System

Abstract

A system is provided.SOLUTION: A system comprising: means for storing a received electronic message; means for parsing a body of the stored electronic message; means for extracting important information from the parsed body and generating a summary; and means for displaying the generated summary along with a title of the electronic message.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In recent years, the use of email in business has increased, resulting in the accumulation of large volumes of email in inboxes. However, it is difficult to immediately grasp the importance and content of each email, making it challenging to efficiently process emails that should be prioritized. In particular, it is difficult to determine which emails should be processed first when there are already many emails being exchanged or when it is difficult to determine the importance of an email from its subject line alone. In this situation, there is a demand for a system that allows users to quickly grasp the contents of emails and improve work efficiency. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means: a system including means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating summaries, and means for displaying the generated summaries together with the titles of the electronic messages. Furthermore, the system includes means for determining the priority of the electronic messages based on the generated summaries, and means for visually displaying the status of the electronic messages according to their contents. This allows users to grasp the contents and priority of emails at a glance in their inbox, enabling them to process emails efficiently.

[0006] "Receiving" refers to obtaining an externally sent electronic message.

[0007] "Electronic message" refers to a means of communication in the form of digital data sent and received over a computer network.

[0008] "Storing" refers to storing a retrieved electronic message in a storage device.

[0009] "Analysis" means the programmatic examination, deciphering, or decomposition of the body of a stored electronic message.

[0010] "Significant information" refers to the content of an electronic message that has particular meaning or value.

[0011] "Extraction" refers to extracting necessary information from the analysis results.

[0012] "Summary" means a brief, written description of the contents of an electronic message.

[0013] "Generation" refers to creating a new summary from the analyzed content.

[0014] "Title" means the subject of an Electronic Message.

[0015] "Display" refers to outputting the generated summary and title in a format that can be visually confirmed by the user.

[0016] "Priority" refers to the order or importance for processing electronic messages.

[0017] "Status" refers to information indicating the current situation, such as the need for a reply to an electronic message or a waiting task. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. 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), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 1, a 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.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0032] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to a system for efficiently managing a large amount of e-mail that arrives in an inbox and quickly understanding its contents. The functions and operations of this system will be explained below with specific examples.

[0040] The core of this system is its function of analyzing the body of e-mails, extracting important information, and generating summaries. This allows users to easily grasp the contents of each e-mail in their inbox. Below, we will explain how it works from the perspectives of the server, terminal, and user.

[0041] Server Operation

[0042] When a new email is received, the server stores the body of the email. Then, the server analyzes the stored email and uses a generative AI model to extract important information from the body and generate a summary. For example, the server operates as follows:

[0043] First, the server connects to the IMAP server via the Internet to check for new emails. If new emails are found, the email body is saved to a database. For each saved email body, a generative AI model is applied to create a summary. The generated summary is then saved to the database and immediately reflected on the device.

[0044] Device behavior

[0045] The device displays a summary of each email along with the subject of the email on the inbox screen, allowing the user to understand the contents of the email without opening each one. For example, the device operates as follows:

[0046] The terminal retrieves email information with summaries from the server and displays them in the inbox. This allows the user to see the sender, subject, and summary of the email at a glance. In addition, the summary also shows the status of whether a reply is required, so the user can quickly determine which emails should be prioritized.

[0047] User operations

[0048] The user checks the inbox screen on the device to understand the contents and priority of the email. For example, when the user opens the inbox, the following information is displayed:

[0049] From: alice@example.com

[0050] Subject: Meeting Agenda

[0051] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0052] ==================================================

[0053] From: bob@example.com

[0054] Subject: Monthly Report Submission

[0055] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0056] ==================================================

[0057] This type of display allows the user to grasp the main points of each email at a glance and quickly determine which email should be given priority.

[0058] The system of the present invention analyzes the contents of emails and generates summaries, thereby streamlining inbox management and improving user work efficiency, allowing users to process emails appropriately without missing important emails.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0062] Step 2:

[0063] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0064] Step 3:

[0065] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0066] Step 4:

[0067] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0068] Step 5:

[0069] The server stores the generated summary together with the corresponding email information in a database. This save process establishes the email subject, sender, body, and summary as a set of data.

[0070] Step 6:

[0071] The terminal displays email information with a summary to the user on the inbox screen. The terminal retrieves email information with a summary from the server and places the sender, subject, and summary on the inbox, allowing the user to check the content and importance of the email at a glance.

[0072] Step 7:

[0073] Users can check the summary displayed on the inbox screen and decide the priority of email processing. They can check the content and status, determine the necessary reply or action, and then process the email. This allows users to efficiently manage email and respond appropriately.

[0074] Example 1

[0075] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0076] In today's world, users receive a large number of electronic messages on a daily basis, which puts them at risk of missing important information and wastes time extracting the necessary information from the overwhelming volume of emails. In business environments, in particular, where prompt responses to important emails are required, a system that can efficiently understand the contents of emails is needed. To solve this problem, a system that can analyze received electronic messages, generate summaries, and determine their priority is required.

[0077] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0078] In this invention, the server includes means for checking newly arrived electronic messages via the Internet, means for saving the bodies of received electronic messages in a database, means for analyzing the bodies of the saved electronic messages using a generative AI model, means for extracting important information from the analysis results and generating summaries, means for saving the generated summaries in a database, means for reflecting the electronic message information with summaries on a terminal in real time, and means for displaying the summaries together with the titles of the electronic messages on the screen of the terminal, thereby enabling users to quickly grasp the main points of emails without opening them and to prioritize responding to important emails.

[0079] The "Internet" is a huge information network that interconnects computer networks all over the world.

[0080] An "electronic message" is a digital communication message, such as an email or text message, sent or received over the Internet.

[0081] A "server" is a computer system that provides data and services in response to requests from clients over a network.

[0082] "IMAP Server" means a server that manages and provides electronic mail using the Internet Message Access Protocol.

[0083] A "database" is a collection of information that allows efficient management of data and allows operations such as searching and updating.

[0084] A "generative AI model" is an artificial intelligence model that performs tasks such as text generation and information extraction based on given input data.

[0085] "Analysis" is the means of examining given data in detail and understanding its structure and meaning.

[0086] A "summary" is a concise summary of the main points or outline of the original information.

[0087] "Real-time" refers to a situation where data or information is processed immediately and the results are available without delay.

[0088] "Terminal" refers to a device such as a computer or mobile phone that is directly operated by a user.

[0089] The present invention relates to a system for efficiently managing a large amount of received electronic messages and quickly understanding their contents. Specific embodiments of this system will be described below.

[0090] The core of the system is its ability to analyze the body of electronic messages, extract key information, and generate summaries, allowing users to get a concise understanding of the contents of each message in their inbox.

[0091] Server behavior:

[0092] The server connects to the IMAP server via the Internet to check whether new electronic messages have been received. If new messages have been received, the message body is retrieved and stored in a database. A generative AI model is used to analyze the message body, extract key information, and generate a summary. The specific generative AI model used is GPT-3 or a similar natural language processing model. The generated summary is then stored back in the database and updated on the device in real time.

[0093] Terminal behavior:

[0094] The device displays a summary of each message along with its subject on the inbox screen. Users can view the summary without opening the message body. This allows users to quickly understand the content of each message and immediately determine which messages should be prioritized. The summary also displays the status of whether a reply is required, allowing users to respond quickly to important messages.

[0095] User Action:

[0096] The user checks the inbox screen on the device to understand the contents and priority of the message. For example, when the user opens the inbox, the following information is displayed:

[0097] From: sender@example.com

[0098] Subject: Meeting Agenda

[0099] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0100] ==================================================

[0101] From: another.sender@example.com

[0102] Subject: Monthly Report Submission

[0103] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0104] ==================================================

[0105] This type of display allows the user to grasp the gist of each message at a glance and quickly determine which message should be given priority.

[0106] Example prompt for a generative AI model:

[0107] An example of a prompt sentence to input to the generative AI model is as follows:

[0108] Extract key information and summarize the following email content:

[0109] "Dear team, Please be reminded of the meeting scheduled on Friday. Key points to be discussed include the project status update, budget review, and planning for the next quarter. Regards, Sender"

[0110] The system of the present invention analyzes the content of electronic messages and generates summaries to improve inbox management and user efficiency, thereby enabling users to avoid missing important messages and to process them appropriately.

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1:

[0113] The server connects to an IMAP server over the Internet to check for new electronic messages.

[0114] Input: IMAP server login information

[0115] Output: List of new email messages

[0116] Specific operation: The server accesses the INBOX folder using the IMAP protocol and checks whether there are any new emails. At this time, the IMAP server returns the unread email ID.

[0117] Step 2:

[0118] When a new electronic message is confirmed, the server retrieves the body of the message and stores it in a database.

[0119] Input: List of new email messages

[0120] Output: Saved email body

[0121] Specific operation: The server retrieves the email content from the IMAP server and saves the retrieved email body in the database.

[0122] Step 3:

[0123] The server analyzes the stored email body using a generative AI model to generate a summary.

[0124] Input: Saved email body

[0125] Output: Generated summary

[0126] Specific operation: The server inputs the prompt sentence into the generative AI model and generates a summary, which is returned in text format.

[0127] Step 4:

[0128] The server stores the generated summary again in the database.

[0129] Input: Generated summary

[0130] Output: Summary stored in database

[0131] Specific operation: The server saves the summary obtained from the generative AI model in the corresponding email entry in the database.

[0132] Step 5:

[0133] The server reflects the summarized electronic message information to the terminal in real time.

[0134] Input: Abstract stored in the database

[0135] Output: Email information sent to terminal with summary

[0136] Specific operation: The server uses WebSocket to send email information with a summary to the terminal.

[0137] Step 6:

[0138] The terminal displays a summary of each email along with its subject on the inbox screen to the user.

[0139] Input: Email information with summary sent from the server

[0140] Output: Summary displayed on the inbox screen

[0141] What it does: The device analyzes the received data and displays the email subject and summary in the inbox using technologies such as HTML and JavaScript.

[0142] Step 7:

[0143] The user checks the inbox screen on the device to understand the contents and priority of the email.

[0144] Input: Summary displayed on the inbox screen

[0145] Output: User's priority judgment

[0146] What happens: The user can read the summary of the emails displayed and decide which ones should be prioritized. If necessary, they can open the emails to view the details.

[0147] (Application example 1)

[0148] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0149] In autonomous vehicles, drivers face challenges in efficiently managing the large volume of emails they receive while driving and quickly understanding their contents. In particular, there is a need for a system that allows drivers to easily obtain important information without using their hands and quickly reply if necessary. Another important challenge is ensuring driver safety by providing information visually and audibly.

[0150] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0151] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for notifying the summary by voice, means for displaying the summary on a visual device, and means for replying to electronic messages based on voice input, thereby enabling the driver of an autonomous vehicle to quickly and accurately understand the content of received emails without using his or her hands and to reply immediately if necessary.

[0152] "Means for storing received electronic messages" refers to a device or software for storing emails received over a network in a database or memory.

[0153] A "means for analyzing the body of stored electronic messages" is a device or software that automatically analyzes the content of emails stored on a storage device and identifies important information.

[0154] "Means for extracting important information from the analyzed text and generating a summary" refers to a device or software that extracts the main points from the information obtained through the analysis and summarizes them in a concise form.

[0155] "Means for displaying the generated summary together with the title of the electronic message" means a device or software for displaying the summarized information and the subject of the original electronic message on a terminal display or other display device.

[0156] The "means for audibly announcing the summary" refers to a device or software for announcing the generated summary to the user through an audio output device.

[0157] The "means for displaying the summary on a visual device" is a device or software for displaying the generated summary on smart glasses or a head-mounted display.

[0158] A "means for replying to electronic messages based on voice input" is a device or software that transcribes a user's voice commands and replies to emails based on them.

[0159] The present invention relates to a system for improving the efficiency of email management for drivers of autonomous vehicles. Specific embodiments of the system are described below.

[0160] Server Operation

[0161] The server connects to an IMAP server over the Internet to check for new emails. When a new email is received, it stores the email body in a database. It then uses a generative AI model (such as OpenAI's GPT model) to analyze the email body, extract key information, and generate a summary. The generated summary is stored in a database and immediately reflected on the client side.

[0162] Device behavior

[0163] The device (e.g., smart glasses or a head-mounted display) retrieves email information with summaries from the server and displays them on the screen. This allows the driver to understand the contents of emails without having to open them one by one. It also has a function to provide audio notification of the summary information. For example, a voice assistant device (e.g., Amazon Echo Auto) can be used to provide audio notification of the summary generated by the generative AI model to the driver.

[0164] User operations

[0165] The user (driver) can check the inbox screen and instantly understand the summary of the email. In addition, it is possible to reply to emails by voice input. When the driver uses voice commands to input the reply content, the content is transcribed and sent as an email.

[0166] Hardware and software used

[0167] Hardware:

[0168] Smart glasses (e.g. Google Glass)

[0169] Head-mounted displays (e.g. Microsoft HoloLens)

[0170] Voice assistant devices (e.g. Amazon Echo Auto)

[0171] software:

[0172] Server side: IMAP server, generative AI model (e.g. OpenAI GPT model), database

[0173] Client side: Smart glasses, HMD applications, speech recognition software (e.g., Google Speech-to-Text)

[0174] Specific examples

[0175] For example, if a driver receives an email while driving with the subject "Meeting Agenda" and the body "Describes the agenda for the upcoming meeting on Friday. Key points include a project status update, budget review, and planning for the next quarter," the generative AI model can generate a summary using prompts like the following:

[0176] Example prompt sentence:

[0177] Summarize the given email text. For example, generate a summary in the following format:

[0178] Email subject: Meeting agenda

[0179] Body: Explain the agenda for Friday's meeting. Key points include a project status update, budget review, and planning for the next quarter.

[0180] Summary: This email outlines the agenda for a meeting scheduled for Friday. Key points include a project status update, budget review, and planning for the next quarter.

[0181] This allows the driver of an autonomous vehicle to quickly and accurately understand the contents of emails received without using their hands, and to reply immediately if necessary.

[0182] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0183] Step 1:

[0184] The server connects to the IMAP server over the Internet to check for new electronic messages. When a new email is received, it stores its body in a database. As input, the server receives an electronic message from the IMAP server, and as output, it records the body of the electronic message in a database.

[0185] Step 2:

[0186] The server passes the body of each stored electronic message to the generative AI model, extracts important information, and generates a summary, using prompts to provide appropriate instructions to the generative AI model. As input, the server sends the body of the electronic message and the prompt to the generative AI model, and as output, receives a summary from the generative AI model.

[0187] Step 3:

[0188] The server stores the generated summary in a database and immediately reflects it on the device.,As input, the summary from the generative AI model is stored in the database,,and as output, the summary is stored in the database.

[0189] Step 4:

[0190] The terminal receives email information with a summary from the server and displays it on the inbox screen. As input, the terminal receives email information with a summary from the server, and as output, it displays a list of the email subject, sender, and summary.

[0191] Step 5:

[0192] The terminal performs speech conversion processing to output the generated summary to the driver through a speech output device. The terminal receives the summary as input and outputs the converted speech information from a speaker as output.

[0193] Step 6:

[0194] The user checks the inbox screen and instantly gets a summary of the email. If necessary, the user can reply to the electronic message by voice input. As input, the user's voice command is converted into text by speech recognition software, and as output, the text reply is sent as an email.

[0195] Step 7:

[0196] The server generates text based on the user's voice input and sends it as a new electronic message. As input, the server receives text data from the speech recognition software and as output, sends it to the recipient in the form of an email.

