed during input are among the elements analyzed.

[0497] Step 3:

[0498] After the emotion engine analyzes the user's emotional state, it passes the results to the server, which then works with an artificial intelligence device to refine the information. If the emotion indicates anxiety, the server prioritizes informing the user that it understands the request.

[0499] Step 4:

[0500] The artificial intelligence system scrutinizes the request information and verifies that all necessary procedural information is present. If any information is missing, the server gently and appropriately notifies the user of the missing information and requests any additional information needed.

[0501] Step 5:

[0502] The artificial intelligence device converts data to match the format of multiple information processing devices. Based on the analysis results of the emotion engine, it may prioritize which system should begin processing the converted data.

[0503] Step 6:

[0504] The server sends the converted data to each information processing device. Depending on the results of the emotion engine, the greeting and message sent may be adjusted.

[0505] Step 7:

[0506] Each information processing unit notifies the server when processing is complete, and the server receives the results. If the emotion engine recognizes dissatisfaction or anxiety, the result notification system communicates the situation to the user in reassuring terms.

[0507] Step 8:

[0508] The server notifies the user that the procedure is complete. At this time, the sentiment engine selects the best words. Efforts are made to enhance the user experience with a positive message that emphasizes the success of the procedure.

[0509] (Example 2)

[0510] 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."

[0511] In corporate procedures, there is a problem where the user experience is insufficient and the smooth progress of business is hindered when processes are carried out mechanically without considering the user's feelings. Furthermore, there is the issue of inefficiency in procedures between multiple systems with different information formats.

[0512] 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.

[0513] In this invention, the server includes artificial intelligence means for scrutinizing request information and determining whether the procedure is appropriate, emotion recognition means for analyzing the user's emotional state, notification adjustment means for adjusting notification content based on the analyzed emotion information, data conversion means for automatically converting different data formats, and data transmission means for transmitting the converted information to multiple information processing means. This enables emotion-based user interaction, making the procedure more efficient and human-centered.

[0514] "Artificial intelligence means" refers to a technological element that has the function of analyzing request information and determining the appropriateness of the procedure.

[0515] "Emotion recognition means" refers to a technological element that analyzes the emotional state from the user's request information and extracts that state.

[0516] A "notification adjustment mechanism" is a technological element that has the function of adjusting the content and method of notifications sent to the user based on analyzed emotional information.

[0517] A "data conversion means" is a technical element that has the function of automatically converting data formats used between different information processing systems to ensure compatibility.

[0518] A "data transmission means" is a technical element that has the function of transmitting converted information to multiple information processing devices.

[0519] This invention is a system that recognizes user emotions in corporate procedures, making the process more effective and humane. Specifically, it uses a server that receives requests, artificial intelligence means, emotion recognition means, notification adjustment means, data conversion means, and data transmission means. The server first passes the request information sent by the user to the artificial intelligence means, which analyzes the request information and determines the appropriateness of the procedure. Next, the emotion recognition means analyzes the user's emotional state from the request information. Based on this, the notification adjustment means determines the appropriate notification method and content. For example, if the user is feeling anxious or tense, a gentler expression may be used. In addition, the data conversion means converts the information into a format that can be easily accepted by other information processing devices as needed, and the data transmission means is responsible for actually transmitting that information.

[0520] Specifically, the system's software elements include generative AI models for text analysis and natural language processing. For example, it employs sentiment recognition algorithms to identify emotions within text and natural language generation engines to generate appropriate tones. Data exchange is efficiently handled through REST APIs and message queues.

[0521] As a concrete example, consider a scenario where a user is in the process of purchasing a new product. The server, using its emotion recognition system, determines that the user is feeling anxious and creates a notification that takes this into consideration, thereby reducing the user's anxiety. An example of a prompt message in this case might be: "Create a reassuring notification message for users who are feeling anxious about the product purchase process."

[0522] The introduction of such systems is expected to make internal corporate procedures more efficient and emotionally sensitive, thereby improving the user experience.

[0523] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0524] Step 1:

[0525] The user sends request information regarding internal company procedures to the server. The server receives the request information and provides this data as input to an artificial intelligence system. The request information includes the type of procedure and related details.

[0526] Step 2:

[0527] The server uses artificial intelligence to analyze the received request information and determine whether the procedure is appropriate. The analysis utilizes a generative AI model to scrutinize the accuracy and completeness of the information. The output of this step is a report evaluating the appropriateness of the procedure.

[0528] Step 3:

[0529] The server passes the request information to the emotion recognition system. The emotion recognition system receives input data from the request information to analyze emotions. This analysis uses a natural language processing algorithm to understand the user's emotional state. The output is an emotion analysis report.

[0530] Step 4:

[0531] The server uses notification adjustment mechanisms to adjust the content of notifications sent to the user based on the sentiment analysis report. Specifically, if the user is stressed, the tone of the notification message is softened, and the information is presented in a gentler manner. The input for this step is the sentiment analysis report, and the output is the adjusted notification message.

