system

Abstract

We provide the system. [Solution] Means for collecting digital information from users' electronic devices, A means for analyzing and integrating collected digital information to generate a chronological record of activities, A means of generating a natural language narrative from an integrated activity log, A means of individually adjusting the narrative based on the user's past activity record, A means for transmitting the adjusted narrative to the user's electronic device, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In many individuals and enterprises, the recording of daily activities and events is a time-consuming and laborious task. Especially when manually creating a diary or a business daily report, there is a problem that memory ambiguity and information leakage may occur. Furthermore, with conventional recording methods, it is difficult to visualize activities as a time series or a story, and there is a problem that past events cannot be effectively reviewed.

Means for Solving the Problems

[0005] This invention solves the aforementioned problems by automatically collecting digital information from users' electronic devices, analyzing and integrating it, and generating highly accurate time-series activity records. Furthermore, it provides personalized content to individual users by generating narratives in natural language based on the generated activity records and making individual adjustments based on the user's past records. In addition, by combining location information and behavioral logs to refine the details of activities and enable users to easily review and analyze them, it achieves improved efficiency and quality of recording activities.

[0006] A "user" refers to an individual or legal entity that utilizes the system and provides digital information through an electronic device.

[0007] An "electronic terminal" is a device that enables the collection, processing, and display of information, and includes devices such as smartphones, tablets, and personal computers.

[0008] "Digital information" refers to a variety of electronically recorded data, such as photographs, videos, activity logs, calendar information, and location information.

[0009] "Means of collection" refers to a method or process for automatically obtaining necessary digital information from a user's electronic device.

[0010] "Means of analysis and integration" refers to the process of analyzing collected digital information, linking it together, and constructing it as a cohesive activity record.

[0011] A "chronological activity record" refers to a collection of acquired and integrated digital information arranged in chronological order.

[0012] "Methods for generating narratives using natural language" refers to methods of constructing human-readable text based on activity records and presenting the content in a user-friendly manner.

[0013] "Means of individual customization" refers to the process of customizing the content and presentation of the generated narrative by taking into account the user's past records and preferences.

[0014] "Means of transmission" refers to a method or communication protocol for delivering generated content in digital format to a user's electronic device.

[0015] "Activity logs" refer to historical information about a user's activities and actions, including data such as time, location, and activity details.

[0016] "Location information" refers to data indicating a geographical location, and specifically refers to latitude and longitude coordinates obtained using GPS technology, etc.

[0017] "Feedback" refers to information provided by users regarding their experience using the system and suggestions for improvement. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

[0021] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

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

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0039] This invention provides a system that effectively records and facilitates the review of users' daily and work activities. The system analyzes digital information collected from the user's electronic device and generates a highly personalized journal. This allows users to eliminate manual record-keeping and improve the quality of activity statistics and reviews.

[0040] Server roles and functions

[0041] The server, as the core of the system, manages and processes digital information. First, the server acquires digital information such as photos, videos, calendars, and activity logs from the user's terminal. The acquired information is analyzed within the server, and an activity timeline is generated based on location and time information. Furthermore, natural language processing technology is used to convert the timeline into a human-readable narrative. This allows the server to provide information to the user in an easy-to-use format.

[0042] Terminal roles and functions

[0043] The user's device displays information provided by the server, allowing the user to review and edit their activities. The device receives journal entries from the server and displays them on the screen in a visualized format. This allows users to easily access data as a diary or daily work report. In addition, it includes a function for users to add comments and supplementary information, which can then be sent back to the server as feedback.

[0044] User interaction and experience

[0045] Users can use the system simply by setting it up and allowing the collection of digital information to the extent necessary. No special operation is required, as the system automatically records activities and events that the user wishes to document. The activity logs and narratives provided by the system are based on the user's past data, making them tailored to individual experiences. For example, if travel photos are registered as data, the server will construct context from the location and time the photos were taken and automatically generate a travelogue.

[0046] As a concrete example, consider a user who goes mountain climbing on a holiday. If the user takes photos and collects activity logs, the server analyzes this data and generates a diary that includes details such as the time it took to reach the summit and the route taken. The photos taken are also used as part of the narrative, providing a visual story of the activity. Later, the user can refer to this digital diary to vividly recall the memories of the day and use that information to plan their next trip.

[0047] Thus, the present invention provides an efficient and high-quality journal, enabling users to record their daily lives while saving them time and effort.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server sends a data collection request to the user's device. At this time, the user specifies the type of digital information to be collected, such as photos, videos, activity logs, and calendar information.

[0051] Step 2:

[0052] The device retrieves the specified digital information from a local database and sends the collected data to the server. This process may include location information and social media information.

[0053] Step 3:

[0054] The server analyzes the received digital information. First, it extracts metadata to obtain the date and time of shooting and location information, and then compares it with activity logs and calendar information to determine the relationships between them.

[0055] Step 4:

[0056] The server generates a timeline of activities in chronological order from the analyzed data. This generated timeline serves as the foundation for organizing the user's activities as a series of stories.

[0057] Step 5:

[0058] The server utilizes AI to construct narratives based on timelines. It uses natural language processing technology to generate text that is easy for users to understand.

[0059] Step 6:

[0060] The server personalizes the generated narrative based on the user's past records and preferences. It selects and highlights important events, completing the content with individual adjustments.

[0061] Step 7:

[0062] The server sends the completed narrative to the user's device. The device receives this data and displays it in its viewing interface.

[0063] Step 8:

[0064] Users view the narrative on their devices and add comments and notes as needed. This feedback information is sent to the server and used for subsequent analytics and content improvement.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] In today's world, information about daily activities and work is increasingly digitized, and data is generated from diverse sources. In this environment, people may face decreased productivity and loss of important information due to overlooked or misinterpreted records. To solve this, a system is needed that automatically generates accurate and personalized activity records with minimal effort and provides them in an easy-to-understand format.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes means for collecting information from the user's information processing device, means for analyzing and integrating the collected information to generate a time-series activity record, and means for generating natural language text from the integrated activity record. This enables the user to efficiently review their activities and make decisions based on the necessary information.

[0070] A "user" refers to a person or organization that uses this system to generate activity records.

[0071] An "information processing device" refers to an electronic device owned or used by a user that has the function of collecting and transmitting digital information.

[0072] "Information" refers to digital data related to user activities, including photos, videos, calendar events, and activity logs.

[0073] A "server" refers to a computer system that receives and analyzes information, and generates and transmits activity records and documents.

[0074] "Activity log" refers to data that summarizes a user's actions and events over a certain period of time in chronological order.

[0075] "Natural language" refers to texts written in the language that humans use on a daily basis.

[0076] "Generating text" means creating a narrative written in natural language from the information received.

[0077] A "generative AI model" refers to an artificial intelligence model trained using machine learning, which analyzes data and generates output suitable for the user.

[0078] This invention supports the automatic recording and review of user activities through a system including a user information processing device and a server. Specifically, the information processing device is an electronic device owned by the user, such as a smartphone or tablet, and these devices first collect various digital information such as photos, videos, calendar information, and activity logs. The information processing device temporarily stores this data and transmits it to the server in a secure manner.

[0079] The server analyzes the received digital information and uses location and time information to generate a timeline of activities. This uses a general database management system and a generative AI model for natural language processing. The generative AI model is equipped with natural language processing technology such as that provided by OpenAI®, and is capable of generating a human-readable narrative from activity records.

[0080] The generated narrative is optimized for each individual user and sent to the information processing device. The information processing device visually displays this narrative, allowing users to easily review their activities. For example, if a user goes mountain climbing on a holiday, the server generates a timeline of the climb based on data such as photos, videos, and GPS logs, and displays it as a travelogue in natural language.

[0081] An example of a prompt would be: "Generate a digital diary about last weekend's mountain climbing. Include information about the climbing route and arrival time from photos and activity logs."

[0082] By building the system in this way, users can efficiently obtain high-quality activity records without requiring any special operations.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] The device collects photos, videos, calendar information, and activity logs with the user's permission. This digital information is collected as input and temporarily stored on the device. Specific operations include using the device's camera app and location services to obtain necessary data.