[0197] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0198] The present invention relates to a system that efficiently manages emails received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority of emails and how to respond to them. The functions and operations of this system are explained below with specific examples.

[0199] This system combines the ability to analyze the body of emails, extract important information, and generate summaries with an emotion engine that recognizes the user's emotions, allowing users to see the content of emails in their inbox, as well as the appropriate priorities and responses based on their emotions.

[0200] Server Operation

[0201] When a new email is received, the server stores the body of the email, then analyzes it and uses a generative AI model to extract key information from the body and generate a summary.

[0202] Furthermore, the server is equipped with an emotion engine that recognizes the user's emotional state. Based on the recognized emotional state, it determines the priority of the email and recommends an appropriate response. For example, the server operates as follows:

[0203] First, the server receives and stores new emails, then uses a generative AI model to generate summaries, and then uses an emotion engine to recognize the user's emotional state and evaluate the importance and urgency of the email.

[0204] Device behavior

[0205] The device displays the email subject, summary, and priority and response instructions based on the user's emotional state as recognized by the emotion engine, allowing the user to easily understand the content and importance of the email and take appropriate action.

[0206] For example, the device receives email information with a summary and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, so users can see at a glance whether an email needs to be addressed.

[0207] User operations

[0208] The user checks the summary of the email displayed on the inbox screen and the results of the emotion engine, and takes action based on the priority of the email. For example, when a user opens their inbox, the following information may be displayed:

[0209] From: alice@example.com

[0210] Subject: Meeting Agenda

[0211] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0212] Emotion: Neutral

[0213] ==================================================

[0214] From: bob@example.com

[0215] Subject: Monthly Report Submission

[0216] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0217] Emotion: Urgent

[0218] ==================================================

[0219] In this way, the results of the emotion engine are also displayed, allowing users to quickly understand the email and respond appropriately based on their emotions. Prioritization and response can be achieved according to the user's emotional state and the content of the email.

[0220] The system of the present invention comprehensively analyzes the content of emails and the user's emotional state to improve email management efficiency, allowing users to respond quickly and appropriately without missing important emails.

[0221] The processing flow will be explained below.

[0222] Step 1:

[0223] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0224] Step 2:

[0225] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0226] Step 3:

[0227] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0228] Step 4:

[0229] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0230] Step 5:

[0231] The server associates the generated summary with the email information and stores it in a database. Through this process, the email's subject, sender, body, and summary are established as a series of data.

[0232] Step 6:

[0233] The server uses an emotion engine to analyze the summary and body of the saved emails to recognize the user's current emotional state, which is then classified into statuses such as "normal," "urgent," "joy," and "anger."

[0234] Step 7:

[0235] The server prioritizes each email based on the results of the emotion engine and stores the necessary status in a database, thereby determining the priority that reflects the email content and the user's emotional state.

[0236] Step 8:

[0237] The terminal displays the email subject, summary, and priority and status based on the user's emotional state recognized by the emotion engine to the user. The terminal obtains email information with summary and the result of the emotion engine from the server and displays them in the inbox.

[0238] Step 9:

[0239] Users can check the summary and emotional state of emails displayed on the inbox screen and respond based on the priority of the email. Users can categorize emails based on the displayed information and immediately determine the priority of their replies or responses.

[0240] By using the above steps, the system of the present invention comprehensively analyzes the content of emails and the user's emotional state, improving the efficiency of email management. This allows users to respond quickly and appropriately to important emails without missing them.

[0241] Example 2

[0242] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0243] Conventional electronic message management systems have the problem that when a large number of messages accumulate in the inbox, the risk of missing important messages increases and the possibility of delayed responses increases. It is also difficult to quickly grasp the content and urgency of messages, which increases the burden on users. In addition to these issues, there is a significant lack of functionality that automatically provides appropriate responses that take into account the user's emotional state.

[0244] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0245] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for recognizing the user's emotional state, and means for determining the priority of the electronic messages based on the recognized emotional state and recommending an appropriate response method, thereby enabling efficient analysis of the content of the electronic messages and the user's emotional state and enabling prompt and appropriate responses.

[0246] "Means" refers to functional components that make up a system, and includes devices and programs capable of executing specific functions or operations.

[0247] A "server" is a computer system that accepts requests from clients on a network and provides the corresponding services or functions.

[0248] "Electronic message" refers to a communication message sent or received in digital form, such as email, and may include text, images, attachments, etc.

[0249] "Storage" refers to the act of recording a received electronic message in a database or storage device so that it can be retrieved at a later time.

[0250] "Analysis" refers to the process of closely examining the content of stored electronic messages and extracting necessary information or patterns.

[0251] A "generative AI model" refers to an artificial intelligence algorithm that uses natural language processing and machine learning to analyze text and generate or transform information.

[0252] "Summary" means a short narrative statement that succinctly sets out the key information extracted from the body of an electronic message.

[0253] The "emotional state" indicates the psychological state of the user when receiving the electronic message, and is classified into categories such as "urgent" and "important."

[0254] "Priority" refers to the order of necessity or urgency of a response among multiple electronic messages.

[0255] "Recommended responses" refers to a function that suggests appropriate responses to users based on the recognized emotional state and summarized content.

[0256] "Visual display" refers to the means by which information such as the content, emotional state, or priority of an electronic message is presented to a user as graphical elements or icons.

[0257] The present invention is a system that efficiently manages electronic messages received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority and response method of the messages. This system includes a server and a terminal as its main components, each of which performs a specific function to realize the overall mail management process.

[0258] Server configuration and operation

[0259] The server consists of hardware and software with the following main functions:

[0260] 1. Receiving and storing emails

[0261] The server receives electronic messages via the Internet and stores them in a database, including sender information, subject lines, and message body text.

[0262] 2. Use of analytical and generative AI models

[0263] The server uses a generative AI model (specifically GPT-4) to analyze the body of the stored electronic message. The following is an example of a prompt:

[0264] Please analyze the email body below and extract the important information.

[0265] Analysis extracts important information and generates summaries.

[0266] 3. Emotion recognition

[0267] The server uses an emotion engine to recognize the user's emotional state, which is classified into categories such as "urgent," "important," and "minor."

[0268] 4. Prioritization and recommended actions

[0269] Prioritize messages based on perceived emotional state and summarized content, and recommend appropriate responses (e.g., "Reply now," "Reply later," etc.).

[0270] 5. Recording user emotions

[0271] The server records the user's emotional state for each electronic message and keeps it as a management history.

[0272] Terminal configuration and operation

[0273] Terminals consist of devices (e.g., smartphones, tablets, and PCs) that have the following functions:

[0274] 1. Obtaining email information

[0275] The terminal obtains the email subject, summary, and emotion engine results from the server.

[0276] 2. Displaying email information

[0277] The device displays the retrieved information in a user interface, including subject line, summary, priority, and emotional state, along with visual icons and statuses, allowing users to quickly determine whether action is required.

[0278] User operations

[0279] Users use this system to manage and respond to electronic messages through the following operations:

[0280] 1. Check your inbox

[0281] Users can view the subject line, summary, and sentiment recognition results in their inbox, allowing them to quickly determine message priorities.

[0282] 2. Responding to emails

[0283] The user can then take appropriate action based on the displayed information, for example, replying immediately to messages of high urgency and responding later to messages of low importance.

[0284] Specific examples

[0285] As a specific example, consider the case where a server receives the following electronic message and performs analysis, summarization, emotion recognition, and prioritization:

[0286] From: johndoe@example.com

[0287] Subject: Project progress review

[0288] Summary: This email is intended to review the progress of an ongoing project. The main points are to confirm the schedule, allocate resources, and report any issues.

[0289] Emotion: emergency

[0290] In this way, the system provides email information in a format that users can intuitively understand, helping them to respond quickly and appropriately.

[0291] The system comprehensively analyzes the content of electronic messages and the user's emotional state to achieve efficient email management, allowing users to avoid missing important messages and respond appropriately in a timely manner.

[0292] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0293] Server Processing Steps

[0294] Step 1:

[0295] The server receives electronic messages. Specifically, it retrieves new emails from an email server over the Internet and receives data including the sender, subject, and body of the email. The input is the new email, and the output is the received email data.

[0296] Step 2:

[0297] The server stores received electronic messages in a database. Specifically, it records the content of the email (sender, subject, and body) in the database. The input is the received email data, and the output is the stored database entry.

[0298] Step 3:

[0299] The server analyzes the body of the stored electronic message. Specifically, it uses a generative AI model to analyze the email body and extract important information. The input is the email body data, and the output is the analysis result data. The prompt is as follows:

[0300] Please analyze the email body below and extract the important information.

[0301] Step 4:

[0302] The server generates a summary based on the analysis results. Specifically, it converts the output of the generative AI model into a summary. The input is the analysis result data, and the output is the generated summary text.

[0303] Step 5:

[0304] The server uses an emotion engine to recognize the user's emotional state. Specifically, it applies an algorithm to classify emotions from the analyzed email content. The input is the email content data, and the output is the emotional state data (e.g., urgent, important, minor, etc.).

[0305] Step 6:

[0306] The server determines the priority of the email based on the recognized emotional state and recommends an appropriate response. Specifically, it applies a prioritization algorithm to determine the response. The input is the emotional state data and a summary, and the output is the priority and the recommended response.

[0307] Step 7:

[0308] The server records the user's emotional state and response in a database. Specifically, it stores the priority and response for each email in the database. The input is the priority and response data, and the output is the updated database entry.

[0309] Terminal processing steps

[0310] Step 1:

[0311] The terminal obtains email information from the server. Specifically, it sends a request to the server and receives the email subject, summary, and emotional state data in return. The input is the request, and the output is the obtained email information data.

[0312] Step 2:

[0313] The terminal displays the acquired email information on the screen. Specifically, the email's subject, summary, emotional state, and priority are displayed on the user interface. The input is the acquired email information data, and the output is the screen information displayed to the user. Visual icons and statuses are also displayed.

[0314] User processing steps

[0315] Step 1:

[0316] The user checks the inbox screen of the terminal. Specifically, the displayed email information (subject, summary, emotional state, and priority) is checked. The input is the screen information, and the output is the user's recognition result.

[0317] Step 2:

[0318] The user responds to the email based on the displayed information. Specifically, they reply immediately to emails with high urgency and respond later to emails with low urgency. The input is the user's recognition result, and the output is the user's response action.

[0319] (Application example 2)

[0320] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0321] It has been a challenge for users to quickly and appropriately identify and respond to important messages from the vast amount of electronic messages they receive. In particular, in security services, it is necessary to take into account the user's emotional state and prioritize messages with high urgency. Therefore, there is a need for a system that integrates electronic message summary generation and emotion recognition to prompt users to take immediate and appropriate action.

[0322] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0323] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating summaries, means for recognizing the user's emotional state, means for generating priorities for electronic messages and recommended responses based on the recognized emotional state, and means for displaying the generated summaries and emotional state together with the titles of the electronic messages. This allows the user to grasp the priorities of electronic messages based on their content and emotional state, and enables them to quickly respond to messages with high urgency.

[0324] An "electronic message" is a form of text data sent or received over the Internet or other network.

[0325] "Storage means" refers to a device or software that has the function of storing received electronic messages in a storage device such as a database or file system.

[0326] A "text analysis means" is an algorithm or software that analyzes the content of a stored electronic message and extracts specific information.

[0327] A "means for extracting key information and generating summaries" is an algorithm or generative AI model for extracting key points from the content of an electronic message and presenting them as a summary.

[0328] The "means for recognizing the emotional state of the user" is an emotion engine or software for analyzing the emotional state of the user when receiving a message and recognizing a particular emotion.

[0329] The "means for generating priorities and recommended responses" is an algorithm or software for determining the importance and urgency of a response to an electronic message based on the recognized emotional state of the user and summary information, and for suggesting an appropriate response.

[0330] The "means for displaying" is a display device or user interface for visually presenting the generated summary, emotional state, and message title to the user.

[0331] The system for implementing the present invention mainly comprises three elements: a server, a terminal, and a user.

[0332] The server stores received electronic messages in a database or file system. The stored electronic messages are processed by algorithms and software that analyze the text, extracting important information and generating summaries. Specifically, a generative AI model is used to extract key points from the content of the electronic message. The server then uses an emotion engine to recognize the user's emotional state and prioritizes the electronic message and recommends a course of action based on the recognized emotional state. The generated summaries and emotional state are then sent to the device along with the title of the electronic message.

[0333] The terminal receives summary information of electronic messages and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, allowing users to see at a glance whether an email requires a response. In addition, special alerts are displayed for messages with high urgency based on the user's emotional state. This allows users to easily identify messages that require immediate attention.

[0334] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. For example, if the message is urgent, an action plan for immediate response is presented. This allows the user to respond quickly and appropriately without missing important electronic messages.

[0335] Consider the following scenario: When a user receives a security-related electronic message, the server processes the message as follows:

[0336] Server Action:

[0337] 1. Store electronic messages.

[0338] 2. Analyze the body of the stored message, extract important information, and generate a summary.

[0339] 3. The emotion engine recognizes the user's emotional state and determines priorities.

[0340] 4. A summary of the electronic message and the emotional state are sent to the terminal along with the title.

[0341] Example of terminal display:

[0342] From: sender@example.com

[0343] Subject: Security Alert

[0344] Summary: We have detected suspicious activity in your account. Please verify your identity immediately.

[0345] Emotion: Urgent

[0346] In this way, the generated summary and emotional state are displayed appropriately, allowing the user to quickly and accurately grasp messages that require a response.

[0347] An example prompt might use the following format:

[0348] "Please summarize the following email and analyze the user's emotion: 'We have detected suspicious activity in your account. Please verify your identity immediately.'"

[0349] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0350] Step 1:

[0351] The server stores the received electronic message. Specifically, when the electronic message arrives at the server via the network, the server stores the contents of the message in a database or file system. The input of this step is the electronic message, and the output is the stored electronic message.

[0352] Step 2:

[0353] The server analyzes the body of the stored electronic message by using analytical algorithms or software to tokenize the text of the message content and identify important information. The input to this step is the body of the stored electronic message, and the output is the analysis results.

[0354] Step 3:

[0355] The server extracts key information from the parsed text and generates a summary. It uses a generative AI model to summarize the key points of the electronic message and generate a concise summary. The input to this step is the analysis result, and the output is the generated summary.

[0356] Step 4:

[0357] The server recognizes the user's emotional state. It uses an emotion engine to analyze the user's emotion upon receiving the electronic message and detects specific emotions (e.g., urgency, surprise, joy, etc.). The input of this step is the body of the electronic message, and the output is the recognized emotional state.

[0358] Step 5:

[0359] The server generates a priority and recommended response for the electronic message based on the recognized emotional state. Based on the emotional state and summary information, it evaluates the importance and urgency of the message and determines a specific response. The input of this step is the summary and emotional state, and the output is a priority and recommended response.

[0360] Step 6:

[0361] The server sends the generated summary and emotional state to the terminal along with the title of the electronic message. The message title, summary, and emotional state are packaged and sent to the terminal. The inputs of this step are the summary, emotional state, and title of the electronic message, and the output is the data sent to the terminal.

[0362] Step 7:

[0363] The terminal receives the summary information of the electronic message and the result of the emotion engine obtained from the server and displays them on the screen. The title, summary, and emotional state of the electronic message are visually presented through the user interface. The input of this step is the data sent from the server, and the output is the information displayed on the terminal screen.

[0364] Step 8:

[0365] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. The user responds immediately to messages with high urgency. The input of this step is the information displayed on the device, and the output is the user's specific action.