[0532] Step 5:

[0533] The server uses data conversion means to convert procedural information into a format that can be easily handled by other systems. This ensures data compatibility between different information processing systems. The input is procedural information, and the output is the converted data format.

[0534] Step 6:

[0535] The server uses a data transmission mechanism to send the converted data to various information processing devices. These devices are systems that support the procedures. After transmission, an operation is performed to verify that the data is processed correctly by the other systems.

[0536] Step 7:

[0537] The server uses emotion recognition to notify the client with appropriate language based on the processing results. It generates messages that reflect the client's emotional state, such as using reassuring language upon success. The input is the processing result, and the output is the adjusted final notification message.

[0538] (Application Example 2)

[0539] 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."

[0540] In modern information processing, improving usability is paramount, and there is a growing need for responses that take emotions into consideration. However, conventional systems have struggled to provide appropriate information and notifications that respond to user emotions, often resulting in mechanical and one-sided responses. Therefore, the challenge is to reduce the stress users experience and achieve more human-centered responses.

[0541] 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.

[0542] In this invention, the server includes an information processing device that learns different procedural rules and scrutinizes request information to verify its accuracy, an emotion estimation means that recognizes and analyzes the emotions of the requester, and a data formatting means that automatically converts different data formats between multiple systems. This enables the provision of appropriate information and notifications that take into account the user's emotions.

[0543] An "information processing device" is a device that learns different procedural rules and has the function of scrutinizing requested information and verifying its accuracy.

[0544] "Emotion estimation methods" are means for recognizing and analyzing the emotions of a client.

[0545] A "data formatting method" is a means for automatically converting different data formats between multiple systems.

[0546] "Communication means" refers to a means for transmitting converted data to multiple information processing devices.

[0547] An "information presentation method" is a means of notifying information in an appropriate manner to the recipient, based on the analysis results of an emotion estimation method.

[0548] A "results reporting means" is a means for aggregating responses from multiple information processing devices and notifying the client of the processing results in an expression appropriate to the analysis results of the emotion estimation means.

[0549] The system that realizes this invention is primarily server-centered and functions by combining multiple means. The server consists of an information processing device, emotion estimation means, data formatting means, communication means, information presentation means, and result reporting means.

[0550] First, the user's request information is sent to the server. The information processing device receives this request information and verifies its accuracy according to procedural rules. A typical server or cloud-based processing system is used to do this.

[0551] Next, the emotion estimation system acquires the user's voice and video data and recognizes and analyzes their emotions. This system utilizes OpenCV and speech analysis technologies, and platforms such as IBM Watson Tone Analyzer are used as needed. The analyzed emotion information is then used in other parts of the system.

[0552] Subsequently, a data formatting tool automatically converts the data into different formats. This conversion uses APIs and software libraries for data format conversion. Then, the converted data is sent to other processing systems using a communication tool.

[0553] The information presentation system adjusts the content and expression of its responses to the user based on the analysis results obtained from the emotion estimation system. This enables more appropriate responses that take the user's emotions into consideration. Specifically, it uses generative AI models such as "GPT-4" to conduct text-based communication.

[0554] Furthermore, the results reporting means aggregates responses from other information processing devices and notifies the user of the final processing result. In this process, too, a prompt message is constructed that adjusts the expression and timing of the content based on the sentiment estimation results.

[0555] For example, if a user is feeling stressed, the emotion estimation tool detects this, and the information presentation tool generates a message such as, "Please take some time to relax today." In this way, a more reassuring response can be provided to the user. As an example of a prompt, by instructing the system to "Suggest appropriate responses if the user is feeling stressed," specific countermeasures will be generated.

[0556] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0557] Step 1:

[0558] The server receives request information from users. The input is the request information sent by the user from their terminal, and the output is the storage and initial confirmation of that information. Specifically, the server records the request details in the database and prepares this information for the next processing step.

[0559] Step 2:

[0560] The server uses an information processing device to examine the received request information. The input is the request information saved in step 1, and the output is the result of the judgment on whether the request conforms to the procedural rules and any necessary corrections. Here, the accuracy of the request content and the completeness of the required information are confirmed by comparing it with a pre-trained procedural rule database.

[0561] Step 3:

[0562] The server analyzes the user's emotions using emotion estimation tools. It receives user audio and video data as input and outputs the results of the emotion analysis. Specifically, it utilizes tools such as "IBM Watson Tone Analyzer" to estimate the emotional state based on the user's tone and facial expressions and generates evaluation results.

[0563] Step 4:

[0564] The server automatically converts different data formats using data formatting tools. The input consists of request information and analysis results, while the output is data converted to a format suitable for different systems. Specifically, it converts the data to the required format via an API and prepares it for transmission to each system.

[0565] Step 5:

[0566] The server transmits the converted data to the information processing device using a communication method. The input is the converted data obtained in step 4, and the output allows each information processing device to receive the processing results. Here, a communication protocol is used to transfer the data to the appropriate destination.