[0086] Step 2:

[0087] The terminal transmits the collected digital information to the server using a secure communication method. The data stored in step 1 is used as input, and the data is sent to the server as output. Specifically, the HTTPS protocol is used for secure data transfer.

[0088] Step 3:

[0089] The server analyzes the received digital information and organizes the data based on time and location information. It receives data transmitted from terminals as input and generates an activity timeline as output. Specifically, it identifies the start and end times of events from location and time information and creates a logical timeline.

[0090] Step 4:

[0091] The server uses a generative AI model to convert the timeline into a natural language narrative. The input is the timeline generated in step 3, and the output is human-readable text. Specifically, the AI ​​model utilizes text generation prompts to describe the activities in easily understandable language.

[0092] Step 5:

[0093] The server sends the generated narrative to the terminal. The input is the narrative generated in step 4, and the output is the data sent to the terminal. Specifically, this involves delivering the narrative data to the user's terminal using a secure communication protocol.

[0094] Step 6:

[0095] The terminal visually displays the received narrative, allowing the user to review it. The input is the narrative received from the server, and the output is displayed on the user's screen. Specifically, the terminal's display interface visualizes the text, allowing the user to scroll and edit it.

[0096] Step 7:

[0097] Users can add comments and supplementary information to the displayed narrative. Input includes user feedback and additional information, which is saved on the device as output. Specifically, this involves users adding information via text or voice to input fields on the device.

[0098] Step 8:

[0099] The terminal sends additional information from the user to the server as feedback. The input is the feedback information generated in step 7, and the output is data sent to the server. Specifically, the operation is to send the data back using the same protocol as the one used to send it earlier.

[0100] (Application Example 1)

[0101] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0102] In today's commercial environment, there is a demand for quick and individualized responses to diverse customer needs. However, it is difficult for store staff to manually understand customer interests and behavior and make appropriate product recommendations, hindering improvements in customer experience and optimization of sales opportunities. To solve this problem, there is a need for technology that automatically understands customer behavior and interests, enabling store staff to respond immediately.

[0103] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0104] In this invention, the server includes means for collecting information data from the user's information processing device, means for analyzing and integrating the collected information data to generate a time-series activity history, and means for displaying customer interest information on a store employee's visual support device. This enables store employees to grasp customer interests and behavior in the store in real time and quickly make optimal product suggestions.

[0105] A "user information processing device" is a device used by a user to collect, display, and edit data, and includes smartphones, tablets, and computers.

[0106] "Information data" refers to electronic data collected from user activities and environment, including photos, videos, calendar information, and activity logs.

[0107] "Activity history" is a record of a user's activities, constructed chronologically, and is generated by analyzing information data.

[0108] A "narrative in natural language" is a description in a user-friendly text format, generated based on the activity history analyzed by the system.

[0109] "Visual assistance devices" are devices used by store employees to visually confirm customer information, and include smart glasses and tablets.

[0110] This invention is a system implemented using a user information processing device, a server, and a visual assistance device. The system is configured as follows:

[0111] First, the user's information processing device plays the role of collecting informational data such as photos, videos, calendar information, and activity logs. This data is fundamental information for recording the user's daily activities and interests.

[0112] Next, the server receives and analyzes the information data sent from the user's information processing device. Specifically, the server uses advanced natural language processing technology to integrate the information data as a chronological activity history. This analysis utilizes natural language processing engines such as Google® Cloud Natural Language API.

[0113] The analyzed activity history is generated as a narrative in natural language and presented in a user-friendly format. Users can add comments and feedback to this narrative, which are then used to further refine the activity history.

[0114] Furthermore, the server displays portions of the generated story on the store clerk's visual assistance device. This device (e.g., smart glasses) provides the clerk with information about the customer's interests, enabling them to make optimal product recommendations in real time.

[0115] As a concrete example, consider a scenario where a store employee wears smart glasses while patrolling the store. Based on data collected by in-store sensors and cameras, a server analyzes and notifies the employee of information about products the customer has shown interest in. For example, a message such as, "This customer is interested in running shoes. Please suggest some new products," might be displayed on the glasses.

[0116] An example of a prompt for a generative AI model is: "Based on historical data and behavioral analysis of the products this customer is most interested in, generate a product description that is best suited to this customer." This allows store employees to provide even more personalized service to customers.

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The user's information processing device collects information data such as photos, videos, calendar information, and activity logs. At this stage, the information data is entered, and the user's daily activities are recorded chronologically. The collected data is then sent to the server.

[0120] Step 2:

[0121] The server receives information data transmitted from the user's information processing device. The input here consists of various digital data from the user, which the server receives for analysis. The server then integrates and organizes this data to generate a chronological activity history. Metadata such as photo timestamps and location information is utilized during this process.

[0122] Step 3:

[0123] The server generates a story in natural language based on the integrated activity history. In this step, natural language processing techniques are applied to the integrated data as input. The generated story is output in a human-readable format for the user. The text is generated using tools such as the Google Cloud Natural Language API.

[0124] Step 4:

[0125] The server extracts customer interest information from the generated stories and sends it to the store clerk's visual assistance device. Here, information about a specific customer's interests is the input, and the data is converted into an appropriate format for display on the visual assistance device. The output information is presented to the store clerk in real time.

[0126] Step 5:

[0127] Users enter comments and feedback on the provided stories and send them to the server. This input constitutes user feedback, which the server receives. This information is used to improve future activity history and story adjustments. User feedback contributes to improving the system's accuracy.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention provides a journal generation system that takes into account the user's emotional state, thereby enabling the addition of emotional insights to daily activity records. In addition to collecting, analyzing, and integrating digital information, the system has the function of analyzing the user's emotional responses using an emotion engine.

[0130] Server roles and functions

[0131] The server analyzes photos, videos, activity logs, and calendar information collected from the user's device and uses an emotion engine to evaluate the user's emotions. The emotion engine extracts emotions from the context and text within the collected digital information and quantifies or qualitatively evaluates how the user felt. Based on this information, the server integrates time-series activity records and emotion data to generate a narrative.

[0132] Terminal roles and functions

[0133] The device displays a journal that includes sentiment analysis sent from the server. The displayed narrative reflects the emotional tone, allowing the user to reflect on their own feelings about past events. Users can also add feedback and new sentiment information, and this data will be used to generate the next journal.

[0134] User interaction and experience

[0135] The invention allows users to reflect on their emotions along with recording their daily lives. For example, if a user spends time with friends over the weekend, the joy and happiness they felt at that time are recognized by the emotion engine and reflected in the narrative. Later, the user can recall the event along with the emotions they felt at the time through this journal.

[0136] For example, if the surprise or satisfaction a user felt during their trip is detected from photos and activity logs, the server generates emotional narratives such as "a wonderful adventure" or "an unexpected encounter" based on those emotions. This allows users to digitally recreate deeper, emotion-based experiences that go beyond mere records of events.

[0137] The system realized by this invention enriches the user experience and enables further personalization through emotion recognition. In this way, users can record their daily lives in a more meaningful way and have more fulfilling recollections on an emotional level.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] The server periodically sends requests to collect digital information from the user's electronic device. This includes photos, videos, activity logs, and calendar information.

[0141] Step 2:

[0142] The terminal retrieves the specified digital information from local storage and sends it to the server. During this process, a prompt will appear to obtain permission from the user if necessary.

[0143] Step 3:

[0144] The server analyzes the received digital information. It extracts date, time, and location information from the metadata of photos and videos, and integrates activity records using activity logs and calendar information.

[0145] Step 4:

[0146] The server uses an emotion engine to analyze the user's emotional state from text and images within digital information. The emotion engine utilizes natural language processing and image analysis to quantify the user's emotional responses.

[0147] Step 5:

[0148] The server generates natural language narratives based on analyzed sentiment data and integrated activity records. During generation, it reflects the sentiment data and constructs the text in a tone that matches the user's experience.

[0149] Step 6:

[0150] The server considers the user's past activity history and emotional tendencies to individually personalize the generated narrative. This adjustment also utilizes previous feedback.

[0151] Step 7:

[0152] The server sends the final narrative to the user's terminal. The terminal displays this journal in a user-friendly interface.