[0366] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0367] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0368] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0369] [Second embodiment]

[0370] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0371] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0372] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0373] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0374] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0375] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0376] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0377] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0378] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0379] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0380] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0381] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0382] The present invention relates to a system for efficiently managing a large amount of e-mail that arrives in an inbox and quickly understanding its contents. The functions and operations of this system will be explained below with specific examples.

[0383] The core of this system is its function of analyzing the body of e-mails, extracting important information, and generating summaries. This allows users to easily grasp the contents of each e-mail in their inbox. Below, we will explain how it works from the perspectives of the server, terminal, and user.

[0384] Server Operation

[0385] When a new email is received, the server stores the body of the email. Then, the server analyzes the stored email and uses a generative AI model to extract important information from the body and generate a summary. For example, the server operates as follows:

[0386] First, the server connects to the IMAP server via the Internet to check for new emails. If new emails are found, the email body is saved to a database. For each saved email body, a generative AI model is applied to create a summary. The generated summary is then saved to the database and immediately reflected on the device.

[0387] Device behavior

[0388] The device displays a summary of each email along with the subject of the email on the inbox screen, allowing the user to understand the contents of the email without opening each one. For example, the device operates as follows:

[0389] The terminal retrieves email information with summaries from the server and displays them in the inbox. This allows the user to see the sender, subject, and summary of the email at a glance. In addition, the summary also shows the status of whether a reply is required, so the user can quickly determine which emails should be prioritized.

[0390] User operations

[0391] The user checks the inbox screen on the device to understand the contents and priority of the email. For example, when the user opens the inbox, the following information is displayed:

[0392] From: alice@example.com

[0393] Subject: Meeting Agenda

[0394] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0395] ==================================================

[0396] From: bob@example.com

[0397] Subject: Monthly Report Submission

[0398] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0399] ==================================================

[0400] This type of display allows the user to grasp the main points of each email at a glance and quickly determine which email should be given priority.

[0401] The system of the present invention analyzes the contents of emails and generates summaries, thereby streamlining inbox management and improving user work efficiency, allowing users to process emails appropriately without missing important emails.

[0402] The processing flow will be explained below.

[0403] Step 1:

[0404] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0405] Step 2:

[0406] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0407] Step 3:

[0408] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0409] Step 4:

[0410] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0411] Step 5:

[0412] The server stores the generated summary together with the corresponding email information in a database. This save process establishes the email subject, sender, body, and summary as a set of data.

[0413] Step 6:

[0414] The terminal displays email information with a summary to the user on the inbox screen. The terminal retrieves email information with a summary from the server and places the sender, subject, and summary on the inbox, allowing the user to check the content and importance of the email at a glance.

[0415] Step 7:

[0416] Users can check the summary displayed on the inbox screen and decide the priority of email processing. They can check the content and status, determine the necessary reply or action, and then process the email. This allows users to efficiently manage email and respond appropriately.

[0417] Example 1

[0418] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0419] In today's world, users receive a large number of electronic messages on a daily basis, which puts them at risk of missing important information and wastes time extracting the necessary information from the overwhelming volume of emails. In business environments, in particular, where prompt responses to important emails are required, a system that can efficiently understand the contents of emails is needed. To solve this problem, a system that can analyze received electronic messages, generate summaries, and determine their priority is required.

[0420] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0421] In this invention, the server includes means for checking newly arrived electronic messages via the Internet, means for saving the bodies of received electronic messages in a database, means for analyzing the bodies of the saved electronic messages using a generative AI model, means for extracting important information from the analysis results and generating summaries, means for saving the generated summaries in a database, means for reflecting the electronic message information with summaries on a terminal in real time, and means for displaying the summaries together with the titles of the electronic messages on the screen of the terminal, thereby enabling users to quickly grasp the main points of emails without opening them and to prioritize responding to important emails.

[0422] The "Internet" is a huge information network that interconnects computer networks all over the world.

[0423] An "electronic message" is a digital communication message, such as an email or text message, sent or received over the Internet.

[0424] A "server" is a computer system that provides data and services in response to requests from clients over a network.

[0425] "IMAP Server" means a server that manages and provides electronic mail using the Internet Message Access Protocol.

[0426] A "database" is a collection of information that allows efficient management of data and allows operations such as searching and updating.

[0427] A "generative AI model" is an artificial intelligence model that performs tasks such as text generation and information extraction based on given input data.

[0428] "Analysis" is the means of examining given data in detail and understanding its structure and meaning.

[0429] A "summary" is a concise summary of the main points or outline of the original information.

[0430] "Real-time" refers to a situation where data or information is processed immediately and the results are available without delay.

[0431] "Terminal" refers to a device such as a computer or mobile phone that is directly operated by a user.

[0432] The present invention relates to a system for efficiently managing a large amount of received electronic messages and quickly understanding their contents. Specific embodiments of this system will be described below.

[0433] The core of the system is its ability to analyze the body of electronic messages, extract key information, and generate summaries, allowing users to get a concise understanding of the contents of each message in their inbox.

[0434] Server behavior:

[0435] The server connects to the IMAP server via the Internet to check whether new electronic messages have been received. If new messages have been received, the message body is retrieved and stored in a database. A generative AI model is used to analyze the message body, extract key information, and generate a summary. The specific generative AI model used is GPT-3 or a similar natural language processing model. The generated summary is then stored back in the database and updated on the device in real time.

[0436] Terminal behavior:

[0437] The device displays a summary of each message along with its subject on the inbox screen. Users can view the summary without opening the message body. This allows users to quickly understand the content of each message and immediately determine which messages should be prioritized. The summary also displays the status of whether a reply is required, allowing users to respond quickly to important messages.

[0438] User Action:

[0439] The user checks the inbox screen on the device to understand the contents and priority of the message. For example, when the user opens the inbox, the following information is displayed:

[0440] From: sender@example.com

[0441] Subject: Meeting Agenda

[0442] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0443] ==================================================

[0444] From: another.sender@example.com

[0445] Subject: Monthly Report Submission

[0446] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0447] ==================================================

[0448] This type of display allows the user to grasp the gist of each message at a glance and quickly determine which message should be given priority.

[0449] Example prompt for a generative AI model:

[0450] An example of a prompt sentence to input to the generative AI model is as follows:

[0451] Extract key information and summarize the following email content:

[0452] "Dear team, Please be reminded of the meeting scheduled on Friday. Key points to be discussed include the project status update, budget review, and planning for the next quarter. Regards, Sender"

[0453] The system of the present invention analyzes the content of electronic messages and generates summaries to improve inbox management and user efficiency, thereby enabling users to avoid missing important messages and to process them appropriately.

[0454] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0455] Step 1:

[0456] The server connects to an IMAP server over the Internet to check for new electronic messages.

[0457] Input: IMAP server login information

[0458] Output: List of new email messages

[0459] Specific operation: The server accesses the INBOX folder using the IMAP protocol and checks whether there are any new emails. At this time, the IMAP server returns the unread email ID.

[0460] Step 2:

[0461] When a new electronic message is confirmed, the server retrieves the body of the message and stores it in a database.

[0462] Input: List of new email messages

[0463] Output: Saved email body

[0464] Specific operation: The server retrieves the email content from the IMAP server and saves the retrieved email body in the database.

[0465] Step 3:

[0466] The server analyzes the stored email body using a generative AI model to generate a summary.

[0467] Input: Saved email body

[0468] Output: Generated summary

[0469] Specific operation: The server inputs the prompt sentence into the generative AI model and generates a summary, which is returned in text format.

[0470] Step 4:

[0471] The server stores the generated summary again in the database.

[0472] Input: Generated summary

[0473] Output: Summary stored in database

[0474] Specific operation: The server saves the summary obtained from the generative AI model in the corresponding email entry in the database.

[0475] Step 5:

[0476] The server reflects the summarized electronic message information to the terminal in real time.

[0477] Input: Abstract stored in the database

[0478] Output: Email information sent to terminal with summary

[0479] Specific operation: The server uses WebSocket to send email information with a summary to the terminal.

[0480] Step 6:

[0481] The terminal displays a summary of each email along with its subject on the inbox screen to the user.

[0482] Input: Email information with summary sent from the server

[0483] Output: Summary displayed on the inbox screen

[0484] What it does: The device analyzes the received data and displays the email subject and summary in the inbox using technologies such as HTML and JavaScript.

[0485] Step 7:

[0486] The user checks the inbox screen on the device to understand the contents and priority of the email.

[0487] Input: Summary displayed on the inbox screen

[0488] Output: User's priority judgment

[0489] What happens: The user can read the summary of the emails displayed and decide which ones should be prioritized. If necessary, they can open the emails to view the details.

[0490] (Application example 1)

[0491] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0492] In autonomous vehicles, drivers face challenges in efficiently managing the large volume of emails they receive while driving and quickly understanding their contents. In particular, there is a need for a system that allows drivers to easily obtain important information without using their hands and quickly reply if necessary. Another important challenge is ensuring driver safety by providing information visually and audibly.

[0493] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0494] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for notifying the summary by voice, means for displaying the summary on a visual device, and means for replying to electronic messages based on voice input, thereby enabling the driver of an autonomous vehicle to quickly and accurately understand the content of received emails without using his or her hands and to reply immediately if necessary.

[0495] "Means for storing received electronic messages" refers to a device or software for storing emails received over a network in a database or memory.

[0496] A "means for analyzing the body of stored electronic messages" is a device or software that automatically analyzes the content of emails stored on a storage device and identifies important information.

[0497] "Means for extracting important information from the analyzed text and generating a summary" refers to a device or software that extracts the main points from the information obtained through the analysis and summarizes them in a concise form.

[0498] "Means for displaying the generated summary together with the title of the electronic message" means a device or software for displaying the summarized information and the subject of the original electronic message on a terminal display or other display device.

[0499] The "means for audibly announcing the summary" refers to a device or software for announcing the generated summary to the user through an audio output device.

[0500] The "means for displaying the summary on a visual device" is a device or software for displaying the generated summary on smart glasses or a head-mounted display.

[0501] A "means for replying to electronic messages based on voice input" is a device or software that transcribes a user's voice commands and replies to emails based on them.

[0502] The present invention relates to a system for improving the efficiency of email management for drivers of autonomous vehicles. Specific embodiments of the system are described below.

[0503] Server Operation

[0504] The server connects to an IMAP server over the Internet to check for new emails. When a new email is received, it stores the email body in a database. It then uses a generative AI model (such as OpenAI's GPT model) to analyze the email body, extract key information, and generate a summary. The generated summary is stored in a database and immediately reflected on the client side.

[0505] Device behavior

[0506] The device (e.g., smart glasses or a head-mounted display) retrieves email information with summaries from the server and displays them on the screen. This allows the driver to understand the contents of emails without having to open them one by one. It also has a function to provide audio notification of the summary information. For example, a voice assistant device (e.g., Amazon Echo Auto) can be used to provide audio notification of the summary generated by the generative AI model to the driver.

[0507] User operations

[0508] The user (driver) can check the inbox screen and instantly understand the summary of the email. In addition, it is possible to reply to emails by voice input. When the driver uses voice commands to input the reply content, the content is transcribed and sent as an email.

[0509] Hardware and software used

[0510] Hardware:

[0511] Smart glasses (e.g. Google Glass)

[0512] Head-mounted displays (e.g. Microsoft HoloLens)

[0513] Voice assistant devices (e.g. Amazon Echo Auto)

[0514] software:

[0515] Server side: IMAP server, generative AI model (e.g. OpenAI GPT model), database

[0516] Client side: Smart glasses, HMD applications, speech recognition software (e.g., Google Speech-to-Text)

[0517] Specific examples

[0518] For example, if a driver receives an email while driving with the subject "Meeting Agenda" and the body "Describes the agenda for the upcoming meeting on Friday. Key points include a project status update, budget review, and planning for the next quarter," the generative AI model can generate a summary using prompts like the following:

[0519] Example prompt sentence:

[0520] Summarize the given email text. For example, generate a summary in the following format:

[0521] Email subject: Meeting agenda

[0522] Body: Explain the agenda for Friday's meeting. Key points include a project status update, budget review, and planning for the next quarter.

[0523] Summary: This email outlines the agenda for a meeting scheduled for Friday. Key points include a project status update, budget review, and planning for the next quarter.

[0524] This allows the driver of an autonomous vehicle to quickly and accurately understand the contents of emails received without using their hands, and to reply immediately if necessary.

[0525] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0526] Step 1:

[0527] The server connects to the IMAP server over the Internet to check for new electronic messages. When a new email is received, it stores its body in a database. As input, the server receives an electronic message from the IMAP server, and as output, it records the body of the electronic message in a database.

[0528] Step 2:

[0529] The server passes the body of each stored electronic message to the generative AI model, extracts important information, and generates a summary, using prompts to provide appropriate instructions to the generative AI model. As input, the server sends the body of the electronic message and the prompt to the generative AI model, and as output, receives a summary from the generative AI model.

[0530] Step 3:

[0531] The server stores the generated summary in a database and immediately reflects it on the device.,As input, the summary from the generative AI model is stored in the database,,and as output, the summary is stored in the database.

[0532] Step 4:

[0533] The terminal receives email information with a summary from the server and displays it on the inbox screen. As input, the terminal receives email information with a summary from the server, and as output, it displays a list of the email subject, sender, and summary.

[0534] Step 5:

[0535] The terminal performs speech conversion processing to output the generated summary to the driver through a speech output device. The terminal receives the summary as input and outputs the converted speech information from a speaker as output.

[0536] Step 6:

[0537] The user checks the inbox screen and instantly gets a summary of the email. If necessary, the user can reply to the electronic message by voice input. As input, the user's voice command is converted into text by speech recognition software, and as output, the text reply is sent as an email.

[0538] Step 7:

[0539] The server generates text based on the user's voice input and sends it as a new electronic message. As input, the server receives text data from the speech recognition software and as output, sends it to the recipient in the form of an email.

[0540] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0541] The present invention relates to a system that efficiently manages emails received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority of emails and how to respond to them. The functions and operations of this system are explained below with specific examples.

[0542] This system combines the ability to analyze the body of emails, extract important information, and generate summaries with an emotion engine that recognizes the user's emotions, allowing users to see the content of emails in their inbox, as well as the appropriate priorities and responses based on their emotions.

[0543] Server Operation

[0544] When a new email is received, the server stores the body of the email, then analyzes it and uses a generative AI model to extract key information from the body and generate a summary.

[0545] Furthermore, the server is equipped with an emotion engine that recognizes the user's emotional state. Based on the recognized emotional state, it determines the priority of the email and recommends an appropriate response. For example, the server operates as follows:

[0546] First, the server receives and stores new emails, then uses a generative AI model to generate summaries, and then uses an emotion engine to recognize the user's emotional state and evaluate the importance and urgency of the email.

[0547] Device behavior

[0548] The device displays the email subject, summary, and priority and response instructions based on the user's emotional state as recognized by the emotion engine, allowing the user to easily understand the content and importance of the email and take appropriate action.

[0549] For example, the device receives email information with a summary and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, so users can see at a glance whether an email needs to be addressed.

[0550] User operations

[0551] The user checks the summary of the email displayed on the inbox screen and the results of the emotion engine, and takes action based on the priority of the email. For example, when a user opens their inbox, the following information may be displayed:

[0552] From: alice@example.com

[0553] Subject: Meeting Agenda

[0554] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0555] Emotion: Neutral

[0556] ==================================================

[0557] From: bob@example.com

[0558] Subject: Monthly Report Submission

[0559] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0560] Emotion: Urgent

[0561] ==================================================

[0562] In this way, the results of the emotion engine are also displayed, allowing users to quickly understand the email and respond appropriately based on their emotions. Prioritization and response can be achieved according to the user's emotional state and the content of the email.