[0567] Step 6:

[0568] The server uses information presentation tools to notify the user in a way that is appropriate to their sentiment analysis results. The input is the sentiment analysis results and processing results, and the output is the notification content for the user. A generative AI model such as "GPT-4" is used to create a message based on the prompt and send it to the user.

[0569] Step 7:

[0570] The server notifies the user of the aggregated processing results using a results reporting mechanism. Inputs are responses from each information processing device and sentiment analysis results, while output is the final result notification to the user. The notification uses polite language tailored to the user's emotions, and is designed to make the processing results easy for the user to understand.

[0571] 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.

[0572] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0573] 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.

[0574] [Fourth Embodiment]

[0575] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0576] 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.

[0577] 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).

[0578] 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.

[0579] 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.

[0580] 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).

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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.

[0587] 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".

[0588] This invention is a system designed to streamline procedures between multiple information processing devices within a company. The system receives request information from a user, an artificial intelligence device examines that information, and enables the automatic conversion and transmission of the data necessary for the procedure. The following describes a specific embodiment of this invention.

[0589] The server receives the request information from the user and passes it on to the artificial intelligence (AI) device. The AI ​​device analyzes the received information in detail and verifies the accuracy of the procedure. For example, it determines whether the new company name conforms to existing regulations. If any necessary information is missing during this process, the server notifies the user and requests that they provide the additional information.

[0590] Once all the necessary information is gathered, the artificial intelligence device converts the data to conform to the standards of multiple information processing devices. This conversion means that information suitable for each system with different formats can be generated. The converted data is then transmitted to the corresponding system via a server.

[0591] The server aggregates responses from each information processing device and notifies the user of the final processing result. This notification may include information on the completion of the procedure and any errors. By utilizing this result notification method, users can check the progress of each procedure in real time.

[0592] For example, if a user requests to change their company name to a "new company name," the server receives the request, and an artificial intelligence system verifies whether the "new company name" is legitimate. Once all the necessary information is gathered, a conversion tool is used to prepare the data in the appropriate format for the HR and financial systems, and then it is sent to each system. Upon completion of all processing, the server notifies the user of the success of the procedure. This model allows companies to integrate internal procedures quickly and accurately, optimizing human resources.

[0593] The following describes the processing flow.

[0594] Step 1:

[0595] The user enters and submits request information to the server. This request information includes details of changes to the company name and address.

[0596] Step 2:

[0597] When the server receives request information from a user, it immediately passes that information to the artificial intelligence device. Here, the received data is checked to ensure it is in the correct format, along with referencing customer information.

[0598] Step 3:

[0599] The artificial intelligence system scrutinizes the request information and checks whether each item conforms to the business standards. For example, in the case of an address change, it verifies that the postal code and city / town name are accurately entered.

[0600] Step 4:

[0601] If necessary information is missing or incomplete, the server will notify the user of the missing or incorrect information and request that they provide the additional information. The user will then review the requested information again and send the completed information back to the server.

[0602] Step 5:

[0603] The artificial intelligence device re-verifies the information, and if there are no deficiencies, converts the data into the format required by each information processing device for the procedure. Through the conversion means, the data is appropriately formatted for systems with different formats.

[0604] Step 6:

[0605] The server sends the transformed data via the API to each information processing device. Each device receives the data and performs internal processing. For example, this could involve changing the company name in the HR system or updating the address in the financial system.

[0606] Step 7:

[0607] The server checks whether each information processing device has completed its processing or if any errors have occurred, and receives the response. If all procedures are completed, the server notifies the user of the results. This notification will include information that the procedures were completed successfully and, if there were any problems, how to deal with them.

[0608] (Example 1)

[0609] 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".

[0610] The aim is to solve the problem of inefficient procedures between multiple information processing devices in companies, which lead to processing delays and errors. Another challenge is the heavy burden of manual conversion work when handling different data formats.

[0611] 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.

[0612] In this invention, the server includes a computing device that learns different operating procedures and analyzes request data to verify accuracy, a conversion means that automatically converts different data arrangements between multiple devices, and a transmission means that transfers the converted data to multiple information processing devices. This enables increased efficiency in procedures and automation of data conversion work.

[0613] A "calculation unit" is a device that learns different operating procedures and analyzes received request data to verify its accuracy.

[0614] A "conversion means" is a mechanism for automatically converting data formats between multiple devices with different data formats.

[0615] "Transmission means" refers to means for transferring converted data to multiple information processing devices.

[0616] A "verification method" is a method for requesting additional data based on a thorough examination of the requested data.

[0617] A "notification method" is a means of collecting responses from multiple information processing devices and reporting the final processing results to the client.

[0618] For this invention to be implemented, the server, terminal, and user must each fulfill their respective roles, and the entire system must function efficiently. The server first receives request data transmitted from the user via the terminal. This request data may relate to procedures such as registering a new company name within a company or format conversion.