[0153] Step 8:

[0154] Users can view the narrative generated on their device and add comments and sentimental feedback as needed. This feedback is then sent back to the server and used for future analysis and content generation.

[0155] (Example 2)

[0156] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0157] When recording users' daily activities, there is a need to go beyond a mere list of facts and provide deeper insights that reflect the user's own emotions. Traditional recording methods have made it difficult to consider users' emotions, making meaningful reflection difficult for users. Therefore, the challenge is to provide a richer experience by analyzing users' emotions and adding emotional insights to activity records.

[0158] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0159] In this invention, the server includes means for collecting electronic information from the user's information processing device, means for analyzing the collected electronic information and using natural language processing technology to evaluate emotions, and means for integrating the evaluated emotion information and activity records in chronological order and generating text in natural language using generative AI technology. This adds emotional insight to the user's activity records, enabling more meaningful reflection for the user.

[0160] An "information processing device" is an electronic device used by users on a daily basis, which collects and displays digital information.

[0161] "Electronic information" refers to all data that represents a user's activities and status in digital format, such as photographs, videos, activity logs, and calendar information.

[0162] "Evaluating emotions" means analyzing a user's emotional state from collected digital information and understanding it either numerically or qualitatively.

[0163] "Natural language processing technology" refers to computational methods for understanding the meaning of information through the analysis of text data and for extracting useful information from that data.

[0164] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate text and other content, and is used to generate text based on the user's emotional state and behavioral logs.

[0165] "Integrating chronologically" is the process of organizing user activity and emotional data in chronological order and combining related information.

[0166] "Natural language text" refers to text expressed in a language format that humans normally use, and is intended to provide information in a way that is easy for users to understand.

[0167] In this invention, users record electronic information using an information processing device on a daily basis. This information processing device refers to, for example, a mobile device such as a smartphone or tablet, which has the function of accumulating daily data such as photos, videos, activity logs, and calendar information. This digital information is transmitted to a server via a wireless network.

[0168] The server is equipped with a large-capacity storage system for receiving and storing large amounts of digital information. The server uses natural language processing technology to analyze the received data. Specifically, this technology is used to analyze collected text and audio data, extracting keywords from them to evaluate the user's emotional state.

[0169] The emotion engine operates based on a generative AI model, integrating emotional information evaluated from analyzed data with activity logs in a time-series manner. This AI model has the ability to determine emotions from text data, qualitatively or numerically evaluate the user's emotions, and utilizes the resulting emotion score to enable narrative generation.

[0170] The terminal displays a generated narrative retrieved from the server to the user. The user reviews the displayed narrative and reflects on their emotions regarding past events. Furthermore, feedback and additional information from the user are collected and incorporated into the next journal generation. The user interface is intuitive and designed to allow users to easily add emotional information.

[0171] For example, when a user uploads photos from their trip, the server detects feelings of surprise and satisfaction from those photos. A generative AI model then generates a narrative of "a wonderful adventure" based on these emotions and displays it on the user's device. This allows users to not only record their trip but also relive the emotions they felt at the time, enabling a deeper reflection.

[0172] An example of a prompt statement can be written as follows:

[0173] "If a user provides a log of their activities over the past week, how can we extract the key events and associated sentiments from that data?"

[0174] "Identify the emotions experienced during a trip from travel photos uploaded by the user, and generate a narrative based on those emotions."

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] Users use an information processing device to record their daily activities as photos, videos, activity logs, and calendar information. The input is this electronic information, and the output is data ready to be sent from the terminal to the server. This involves data format conversion and necessary tagging.

[0178] Step 2:

[0179] The device periodically transmits digital information to the server. The input is electronic information stored on the user's device, and the output is information transferred to the server. Transmission occurs automatically via Wi-Fi or a mobile network.

[0180] Step 3:

[0181] The server stores the received electronic information and begins analysis using natural language processing techniques. The input is the transmitted electronic information, and the output is data representing emotion scores and emotional states. The server applies pattern recognition to extract keywords from text and audio and evaluate emotions.

[0182] Step 4:

[0183] The server uses a generative AI model to integrate analyzed sentiment data with chronologically organized activity logs. The input consists of sentiment scores and activity logs, while the output is a narrative containing emotional insights. The generative AI model generates text based on the extracted sentiments to form the narrative.

[0184] Step 5:

[0185] The terminal displays narratives sent from the server on the user interface. The input is the narrative received from the server, and the output is information visually presented on the terminal. The user can view this and reflect on past emotions.

[0186] Step 6:

[0187] Users input feedback and additional sentiment information about the narrative on their device. The input consists of user feedback and additional information, while the output is data that will be reflected in the next journal generation. This allows for a more personalized generation process.

[0188] (Application Example 2)

[0189] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0190] In today's world, users are exposed to a vast amount of content daily, yet there is a lack of effective means to properly record and reflect on their viewing experiences. Traditional recording methods only provide a basic viewing history, making it difficult to reflect on emotional responses and the feelings experienced during viewing. Therefore, a system is needed that provides emotional insights based on viewing experiences, enabling users to engage in more profound reflection.

[0191] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0192] In this invention, the server includes means for collecting data from the user's information processing device, means for analyzing the collected data and generating chronologically recorded information, and means for evaluating emotional responses and generating a narrative based on them. This makes it possible to review emotional insights obtained from the user's viewing experience as a narrative.

[0193] An "information processing device" is an electronic device used to collect and analyze user data and provide information based on that data.

[0194] "Data" refers to a collection of user-related information, including visual and auditory information.

[0195] "Recorded information" refers to information that is structured by arranging collected data chronologically.

[0196] A "story" is a narrative in natural language generated based on data and emotional responses.

[0197] "Emotional response" refers to data that indicates the user's emotional state, analyzed from the user's visual and auditory information.

[0198] "Visual information" refers to visual data such as images and videos.

[0199] "Audio information" refers to data collected from audio and is the subject of analysis.

[0200] The system implementing this invention operates primarily through the collaboration of a server, an information processing terminal, and a user. The server is responsible for collecting data transmitted from the user and performing analysis and integration based on that data. Specifically, the server is equipped with the latest data analysis technology and uses NVIDIA's CUDA to quickly and efficiently evaluate emotional responses from image and audio data.

[0201] The analyzed data is processed on a large scale using Apache Hadoop to generate a time-series record that takes into account the context of viewing and experience. This record is structured to gain deep insights into the viewing experience. For specific narrative generation, OpenAI's GPT model is used, and a personalized natural language story is automatically generated based on the evaluated emotional responses.

[0202] The device acts as an interface that delivers these stories to the user. The generated narratives are sent to the device, and the user can provide feedback with emotional insights based on their viewing experience.

[0203] For example, based on the surprise and emotion a user felt while watching a movie on their day off, the server generates a narrative such as "A holiday spent overwhelmed by a magnificent story." This process is instructed to the model in the form of a prompt message such as, "The content the user watched was a movie, and the main emotions were surprise and emotion. Please generate a narrative of the viewing experience based on these emotions."

[0204] In this way, it becomes possible to reflect on the viewing experience with emotional insights, allowing users to have a richer experience.

[0205] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0206] Step 1:

[0207] The server receives visual and audio information as data from the user's information processing terminal. This data includes information about the content the user has viewed. The server receives this data as input and prepares it for analysis.

[0208] Step 2:

[0209] The server uses NVIDIA's CUDA to analyze emotional responses to the received visual and auditory information. This analysis involves image processing and audio analysis to quantify specific emotional states (e.g., surprise, emotion). The output of this step is the evaluation result of the emotional state.

[0210] Step 3:

[0211] The server uses Apache Hadoop to perform large-scale data processing and integrate analysis results and viewing data. In particular, each emotional state is arranged as time-series data and associated with background information of the viewing experience. This process generates time-series recorded information.

[0212] Step 4:

[0213] The server uses OpenAI's generative AI model, GPT, to automatically generate narratives based on the generated time-series recording information. This model converts emotion evaluation results and viewing information into narratives based on prompt text. The output is a natural language story that includes emotional elements.

[0214] Step 5:

[0215] The server sends the generated narrative to the user's device. The device receives this and functions as an interface to visually present it to the user. The user can use this narrative to emotionally reflect on their viewing experience.