[0563] The system of the present invention comprehensively analyzes the content of emails and the user's emotional state to improve email management efficiency, allowing users to respond quickly and appropriately without missing important emails.

[0564] The processing flow will be explained below.

[0565] Step 1:

[0566] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0567] Step 2:

[0568] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0569] Step 3:

[0570] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0571] Step 4:

[0572] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0573] Step 5:

[0574] The server associates the generated summary with the email information and stores it in a database. Through this process, the email's subject, sender, body, and summary are established as a series of data.

[0575] Step 6:

[0576] The server uses an emotion engine to analyze the summary and body of the saved emails to recognize the user's current emotional state, which is then classified into statuses such as "normal," "urgent," "joy," and "anger."

[0577] Step 7:

[0578] The server prioritizes each email based on the results of the emotion engine and stores the necessary status in a database, thereby determining the priority that reflects the email content and the user's emotional state.

[0579] Step 8:

[0580] The terminal displays the email subject, summary, and priority and status based on the user's emotional state recognized by the emotion engine to the user. The terminal obtains email information with summary and the result of the emotion engine from the server and displays them in the inbox.

[0581] Step 9:

[0582] Users can check the summary and emotional state of emails displayed on the inbox screen and respond based on the priority of the email. Users can categorize emails based on the displayed information and immediately determine the priority of their replies or responses.

[0583] By using the above steps, the system of the present invention comprehensively analyzes the content of emails and the user's emotional state, improving the efficiency of email management. This allows users to respond quickly and appropriately to important emails without missing them.

[0584] Example 2

[0585] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0586] Conventional electronic message management systems have the problem that when a large number of messages accumulate in the inbox, the risk of missing important messages increases and the possibility of delayed responses increases. It is also difficult to quickly grasp the content and urgency of messages, which increases the burden on users. In addition to these issues, there is a significant lack of functionality that automatically provides appropriate responses that take into account the user's emotional state.

[0587] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0588] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for recognizing the user's emotional state, and means for determining the priority of the electronic messages based on the recognized emotional state and recommending an appropriate response method, thereby enabling efficient analysis of the content of the electronic messages and the user's emotional state and enabling prompt and appropriate responses.

[0589] "Means" refers to functional components that make up a system, and includes devices and programs capable of executing specific functions or operations.

[0590] A "server" is a computer system that accepts requests from clients on a network and provides the corresponding services or functions.

[0591] "Electronic message" refers to a communication message sent or received in digital form, such as email, and may include text, images, attachments, etc.

[0592] "Storage" refers to the act of recording a received electronic message in a database or storage device so that it can be retrieved at a later time.

[0593] "Analysis" refers to the process of closely examining the content of stored electronic messages and extracting necessary information or patterns.

[0594] A "generative AI model" refers to an artificial intelligence algorithm that uses natural language processing and machine learning to analyze text and generate or transform information.

[0595] "Summary" means a short narrative statement that succinctly sets out the key information extracted from the body of an electronic message.

[0596] The "emotional state" indicates the psychological state of the user when receiving the electronic message, and is classified into categories such as "urgent" and "important."

[0597] "Priority" refers to the order of necessity or urgency of a response among multiple electronic messages.

[0598] "Recommended responses" refers to a function that suggests appropriate responses to users based on the recognized emotional state and summarized content.

[0599] "Visual display" refers to the means by which information such as the content, emotional state, or priority of an electronic message is presented to a user as graphical elements or icons.

[0600] The present invention is a system that efficiently manages electronic messages received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority and response method of the messages. This system includes a server and a terminal as its main components, each of which performs a specific function to realize the overall mail management process.

[0601] Server configuration and operation

[0602] The server consists of hardware and software with the following main functions:

[0603] 1. Receiving and storing emails

[0604] The server receives electronic messages via the Internet and stores them in a database, including sender information, subject lines, and message body text.

[0605] 2. Use of analytical and generative AI models

[0606] The server uses a generative AI model (specifically GPT-4) to analyze the body of the stored electronic message. The following is an example of a prompt:

[0607] Please analyze the email body below and extract the important information.

[0608] Analysis extracts important information and generates summaries.

[0609] 3. Emotion recognition

[0610] The server uses an emotion engine to recognize the user's emotional state, which is classified into categories such as "urgent," "important," and "minor."

[0611] 4. Prioritization and recommended actions

[0612] Prioritize messages based on perceived emotional state and summarized content, and recommend appropriate responses (e.g., "Reply now," "Reply later," etc.).

[0613] 5. Recording user emotions

[0614] The server records the user's emotional state for each electronic message and keeps it as a management history.

[0615] Terminal configuration and operation

[0616] Terminals consist of devices (e.g., smartphones, tablets, and PCs) that have the following functions:

[0617] 1. Obtaining email information

[0618] The terminal obtains the email subject, summary, and emotion engine results from the server.

[0619] 2. Displaying email information

[0620] The device displays the retrieved information in a user interface, including subject line, summary, priority, and emotional state, along with visual icons and statuses, allowing users to quickly determine whether action is required.

[0621] User operations

[0622] Users use this system to manage and respond to electronic messages through the following operations:

[0623] 1. Check your inbox

[0624] Users can view the subject line, summary, and sentiment recognition results in their inbox, allowing them to quickly determine message priorities.

[0625] 2. Responding to emails

[0626] The user can then take appropriate action based on the displayed information, for example, replying immediately to messages of high urgency and responding later to messages of low importance.

[0627] Specific examples

[0628] As a specific example, consider the case where a server receives the following electronic message and performs analysis, summarization, emotion recognition, and prioritization:

[0629] From: johndoe@example.com

[0630] Subject: Project progress review

[0631] Summary: This email is intended to review the progress of an ongoing project. The main points are to confirm the schedule, allocate resources, and report any issues.

[0632] Emotion: emergency

[0633] In this way, the system provides email information in a format that users can intuitively understand, helping them to respond quickly and appropriately.

[0634] The system comprehensively analyzes the content of electronic messages and the user's emotional state to achieve efficient email management, allowing users to avoid missing important messages and respond appropriately in a timely manner.

[0635] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0636] Server Processing Steps

[0637] Step 1:

[0638] The server receives electronic messages. Specifically, it retrieves new emails from an email server over the Internet and receives data including the sender, subject, and body of the email. The input is the new email, and the output is the received email data.

[0639] Step 2:

[0640] The server stores received electronic messages in a database. Specifically, it records the content of the email (sender, subject, and body) in the database. The input is the received email data, and the output is the stored database entry.

[0641] Step 3:

[0642] The server analyzes the body of the stored electronic message. Specifically, it uses a generative AI model to analyze the email body and extract important information. The input is the email body data, and the output is the analysis result data. The prompt is as follows:

[0643] Please analyze the email body below and extract the important information.

[0644] Step 4:

[0645] The server generates a summary based on the analysis results. Specifically, it converts the output of the generative AI model into a summary. The input is the analysis result data, and the output is the generated summary text.

[0646] Step 5:

[0647] The server uses an emotion engine to recognize the user's emotional state. Specifically, it applies an algorithm to classify emotions from the analyzed email content. The input is the email content data, and the output is the emotional state data (e.g., urgent, important, minor, etc.).

[0648] Step 6:

[0649] The server determines the priority of the email based on the recognized emotional state and recommends an appropriate response. Specifically, it applies a prioritization algorithm to determine the response. The input is the emotional state data and a summary, and the output is the priority and the recommended response.

[0650] Step 7:

[0651] The server records the user's emotional state and response in a database. Specifically, it stores the priority and response for each email in the database. The input is the priority and response data, and the output is the updated database entry.

[0652] Terminal processing steps

[0653] Step 1:

[0654] The terminal obtains email information from the server. Specifically, it sends a request to the server and receives the email subject, summary, and emotional state data in return. The input is the request, and the output is the obtained email information data.

[0655] Step 2:

[0656] The terminal displays the acquired email information on the screen. Specifically, the email's subject, summary, emotional state, and priority are displayed on the user interface. The input is the acquired email information data, and the output is the screen information displayed to the user. Visual icons and statuses are also displayed.

[0657] User processing steps

[0658] Step 1:

[0659] The user checks the inbox screen of the terminal. Specifically, the displayed email information (subject, summary, emotional state, and priority) is checked. The input is the screen information, and the output is the user's recognition result.

[0660] Step 2:

[0661] The user responds to the email based on the displayed information. Specifically, they reply immediately to emails with high urgency and respond later to emails with low urgency. The input is the user's recognition result, and the output is the user's response action.

[0662] (Application example 2)

[0663] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0664] It has been a challenge for users to quickly and appropriately identify and respond to important messages from the vast amount of electronic messages they receive. In particular, in security services, it is necessary to take into account the user's emotional state and prioritize messages with high urgency. Therefore, there is a need for a system that integrates electronic message summary generation and emotion recognition to prompt users to take immediate and appropriate action.

[0665] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0666] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating summaries, means for recognizing the user's emotional state, means for generating priorities for electronic messages and recommended responses based on the recognized emotional state, and means for displaying the generated summaries and emotional state together with the titles of the electronic messages. This allows the user to grasp the priorities of electronic messages based on their content and emotional state, and enables them to quickly respond to messages with high urgency.

[0667] An "electronic message" is a form of text data sent or received over the Internet or other network.

[0668] "Storage means" refers to a device or software that has the function of storing received electronic messages in a storage device such as a database or file system.

[0669] A "text analysis means" is an algorithm or software that analyzes the content of a stored electronic message and extracts specific information.

[0670] A "means for extracting key information and generating summaries" is an algorithm or generative AI model for extracting key points from the content of an electronic message and presenting them as a summary.

[0671] The "means for recognizing the emotional state of the user" is an emotion engine or software for analyzing the emotional state of the user when receiving a message and recognizing a particular emotion.

[0672] The "means for generating priorities and recommended responses" is an algorithm or software for determining the importance and urgency of a response to an electronic message based on the recognized emotional state of the user and summary information, and for suggesting an appropriate response.

[0673] The "means for displaying" is a display device or user interface for visually presenting the generated summary, emotional state, and message title to the user.

[0674] The system for implementing the present invention mainly comprises three elements: a server, a terminal, and a user.

[0675] The server stores received electronic messages in a database or file system. The stored electronic messages are processed by algorithms and software that analyze the text, extracting important information and generating summaries. Specifically, a generative AI model is used to extract key points from the content of the electronic message. The server then uses an emotion engine to recognize the user's emotional state and prioritizes the electronic message and recommends a course of action based on the recognized emotional state. The generated summaries and emotional state are then sent to the device along with the title of the electronic message.

[0676] The terminal receives summary information of electronic messages and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, allowing users to see at a glance whether an email requires a response. In addition, special alerts are displayed for messages with high urgency based on the user's emotional state. This allows users to easily identify messages that require immediate attention.

[0677] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. For example, if the message is urgent, an action plan for immediate response is presented. This allows the user to respond quickly and appropriately without missing important electronic messages.

[0678] Consider the following scenario: When a user receives a security-related electronic message, the server processes the message as follows:

[0679] Server Action:

[0680] 1. Store electronic messages.

[0681] 2. Analyze the body of the stored message, extract important information, and generate a summary.

[0682] 3. The emotion engine recognizes the user's emotional state and determines priorities.

[0683] 4. A summary of the electronic message and the emotional state are sent to the terminal along with the title.

[0684] Example of terminal display:

[0685] From: sender@example.com

[0686] Subject: Security Alert

[0687] Summary: We have detected suspicious activity in your account. Please verify your identity immediately.

[0688] Emotion: Urgent

[0689] In this way, the generated summary and emotional state are displayed appropriately, allowing the user to quickly and accurately grasp messages that require a response.

[0690] An example prompt might use the following format:

[0691] "Please summarize the following email and analyze the user's emotion: 'We have detected suspicious activity in your account. Please verify your identity immediately.'"

[0692] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0693] Step 1:

[0694] The server stores the received electronic message. Specifically, when the electronic message arrives at the server via the network, the server stores the contents of the message in a database or file system. The input of this step is the electronic message, and the output is the stored electronic message.

[0695] Step 2:

[0696] The server analyzes the body of the stored electronic message by using analytical algorithms or software to tokenize the text of the message content and identify important information. The input to this step is the body of the stored electronic message, and the output is the analysis results.

[0697] Step 3:

[0698] The server extracts key information from the parsed text and generates a summary. It uses a generative AI model to summarize the key points of the electronic message and generate a concise summary. The input to this step is the analysis result, and the output is the generated summary.

[0699] Step 4:

[0700] The server recognizes the user's emotional state. It uses an emotion engine to analyze the user's emotion upon receiving the electronic message and detects specific emotions (e.g., urgency, surprise, joy, etc.). The input of this step is the body of the electronic message, and the output is the recognized emotional state.

[0701] Step 5:

[0702] The server generates a priority and recommended response for the electronic message based on the recognized emotional state. Based on the emotional state and summary information, it evaluates the importance and urgency of the message and determines a specific response. The input of this step is the summary and emotional state, and the output is a priority and recommended response.

[0703] Step 6:

[0704] The server sends the generated summary and emotional state to the terminal along with the title of the electronic message. The message title, summary, and emotional state are packaged and sent to the terminal. The inputs of this step are the summary, emotional state, and title of the electronic message, and the output is the data sent to the terminal.

[0705] Step 7:

[0706] The terminal receives the summary information of the electronic message and the result of the emotion engine obtained from the server and displays them on the screen. The title, summary, and emotional state of the electronic message are visually presented through the user interface. The input of this step is the data sent from the server, and the output is the information displayed on the terminal screen.

[0707] Step 8:

[0708] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. The user responds immediately to messages with high urgency. The input of this step is the information displayed on the device, and the output is the user's specific action.

[0709] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0710] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0711] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0712] [Third embodiment]

[0713] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0714] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0715] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0716] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0717] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0718] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0719] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0720] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0721] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0722] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0723] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0724] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0725] The present invention relates to a system for efficiently managing a large amount of e-mail that arrives in an inbox and quickly understanding its contents. The functions and operations of this system will be explained below with specific examples.

[0726] The core of this system is its function of analyzing the body of e-mails, extracting important information, and generating summaries. This allows users to easily grasp the contents of each e-mail in their inbox. Below, we will explain how it works from the perspectives of the server, terminal, and user.

[0727] Server Operation

[0728] When a new email is received, the server stores the body of the email. Then, the server analyzes the stored email and uses a generative AI model to extract important information from the body and generate a summary. For example, the server operates as follows:

[0729] First, the server connects to the IMAP server via the Internet to check for new emails. If new emails are found, the email body is saved to a database. For each saved email body, a generative AI model is applied to create a summary. The generated summary is then saved to the database and immediately reflected on the device.

[0730] Device behavior

[0731] The device displays a summary of each email along with the subject of the email on the inbox screen, allowing the user to understand the contents of the email without opening each one. For example, the device operates as follows:

[0732] The terminal retrieves email information with summaries from the server and displays them in the inbox. This allows the user to see the sender, subject, and summary of the email at a glance. In addition, the summary also shows the status of whether a reply is required, so the user can quickly determine which emails should be prioritized.

[0733] User operations

[0734] The user checks the inbox screen on the device to understand the contents and priority of the email. For example, when the user opens the inbox, the following information is displayed:

[0735] From: alice@example.com

[0736] Subject: Meeting Agenda

[0737] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0738] ==================================================

[0739] From: bob@example.com

[0740] Subject: Monthly Report Submission

[0741] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0742] ==================================================

[0743] This type of display allows the user to grasp the main points of each email at a glance and quickly determine which email should be given priority.

[0744] The system of the present invention analyzes the contents of emails and generates summaries, thereby streamlining inbox management and improving user work efficiency, allowing users to process emails appropriately without missing important emails.