[0619] The server transfers the received request data to an artificial intelligence (AI) device. This AI device possesses advanced computing capabilities, including generative AI models, and performs learning of different operational procedures and data analysis. Specific software includes natural language processing techniques and pattern matching algorithms. This allows for checking the accuracy and consistency of the data.

[0620] The artificial intelligence device sends notifications to the server as needed, prompting the user to provide additional information if the requested data is incomplete. This exchange is carried out quickly by the user entering the additional information from their terminal and resending it.

[0621] Once all the necessary information is gathered, the artificial intelligence device converts the data format. This conversion process automatically handles data conversion between multiple devices with different data structures, using conversion tools. For example, it can convert JSON data to CSV format and generate a data format compatible with a specific information processing device.

[0622] The generated data is transferred from the server to multiple information processing devices, where it is processed appropriately. The server then integrates the responses from each device and notifies the user of the final processing result. This notification may include confirmation of the procedure's completion as well as error information.

[0623] As a concrete example, consider a case where a user changes their company name to "New Company Name." The user sends a request from their terminal, and the server forwards the request to an artificial intelligence (AI) device. The AI ​​device verifies compliance with laws and regulations and notifies the user via the server of any missing information. In this case, an example of a prompt message might be, "Please begin the necessary procedures to register the new company name. Please ensure compliance with legal regulations and prepare and submit data for the HR and financial systems." This allows companies to integrate procedures efficiently and accurately and optimize resources.

[0624] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0625] Step 1:

[0626] The user uses a terminal to input the necessary request data for the procedure and sends it to the server. Specifically, the user enters the company name and related information into a form and clicks the "Submit" button. The entered data is sent to the server as output. At this point, the output is the raw data entered by the user.

[0627] Step 2:

[0628] The server temporarily holds the received request data and transfers it to the computing unit. The input is the raw data received from the user, and the output is the procedure for passing that data to the computing unit. Specifically, after the server confirms receipt of the data, it formats it into the appropriate format and transfers it. This transferred data becomes the input to the computing unit.

[0629] Step 3:

[0630] The computing unit uses a generation AI model to analyze the received data. Here, it verifies whether the "new company name" complies with legal regulations. The input is formatted request data, and the output is the analysis result. Specific operations include matching against a registered database and comparing against a blacklist. The analysis result outputs the verification of legitimacy.

[0631] Step 4:

[0632] The server receives the analysis results from the computing unit to verify that all the necessary information is available. The input is the analysis results, and the output is a pass / fail status indicating whether the information is sufficient. Specifically, based on the analysis results, if there is any missing information, the server prepares to send a notification to the user.

[0633] Step 5:

[0634] The server sends a notification to the user requesting additional information if any is missing. The input is the notification content based on the previous pass / fail decision, and the output is the notification message to the user. Specifically, a dialog box is displayed on the user's terminal requesting additional input. The user receives the notification, re-enters the necessary information, and submits it.

[0635] Step 6:

[0636] After confirming that all necessary information is available, the processing unit performs data conversion. The input is the complete request data, and the output is the converted data. Specifically, this involves format conversion from JSON to CSV. This ensures that the output data is adaptable to different data processing devices.

[0637] Step 7:

[0638] The server transfers the converted data to multiple information processing devices. The input is the converted data, and the output is the accurate data delivery to the multiple devices. Specific operations include monitoring and logging of data delivery.

[0639] Step 8:

[0640] The server collects processing responses from all information processing devices and notifies the user of the final processing result. The input is the response data from each device, and the output is the summarized processing result. Specifically, it sends a notification to the terminal, allowing the user to confirm the success or error information of the process. This notification enables the user to recognize the completion of the procedure.

[0641] (Application Example 1)

[0642] 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".

[0643] In today's information processing environment, different procedural norms and data formats exist across multiple information processing devices, making it difficult to manage and operate them uniformly. Furthermore, efficient and accurate management is required for information input and verification, but this is difficult to achieve with conventional systems. It is necessary to solve these problems and improve the efficiency and accuracy of information processing.

[0644] 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.

[0645] In this invention, the server includes an intelligent device that acquires different procedural norms, analyzes request information, and verifies its accuracy; a conversion means for automatically converting and managing different information formats between multiple information processing devices; and a means for inputting and verifying information via a portable electronic device or display device operated by the user. This enables improved efficiency and accuracy in information processing.

[0646] "Different procedural norms" refer to the individual standards and rules that various information processing devices and systems possess.

[0647] An "intelligent device that analyzes requested information and verifies its accuracy" is a device equipped with artificial intelligence that automatically analyzes input information and determines whether it should be processed appropriately.

[0648] A "conversion means for automatically converting and managing different information formats" is a means that has the function of appropriately converting and organizing information across diverse formats based on common standards.

[0649] "A user-operated portable electronic device or display device" refers to a portable electronic device used for inputting or checking information, such as a smartphone, tablet, or head-mounted display.

[0650] "Communication means for transmitting converted information" refers to means for transmitting information to a specific device or system after it has been appropriately converted.