[0216] Step 6:

[0217] Users send feedback on the narrative to the server via their device. The server collects this feedback as new input data and uses it to improve the next analysis and narrative generation process. This improves the overall accuracy and personalization of the system.

[0218] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0234] This invention provides a system that effectively records and facilitates the review of users' daily and work activities. The system analyzes digital information collected from the user's electronic device and generates a highly personalized journal. This allows users to eliminate manual record-keeping and improve the quality of activity statistics and reviews.

[0235] Server roles and functions

[0236] The server, as the core of the system, manages and processes digital information. First, the server acquires digital information such as photos, videos, calendars, and activity logs from the user's terminal. The acquired information is analyzed within the server, and an activity timeline is generated based on location and time information. Furthermore, natural language processing technology is used to convert the timeline into a human-readable narrative. This allows the server to provide information to the user in an easy-to-use format.

[0237] Terminal roles and functions

[0238] The user's device displays information provided by the server, allowing the user to review and edit their activities. The device receives journal entries from the server and displays them on the screen in a visualized format. This allows users to easily access data as a diary or daily work report. In addition, it includes a function for users to add comments and supplementary information, which can then be sent back to the server as feedback.

[0239] User interaction and experience

[0240] Users can use the system simply by setting it up and allowing the collection of digital information to the extent necessary. No special operation is required, as the system automatically records activities and events that the user wishes to document. The activity logs and narratives provided by the system are based on the user's past data, making them tailored to individual experiences. For example, if travel photos are registered as data, the server will construct context from the location and time the photos were taken and automatically generate a travelogue.

[0241] As a concrete example, consider a user who goes mountain climbing on a holiday. If the user takes photos and collects activity logs, the server analyzes this data and generates a diary that includes details such as the time it took to reach the summit and the route taken. The photos taken are also used as part of the narrative, providing a visual story of the activity. Later, the user can refer to this digital diary to vividly recall the memories of the day and use that information to plan their next trip.

[0242] Thus, the present invention provides an efficient and high-quality journal, enabling users to record their daily lives while saving them time and effort.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The server sends a data collection request to the user's device. At this time, the user specifies the type of digital information to be collected, such as photos, videos, activity logs, and calendar information.

[0246] Step 2:

[0247] The device retrieves the specified digital information from a local database and sends the collected data to the server. This process may include location information and social media information.

[0248] Step 3:

[0249] The server analyzes the received digital information. First, it extracts metadata to obtain the date and time of shooting and location information, and then compares it with activity logs and calendar information to determine the relationships between them.

[0250] Step 4:

[0251] The server generates a timeline of activities in chronological order from the analyzed data. This generated timeline serves as the foundation for organizing the user's activities as a series of stories.

[0252] Step 5:

[0253] The server utilizes AI to construct narratives based on timelines. It uses natural language processing technology to generate text that is easy for users to understand.

[0254] Step 6:

[0255] The server personalizes the generated narrative based on the user's past records and preferences. It selects and highlights important events, completing the content with individual adjustments.

[0256] Step 7:

[0257] The server sends the completed narrative to the user's device. The device receives this data and displays it in its viewing interface.

[0258] Step 8:

[0259] Users view the narrative on their devices and add comments and notes as needed. This feedback information is sent to the server and used for subsequent analytics and content improvement.

[0260] (Example 1)

[0261] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0262] In today's world, information about daily activities and work is increasingly digitized, and data is generated from diverse sources. In this environment, people may face decreased productivity and loss of important information due to overlooked or misinterpreted records. To solve this, a system is needed that automatically generates accurate and personalized activity records with minimal effort and provides them in an easy-to-understand format.

[0263] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0264] In this invention, the server includes means for collecting information from the user's information processing device, means for analyzing and integrating the collected information to generate a time-series activity record, and means for generating natural language text from the integrated activity record. This enables the user to efficiently review their activities and make decisions based on the necessary information.

[0265] A "user" refers to a person or organization that uses this system to generate activity records.

[0266] An "information processing device" refers to an electronic device owned or used by a user that has the function of collecting and transmitting digital information.

[0267] "Information" refers to digital data related to user activities, including photos, videos, calendar events, and activity logs.

[0268] A "server" refers to a computer system that receives and analyzes information, and generates and transmits activity records and documents.

[0269] "Activity log" refers to data that summarizes a user's actions and events over a certain period of time in chronological order.

[0270] "Natural language" refers to texts written in the language that humans use on a daily basis.

[0271] "Generating text" means creating a narrative written in natural language from the information received.

[0272] A "generative AI model" refers to an artificial intelligence model trained using machine learning, which analyzes data and generates output suitable for the user.

[0273] This invention supports the automatic recording and review of user activities through a system including a user information processing device and a server. Specifically, the information processing device is an electronic device owned by the user, such as a smartphone or tablet, and these devices first collect various digital information such as photos, videos, calendar information, and activity logs. The information processing device temporarily stores this data and transmits it to the server in a secure manner.

[0274] The server analyzes the received digital information and uses location and time data to generate a timeline of activities. This uses a general database management system and a generative AI model for natural language processing. The generative AI model is equipped with natural language processing technology such as that provided by OpenAI, and is capable of generating a human-readable narrative from activity records.

[0275] The generated narrative is optimized for each individual user and sent to the information processing device. The information processing device visually displays this narrative, allowing users to easily review their activities. For example, if a user goes mountain climbing on a holiday, the server generates a timeline of the climb based on data such as photos, videos, and GPS logs, and displays it as a travelogue in natural language.

[0276] An example of a prompt would be: "Generate a digital diary about last weekend's mountain climbing. Include information about the climbing route and arrival time from photos and activity logs."

[0277] By constructing the system in this way, the user can efficiently obtain high-quality activity records without the need for special operations.

[0278] The flow of the specific process in Example 1 will be described using FIG. 11.

[0279] Step 1:

[0280] The terminal collects photos, videos, calendar information, and action logs under the user's permission. As input, these digital information are collected and temporarily stored in the terminal. Specific operations include obtaining necessary data using the terminal's camera app and location information service.

[0281] Step 2:

[0282] The terminal transmits the collected digital information to the server using secure communication means. As input, the data saved in Step 1 is used, and as output, the data is transmitted to the server. Specifically, the secure transfer of data is performed using the HTTPS protocol.

[0283] Step 3:

[0284] The server analyzes the received digital information and organizes the data based on time and location information. As input, it receives the data transmitted from the terminal, and as output, it generates a timeline of activities. Specifically, it identifies the start and end times of events from the location information and time information, and creates a logical timeline.

[0285] Step 4:

[0286] The server uses the generated AI model to convert the timeline into a natural language narrative. As input, there is the timeline generated in Step 3, and as output, it outputs a human-readable text. Specific operations include the AI model utilizing the prompt text for text generation and describing activities in easy-to-understand words.

[0287] Step 5:

[0288] The server sends the generated narrative to the terminal. The input is the narrative generated in Step 4, and the output is to send data to the terminal. Specifically, it is the operation of delivering narrative data to the user's terminal using a secure communication protocol again.

[0289] Step 6:

[0290] The terminal visually displays the received narrative so that the user can view it. The input is the narrative received from the server, and the output is displayed on the user's screen. As a specific operation, the text is visualized through the display interface of the terminal, and the user can scroll and edit it.

[0291] Step 7:

[0292] The user can add comments or supplementary information to the displayed narrative. The input is the feedback or additional information from the user, and the output is saved on the terminal. Specifically, it includes the operation of the user adding information in text or voice to the input field of the terminal.

[0293] Step 8:

[0294] The terminal sends the additional information from the user to the server as feedback. The input is the feedback information generated in Step 7, and the output is to send data to the server. As a specific operation, it is to send back the data in the same way as the previously sent protocol.

[0295] (Application Example 1)

[0296] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0297] In today's commercial environment, there is a demand for quick and individualized responses to diverse customer needs. However, it is difficult for store staff to manually understand customer interests and behavior and make appropriate product recommendations, hindering improvements in customer experience and optimization of sales opportunities. To solve this problem, there is a need for technology that automatically understands customer behavior and interests, enabling store staff to respond immediately.