[0745] The processing flow will be explained below.

[0746] Step 1:

[0747] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0748] Step 2:

[0749] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0750] Step 3:

[0751] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0752] Step 4:

[0753] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0754] Step 5:

[0755] The server stores the generated summary together with the corresponding email information in a database. This save process establishes the email subject, sender, body, and summary as a set of data.

[0756] Step 6:

[0757] The terminal displays email information with a summary to the user on the inbox screen. The terminal retrieves email information with a summary from the server and places the sender, subject, and summary on the inbox, allowing the user to check the content and importance of the email at a glance.

[0758] Step 7:

[0759] Users can check the summary displayed on the inbox screen and decide the priority of email processing. They can check the content and status, determine the necessary reply or action, and then process the email. This allows users to efficiently manage email and respond appropriately.

[0760] Example 1

[0761] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0762] In today's world, users receive a large number of electronic messages on a daily basis, which puts them at risk of missing important information and wastes time extracting the necessary information from the overwhelming volume of emails. In business environments, in particular, where prompt responses to important emails are required, a system that can efficiently understand the contents of emails is needed. To solve this problem, a system that can analyze received electronic messages, generate summaries, and determine their priority is required.

[0763] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0764] In this invention, the server includes means for checking newly arrived electronic messages via the Internet, means for saving the bodies of received electronic messages in a database, means for analyzing the bodies of the saved electronic messages using a generative AI model, means for extracting important information from the analysis results and generating summaries, means for saving the generated summaries in a database, means for reflecting the electronic message information with summaries on a terminal in real time, and means for displaying the summaries together with the titles of the electronic messages on the screen of the terminal, thereby enabling users to quickly grasp the main points of emails without opening them and to prioritize responding to important emails.

[0765] The "Internet" is a huge information network that interconnects computer networks all over the world.

[0766] An "electronic message" is a digital communication message, such as an email or text message, sent or received over the Internet.

[0767] A "server" is a computer system that provides data and services in response to requests from clients over a network.

[0768] "IMAP Server" means a server that manages and provides electronic mail using the Internet Message Access Protocol.

[0769] A "database" is a collection of information that allows efficient management of data and allows operations such as searching and updating.

[0770] A "generative AI model" is an artificial intelligence model that performs tasks such as text generation and information extraction based on given input data.

[0771] "Analysis" is the means of examining given data in detail and understanding its structure and meaning.

[0772] A "summary" is a concise summary of the main points or outline of the original information.

[0773] "Real-time" refers to a situation where data or information is processed immediately and the results are available without delay.

[0774] "Terminal" refers to a device such as a computer or mobile phone that is directly operated by a user.

[0775] The present invention relates to a system for efficiently managing a large amount of received electronic messages and quickly understanding their contents. Specific embodiments of this system will be described below.

[0776] The core of the system is its ability to analyze the body of electronic messages, extract key information, and generate summaries, allowing users to get a concise understanding of the contents of each message in their inbox.

[0777] Server behavior:

[0778] The server connects to the IMAP server via the Internet to check whether new electronic messages have been received. If new messages have been received, the message body is retrieved and stored in a database. A generative AI model is used to analyze the message body, extract key information, and generate a summary. The specific generative AI model used is GPT-3 or a similar natural language processing model. The generated summary is then stored back in the database and updated on the device in real time.

[0779] Terminal behavior:

[0780] The device displays a summary of each message along with its subject on the inbox screen. Users can view the summary without opening the message body. This allows users to quickly understand the content of each message and immediately determine which messages should be prioritized. The summary also displays the status of whether a reply is required, allowing users to respond quickly to important messages.

[0781] User Action:

[0782] The user checks the inbox screen on the device to understand the contents and priority of the message. For example, when the user opens the inbox, the following information is displayed:

[0783] From: sender@example.com

[0784] Subject: Meeting Agenda

[0785] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0786] ==================================================

[0787] From: another.sender@example.com

[0788] Subject: Monthly Report Submission

[0789] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0790] ==================================================

[0791] This type of display allows the user to grasp the gist of each message at a glance and quickly determine which message should be given priority.

[0792] Example prompt for a generative AI model:

[0793] An example of a prompt sentence to input to the generative AI model is as follows:

[0794] Extract key information and summarize the following email content:

[0795] "Dear team, Please be reminded of the meeting scheduled on Friday. Key points to be discussed include the project status update, budget review, and planning for the next quarter. Regards, Sender"

[0796] The system of the present invention analyzes the content of electronic messages and generates summaries to improve inbox management and user efficiency, thereby enabling users to avoid missing important messages and to process them appropriately.

[0797] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0798] Step 1:

[0799] The server connects to an IMAP server over the Internet to check for new electronic messages.

[0800] Input: IMAP server login information

[0801] Output: List of new email messages

[0802] Specific operation: The server accesses the INBOX folder using the IMAP protocol and checks whether there are any new emails. At this time, the IMAP server returns the unread email ID.

[0803] Step 2:

[0804] When a new electronic message is confirmed, the server retrieves the body of the message and stores it in a database.

[0805] Input: List of new email messages

[0806] Output: Saved email body

[0807] Specific operation: The server retrieves the email content from the IMAP server and saves the retrieved email body in the database.

[0808] Step 3:

[0809] The server analyzes the stored email body using a generative AI model to generate a summary.

[0810] Input: Saved email body

[0811] Output: Generated summary

[0812] Specific operation: The server inputs the prompt sentence into the generative AI model and generates a summary, which is returned in text format.

[0813] Step 4:

[0814] The server stores the generated summary again in the database.

[0815] Input: Generated summary

[0816] Output: Summary stored in database

[0817] Specific operation: The server saves the summary obtained from the generative AI model in the corresponding email entry in the database.

[0818] Step 5:

[0819] The server reflects the summarized electronic message information to the terminal in real time.

[0820] Input: Abstract stored in the database

[0821] Output: Email information sent to terminal with summary

[0822] Specific operation: The server uses WebSocket to send email information with a summary to the terminal.

[0823] Step 6:

[0824] The terminal displays a summary of each email along with its subject on the inbox screen to the user.

[0825] Input: Email information with summary sent from the server

[0826] Output: Summary displayed on the inbox screen

[0827] What it does: The device analyzes the received data and displays the email subject and summary in the inbox using technologies such as HTML and JavaScript.

[0828] Step 7:

[0829] The user checks the inbox screen on the device to understand the contents and priority of the email.

[0830] Input: Summary displayed on the inbox screen

[0831] Output: User's priority judgment

[0832] What happens: The user can read the summary of the emails displayed and decide which ones should be prioritized. If necessary, they can open the emails to view the details.

[0833] (Application example 1)

[0834] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0835] In autonomous vehicles, drivers face challenges in efficiently managing the large volume of emails they receive while driving and quickly understanding their contents. In particular, there is a need for a system that allows drivers to easily obtain important information without using their hands and quickly reply if necessary. Another important challenge is ensuring driver safety by providing information visually and audibly.

[0836] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0837] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for notifying the summary by voice, means for displaying the summary on a visual device, and means for replying to electronic messages based on voice input, thereby enabling the driver of an autonomous vehicle to quickly and accurately understand the content of received emails without using his or her hands and to reply immediately if necessary.

[0838] "Means for storing received electronic messages" refers to a device or software for storing emails received over a network in a database or memory.

[0839] A "means for analyzing the body of stored electronic messages" is a device or software that automatically analyzes the content of emails stored on a storage device and identifies important information.

[0840] "Means for extracting important information from the analyzed text and generating a summary" refers to a device or software that extracts the main points from the information obtained through the analysis and summarizes them in a concise form.

[0841] "Means for displaying the generated summary together with the title of the electronic message" means a device or software for displaying the summarized information and the subject of the original electronic message on a terminal display or other display device.

[0842] The "means for audibly announcing the summary" refers to a device or software for announcing the generated summary to the user through an audio output device.

[0843] The "means for displaying the summary on a visual device" is a device or software for displaying the generated summary on smart glasses or a head-mounted display.

[0844] A "means for replying to electronic messages based on voice input" is a device or software that transcribes a user's voice commands and replies to emails based on them.

[0845] The present invention relates to a system for improving the efficiency of email management for drivers of autonomous vehicles. Specific embodiments of the system are described below.

[0846] Server Operation

[0847] The server connects to an IMAP server over the Internet to check for new emails. When a new email is received, it stores the email body in a database. It then uses a generative AI model (such as OpenAI's GPT model) to analyze the email body, extract key information, and generate a summary. The generated summary is stored in a database and immediately reflected on the client side.

[0848] Device behavior

[0849] The device (e.g., smart glasses or a head-mounted display) retrieves email information with summaries from the server and displays them on the screen. This allows the driver to understand the contents of emails without having to open them one by one. It also has a function to provide audio notification of the summary information. For example, a voice assistant device (e.g., Amazon Echo Auto) can be used to provide audio notification of the summary generated by the generative AI model to the driver.

[0850] User operations

[0851] The user (driver) can check the inbox screen and instantly understand the summary of the email. In addition, it is possible to reply to emails by voice input. When the driver uses voice commands to input the reply content, the content is transcribed and sent as an email.

[0852] Hardware and software used

[0853] Hardware:

[0854] Smart glasses (e.g. Google Glass)

[0855] Head-mounted displays (e.g. Microsoft HoloLens)

[0856] Voice assistant devices (e.g. Amazon Echo Auto)

[0857] software:

[0858] Server side: IMAP server, generative AI model (e.g. OpenAI GPT model), database

[0859] Client side: Smart glasses, HMD applications, speech recognition software (e.g., Google Speech-to-Text)

[0860] Specific examples

[0861] For example, if a driver receives an email while driving with the subject "Meeting Agenda" and the body "Describes the agenda for the upcoming meeting on Friday. Key points include a project status update, budget review, and planning for the next quarter," the generative AI model can generate a summary using prompts like the following:

[0862] Example prompt sentence:

[0863] Summarize the given email text. For example, generate a summary in the following format:

[0864] Email subject: Meeting agenda

[0865] Body: Explain the agenda for Friday's meeting. Key points include a project status update, budget review, and planning for the next quarter.

[0866] Summary: This email outlines the agenda for a meeting scheduled for Friday. Key points include a project status update, budget review, and planning for the next quarter.

[0867] This allows the driver of an autonomous vehicle to quickly and accurately understand the contents of emails received without using their hands, and to reply immediately if necessary.

[0868] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0869] Step 1:

[0870] The server connects to the IMAP server over the Internet to check for new electronic messages. When a new email is received, it stores its body in a database. As input, the server receives an electronic message from the IMAP server, and as output, it records the body of the electronic message in a database.

[0871] Step 2:

[0872] The server passes the body of each stored electronic message to the generative AI model, extracts important information, and generates a summary, using prompts to provide appropriate instructions to the generative AI model. As input, the server sends the body of the electronic message and the prompt to the generative AI model, and as output, receives a summary from the generative AI model.

[0873] Step 3:

[0874] The server stores the generated summary in a database and immediately reflects it on the device.,As input, the summary from the generative AI model is stored in the database,,and as output, the summary is stored in the database.

[0875] Step 4:

[0876] The terminal receives email information with a summary from the server and displays it on the inbox screen. As input, the terminal receives email information with a summary from the server, and as output, it displays a list of the email subject, sender, and summary.

[0877] Step 5:

[0878] The terminal performs speech conversion processing to output the generated summary to the driver through a speech output device. The terminal receives the summary as input and outputs the converted speech information from a speaker as output.

[0879] Step 6:

[0880] The user checks the inbox screen and instantly gets a summary of the email. If necessary, the user can reply to the electronic message by voice input. As input, the user's voice command is converted into text by speech recognition software, and as output, the text reply is sent as an email.

[0881] Step 7:

[0882] The server generates text based on the user's voice input and sends it as a new electronic message. As input, the server receives text data from the speech recognition software and as output, sends it to the recipient in the form of an email.

[0883] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0884] The present invention relates to a system that efficiently manages emails received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority of emails and how to respond to them. The functions and operations of this system are explained below with specific examples.

[0885] This system combines the ability to analyze the body of emails, extract important information, and generate summaries with an emotion engine that recognizes the user's emotions, allowing users to see the content of emails in their inbox, as well as the appropriate priorities and responses based on their emotions.

[0886] Server Operation

[0887] When a new email is received, the server stores the body of the email, then analyzes it and uses a generative AI model to extract key information from the body and generate a summary.

[0888] Furthermore, the server is equipped with an emotion engine that recognizes the user's emotional state. Based on the recognized emotional state, it determines the priority of the email and recommends an appropriate response. For example, the server operates as follows:

[0889] First, the server receives and stores new emails, then uses a generative AI model to generate summaries, and then uses an emotion engine to recognize the user's emotional state and evaluate the importance and urgency of the email.

[0890] Device behavior

[0891] The device displays the email subject, summary, and priority and response instructions based on the user's emotional state as recognized by the emotion engine, allowing the user to easily understand the content and importance of the email and take appropriate action.

[0892] For example, the device receives email information with a summary and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, so users can see at a glance whether an email needs to be addressed.

[0893] User operations

[0894] The user checks the summary of the email displayed on the inbox screen and the results of the emotion engine, and takes action based on the priority of the email. For example, when a user opens their inbox, the following information may be displayed:

[0895] From: alice@example.com

[0896] Subject: Meeting Agenda

[0897] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[0898] Emotion: Neutral

[0899] ==================================================

[0900] From: bob@example.com

[0901] Subject: Monthly Report Submission

[0902] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[0903] Emotion: Urgent

[0904] ==================================================

[0905] In this way, the results of the emotion engine are also displayed, allowing users to quickly understand the email and respond appropriately based on their emotions. Prioritization and response can be achieved according to the user's emotional state and the content of the email.

[0906] The system of the present invention comprehensively analyzes the content of emails and the user's emotional state to improve email management efficiency, allowing users to respond quickly and appropriately without missing important emails.

[0907] The processing flow will be explained below.

[0908] Step 1:

[0909] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[0910] Step 2:

[0911] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[0912] Step 3:

[0913] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[0914] Step 4:

[0915] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[0916] Step 5:

[0917] The server associates the generated summary with the email information and stores it in a database. Through this process, the email's subject, sender, body, and summary are established as a series of data.

[0918] Step 6:

[0919] The server uses an emotion engine to analyze the summary and body of the saved emails to recognize the user's current emotional state, which is then classified into statuses such as "normal," "urgent," "joy," and "anger."

[0920] Step 7:

[0921] The server prioritizes each email based on the results of the emotion engine and stores the necessary status in a database, thereby determining the priority that reflects the email content and the user's emotional state.

[0922] Step 8:

[0923] The terminal displays the email subject, summary, and priority and status based on the user's emotional state recognized by the emotion engine to the user. The terminal obtains email information with summary and the result of the emotion engine from the server and displays them in the inbox.

[0924] Step 9:

[0925] Users can check the summary and emotional state of emails displayed on the inbox screen and respond based on the priority of the email. Users can categorize emails based on the displayed information and immediately determine the priority of their replies or responses.

[0926] By using the above steps, the system of the present invention comprehensively analyzes the content of emails and the user's emotional state, improving the efficiency of email management. This allows users to respond quickly and appropriately to important emails without missing them.

[0927] Example 2

[0928] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0929] Conventional electronic message management systems have the problem that when a large number of messages accumulate in the inbox, the risk of missing important messages increases and the possibility of delayed responses increases. It is also difficult to quickly grasp the content and urgency of messages, which increases the burden on users. In addition to these issues, there is a significant lack of functionality that automatically provides appropriate responses that take into account the user's emotional state.