[0651] A "signaling means for requesting supplementary information" is a means for sending a signal to notify the user if there is insufficient input information and to request additional information.

[0652] "Result presentation means for presenting results to the operator" refers to functions or devices that enable the display of information processing results to the user in an easily understandable manner.

[0653] To realize this invention, the server first receives the request information and provides it to the intelligent device. The intelligent device then analyzes the request information in detail, using, for example, a natural language processing library such as Python, and verifies its accuracy. If the analyzed information is deemed incomplete, the server notifies the user and requests the provision of any additional information.

[0654] After the information is confirmed to be complete, the server uses a conversion mechanism that automatically converts between different information formats. This conversion mechanism uses technologies such as REST APIs to format the information according to the requirements of each information processing device. The information thus prepared is then transmitted from the server to the multiple information processing devices as converted information.

[0655] Furthermore, responses from information processing devices acquired by the server are collected, and the intelligent device notifies the user of the success / failure result. Users can use smartphones, tablets, head-mounted displays, etc., to check the information transmission status and results in real time. As a specific example, when setting up a new device, request information such as "Install new server A01" is entered. The AI ​​analyzes this information and sends it to each system in the specified format, thereby centrally managing and streamlining multiple procedures.

[0656] As an example of a prompt message, the user can enter, "Please add a new server to the data center. The server name is 'Server A01'. Please proceed with the procedure, including the relevant network settings," which will allow the procedure to proceed smoothly. This invention efficiently manages procedures that span multiple systems and reduces the burden on the user.

[0657] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0658] Step 1:

[0659] The server receives request information sent by the user. This request information includes details about device setup and registration. The server prepares this information for transfer to the intelligent device. The input is the user's request data, and the output is the data converted into a format for parsing.

[0660] Step 2:

[0661] The intelligent device analyzes the received request information using a generative AI model. At this stage, it verifies the accuracy of the information and determines if there are any deficiencies. Natural language processing is used for the analysis to check the integrity of the data. The input is the request data formatted in step 1, and the output is the analysis result and any supplementary information that should be notified to the user as needed.

[0662] Step 3:

[0663] Based on the analysis results, the server sends a notification to the user requesting supplementary information. This notification is displayed on the user's device, prompting them to enter additional information. The input here is a request for supplementary information generated from the analysis results, and the output is the supplementary information request notification displayed on the device.

[0664] Step 4:

[0665] The user inputs the requested supplementary information on the terminal and sends it to the server. The server receives this information and resends it to the intelligent device. The input is the supplementary information newly provided by the user, and the output is data whose completeness has been confirmed.

[0666] Step 5:

[0667] Intelligent devices perform information format conversion using complete data. They convert and manage data in formats suitable for different information processing devices. The input is data that has been verified for completeness, and the output is data converted to a different system format.

[0668] Step 6:

[0669] The server transmits the converted data to each information processing device. The data is transmitted to the necessary systems using communication methods. The input is the converted data from the intelligent device, and the output is the data received by each destination device.

[0670] Step 7:

[0671] The server aggregates the results received from the information processing devices and notifies the user of the results via an intelligent device. The user can check the success or failure of the procedure through the terminal. The input is the response data from each information processing device, and the output is the result notification presented to the user.

[0672] 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.

[0673] This invention is a system that recognizes and takes into account user emotions during internal corporate procedures. The system receives request information from users and combines artificial intelligence and an emotion engine into the process, enabling efficient and human-centered responses. Specific embodiments of this invention are described below.

[0674] When a user submits request information to the server, the server immediately passes that information to the artificial intelligence (AI) device and the emotion engine. The AI ​​device scrutinizes the information and determines whether the procedure is appropriate. In parallel, the emotion engine analyzes the user's emotions and understands their emotional state at the time of submitting the request information. For example, if the user is nervous, the system can determine that appropriate information or explanations are needed.

[0675] When all the necessary information for the procedure is available, the emotion engine uses the analysis results to adjust how and when the notification system delivers additional information. For example, it can make notifications for missing information more discreet or gentler in its wording.

[0676] Subsequently, the artificial intelligence device converts the data to conform to the specifications of multiple information processing devices. At this stage, the analysis results of the emotion engine may influence processing priorities and the progression of procedures. The conversion process ensures the data is formatted accurately and transmitted to each information processing device via a server.

[0677] Once all processing is complete, the emotion engine selects the wording and method for notifying the requester of the results. For example, if it determines that the user is seeking reassurance upon successful completion of the request, the notification will be delivered using appropriate reassuring language. The server then communicates this information to the user, confirming that the procedure proceeded without any issues. This improves the user experience and is expected to lead to smoother business operations.

[0678] The following describes the processing flow.

[0679] Step 1:

[0680] The user enters and submits request information to the server. The interface is optimized to minimize the psychological burden of input, taking emotions into consideration.