[0298] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0299] In this invention, the server includes means for collecting information data from the user's information processing device, means for analyzing and integrating the collected information data to generate a time-series activity history, and means for displaying customer interest information on a store employee's visual support device. This enables store employees to grasp customer interests and behavior in the store in real time and quickly make optimal product suggestions.

[0300] A "user information processing device" is a device used by a user to collect, display, and edit data, and includes smartphones, tablets, and computers.

[0301] "Information data" refers to electronic data collected from user activities and environment, including photos, videos, calendar information, and activity logs.

[0302] "Activity history" is a record of a user's activities, constructed chronologically, and is generated by analyzing information data.

[0303] A "narrative in natural language" is a description in a user-friendly text format, generated based on the activity history analyzed by the system.

[0304] A "visual assistance device" is a device used by store clerks to visually confirm customer information, such as smart glasses and tablets.

[0305] This invention is a system implemented using a user's information processing device, a server, and a visual assistance device. The system is configured as follows.

[0306] First, the user's information processing device serves to collect information data such as photos, videos, calendar information, and activity logs. These data are basic information for recording the user's daily activities and interests.

[0307] Next, the server receives the information data transmitted from the user's information processing device and performs analysis. Specifically, the server uses advanced natural language processing technology to integrate the information data as an activity history along the time series. In this analysis, a natural language processing engine such as the Google Cloud Natural Language API is utilized.

[0308] The analyzed activity history is generated as a story in natural language and provided in a form that is easy for the user to understand. The user can add comments and feedback to this story, which is then utilized again for adjusting the activity history.

[0309] Furthermore, the server displays a part of the generated story on the visual assistance device of the store clerk. This visual assistance device (such as smart glasses) provides the store clerk with information on the customer's interests, enabling real-time optimal product recommendations.

[0310] As a specific example, consider the situation where a store clerk is walking around the store wearing smart glasses. Based on the data collected by in-store sensors and cameras, the server analyzes and notifies the store clerk of information about the products that the customer is interested in. For example, a message such as "This customer is interested in running shoes. Please recommend new products." is displayed on the glasses.

[0311] An example of a prompt for a generative AI model is: "Based on historical data and behavioral analysis of the products this customer is most interested in, generate a product description that is best suited to this customer." This allows store employees to provide even more personalized service to customers.

[0312] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0313] Step 1:

[0314] The user's information processing device collects information data such as photos, videos, calendar information, and activity logs. At this stage, the information data is entered, and the user's daily activities are recorded chronologically. The collected data is then sent to the server.

[0315] Step 2:

[0316] The server receives information data transmitted from the user's information processing device. The input here consists of various digital data from the user, which the server receives for analysis. The server then integrates and organizes this data to generate a chronological activity history. Metadata such as photo timestamps and location information is utilized during this process.

[0317] Step 3:

[0318] The server generates a story in natural language based on the integrated activity history. In this step, natural language processing techniques are applied to the integrated data as input. The generated story is output in a human-readable format for the user. The text is generated using tools such as the Google Cloud Natural Language API.

[0319] Step 4:

[0320] The server extracts customer interest information from the generated stories and sends it to the store clerk's visual assistance device. Here, information about a specific customer's interests is the input, and the data is converted into an appropriate format for display on the visual assistance device. The output information is presented to the store clerk in real time.

[0321] Step 5:

[0322] Users enter comments and feedback on the provided stories and send them to the server. This input constitutes user feedback, which the server receives. This information is used to improve future activity history and story adjustments. User feedback contributes to improving the system's accuracy.

[0323] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0324] This invention provides a journal generation system that takes into account the user's emotional state, thereby enabling the addition of emotional insights to daily activity records. In addition to collecting, analyzing, and integrating digital information, the system has the function of analyzing the user's emotional responses using an emotion engine.

[0325] Server roles and functions

[0326] The server analyzes photos, videos, activity logs, and calendar information collected from the user's device and uses an emotion engine to evaluate the user's emotions. The emotion engine extracts emotions from the context and text within the collected digital information and quantifies or qualitatively evaluates how the user felt. Based on this information, the server integrates time-series activity records and emotion data to generate a narrative.

[0327] Terminal roles and functions

[0328] The device displays a journal that includes sentiment analysis sent from the server. The displayed narrative reflects the emotional tone, allowing the user to reflect on their own feelings about past events. Users can also add feedback and new sentiment information, and this data will be used to generate the next journal.

[0329] User interaction and experience

[0330] The invention allows users to reflect on their emotions along with recording their daily lives. For example, if a user spends time with friends over the weekend, the joy and happiness they felt at that time are recognized by the emotion engine and reflected in the narrative. Later, the user can recall the event along with the emotions they felt at the time through this journal.

[0331] For example, if the surprise or satisfaction a user felt during their trip is detected from photos and activity logs, the server generates emotional narratives such as "a wonderful adventure" or "an unexpected encounter" based on those emotions. This allows users to digitally recreate deeper, emotion-based experiences that go beyond mere records of events.

[0332] The system realized by this invention enriches the user experience and enables further personalization through emotion recognition. In this way, users can record their daily lives in a more meaningful way and have more fulfilling recollections on an emotional level.

[0333] The following describes the processing flow.

[0334] Step 1:

[0335] The server periodically sends requests to collect digital information from the user's electronic device. This includes photos, videos, activity logs, and calendar information.

[0336] Step 2:

[0337] The terminal retrieves the specified digital information from local storage and sends it to the server. During this process, a prompt will appear to obtain permission from the user if necessary.

[0338] Step 3:

[0339] The server analyzes the received digital information. It extracts date, time, and location information from the metadata of photos and videos, and integrates activity records using activity logs and calendar information.

[0340] Step 4:

[0341] The server uses an emotion engine to analyze the user's emotional state from text and images within digital information. The emotion engine utilizes natural language processing and image analysis to quantify the user's emotional responses.

[0342] Step 5:

[0343] The server generates natural language narratives based on analyzed sentiment data and integrated activity records. During generation, it reflects the sentiment data and constructs the text in a tone that matches the user's experience.

[0344] Step 6:

[0345] The server considers the user's past activity history and emotional tendencies to individually personalize the generated narrative. This adjustment also utilizes previous feedback.

[0346] Step 7:

[0347] The server sends the final narrative to the user's terminal. The terminal displays this journal in a user-friendly interface.

[0348] Step 8:

[0349] Users can view the narrative generated on their device and add comments and sentimental feedback as needed. This feedback is then sent back to the server and used for future analysis and content generation.

[0350] (Example 2)

[0351] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0352] When recording users' daily activities, there is a need to go beyond a mere list of facts and provide deeper insights that reflect the user's own emotions. Traditional recording methods have made it difficult to consider users' emotions, making meaningful reflection difficult for users. Therefore, the challenge is to provide a richer experience by analyzing users' emotions and adding emotional insights to activity records.

[0353] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0354] In this invention, the server includes means for collecting electronic information from the user's information processing device, means for analyzing the collected electronic information and using natural language processing technology to evaluate emotions, and means for integrating the evaluated emotion information and activity records in chronological order and generating text in natural language using generative AI technology. This adds emotional insight to the user's activity records, enabling more meaningful reflection for the user.

[0355] An "information processing device" is an electronic device used by users on a daily basis, which collects and displays digital information.

[0356] "Electronic information" refers to all data that represents a user's activities and status in digital format, such as photographs, videos, activity logs, and calendar information.

[0357] "Evaluating emotions" means analyzing a user's emotional state from collected digital information and understanding it either numerically or qualitatively.

[0358] "Natural language processing technology" refers to computational methods for understanding the meaning of information through the analysis of text data and for extracting useful information from that data.

[0359] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate text and other content, and is used to generate text based on the user's emotional state and behavioral logs.

[0360] "Integrating chronologically" is the process of organizing user activity and emotional data in chronological order and combining related information.

[0361] "Natural language text" refers to text expressed in a language format that humans normally use, and is intended to provide information in a way that is easy for users to understand.

[0362] In this invention, users record electronic information using an information processing device on a daily basis. This information processing device refers to, for example, a mobile device such as a smartphone or tablet, which has the function of accumulating daily data such as photos, videos, activity logs, and calendar information. This digital information is transmitted to a server via a wireless network.