[0930] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0931] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for recognizing the user's emotional state, and means for determining the priority of the electronic messages based on the recognized emotional state and recommending an appropriate response method, thereby enabling efficient analysis of the content of the electronic messages and the user's emotional state and enabling prompt and appropriate responses.

[0932] "Means" refers to functional components that make up a system, and includes devices and programs capable of executing specific functions or operations.

[0933] A "server" is a computer system that accepts requests from clients on a network and provides the corresponding services or functions.

[0934] "Electronic message" refers to a communication message sent or received in digital form, such as email, and may include text, images, attachments, etc.

[0935] "Storage" refers to the act of recording a received electronic message in a database or storage device so that it can be retrieved at a later time.

[0936] "Analysis" refers to the process of closely examining the content of stored electronic messages and extracting necessary information or patterns.

[0937] A "generative AI model" refers to an artificial intelligence algorithm that uses natural language processing and machine learning to analyze text and generate or transform information.

[0938] "Summary" means a short narrative statement that succinctly sets out the key information extracted from the body of an electronic message.

[0939] The "emotional state" indicates the psychological state of the user when receiving the electronic message, and is classified into categories such as "urgent" and "important."

[0940] "Priority" refers to the order of necessity or urgency of a response among multiple electronic messages.

[0941] "Recommended responses" refers to a function that suggests appropriate responses to users based on the recognized emotional state and summarized content.

[0942] "Visual display" refers to the means by which information such as the content, emotional state, or priority of an electronic message is presented to a user as graphical elements or icons.

[0943] The present invention is a system that efficiently manages electronic messages received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority and response method of the messages. This system includes a server and a terminal as its main components, each of which performs a specific function to realize the overall mail management process.

[0944] Server configuration and operation

[0945] The server consists of hardware and software with the following main functions:

[0946] 1. Receiving and storing emails

[0947] The server receives electronic messages via the Internet and stores them in a database, including sender information, subject lines, and message body text.

[0948] 2. Use of analytical and generative AI models

[0949] The server uses a generative AI model (specifically GPT-4) to analyze the body of the stored electronic message. The following is an example of a prompt:

[0950] Please analyze the email body below and extract the important information.

[0951] Analysis extracts important information and generates summaries.

[0952] 3. Emotion recognition

[0953] The server uses an emotion engine to recognize the user's emotional state, which is classified into categories such as "urgent," "important," and "minor."

[0954] 4. Prioritization and recommended actions

[0955] Prioritize messages based on perceived emotional state and summarized content, and recommend appropriate responses (e.g., "Reply now," "Reply later," etc.).

[0956] 5. Recording user emotions

[0957] The server records the user's emotional state for each electronic message and keeps it as a management history.

[0958] Terminal configuration and operation

[0959] Terminals consist of devices (e.g., smartphones, tablets, and PCs) that have the following functions:

[0960] 1. Obtaining email information

[0961] The terminal obtains the email subject, summary, and emotion engine results from the server.

[0962] 2. Displaying email information

[0963] The device displays the retrieved information in a user interface, including subject line, summary, priority, and emotional state, along with visual icons and statuses, allowing users to quickly determine whether action is required.

[0964] User operations

[0965] Users use this system to manage and respond to electronic messages through the following operations:

[0966] 1. Check your inbox

[0967] Users can view the subject line, summary, and sentiment recognition results in their inbox, allowing them to quickly determine message priorities.

[0968] 2. Responding to emails

[0969] The user can then take appropriate action based on the displayed information, for example, replying immediately to messages of high urgency and responding later to messages of low importance.

[0970] Specific examples

[0971] As a specific example, consider the case where a server receives the following electronic message and performs analysis, summarization, emotion recognition, and prioritization:

[0972] From: johndoe@example.com

[0973] Subject: Project progress review

[0974] Summary: This email is intended to review the progress of an ongoing project. The main points are to confirm the schedule, allocate resources, and report any issues.

[0975] Emotion: emergency

[0976] In this way, the system provides email information in a format that users can intuitively understand, helping them to respond quickly and appropriately.

[0977] The system comprehensively analyzes the content of electronic messages and the user's emotional state to achieve efficient email management, allowing users to avoid missing important messages and respond appropriately in a timely manner.

[0978] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0979] Server Processing Steps

[0980] Step 1:

[0981] The server receives electronic messages. Specifically, it retrieves new emails from an email server over the Internet and receives data including the sender, subject, and body of the email. The input is the new email, and the output is the received email data.

[0982] Step 2:

[0983] The server stores received electronic messages in a database. Specifically, it records the content of the email (sender, subject, and body) in the database. The input is the received email data, and the output is the stored database entry.

[0984] Step 3:

[0985] The server analyzes the body of the stored electronic message. Specifically, it uses a generative AI model to analyze the email body and extract important information. The input is the email body data, and the output is the analysis result data. The prompt is as follows:

[0986] Please analyze the email body below and extract the important information.

[0987] Step 4:

[0988] The server generates a summary based on the analysis results. Specifically, it converts the output of the generative AI model into a summary. The input is the analysis result data, and the output is the generated summary text.

[0989] Step 5:

[0990] The server uses an emotion engine to recognize the user's emotional state. Specifically, it applies an algorithm to classify emotions from the analyzed email content. The input is the email content data, and the output is the emotional state data (e.g., urgent, important, minor, etc.).

[0991] Step 6:

[0992] The server determines the priority of the email based on the recognized emotional state and recommends an appropriate response. Specifically, it applies a prioritization algorithm to determine the response. The input is the emotional state data and a summary, and the output is the priority and the recommended response.

[0993] Step 7:

[0994] The server records the user's emotional state and response in a database. Specifically, it stores the priority and response for each email in the database. The input is the priority and response data, and the output is the updated database entry.

[0995] Terminal processing steps

[0996] Step 1:

[0997] The terminal obtains email information from the server. Specifically, it sends a request to the server and receives the email subject, summary, and emotional state data in return. The input is the request, and the output is the obtained email information data.

[0998] Step 2:

[0999] The terminal displays the acquired email information on the screen. Specifically, the email's subject, summary, emotional state, and priority are displayed on the user interface. The input is the acquired email information data, and the output is the screen information displayed to the user. Visual icons and statuses are also displayed.

[1000] User processing steps

[1001] Step 1:

[1002] The user checks the inbox screen of the terminal. Specifically, the displayed email information (subject, summary, emotional state, and priority) is checked. The input is the screen information, and the output is the user's recognition result.

[1003] Step 2:

[1004] The user responds to the email based on the displayed information. Specifically, they reply immediately to emails with high urgency and respond later to emails with low urgency. The input is the user's recognition result, and the output is the user's response action.

[1005] (Application example 2)

[1006] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1007] It has been a challenge for users to quickly and appropriately identify and respond to important messages from the vast amount of electronic messages they receive. In particular, in security services, it is necessary to take into account the user's emotional state and prioritize messages with high urgency. Therefore, there is a need for a system that integrates electronic message summary generation and emotion recognition to prompt users to take immediate and appropriate action.

[1008] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1009] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating summaries, means for recognizing the user's emotional state, means for generating priorities for electronic messages and recommended responses based on the recognized emotional state, and means for displaying the generated summaries and emotional state together with the titles of the electronic messages. This allows the user to grasp the priorities of electronic messages based on their content and emotional state, and enables them to quickly respond to messages with high urgency.

[1010] An "electronic message" is a form of text data sent or received over the Internet or other network.

[1011] "Storage means" refers to a device or software that has the function of storing received electronic messages in a storage device such as a database or file system.

[1012] A "text analysis means" is an algorithm or software that analyzes the content of a stored electronic message and extracts specific information.

[1013] A "means for extracting key information and generating summaries" is an algorithm or generative AI model for extracting key points from the content of an electronic message and presenting them as a summary.

[1014] The "means for recognizing the emotional state of the user" is an emotion engine or software for analyzing the emotional state of the user when receiving a message and recognizing a particular emotion.

[1015] The "means for generating priorities and recommended responses" is an algorithm or software for determining the importance and urgency of a response to an electronic message based on the recognized emotional state of the user and summary information, and for suggesting an appropriate response.

[1016] The "means for displaying" is a display device or user interface for visually presenting the generated summary, emotional state, and message title to the user.

[1017] The system for implementing the present invention mainly comprises three elements: a server, a terminal, and a user.

[1018] The server stores received electronic messages in a database or file system. The stored electronic messages are processed by algorithms and software that analyze the text, extracting important information and generating summaries. Specifically, a generative AI model is used to extract key points from the content of the electronic message. The server then uses an emotion engine to recognize the user's emotional state and prioritizes the electronic message and recommends a course of action based on the recognized emotional state. The generated summaries and emotional state are then sent to the device along with the title of the electronic message.

[1019] The terminal receives summary information of electronic messages and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, allowing users to see at a glance whether an email requires a response. In addition, special alerts are displayed for messages with high urgency based on the user's emotional state. This allows users to easily identify messages that require immediate attention.

[1020] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. For example, if the message is urgent, an action plan for immediate response is presented. This allows the user to respond quickly and appropriately without missing important electronic messages.

[1021] Consider the following scenario: When a user receives a security-related electronic message, the server processes the message as follows:

[1022] Server Action:

[1023] 1. Store electronic messages.

[1024] 2. Analyze the body of the stored message, extract important information, and generate a summary.

[1025] 3. The emotion engine recognizes the user's emotional state and determines priorities.

[1026] 4. A summary of the electronic message and the emotional state are sent to the terminal along with the title.

[1027] Example of terminal display:

[1028] From: sender@example.com

[1029] Subject: Security Alert

[1030] Summary: We have detected suspicious activity in your account. Please verify your identity immediately.

[1031] Emotion: Urgent

[1032] In this way, the generated summary and emotional state are displayed appropriately, allowing the user to quickly and accurately grasp messages that require a response.

[1033] An example prompt might use the following format:

[1034] "Please summarize the following email and analyze the user's emotion: 'We have detected suspicious activity in your account. Please verify your identity immediately.'"

[1035] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1036] Step 1:

[1037] The server stores the received electronic message. Specifically, when the electronic message arrives at the server via the network, the server stores the contents of the message in a database or file system. The input of this step is the electronic message, and the output is the stored electronic message.

[1038] Step 2:

[1039] The server analyzes the body of the stored electronic message by using analytical algorithms or software to tokenize the text of the message content and identify important information. The input to this step is the body of the stored electronic message, and the output is the analysis results.

[1040] Step 3:

[1041] The server extracts key information from the parsed text and generates a summary. It uses a generative AI model to summarize the key points of the electronic message and generate a concise summary. The input to this step is the analysis result, and the output is the generated summary.

[1042] Step 4:

[1043] The server recognizes the user's emotional state. It uses an emotion engine to analyze the user's emotion upon receiving the electronic message and detects specific emotions (e.g., urgency, surprise, joy, etc.). The input of this step is the body of the electronic message, and the output is the recognized emotional state.

[1044] Step 5:

[1045] The server generates a priority and recommended response for the electronic message based on the recognized emotional state. Based on the emotional state and summary information, it evaluates the importance and urgency of the message and determines a specific response. The input of this step is the summary and emotional state, and the output is a priority and recommended response.

[1046] Step 6:

[1047] The server sends the generated summary and emotional state to the terminal along with the title of the electronic message. The message title, summary, and emotional state are packaged and sent to the terminal. The inputs of this step are the summary, emotional state, and title of the electronic message, and the output is the data sent to the terminal.

[1048] Step 7:

[1049] The terminal receives the summary information of the electronic message and the result of the emotion engine obtained from the server and displays them on the screen. The title, summary, and emotional state of the electronic message are visually presented through the user interface. The input of this step is the data sent from the server, and the output is the information displayed on the terminal screen.

[1050] Step 8:

[1051] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. The user responds immediately to messages with high urgency. The input of this step is the information displayed on the device, and the output is the user's specific action.

[1052] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1053] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1054] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1055] [Fourth embodiment]

[1056] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1057] 7, a 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.

[1058] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1059] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1060] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1061] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1062] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1063] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1064] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1065] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1066] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1067] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1068] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1069] The present invention relates to a system for efficiently managing a large amount of e-mail that arrives in an inbox and quickly understanding its contents. The functions and operations of this system will be explained below with specific examples.

[1070] The core of this system is its function of analyzing the body of e-mails, extracting important information, and generating summaries. This allows users to easily grasp the contents of each e-mail in their inbox. Below, we will explain how it works from the perspectives of the server, terminal, and user.

[1071] Server Operation

[1072] When a new email is received, the server stores the body of the email. Then, the server analyzes the stored email and uses a generative AI model to extract important information from the body and generate a summary. For example, the server operates as follows:

[1073] First, the server connects to the IMAP server via the Internet to check for new emails. If new emails are found, the email body is saved to a database. For each saved email body, a generative AI model is applied to create a summary. The generated summary is then saved to the database and immediately reflected on the device.

[1074] Device behavior

[1075] The device displays a summary of each email along with the subject of the email on the inbox screen, allowing the user to understand the contents of the email without opening each one. For example, the device operates as follows:

[1076] The terminal retrieves email information with summaries from the server and displays them in the inbox. This allows the user to see the sender, subject, and summary of the email at a glance. In addition, the summary also shows the status of whether a reply is required, so the user can quickly determine which emails should be prioritized.

[1077] User operations

[1078] The user checks the inbox screen on the device to understand the contents and priority of the email. For example, when the user opens the inbox, the following information is displayed:

[1079] From: alice@example.com

[1080] Subject: Meeting Agenda

[1081] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[1082] ==================================================

[1083] From: bob@example.com

[1084] Subject: Monthly Report Submission

[1085] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[1086] ==================================================

[1087] This type of display allows the user to grasp the main points of each email at a glance and quickly determine which email should be given priority.

[1088] The system of the present invention analyzes the contents of emails and generates summaries, thereby streamlining inbox management and improving user work efficiency, allowing users to process emails appropriately without missing important emails.

[1089] The processing flow will be explained below.

[1090] Step 1:

[1091] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[1092] Step 2:

[1093] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[1094] Step 3:

[1095] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[1096] Step 4:

[1097] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[1098] Step 5:

[1099] The server stores the generated summary together with the corresponding email information in a database. This save process establishes the email subject, sender, body, and summary as a set of data.

[1100] Step 6:

[1101] The terminal displays email information with a summary to the user on the inbox screen. The terminal retrieves email information with a summary from the server and places the sender, subject, and summary on the inbox, allowing the user to check the content and importance of the email at a glance.

[1102] Step 7:

[1103] Users can check the summary displayed on the inbox screen and decide the priority of email processing. They can check the content and status, determine the necessary reply or action, and then process the email. This allows users to efficiently manage email and respond appropriately.

[1104] Example 1

[1105] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1106] In today's world, users receive a large number of electronic messages on a daily basis, which puts them at risk of missing important information and wastes time extracting the necessary information from the overwhelming volume of emails. In business environments, in particular, where prompt responses to important emails are required, a system that can efficiently understand the contents of emails is needed. To solve this problem, a system that can analyze received electronic messages, generate summaries, and determine their priority is required.

[1107] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1108] In this invention, the server includes means for checking newly arrived electronic messages via the Internet, means for saving the bodies of received electronic messages in a database, means for analyzing the bodies of the saved electronic messages using a generative AI model, means for extracting important information from the analysis results and generating summaries, means for saving the generated summaries in a database, means for reflecting the electronic message information with summaries on a terminal in real time, and means for displaying the summaries together with the titles of the electronic messages on the screen of the terminal, thereby enabling users to quickly grasp the main points of emails without opening them and to prioritize responding to important emails.