[0681] Step 2:

[0682] As soon as the server receives the request information, the emotion engine analyzes the user's voice and visual elements to infer the user's emotional state. For example, the pitch and speed of the voice tone and the mouse speed during input are among the elements analyzed.

[0683] Step 3:

[0684] After the emotion engine analyzes the user's emotional state, it passes the results to the server, which then works with an artificial intelligence device to refine the information. If the emotion indicates anxiety, the server prioritizes informing the user that it understands the request.

[0685] Step 4:

[0686] The artificial intelligence system scrutinizes the request information and verifies that all necessary procedural information is present. If any information is missing, the server gently and appropriately notifies the user of the missing information and requests any additional information needed.

[0687] Step 5:

[0688] The artificial intelligence device converts data to match the format of multiple information processing devices. Based on the analysis results of the emotion engine, it may prioritize which system should begin processing the converted data.

[0689] Step 6:

[0690] The server sends the converted data to each information processing device. Depending on the results of the emotion engine, the greeting and message sent may be adjusted.

[0691] Step 7:

[0692] Each information processing unit notifies the server when processing is complete, and the server receives the results. If the emotion engine recognizes dissatisfaction or anxiety, the result notification system communicates the situation to the user in reassuring terms.

[0693] Step 8:

[0694] The server notifies the user that the procedure is complete. At this time, the sentiment engine selects the best words. Efforts are made to enhance the user experience with a positive message that emphasizes the success of the procedure.

[0695] (Example 2)

[0696] 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".

[0697] In corporate procedures, there is a problem where the user experience is insufficient and the smooth progress of business is hindered when processes are carried out mechanically without considering the user's feelings. Furthermore, there is the issue of inefficiency in procedures between multiple systems with different information formats.

[0698] 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.

[0699] In this invention, the server includes artificial intelligence means for scrutinizing request information and determining whether the procedure is appropriate, emotion recognition means for analyzing the user's emotional state, notification adjustment means for adjusting notification content based on the analyzed emotion information, data conversion means for automatically converting different data formats, and data transmission means for transmitting the converted information to multiple information processing means. This enables emotion-based user interaction, making the procedure more efficient and human-centered.

[0700] "Artificial intelligence means" refers to a technological element that has the function of analyzing request information and determining the appropriateness of the procedure.

[0701] "Emotion recognition means" refers to a technological element that analyzes the emotional state from the user's request information and extracts that state.

[0702] A "notification adjustment mechanism" is a technological element that has the function of adjusting the content and method of notifications sent to the user based on analyzed emotional information.

[0703] A "data conversion means" is a technical element that has the function of automatically converting data formats used between different information processing systems to ensure compatibility.

[0704] A "data transmission means" is a technical element that has the function of transmitting converted information to multiple information processing devices.

[0705] This invention is a system that recognizes user emotions in corporate procedures, making the process more effective and humane. Specifically, it uses a server that receives requests, artificial intelligence means, emotion recognition means, notification adjustment means, data conversion means, and data transmission means. The server first passes the request information sent by the user to the artificial intelligence means, which analyzes the request information and determines the appropriateness of the procedure. Next, the emotion recognition means analyzes the user's emotional state from the request information. Based on this, the notification adjustment means determines the appropriate notification method and content. For example, if the user is feeling anxious or tense, a gentler expression may be used. In addition, the data conversion means converts the information into a format that can be easily accepted by other information processing devices as needed, and the data transmission means is responsible for actually transmitting that information.

[0706] Specifically, the system's software elements include generative AI models for text analysis and natural language processing. For example, it employs sentiment recognition algorithms to identify emotions within text and natural language generation engines to generate appropriate tones. Data exchange is efficiently handled through REST APIs and message queues.

[0707] As a concrete example, consider a scenario where a user is in the process of purchasing a new product. The server, using its emotion recognition system, determines that the user is feeling anxious and creates a notification that takes this into consideration, thereby reducing the user's anxiety. An example of a prompt message in this case might be: "Create a reassuring notification message for users who are feeling anxious about the product purchase process."

[0708] The introduction of such systems is expected to make internal corporate procedures more efficient and emotionally sensitive, thereby improving the user experience.

[0709] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0710] Step 1:

[0711] The user sends request information regarding internal company procedures to the server. The server receives the request information and provides this data as input to an artificial intelligence system. The request information includes the type of procedure and related details.

[0712] Step 2:

[0713] The server uses artificial intelligence to analyze the received request information and determine whether the procedure is appropriate. The analysis utilizes a generative AI model to scrutinize the accuracy and completeness of the information. The output of this step is a report evaluating the appropriateness of the procedure.

[0714] Step 3:

[0715] The server passes the request information to the emotion recognition system. The emotion recognition system receives input data from the request information to analyze emotions. This analysis uses a natural language processing algorithm to understand the user's emotional state. The output is an emotion analysis report.

[0716] Step 4:

[0717] The server uses notification adjustment mechanisms to adjust the content of notifications sent to the user based on the sentiment analysis report. Specifically, if the user is stressed, the tone of the notification message is softened, and the information is presented in a gentler manner. The input for this step is the sentiment analysis report, and the output is the adjusted notification message.