[0363] The server is equipped with a large-capacity storage system for receiving and storing large amounts of digital information. The server uses natural language processing technology to analyze the received data. Specifically, this technology is used to analyze collected text and audio data, extracting keywords from them to evaluate the user's emotional state.

[0364] The emotion engine operates based on a generative AI model, integrating emotional information evaluated from analyzed data with activity logs in a time-series manner. This AI model has the ability to determine emotions from text data, qualitatively or numerically evaluate the user's emotions, and utilizes the resulting emotion score to enable narrative generation.

[0365] The terminal displays a generated narrative retrieved from the server to the user. The user reviews the displayed narrative and reflects on their emotions regarding past events. Furthermore, feedback and additional information from the user are collected and incorporated into the next journal generation. The user interface is intuitive and designed to allow users to easily add emotional information.

[0366] For example, when a user uploads photos from their trip, the server detects feelings of surprise and satisfaction from those photos. A generative AI model then generates a narrative of "a wonderful adventure" based on these emotions and displays it on the user's device. This allows users to not only record their trip but also relive the emotions they felt at the time, enabling a deeper reflection.

[0367] An example of a prompt statement can be written as follows:

[0368] "If a user provides a log of their activities over the past week, how can we extract the key events and associated sentiments from that data?"

[0369] "Identify the emotions experienced during a trip from travel photos uploaded by the user, and generate a narrative based on those emotions."

[0370] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0371] Step 1:

[0372] Users use an information processing device to record their daily activities as photos, videos, activity logs, and calendar information. The input is this electronic information, and the output is data ready to be sent from the terminal to the server. This involves data format conversion and necessary tagging.

[0373] Step 2:

[0374] The device periodically transmits digital information to the server. The input is electronic information stored on the user's device, and the output is information transferred to the server. Transmission occurs automatically via Wi-Fi or a mobile network.

[0375] Step 3:

[0376] The server stores the received electronic information and begins analysis using natural language processing techniques. The input is the transmitted electronic information, and the output is data representing emotion scores and emotional states. The server applies pattern recognition to extract keywords from text and audio and evaluate emotions.

[0377] Step 4:

[0378] The server uses a generative AI model to integrate analyzed sentiment data with chronologically organized activity logs. The input consists of sentiment scores and activity logs, while the output is a narrative containing emotional insights. The generative AI model generates text based on the extracted sentiments to form the narrative.

[0379] Step 5:

[0380] The terminal displays narratives sent from the server on the user interface. The input is the narrative received from the server, and the output is information visually presented on the terminal. The user can view this and reflect on past emotions.

[0381] Step 6:

[0382] Users input feedback and additional sentiment information about the narrative on their device. The input consists of user feedback and additional information, while the output is data that will be reflected in the next journal generation. This allows for a more personalized generation process.

[0383] (Application Example 2)

[0384] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0385] In today's world, users are exposed to a vast amount of content daily, yet there is a lack of effective means to properly record and reflect on their viewing experiences. Traditional recording methods only provide a basic viewing history, making it difficult to reflect on emotional responses and the feelings experienced during viewing. Therefore, a system is needed that provides emotional insights based on viewing experiences, enabling users to engage in more profound reflection.

[0386] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0387] In this invention, the server includes means for collecting data from the user's information processing device, means for analyzing the collected data and generating chronologically recorded information, and means for evaluating emotional responses and generating a narrative based on them. This makes it possible to review emotional insights obtained from the user's viewing experience as a narrative.

[0388] An "information processing device" is an electronic device used to collect and analyze user data and provide information based on that data.

[0389] "Data" refers to a collection of user-related information, including visual and auditory information.

[0390] "Recorded information" refers to information that is structured by arranging collected data chronologically.

[0391] A "story" is a narrative in natural language generated based on data and emotional responses.

[0392] "Emotional response" refers to data that indicates the user's emotional state, analyzed from the user's visual and auditory information.

[0393] "Visual information" refers to visual data such as images and videos.

[0394] "Audio information" refers to data collected from audio and is the subject of analysis.

[0395] The system implementing this invention operates primarily through the collaboration of a server, an information processing terminal, and a user. The server is responsible for collecting data transmitted from the user and performing analysis and integration based on that data. Specifically, the server is equipped with the latest data analysis technology and uses NVIDIA's CUDA to quickly and efficiently evaluate emotional responses from image and audio data.

[0396] The analyzed data is processed on a large scale using Apache Hadoop to generate a time-series record that takes into account the context of viewing and experience. This record is structured to gain deep insights into the viewing experience. For specific narrative generation, OpenAI's GPT model is used, and a personalized natural language story is automatically generated based on the evaluated emotional responses.

[0397] The device acts as an interface that delivers these stories to the user. The generated narratives are sent to the device, and the user can provide feedback with emotional insights based on their viewing experience.

[0398] For example, based on the surprise and emotion a user felt while watching a movie on their day off, the server generates a narrative such as "A holiday spent overwhelmed by a magnificent story." This process is instructed to the model in the form of a prompt message such as, "The content the user watched was a movie, and the main emotions were surprise and emotion. Please generate a narrative of the viewing experience based on these emotions."

[0399] In this way, it becomes possible to reflect on the viewing experience with emotional insights, allowing users to have a richer experience.

[0400] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0401] Step 1:

[0402] The server receives visual and audio information as data from the user's information processing terminal. This data includes information about the content the user has viewed. The server receives this data as input and prepares it for analysis.

[0403] Step 2:

[0404] The server uses NVIDIA's CUDA to analyze emotional responses to the received visual and auditory information. This analysis involves image processing and audio analysis to quantify specific emotional states (e.g., surprise, emotion). The output of this step is the evaluation result of the emotional state.

[0405] Step 3:

[0406] The server uses Apache Hadoop to perform large-scale data processing and integrate analysis results and viewing data. In particular, each emotional state is arranged as time-series data and associated with background information of the viewing experience. This process generates time-series recorded information.

[0407] Step 4:

[0408] The server uses OpenAI's generative AI model, GPT, to automatically generate narratives based on the generated time-series recording information. This model converts emotion evaluation results and viewing information into narratives based on prompt text. The output is a natural language story that includes emotional elements.

[0409] Step 5:

[0410] The server sends the generated narrative to the user's device. The device receives this and functions as an interface to visually present it to the user. The user can use this narrative to emotionally reflect on their viewing experience.

[0411] Step 6:

[0412] Users send feedback on the narrative to the server via their device. The server collects this feedback as new input data and uses it to improve the next analysis and narrative generation process. This improves the overall accuracy and personalization of the system.

[0413] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0414] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0415] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0416] [Third Embodiment]

[0417] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0418] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0419] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0420] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0421] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0422] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0423] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0424] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0425] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0426] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0427] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0428] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0429] This invention provides a system that effectively records and facilitates the review of users' daily and work activities. The system analyzes digital information collected from the user's electronic device and generates a highly personalized journal. This allows users to eliminate manual record-keeping and improve the quality of activity statistics and reviews.

[0430] Server roles and functions

[0431] The server, as the core of the system, manages and processes digital information. First, the server acquires digital information such as photos, videos, calendars, and activity logs from the user's terminal. The acquired information is analyzed within the server, and an activity timeline is generated based on location and time information. Furthermore, natural language processing technology is used to convert the timeline into a human-readable narrative. This allows the server to provide information to the user in an easy-to-use format.

[0432] Terminal roles and functions

[0433] The user's device displays information provided by the server, allowing the user to review and edit their activities. The device receives journal entries from the server and displays them on the screen in a visualized format. This allows users to easily access data as a diary or daily work report. In addition, it includes a function for users to add comments and supplementary information, which can then be sent back to the server as feedback.

[0434] User interaction and experience

[0435] Users can use the system simply by setting it up and allowing the collection of digital information to the extent necessary. No special operation is required, as the system automatically records activities and events that the user wishes to document. The activity logs and narratives provided by the system are based on the user's past data, making them tailored to individual experiences. For example, if travel photos are registered as data, the server will construct context from the location and time the photos were taken and automatically generate a travelogue.