[1109] The "Internet" is a huge information network that interconnects computer networks all over the world.

[1110] An "electronic message" is a digital communication message, such as an email or text message, sent or received over the Internet.

[1111] A "server" is a computer system that provides data and services in response to requests from clients over a network.

[1112] "IMAP Server" means a server that manages and provides electronic mail using the Internet Message Access Protocol.

[1113] A "database" is a collection of information that allows efficient management of data and allows operations such as searching and updating.

[1114] A "generative AI model" is an artificial intelligence model that performs tasks such as text generation and information extraction based on given input data.

[1115] "Analysis" is the means of examining given data in detail and understanding its structure and meaning.

[1116] A "summary" is a concise summary of the main points or outline of the original information.

[1117] "Real-time" refers to a situation where data or information is processed immediately and the results are available without delay.

[1118] "Terminal" refers to a device such as a computer or mobile phone that is directly operated by a user.

[1119] The present invention relates to a system for efficiently managing a large amount of received electronic messages and quickly understanding their contents. Specific embodiments of this system will be described below.

[1120] The core of the system is its ability to analyze the body of electronic messages, extract key information, and generate summaries, allowing users to get a concise understanding of the contents of each message in their inbox.

[1121] Server behavior:

[1122] The server connects to the IMAP server via the Internet to check whether new electronic messages have been received. If new messages have been received, the message body is retrieved and stored in a database. A generative AI model is used to analyze the message body, extract key information, and generate a summary. The specific generative AI model used is GPT-3 or a similar natural language processing model. The generated summary is then stored back in the database and updated on the device in real time.

[1123] Terminal behavior:

[1124] The device displays a summary of each message along with its subject on the inbox screen. Users can view the summary without opening the message body. This allows users to quickly understand the content of each message and immediately determine which messages should be prioritized. The summary also displays the status of whether a reply is required, allowing users to respond quickly to important messages.

[1125] User Action:

[1126] The user checks the inbox screen on the device to understand the contents and priority of the message. For example, when the user opens the inbox, the following information is displayed:

[1127] From: sender@example.com

[1128] Subject: Meeting Agenda

[1129] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[1130] ==================================================

[1131] From: another.sender@example.com

[1132] Subject: Monthly Report Submission

[1133] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[1134] ==================================================

[1135] This type of display allows the user to grasp the gist of each message at a glance and quickly determine which message should be given priority.

[1136] Example prompt for a generative AI model:

[1137] An example of a prompt sentence to input to the generative AI model is as follows:

[1138] Extract key information and summarize the following email content:

[1139] "Dear team, Please be reminded of the meeting scheduled on Friday. Key points to be discussed include the project status update, budget review, and planning for the next quarter. Regards, Sender"

[1140] The system of the present invention analyzes the content of electronic messages and generates summaries to improve inbox management and user efficiency, thereby enabling users to avoid missing important messages and to process them appropriately.

[1141] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1142] Step 1:

[1143] The server connects to an IMAP server over the Internet to check for new electronic messages.

[1144] Input: IMAP server login information

[1145] Output: List of new email messages

[1146] Specific operation: The server accesses the INBOX folder using the IMAP protocol and checks whether there are any new emails. At this time, the IMAP server returns the unread email ID.

[1147] Step 2:

[1148] When a new electronic message is confirmed, the server retrieves the body of the message and stores it in a database.

[1149] Input: List of new email messages

[1150] Output: Saved email body

[1151] Specific operation: The server retrieves the email content from the IMAP server and saves the retrieved email body in the database.

[1152] Step 3:

[1153] The server analyzes the stored email body using a generative AI model to generate a summary.

[1154] Input: Saved email body

[1155] Output: Generated summary

[1156] Specific operation: The server inputs the prompt sentence into the generative AI model and generates a summary, which is returned in text format.

[1157] Step 4:

[1158] The server stores the generated summary again in the database.

[1159] Input: Generated summary

[1160] Output: Summary stored in database

[1161] Specific operation: The server saves the summary obtained from the generative AI model in the corresponding email entry in the database.

[1162] Step 5:

[1163] The server reflects the summarized electronic message information to the terminal in real time.

[1164] Input: Abstract stored in the database

[1165] Output: Email information sent to terminal with summary

[1166] Specific operation: The server uses WebSocket to send email information with a summary to the terminal.

[1167] Step 6:

[1168] The terminal displays a summary of each email along with its subject on the inbox screen to the user.

[1169] Input: Email information with summary sent from the server

[1170] Output: Summary displayed on the inbox screen

[1171] What it does: The device analyzes the received data and displays the email subject and summary in the inbox using technologies such as HTML and JavaScript.

[1172] Step 7:

[1173] The user checks the inbox screen on the device to understand the contents and priority of the email.

[1174] Input: Summary displayed on the inbox screen

[1175] Output: User's priority judgment

[1176] What happens: The user can read the summary of the emails displayed and decide which ones should be prioritized. If necessary, they can open the emails to view the details.

[1177] (Application example 1)

[1178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1179] In autonomous vehicles, drivers face challenges in efficiently managing the large volume of emails they receive while driving and quickly understanding their contents. In particular, there is a need for a system that allows drivers to easily obtain important information without using their hands and quickly reply if necessary. Another important challenge is ensuring driver safety by providing information visually and audibly.

[1180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1181] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for notifying the summary by voice, means for displaying the summary on a visual device, and means for replying to electronic messages based on voice input, thereby enabling the driver of an autonomous vehicle to quickly and accurately understand the content of received emails without using his or her hands and to reply immediately if necessary.

[1182] "Means for storing received electronic messages" refers to a device or software for storing emails received over a network in a database or memory.

[1183] A "means for analyzing the body of stored electronic messages" is a device or software that automatically analyzes the content of emails stored on a storage device and identifies important information.

[1184] "Means for extracting important information from the analyzed text and generating a summary" refers to a device or software that extracts the main points from the information obtained through the analysis and summarizes them in a concise form.

[1185] "Means for displaying the generated summary together with the title of the electronic message" means a device or software for displaying the summarized information and the subject of the original electronic message on a terminal display or other display device.

[1186] The "means for audibly announcing the summary" refers to a device or software for announcing the generated summary to the user through an audio output device.

[1187] The "means for displaying the summary on a visual device" is a device or software for displaying the generated summary on smart glasses or a head-mounted display.

[1188] A "means for replying to electronic messages based on voice input" is a device or software that transcribes a user's voice commands and replies to emails based on them.

[1189] The present invention relates to a system for improving the efficiency of email management for drivers of autonomous vehicles. Specific embodiments of the system are described below.

[1190] Server Operation

[1191] The server connects to an IMAP server over the Internet to check for new emails. When a new email is received, it stores the email body in a database. It then uses a generative AI model (such as OpenAI's GPT model) to analyze the email body, extract key information, and generate a summary. The generated summary is stored in a database and immediately reflected on the client side.

[1192] Device behavior

[1193] The device (e.g., smart glasses or a head-mounted display) retrieves email information with summaries from the server and displays them on the screen. This allows the driver to understand the contents of emails without having to open them one by one. It also has a function to provide audio notification of the summary information. For example, a voice assistant device (e.g., Amazon Echo Auto) can be used to provide audio notification of the summary generated by the generative AI model to the driver.

[1194] User operations

[1195] The user (driver) can check the inbox screen and instantly understand the summary of the email. In addition, it is possible to reply to emails by voice input. When the driver uses voice commands to input the reply content, the content is transcribed and sent as an email.

[1196] Hardware and software used

[1197] Hardware:

[1198] Smart glasses (e.g. Google Glass)

[1199] Head-mounted displays (e.g. Microsoft HoloLens)

[1200] Voice assistant devices (e.g. Amazon Echo Auto)

[1201] software:

[1202] Server side: IMAP server, generative AI model (e.g. OpenAI GPT model), database

[1203] Client side: Smart glasses, HMD applications, speech recognition software (e.g., Google Speech-to-Text)

[1204] Specific examples

[1205] For example, if a driver receives an email while driving with the subject "Meeting Agenda" and the body "Describes the agenda for the upcoming meeting on Friday. Key points include a project status update, budget review, and planning for the next quarter," the generative AI model can generate a summary using prompts like the following:

[1206] Example prompt sentence:

[1207] Summarize the given email text. For example, generate a summary in the following format:

[1208] Email subject: Meeting agenda

[1209] Body: Explain the agenda for Friday's meeting. Key points include a project status update, budget review, and planning for the next quarter.

[1210] Summary: This email outlines the agenda for a meeting scheduled for Friday. Key points include a project status update, budget review, and planning for the next quarter.

[1211] This allows the driver of an autonomous vehicle to quickly and accurately understand the contents of emails received without using their hands, and to reply immediately if necessary.

[1212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1213] Step 1:

[1214] The server connects to the IMAP server over the Internet to check for new electronic messages. When a new email is received, it stores its body in a database. As input, the server receives an electronic message from the IMAP server, and as output, it records the body of the electronic message in a database.

[1215] Step 2:

[1216] The server passes the body of each stored electronic message to the generative AI model, extracts important information, and generates a summary, using prompts to provide appropriate instructions to the generative AI model. As input, the server sends the body of the electronic message and the prompt to the generative AI model, and as output, receives a summary from the generative AI model.

[1217] Step 3:

[1218] The server stores the generated summary in a database and immediately reflects it on the device.,As input, the summary from the generative AI model is stored in the database,,and as output, the summary is stored in the database.

[1219] Step 4:

[1220] The terminal receives email information with a summary from the server and displays it on the inbox screen. As input, the terminal receives email information with a summary from the server, and as output, it displays a list of the email subject, sender, and summary.

[1221] Step 5:

[1222] The terminal performs speech conversion processing to output the generated summary to the driver through a speech output device. The terminal receives the summary as input and outputs the converted speech information from a speaker as output.

[1223] Step 6:

[1224] The user checks the inbox screen and instantly gets a summary of the email. If necessary, the user can reply to the electronic message by voice input. As input, the user's voice command is converted into text by speech recognition software, and as output, the text reply is sent as an email.

[1225] Step 7:

[1226] The server generates text based on the user's voice input and sends it as a new electronic message. As input, the server receives text data from the speech recognition software and as output, sends it to the recipient in the form of an email.

[1227] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1228] The present invention relates to a system that efficiently manages emails received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority of emails and how to respond to them. The functions and operations of this system are explained below with specific examples.

[1229] This system combines the ability to analyze the body of emails, extract important information, and generate summaries with an emotion engine that recognizes the user's emotions, allowing users to see the content of emails in their inbox, as well as the appropriate priorities and responses based on their emotions.

[1230] Server Operation

[1231] When a new email is received, the server stores the body of the email, then analyzes it and uses a generative AI model to extract key information from the body and generate a summary.

[1232] Furthermore, the server is equipped with an emotion engine that recognizes the user's emotional state. Based on the recognized emotional state, it determines the priority of the email and recommends an appropriate response. For example, the server operates as follows:

[1233] First, the server receives and stores new emails, then uses a generative AI model to generate summaries, and then uses an emotion engine to recognize the user's emotional state and evaluate the importance and urgency of the email.

[1234] Device behavior

[1235] The device displays the email subject, summary, and priority and response instructions based on the user's emotional state as recognized by the emotion engine, allowing the user to easily understand the content and importance of the email and take appropriate action.

[1236] For example, the device receives email information with a summary and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, so users can see at a glance whether an email needs to be addressed.

[1237] User operations

[1238] The user checks the summary of the email displayed on the inbox screen and the results of the emotion engine, and takes action based on the priority of the email. For example, when a user opens their inbox, the following information may be displayed:

[1239] From: alice@example.com

[1240] Subject: Meeting Agenda

[1241] Summary: This email outlines the agenda for the meeting scheduled on Friday. Key points include the project status update, budget review, and planning for the next quarter.

[1242] Emotion: Neutral

[1243] ==================================================

[1244] From: bob@example.com

[1245] Subject: Monthly Report Submission

[1246] Summary: Please be reminded to submit your monthly reports by the end of the week. The reports should include the progress on current projects and any issues faced.

[1247] Emotion: Urgent

[1248] ==================================================

[1249] In this way, the results of the emotion engine are also displayed, allowing users to quickly understand the email and respond appropriately based on their emotions. Prioritization and response can be achieved according to the user's emotional state and the content of the email.

[1250] The system of the present invention comprehensively analyzes the content of emails and the user's emotional state to improve email management efficiency, allowing users to respond quickly and appropriately without missing important emails.

[1251] The processing flow will be explained below.

[1252] Step 1:

[1253] The server connects to the IMAP server to receive new emails. First, the server logs into the IMAP server with the user's mail account and selects the "inbox" folder. Then it searches for new mail and retrieves a list of unread mails.

[1254] Step 2:

[1255] The server reads the data of the retrieved unread emails. It retrieves the email data for each email and begins parsing the entire email. If the email is in multipart format, it checks each part in turn, identifies the text part ("text / plain"), and extracts the body. If the email is a single-part email, it retrieves the body as is.

[1256] Step 3:

[1257] The server saves the extracted email body in a database. The saved information includes the sender, subject, and body. This saving step ensures that the email body to be analyzed is secured within the system.

[1258] Step 4:

[1259] The server analyzes the stored email bodies with a generative AI model to generate summaries. First, it retrieves the raw email bodies from the database. Then it uses the generative AI model to extract key information from each email body and generate a concise summary.

[1260] Step 5:

[1261] The server associates the generated summary with the email information and stores it in a database. Through this process, the email's subject, sender, body, and summary are established as a series of data.

[1262] Step 6:

[1263] The server uses an emotion engine to analyze the summary and body of the saved emails to recognize the user's current emotional state, which is then classified into statuses such as "normal," "urgent," "joy," and "anger."

[1264] Step 7:

[1265] The server prioritizes each email based on the results of the emotion engine and stores the necessary status in a database, thereby determining the priority that reflects the email content and the user's emotional state.

[1266] Step 8:

[1267] The terminal displays the email subject, summary, and priority and status based on the user's emotional state recognized by the emotion engine to the user. The terminal obtains email information with summary and the result of the emotion engine from the server and displays them in the inbox.

[1268] Step 9:

[1269] Users can check the summary and emotional state of emails displayed on the inbox screen and respond based on the priority of the email. Users can categorize emails based on the displayed information and immediately determine the priority of their replies or responses.

[1270] By using the above steps, the system of the present invention comprehensively analyzes the content of emails and the user's emotional state, improving the efficiency of email management. This allows users to respond quickly and appropriately to important emails without missing them.

[1271] Example 2

[1272] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1273] Conventional electronic message management systems have the problem that when a large number of messages accumulate in the inbox, the risk of missing important messages increases and the possibility of delayed responses increases. It is also difficult to quickly grasp the content and urgency of messages, which increases the burden on users. In addition to these issues, there is a significant lack of functionality that automatically provides appropriate responses that take into account the user's emotional state.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1275] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating a summary, means for recognizing the user's emotional state, and means for determining the priority of the electronic messages based on the recognized emotional state and recommending an appropriate response method, thereby enabling efficient analysis of the content of the electronic messages and the user's emotional state and enabling prompt and appropriate responses.

[1276] "Means" refers to functional components that make up a system, and includes devices and programs capable of executing specific functions or operations.

[1277] A "server" is a computer system that accepts requests from clients on a network and provides the corresponding services or functions.

[1278] "Electronic message" refers to a communication message sent or received in digital form, such as email, and may include text, images, attachments, etc.

[1279] "Storage" refers to the act of recording a received electronic message in a database or storage device so that it can be retrieved at a later time.

[1280] "Analysis" refers to the process of closely examining the content of stored electronic messages and extracting necessary information or patterns.