[0718] Step 5:

[0719] The server uses data conversion means to convert procedural information into a format that can be easily handled by other systems. This ensures data compatibility between different information processing systems. The input is procedural information, and the output is the converted data format.

[0720] Step 6:

[0721] The server uses a data transmission mechanism to send the converted data to various information processing devices. These devices are systems that support the procedures. After transmission, an operation is performed to verify that the data is processed correctly by the other systems.

[0722] Step 7:

[0723] The server uses emotion recognition to notify the client with appropriate language based on the processing results. It generates messages that reflect the client's emotional state, such as using reassuring language upon success. The input is the processing result, and the output is the adjusted final notification message.

[0724] (Application Example 2)

[0725] 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".

[0726] In modern information processing, improving usability is paramount, and there is a growing need for responses that take emotions into consideration. However, conventional systems have struggled to provide appropriate information and notifications that respond to user emotions, often resulting in mechanical and one-sided responses. Therefore, the challenge is to reduce the stress users experience and achieve more human-centered responses.

[0727] 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.

[0728] In this invention, the server includes an information processing device that learns different procedural rules and scrutinizes request information to verify its accuracy, an emotion estimation means that recognizes and analyzes the emotions of the requester, and a data formatting means that automatically converts different data formats between multiple systems. This enables the provision of appropriate information and notifications that take into account the user's emotions.

[0729] An "information processing device" is a device that learns different procedural rules and has the function of scrutinizing requested information and verifying its accuracy.

[0730] "Emotion estimation methods" are means for recognizing and analyzing the emotions of a client.

[0731] A "data formatting method" is a means for automatically converting different data formats between multiple systems.

[0732] "Communication means" refers to a means for transmitting converted data to multiple information processing devices.

[0733] An "information presentation method" is a means of notifying information in an appropriate manner to the recipient, based on the analysis results of an emotion estimation method.

[0734] A "results reporting means" is a means for aggregating responses from multiple information processing devices and notifying the client of the processing results in an expression appropriate to the analysis results of the emotion estimation means.

[0735] The system that realizes this invention is primarily server-centered and functions by combining multiple means. The server consists of an information processing device, emotion estimation means, data formatting means, communication means, information presentation means, and result reporting means.

[0736] First, the user's request information is sent to the server. The information processing device receives this request information and verifies its accuracy according to procedural rules. A typical server or cloud-based processing system is used to do this.

[0737] Next, the emotion estimation system acquires the user's voice and video data and recognizes and analyzes their emotions. This system utilizes OpenCV and speech analysis technologies, and platforms such as IBM Watson Tone Analyzer are used as needed. The analyzed emotion information is then used in other parts of the system.

[0738] Subsequently, a data formatting tool automatically converts the data into different formats. This conversion uses APIs and software libraries for data format conversion. Then, the converted data is sent to other processing systems using a communication tool.

[0739] The information presentation system adjusts the content and expression of its responses to the user based on the analysis results obtained from the emotion estimation system. This enables more appropriate responses that take the user's emotions into consideration. Specifically, it uses generative AI models such as "GPT-4" to conduct text-based communication.

[0740] Furthermore, the results reporting means aggregates responses from other information processing devices and notifies the user of the final processing result. In this process, too, a prompt message is constructed that adjusts the expression and timing of the content based on the sentiment estimation results.

[0741] For example, if a user is feeling stressed, the emotion estimation tool detects this, and the information presentation tool generates a message such as, "Please take some time to relax today." In this way, a more reassuring response can be provided to the user. As an example of a prompt, by instructing the system to "Suggest appropriate responses if the user is feeling stressed," specific countermeasures will be generated.

[0742] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0743] Step 1:

[0744] The server receives request information from users. The input is the request information sent by the user from their terminal, and the output is the storage and initial confirmation of that information. Specifically, the server records the request details in the database and prepares this information for the next processing step.

[0745] Step 2:

[0746] The server uses an information processing device to examine the received request information. The input is the request information saved in step 1, and the output is the result of the judgment on whether the request conforms to the procedural rules and any necessary corrections. Here, the accuracy of the request content and the completeness of the required information are confirmed by comparing it with a pre-trained procedural rule database.

[0747] Step 3:

[0748] The server analyzes the user's emotions using emotion estimation tools. It receives user audio and video data as input and outputs the results of the emotion analysis. Specifically, it utilizes tools such as "IBM Watson Tone Analyzer" to estimate the emotional state based on the user's tone and facial expressions and generates evaluation results.

[0749] Step 4:

[0750] The server automatically converts different data formats using data formatting tools. The input consists of request information and analysis results, while the output is data converted to a format suitable for different systems. Specifically, it converts the data to the required format via an API and prepares it for transmission to each system.