[0436] As a concrete example, consider a user who goes mountain climbing on a holiday. If the user takes photos and collects activity logs, the server analyzes this data and generates a diary that includes details such as the time it took to reach the summit and the route taken. The photos taken are also used as part of the narrative, providing a visual story of the activity. Later, the user can refer to this digital diary to vividly recall the memories of the day and use that information to plan their next trip.

[0437] Thus, the present invention provides an efficient and high-quality journal, enabling users to record their daily lives while saving them time and effort.

[0438] The following describes the processing flow.

[0439] Step 1:

[0440] The server sends a data collection request to the user's device. At this time, the user specifies the type of digital information to be collected, such as photos, videos, activity logs, and calendar information.

[0441] Step 2:

[0442] The device retrieves the specified digital information from a local database and sends the collected data to the server. This process may include location information and social media information.

[0443] Step 3:

[0444] The server analyzes the received digital information. First, it extracts metadata to obtain the date and time of shooting and location information, and then compares it with activity logs and calendar information to determine the relationships between them.

[0445] Step 4:

[0446] The server generates a timeline of activities in chronological order from the analyzed data. This generated timeline serves as the foundation for organizing the user's activities as a series of stories.

[0447] Step 5:

[0448] The server utilizes AI to construct narratives based on timelines. It uses natural language processing technology to generate text that is easy for users to understand.

[0449] Step 6:

[0450] The server personalizes the generated narrative based on the user's past records and preferences. It selects and highlights important events, completing the content with individual adjustments.

[0451] Step 7:

[0452] The server sends the completed narrative to the user's device. The device receives this data and displays it in its viewing interface.

[0453] Step 8:

[0454] Users view the narrative on their devices and add comments and notes as needed. This feedback information is sent to the server and used for subsequent analytics and content improvement.

[0455] (Example 1)

[0456] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0457] In today's world, information about daily activities and work is increasingly digitized, and data is generated from diverse sources. In this environment, people may face decreased productivity and loss of important information due to overlooked or misinterpreted records. To solve this, a system is needed that automatically generates accurate and personalized activity records with minimal effort and provides them in an easy-to-understand format.

[0458] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0459] In this invention, the server includes means for collecting information from the user's information processing device, means for analyzing and integrating the collected information to generate a time-series activity record, and means for generating natural language text from the integrated activity record. This enables the user to efficiently review their activities and make decisions based on the necessary information.

[0460] A "user" refers to a person or organization that uses this system to generate activity records.

[0461] An "information processing device" refers to an electronic device owned or used by a user that has the function of collecting and transmitting digital information.

[0462] "Information" refers to digital data related to user activities, including photos, videos, calendar events, and activity logs.

[0463] A "server" refers to a computer system that receives and analyzes information, and generates and transmits activity records and documents.

[0464] "Activity log" refers to data that summarizes a user's actions and events over a certain period of time in chronological order.

[0465] "Natural language" refers to texts written in the language that humans use on a daily basis.

[0466] "Generating text" means creating a narrative written in natural language from the information received.

[0467] A "generative AI model" refers to an artificial intelligence model trained using machine learning, which analyzes data and generates output suitable for the user.

[0468] This invention supports the automatic recording and review of user activities through a system including a user information processing device and a server. Specifically, the information processing device is an electronic device owned by the user, such as a smartphone or tablet, and these devices first collect various digital information such as photos, videos, calendar information, and activity logs. The information processing device temporarily stores this data and transmits it to the server in a secure manner.

[0469] The server analyzes the received digital information and uses location and time data to generate a timeline of activities. This uses a general database management system and a generative AI model for natural language processing. The generative AI model is equipped with natural language processing technology such as that provided by OpenAI, and is capable of generating a human-readable narrative from activity records.

[0470] The generated narrative is optimized for each individual user and sent to the information processing device. The information processing device visually displays this narrative, allowing users to easily review their activities. For example, if a user goes mountain climbing on a holiday, the server generates a timeline of the climb based on data such as photos, videos, and GPS logs, and displays it as a travelogue in natural language.

[0471] An example of a prompt would be: "Generate a digital diary about last weekend's mountain climbing. Include information about the climbing route and arrival time from photos and activity logs."

[0472] By building the system in this way, users can efficiently obtain high-quality activity records without requiring any special operations.

[0473] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0474] Step 1:

[0475] The device collects photos, videos, calendar information, and activity logs with the user's permission. This digital information is collected as input and temporarily stored on the device. Specific operations include using the device's camera app and location services to obtain necessary data.

[0476] Step 2:

[0477] The terminal transmits the collected digital information to the server using a secure communication method. The data stored in step 1 is used as input, and the data is sent to the server as output. Specifically, the HTTPS protocol is used for secure data transfer.

[0478] Step 3:

[0479] The server analyzes the received digital information and organizes the data based on time and location information. It receives data transmitted from terminals as input and generates an activity timeline as output. Specifically, it identifies the start and end times of events from location and time information and creates a logical timeline.

[0480] Step 4:

[0481] The server uses a generative AI model to convert the timeline into a natural language narrative. The input is the timeline generated in step 3, and the output is human-readable text. Specifically, the AI ​​model utilizes text generation prompts to describe the activities in easily understandable language.

[0482] Step 5:

[0483] The server sends the generated narrative to the terminal. The input is the narrative generated in step 4, and the output is the data sent to the terminal. Specifically, this involves delivering the narrative data to the user's terminal using a secure communication protocol.

[0484] Step 6:

[0485] The terminal visually displays the received narrative, allowing the user to review it. The input is the narrative received from the server, and the output is displayed on the user's screen. Specifically, the terminal's display interface visualizes the text, allowing the user to scroll and edit it.

[0486] Step 7:

[0487] Users can add comments and supplementary information to the displayed narrative. Input includes user feedback and additional information, which is saved on the device as output. Specifically, this involves users adding information via text or voice to input fields on the device.

[0488] Step 8:

[0489] The terminal sends additional information from the user to the server as feedback. The input is the feedback information generated in step 7, and the output is data sent to the server. Specifically, the operation is to send the data back using the same protocol as the one used to send it earlier.

[0490] (Application Example 1)

[0491] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0492] In today's commercial environment, there is a demand for quick and individualized responses to diverse customer needs. However, it is difficult for store staff to manually understand customer interests and behavior and make appropriate product recommendations, hindering improvements in customer experience and optimization of sales opportunities. To solve this problem, there is a need for technology that automatically understands customer behavior and interests, enabling store staff to respond immediately.

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

[0494] In this invention, the server includes means for collecting information data from the user's information processing device, means for analyzing and integrating the collected information data to generate a time-series activity history, and means for displaying customer interest information on a store employee's visual support device. This enables store employees to grasp customer interests and behavior in the store in real time and quickly make optimal product suggestions.

[0495] A "user information processing device" is a device used by a user to collect, display, and edit data, and includes smartphones, tablets, and computers.

[0496] "Information data" refers to electronic data collected from user activities and environment, including photos, videos, calendar information, and activity logs.

[0497] "Activity history" is a record of a user's activities, constructed chronologically, and is generated by analyzing information data.

[0498] A "narrative in natural language" is a description in a user-friendly text format, generated based on the activity history analyzed by the system.

[0499] "Visual assistance devices" are devices used by store employees to visually confirm customer information, and include smart glasses and tablets.

[0500] This invention is a system implemented using a user information processing device, a server, and a visual assistance device. The system is configured as follows:

[0501] First, the user's information processing device plays the role of collecting informational data such as photos, videos, calendar information, and activity logs. This data is fundamental information for recording the user's daily activities and interests.

[0502] Next, the server receives and analyzes the information data sent from the user's information processing device. Specifically, the server uses advanced natural language processing techniques to integrate the information data as a chronological activity history. This analysis utilizes natural language processing engines such as the Google Cloud Natural Language API.

[0503] The analyzed activity history is generated as a narrative in natural language and presented in a user-friendly format. Users can add comments and feedback to this narrative, which are then used to further refine the activity history.

[0504] Furthermore, the server displays portions of the generated story on the store clerk's visual assistance device. This device (e.g., smart glasses) provides the clerk with information about the customer's interests, enabling them to make optimal product recommendations in real time.