[1281] A "generative AI model" refers to an artificial intelligence algorithm that uses natural language processing and machine learning to analyze text and generate or transform information.

[1282] "Summary" means a short narrative statement that succinctly sets out the key information extracted from the body of an electronic message.

[1283] The "emotional state" indicates the psychological state of the user when receiving the electronic message, and is classified into categories such as "urgent" and "important."

[1284] "Priority" refers to the order of necessity or urgency of a response among multiple electronic messages.

[1285] "Recommended responses" refers to a function that suggests appropriate responses to users based on the recognized emotional state and summarized content.

[1286] "Visual display" refers to the means by which information such as the content, emotional state, or priority of an electronic message is presented to a user as graphical elements or icons.

[1287] The present invention is a system that efficiently manages electronic messages received in an inbox, quickly understands their contents, and recognizes the user's emotions to adjust the priority and response method of the messages. This system includes a server and a terminal as its main components, each of which performs a specific function to realize the overall mail management process.

[1288] Server configuration and operation

[1289] The server consists of hardware and software with the following main functions:

[1290] 1. Receiving and storing emails

[1291] The server receives electronic messages via the Internet and stores them in a database, including sender information, subject lines, and message body text.

[1292] 2. Use of analytical and generative AI models

[1293] The server uses a generative AI model (specifically GPT-4) to analyze the body of the stored electronic message. The following is an example of a prompt:

[1294] Please analyze the email body below and extract the important information.

[1295] Analysis extracts important information and generates summaries.

[1296] 3. Emotion recognition

[1297] The server uses an emotion engine to recognize the user's emotional state, which is classified into categories such as "urgent," "important," and "minor."

[1298] 4. Prioritization and recommended actions

[1299] Prioritize messages based on perceived emotional state and summarized content, and recommend appropriate responses (e.g., "Reply now," "Reply later," etc.).

[1300] 5. Recording user emotions

[1301] The server records the user's emotional state for each electronic message and keeps it as a management history.

[1302] Terminal configuration and operation

[1303] Terminals consist of devices (e.g., smartphones, tablets, and PCs) that have the following functions:

[1304] 1. Obtaining email information

[1305] The terminal obtains the email subject, summary, and emotion engine results from the server.

[1306] 2. Displaying email information

[1307] The device displays the retrieved information in a user interface, including subject line, summary, priority, and emotional state, along with visual icons and statuses, allowing users to quickly determine whether action is required.

[1308] User operations

[1309] Users use this system to manage and respond to electronic messages through the following operations:

[1310] 1. Check your inbox

[1311] Users can view the subject line, summary, and sentiment recognition results in their inbox, allowing them to quickly determine message priorities.

[1312] 2. Responding to emails

[1313] The user can then take appropriate action based on the displayed information, for example, replying immediately to messages of high urgency and responding later to messages of low importance.

[1314] Specific examples

[1315] As a specific example, consider the case where a server receives the following electronic message and performs analysis, summarization, emotion recognition, and prioritization:

[1316] From: johndoe@example.com

[1317] Subject: Project progress review

[1318] Summary: This email is intended to review the progress of an ongoing project. The main points are to confirm the schedule, allocate resources, and report any issues.

[1319] Emotion: emergency

[1320] In this way, the system provides email information in a format that users can intuitively understand, helping them to respond quickly and appropriately.

[1321] The system comprehensively analyzes the content of electronic messages and the user's emotional state to achieve efficient email management, allowing users to avoid missing important messages and respond appropriately in a timely manner.

[1322] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1323] Server Processing Steps

[1324] Step 1:

[1325] The server receives electronic messages. Specifically, it retrieves new emails from an email server over the Internet and receives data including the sender, subject, and body of the email. The input is the new email, and the output is the received email data.

[1326] Step 2:

[1327] The server stores received electronic messages in a database. Specifically, it records the content of the email (sender, subject, and body) in the database. The input is the received email data, and the output is the stored database entry.

[1328] Step 3:

[1329] The server analyzes the body of the stored electronic message. Specifically, it uses a generative AI model to analyze the email body and extract important information. The input is the email body data, and the output is the analysis result data. The prompt is as follows:

[1330] Please analyze the email body below and extract the important information.

[1331] Step 4:

[1332] The server generates a summary based on the analysis results. Specifically, it converts the output of the generative AI model into a summary. The input is the analysis result data, and the output is the generated summary text.

[1333] Step 5:

[1334] The server uses an emotion engine to recognize the user's emotional state. Specifically, it applies an algorithm to classify emotions from the analyzed email content. The input is the email content data, and the output is the emotional state data (e.g., urgent, important, minor, etc.).

[1335] Step 6:

[1336] The server determines the priority of the email based on the recognized emotional state and recommends an appropriate response. Specifically, it applies a prioritization algorithm to determine the response. The input is the emotional state data and a summary, and the output is the priority and the recommended response.

[1337] Step 7:

[1338] The server records the user's emotional state and response in a database. Specifically, it stores the priority and response for each email in the database. The input is the priority and response data, and the output is the updated database entry.

[1339] Terminal processing steps

[1340] Step 1:

[1341] The terminal obtains email information from the server. Specifically, it sends a request to the server and receives the email subject, summary, and emotional state data in return. The input is the request, and the output is the obtained email information data.

[1342] Step 2:

[1343] The terminal displays the acquired email information on the screen. Specifically, the email's subject, summary, emotional state, and priority are displayed on the user interface. The input is the acquired email information data, and the output is the screen information displayed to the user. Visual icons and statuses are also displayed.

[1344] User processing steps

[1345] Step 1:

[1346] The user checks the inbox screen of the terminal. Specifically, the displayed email information (subject, summary, emotional state, and priority) is checked. The input is the screen information, and the output is the user's recognition result.

[1347] Step 2:

[1348] The user responds to the email based on the displayed information. Specifically, they reply immediately to emails with high urgency and respond later to emails with low urgency. The input is the user's recognition result, and the output is the user's response action.

[1349] (Application example 2)

[1350] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1351] It has been a challenge for users to quickly and appropriately identify and respond to important messages from the vast amount of electronic messages they receive. In particular, in security services, it is necessary to take into account the user's emotional state and prioritize messages with high urgency. Therefore, there is a need for a system that integrates electronic message summary generation and emotion recognition to prompt users to take immediate and appropriate action.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1353] In this invention, the server includes means for saving received electronic messages, means for analyzing the text of the saved electronic messages, means for extracting important information from the analyzed text and generating summaries, means for recognizing the user's emotional state, means for generating priorities for electronic messages and recommended responses based on the recognized emotional state, and means for displaying the generated summaries and emotional state together with the titles of the electronic messages. This allows the user to grasp the priorities of electronic messages based on their content and emotional state, and enables them to quickly respond to messages with high urgency.

[1354] An "electronic message" is a form of text data sent or received over the Internet or other network.

[1355] "Storage means" refers to a device or software that has the function of storing received electronic messages in a storage device such as a database or file system.

[1356] A "text analysis means" is an algorithm or software that analyzes the content of a stored electronic message and extracts specific information.

[1357] A "means for extracting key information and generating summaries" is an algorithm or generative AI model for extracting key points from the content of an electronic message and presenting them as a summary.

[1358] The "means for recognizing the emotional state of the user" is an emotion engine or software for analyzing the emotional state of the user when receiving a message and recognizing a particular emotion.

[1359] The "means for generating priorities and recommended responses" is an algorithm or software for determining the importance and urgency of a response to an electronic message based on the recognized emotional state of the user and summary information, and for suggesting an appropriate response.

[1360] The "means for displaying" is a display device or user interface for visually presenting the generated summary, emotional state, and message title to the user.

[1361] The system for implementing the present invention mainly comprises three elements: a server, a terminal, and a user.

[1362] The server stores received electronic messages in a database or file system. The stored electronic messages are processed by algorithms and software that analyze the text, extracting important information and generating summaries. Specifically, a generative AI model is used to extract key points from the content of the electronic message. The server then uses an emotion engine to recognize the user's emotional state and prioritizes the electronic message and recommends a course of action based on the recognized emotional state. The generated summaries and emotional state are then sent to the device along with the title of the electronic message.

[1363] The terminal receives summary information of electronic messages and the results of the emotion engine from the server and displays them on the screen. The display also includes icons and statuses, allowing users to see at a glance whether an email requires a response. In addition, special alerts are displayed for messages with high urgency based on the user's emotional state. This allows users to easily identify messages that require immediate attention.

[1364] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. For example, if the message is urgent, an action plan for immediate response is presented. This allows the user to respond quickly and appropriately without missing important electronic messages.

[1365] Consider the following scenario: When a user receives a security-related electronic message, the server processes the message as follows:

[1366] Server Action:

[1367] 1. Store electronic messages.

[1368] 2. Analyze the body of the stored message, extract important information, and generate a summary.

[1369] 3. The emotion engine recognizes the user's emotional state and determines priorities.

[1370] 4. A summary of the electronic message and the emotional state are sent to the terminal along with the title.

[1371] Example of terminal display:

[1372] From: sender@example.com

[1373] Subject: Security Alert

[1374] Summary: We have detected suspicious activity in your account. Please verify your identity immediately.

[1375] Emotion: Urgent

[1376] In this way, the generated summary and emotional state are displayed appropriately, allowing the user to quickly and accurately grasp messages that require a response.

[1377] An example prompt might use the following format:

[1378] "Please summarize the following email and analyze the user's emotion: 'We have detected suspicious activity in your account. Please verify your identity immediately.'"

[1379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1380] Step 1:

[1381] The server stores the received electronic message. Specifically, when the electronic message arrives at the server via the network, the server stores the contents of the message in a database or file system. The input of this step is the electronic message, and the output is the stored electronic message.

[1382] Step 2:

[1383] The server analyzes the body of the stored electronic message by using analytical algorithms or software to tokenize the text of the message content and identify important information. The input to this step is the body of the stored electronic message, and the output is the analysis results.

[1384] Step 3:

[1385] The server extracts key information from the parsed text and generates a summary. It uses a generative AI model to summarize the key points of the electronic message and generate a concise summary. The input to this step is the analysis result, and the output is the generated summary.

[1386] Step 4:

[1387] The server recognizes the user's emotional state. It uses an emotion engine to analyze the user's emotion upon receiving the electronic message and detects specific emotions (e.g., urgency, surprise, joy, etc.). The input of this step is the body of the electronic message, and the output is the recognized emotional state.

[1388] Step 5:

[1389] The server generates a priority and recommended response for the electronic message based on the recognized emotional state. Based on the emotional state and summary information, it evaluates the importance and urgency of the message and determines a specific response. The input of this step is the summary and emotional state, and the output is a priority and recommended response.

[1390] Step 6:

[1391] The server sends the generated summary and emotional state to the terminal along with the title of the electronic message. The message title, summary, and emotional state are packaged and sent to the terminal. The inputs of this step are the summary, emotional state, and title of the electronic message, and the output is the data sent to the terminal.

[1392] Step 7:

[1393] The terminal receives the summary information of the electronic message and the result of the emotion engine obtained from the server and displays them on the screen. The title, summary, and emotional state of the electronic message are visually presented through the user interface. The input of this step is the data sent from the server, and the output is the information displayed on the terminal screen.

[1394] Step 8:

[1395] The user checks the summary of the electronic message displayed on the device and the results of the emotion engine, and responds according to the priority. The user responds immediately to messages with high urgency. The input of this step is the information displayed on the device, and the output is the user's specific action.

[1396] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1397] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1398] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1399] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1400] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1401] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1402] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1403] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1404] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1405] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1406] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1407] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1408] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1409] 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.

[1410] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1411] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1412] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1413] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1414] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1415] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1416] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1417] The following is further disclosed regarding the above embodiment.

[1418] (Claim 1)

[1419] means for storing received electronic messages;

[1420] means for analyzing the body of the stored electronic message;

[1421] A means for extracting important information from the analyzed text and generating a summary;

[1422] means for displaying the generated summary together with the title of the electronic message;

[1423] A system including:

[1424] (Claim 2)

[1425] 10. The system of claim 1, further comprising means for determining a priority of the electronic message based on the generated summary.

[1426] (Claim 3)

[1427] 10. The system of claim 1, further comprising means for visually displaying a status according to the content of the electronic message.

[1428] "Example 1"

[1429] (Claim 1)

[1430] means for checking for new electronic messages via the Internet;

[1431] means for storing the body of the received electronic message in a database;

[1432] means for analyzing the body of the stored electronic message using a generative AI model;

[1433] A means of extracting important information from the analysis results and generating a summary;

[1434] means for storing the generated summaries in a database;

[1435] means for reflecting the summarized electronic message information on the terminal in real time;

[1436] means for displaying a summary of the electronic message together with its title on a screen of the terminal;

[1437] A system including:

[1438] (Claim 2)

[1439] 10. The system of claim 1, further comprising means for determining a priority of the electronic message based on the generated summary.

[1440] (Claim 3)

[1441] 10. The system of claim 1, further comprising means for visually displaying a status according to the content of the electronic message.

[1442] "Application Example 1"

[1443] (Claim 1)

[1444] means for storing received electronic messages;

[1445] means for analyzing the body of the stored electronic message;

[1446] A means for extracting important information from the analyzed text and generating a summary;

[1447] means for displaying the generated summary together with the title of the electronic message;

[1448] a means for announcing the summary by voice;

[1449] means for displaying the summary on a visual device;

[1450] means for replying an electronic message based on the voice input;

[1451] A system including:

[1452] (Claim 2)

[1453] 10. The system of claim 1, further comprising means for determining a priority of the electronic message based on the generated summary.

[1454] (Claim 3)

[1455] 10. The system of claim 1, further comprising means for visually displaying a status according to the content of the electronic message.

[1456] "Example 2: Combining Emotion Engines"

[1457] (Claim 1)

[1458] means for storing received electronic messages;

[1459] means for analyzing the body of the stored electronic message;

[1460] A means for extracting important information from the analyzed text and generating a summary;

[1461] means for displaying the generated summary together with the title of the electronic message;

[1462] means for recognizing the emotional state of a user;

[1463] a means for prioritizing electronic messages based on a perceived emotional state and recommending appropriate responses;

[1464] A system including:

[1465] (Claim 2)

[1466] 10. The system of claim 1, further comprising means for determining a priority of the electronic message based on the generated summary and the user's emotional state.

[1467] (Claim 3)

[1468] 10. The system of claim 1, further comprising means for visually displaying a status according to the content of the electronic message and the emotional state of the user.

[1469] "Application example 2 when combining emotion engines"

[1470] (Claim 1)

[1471] means for storing received electronic messages;

[1472] means for analyzing the body of the stored electronic message;

[1473] A means for extracting important information from the analyzed text and generating a summary;

[1474] means for recognizing the emotional state of a user;

[1475] means for generating priorities and recommended responses to electronic messages based on the perceived emotional state;

[1476] means for displaying the generated summary and emotional state together with the title of the electronic message;

[1477] A system including:

[1478] (Claim 2)

[1479] 10. The system of claim 1, further comprising means for determining a priority of the electronic message based on the generated summary and the emotional state.

[1480] (Claim 3)

[1481] 10. The system of claim 1, further comprising means for visually displaying a status according to the content and emotional state of the electronic message. [Explanation of symbols]

[1482] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for storing received electronic messages; means for analyzing the body of the stored electronic message; A means for extracting important information from the analyzed text and generating a summary; means for displaying the generated summary together with the title of the electronic message; A system including:

2. The system of claim 1 further comprising means for determining a priority of the electronic message based on the generated summary.

3. 10. The system of claim 1, further comprising means for visually displaying a status according to the content of the electronic message.

Images