[0751] Step 5:

[0752] The server transmits the converted data to the information processing device using a communication method. The input is the converted data obtained in step 4, and the output allows each information processing device to receive the processing results. Here, a communication protocol is used to transfer the data to the appropriate destination.

[0753] Step 6:

[0754] The server uses information presentation tools to notify the user in a way that is appropriate to their sentiment analysis results. The input is the sentiment analysis results and processing results, and the output is the notification content for the user. A generative AI model such as "GPT-4" is used to create a message based on the prompt and send it to the user.

[0755] Step 7:

[0756] The server notifies the user of the aggregated processing results using a results reporting mechanism. Inputs are responses from each information processing device and sentiment analysis results, while output is the final result notification to the user. The notification uses polite language tailored to the user's emotions, and is designed to make the processing results easy for the user to understand.

[0757] 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.

[0758] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] 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.

[0765] 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."

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0778] The following is further disclosed regarding the embodiments described above.

[0779] (Claim 1)

[0780] An artificial intelligence device that learns different procedural rules, scrutinizes request information, and verifies its accuracy,

[0781] A conversion means for automatically converting different data formats between multiple systems,

[0782] A transmission means for transmitting the converted data to multiple information processing devices,

[0783] A system that includes this.

[0784] (Claim 2)

[0785] The system according to claim 1, further comprising a notification means for requesting additional information if there is a deficiency in the requested information.

[0786] (Claim 3)

[0787] The system according to claim 1, further comprising a result notification means for collecting responses from multiple systems and notifying the client of the processing results.

[0788] "Example 1"

[0789] (Claim 1)

[0790] A computing device that learns different operating procedures, analyzes the requested data, and verifies accuracy,

[0791] A conversion means for automatically converting different data arrangements between multiple devices,

[0792] A transmission means for transferring the converted data to multiple information processing devices,

[0793] A confirmation method for requesting additional data based on the results of scrutinizing the requested data,

[0794] A notification means that integrates responses from multiple information processing devices and notifies the client of the final processing result,

[0795] A system that includes this.

[0796] (Claim 2)

[0797] The system according to claim 1, further comprising a notification means for requesting additional data if there is a shortage of requested data.

[0798] (Claim 3)

[0799] The system according to claim 1, further comprising a result notification means for collecting responses from multiple information processing devices and notifying the client of the processing results.

[0800] "Application Example 1"

[0801] (Claim 1)

[0802] An intelligent device that acquires different procedural norms, analyzes the request information, and verifies its accuracy,

[0803] A conversion means for automatically converting and managing different information formats between multiple information processing devices,

[0804] Means for inputting and confirming information via a portable electronic device or display device operated by the user,

[0805] A communication means for transmitting the converted information to multiple information processing devices,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] The system according to claim 1, further comprising a signaling means for requesting supplementary information if there is a deficiency in the requested information.

[0809] (Claim 3)

[0810] The system according to claim 1, further comprising result presentation means for collecting responses from multiple information processing devices and presenting the results to an operator.

[0811] "Example 2 of combining an emotion engine"

[0812] (Claim 1)

[0813] An artificial intelligence tool that scrutinizes the request information and determines whether the procedure is appropriate,

[0814] An emotion recognition method for analyzing the user's emotional state,

[0815] A notification adjustment means that adjusts the content of notifications based on analyzed emotional information,

[0816] A data conversion means that automatically converts different data formats,

[0817] A data transmission means that transmits the converted information to multiple information processing means,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, further comprising a notification means for discreetly requesting additional information if the requested information is incomplete.

[0821] (Claim 3)

[0822] The system according to claim 1, further comprising a means for analyzing the processing results and notifying the client in an appropriate expression according to the client's emotional state.

[0823] "Application example 2 when combining with an emotional engine"

[0824] (Claim 1)

[0825] An information processing device that learns different procedural rules, scrutinizes request information, and verifies its accuracy,

[0826] A means of estimating emotions that recognizes and analyzes the emotions of the client,

[0827] A data formatting means that automatically converts different data formats between multiple systems,

[0828] A communication means for transmitting the converted data to multiple information processing devices,

[0829] An information presentation means that notifies the recipient using appropriate language based on the analysis results of the emotion estimation means,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The system according to claim 1, further comprising an information presentation means that requests additional information in an expression based on the analysis of the emotion estimation means when there is insufficient information in the request.

[0833] (Claim 3)

[0834] The system according to claim 1, further comprising a result reporting means that aggregates responses from multiple information processing devices and notifies the client of the processing results in an expression appropriate to the client according to the analysis results of the emotion estimation means. [Explanation of symbols]

[0835] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An artificial intelligence device that learns different procedural rules, scrutinizes request information, and verifies its accuracy, A conversion means for automatically converting different data formats between multiple systems, A transmission means for transmitting the converted data to multiple information processing devices, A system that includes this.

2. The system according to claim 1, further comprising a notification means for requesting additional information if there is a deficiency in the requested information.

3. The system according to claim 1, further comprising a result notification means for collecting responses from multiple systems and notifying the client of the processing results.

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