[0505] As a concrete example, consider a scenario where a store employee wears smart glasses while patrolling the store. Based on data collected by in-store sensors and cameras, a server analyzes and notifies the employee of information about products the customer has shown interest in. For example, a message such as, "This customer is interested in running shoes. Please suggest some new products," might be displayed on the glasses.

[0506] An example of a prompt for a generative AI model is: "Based on historical data and behavioral analysis of the products this customer is most interested in, generate a product description that is best suited to this customer." This allows store employees to provide even more personalized service to customers.

[0507] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0508] Step 1:

[0509] The user's information processing device collects information data such as photos, videos, calendar information, and activity logs. At this stage, the information data is entered, and the user's daily activities are recorded chronologically. The collected data is then sent to the server.

[0510] Step 2:

[0511] The server receives information data transmitted from the user's information processing device. The input here consists of various digital data from the user, which the server receives for analysis. The server then integrates and organizes this data to generate a chronological activity history. Metadata such as photo timestamps and location information is utilized during this process.

[0512] Step 3:

[0513] The server generates a story in natural language based on the integrated activity history. In this step, natural language processing techniques are applied to the integrated data as input. The generated story is output in a human-readable format for the user. The text is generated using tools such as the Google Cloud Natural Language API.

[0514] Step 4:

[0515] The server extracts customer interest information from the generated stories and sends it to the store clerk's visual assistance device. Here, information about a specific customer's interests is the input, and the data is converted into an appropriate format for display on the visual assistance device. The output information is presented to the store clerk in real time.

[0516] Step 5:

[0517] Users enter comments and feedback on the provided stories and send them to the server. This input constitutes user feedback, which the server receives. This information is used to improve future activity history and story adjustments. User feedback contributes to improving the system's accuracy.

[0518] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0519] This invention provides a journal generation system that takes into account the user's emotional state, thereby enabling the addition of emotional insights to daily activity records. In addition to collecting, analyzing, and integrating digital information, the system has the function of analyzing the user's emotional responses using an emotion engine.

[0520] Server roles and functions

[0521] The server analyzes photos, videos, activity logs, and calendar information collected from the user's device and uses an emotion engine to evaluate the user's emotions. The emotion engine extracts emotions from the context and text within the collected digital information and quantifies or qualitatively evaluates how the user felt. Based on this information, the server integrates time-series activity records and emotion data to generate a narrative.

[0522] Terminal roles and functions

[0523] The device displays a journal that includes sentiment analysis sent from the server. The displayed narrative reflects the emotional tone, allowing the user to reflect on their own feelings about past events. Users can also add feedback and new sentiment information, and this data will be used to generate the next journal.

[0524] User interaction and experience

[0525] The invention allows users to reflect on their emotions along with recording their daily lives. For example, if a user spends time with friends over the weekend, the joy and happiness they felt at that time are recognized by the emotion engine and reflected in the narrative. Later, the user can recall the event along with the emotions they felt at the time through this journal.

[0526] For example, if the surprise or satisfaction a user felt during their trip is detected from photos and activity logs, the server generates emotional narratives such as "a wonderful adventure" or "an unexpected encounter" based on those emotions. This allows users to digitally recreate deeper, emotion-based experiences that go beyond mere records of events.

[0527] The system realized by this invention enriches the user experience and enables further personalization through emotion recognition. In this way, users can record their daily lives in a more meaningful way and have more fulfilling recollections on an emotional level.

[0528] The following describes the processing flow.

[0529] Step 1:

[0530] The server periodically sends requests to collect digital information from the user's electronic device. This includes photos, videos, activity logs, and calendar information.

[0531] Step 2:

[0532] The terminal retrieves the specified digital information from local storage and sends it to the server. During this process, a prompt will appear to obtain permission from the user if necessary.

[0533] Step 3:

[0534] The server analyzes the received digital information. It extracts date, time, and location information from the metadata of photos and videos, and integrates activity records using activity logs and calendar information.

[0535] Step 4:

[0536] The server uses an emotion engine to analyze the user's emotional state from text and images within digital information. The emotion engine utilizes natural language processing and image analysis to quantify the user's emotional responses.

[0537] Step 5:

[0538] The server generates natural language narratives based on analyzed sentiment data and integrated activity records. During generation, it reflects the sentiment data and constructs the text in a tone that matches the user's experience.

[0539] Step 6:

[0540] The server considers the user's past activity history and emotional tendencies to individually personalize the generated narrative. This adjustment also utilizes previous feedback.

[0541] Step 7:

[0542] The server sends the final narrative to the user's terminal. The terminal displays this journal in a user-friendly interface.

[0543] Step 8:

[0544] Users can view the narrative generated on their device and add comments and sentimental feedback as needed. This feedback is then sent back to the server and used for future analysis and content generation.

[0545] (Example 2)

[0546] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] When recording users' daily activities, there is a need to go beyond a mere list of facts and provide deeper insights that reflect the user's own emotions. Traditional recording methods have made it difficult to consider users' emotions, making meaningful reflection difficult for users. Therefore, the challenge is to provide a richer experience by analyzing users' emotions and adding emotional insights to activity records.

[0548] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0549] In this invention, the server includes means for collecting electronic information from the user's information processing device, means for analyzing the collected electronic information and using natural language processing technology to evaluate emotions, and means for integrating the evaluated emotion information and activity records in chronological order and generating text in natural language using generative AI technology. This adds emotional insight to the user's activity records, enabling more meaningful reflection for the user.

[0550] An "information processing device" is an electronic device used by users on a daily basis, which collects and displays digital information.

[0551] "Electronic information" refers to all data that represents a user's activities and status in digital format, such as photographs, videos, activity logs, and calendar information.

[0552] "Evaluating emotions" means analyzing a user's emotional state from collected digital information and understanding it either numerically or qualitatively.

[0553] "Natural language processing technology" refers to computational methods for understanding the meaning of information through the analysis of text data and for extracting useful information from that data.

[0554] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate text and other content, and is used to generate text based on the user's emotional state and behavioral logs.

[0555] "Integrating chronologically" is the process of organizing user activity and emotional data in chronological order and combining related information.

[0556] "Natural language text" refers to text expressed in a language format that humans normally use, and is intended to provide information in a way that is easy for users to understand.

[0557] In this invention, users record electronic information using an information processing device on a daily basis. This information processing device refers to, for example, a mobile device such as a smartphone or tablet, which has the function of accumulating daily data such as photos, videos, activity logs, and calendar information. This digital information is transmitted to a server via a wireless network.

[0558] The server is equipped with a large-capacity storage system for receiving and storing large amounts of digital information. The server uses natural language processing technology to analyze the received data. Specifically, this technology is used to analyze collected text and audio data, extracting keywords from them to evaluate the user's emotional state.

[0559] The emotion engine operates based on a generative AI model, integrating emotional information evaluated from analyzed data with activity logs in a time-series manner. This AI model has the ability to determine emotions from text data, qualitatively or numerically evaluate the user's emotions, and utilizes the resulting emotion score to enable narrative generation.

[0560] The terminal displays a generated narrative retrieved from the server to the user. The user reviews the displayed narrative and reflects on their emotions regarding past events. Furthermore, feedback and additional information from the user are collected and incorporated into the next journal generation. The user interface is intuitive and designed to allow users to easily add emotional information.

[0561] For example, when a user uploads photos from their trip, the server detects feelings of surprise and satisfaction from those photos. A generative AI model then generates a narrative of "a wonderful adventure" based on these emotions and displays it on the user's device. This allows users to not only record their trip but also relive the emotions they felt at the time, enabling a deeper reflection.

[0562] An example of a prompt statement can be written as follows:

[0563] "If a user provides a log of their activities over the past week, how can we extract the key events and associated sentiments from that data?"

[0564] "Identify the emotions experienced during a trip from travel photos uploaded by the user, and generate a narrative based on those emotions."

[0565] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0566] Step 1:

[0567] Users use an information processing device to record their daily activities as photos, videos, activity logs, and calendar information. The input is this electronic information, and the output is data ready to be sent from the terminal to the server. This involves data format conversion and necessary tagging.

[0568] Step 2:

[0569] The device periodically transmits digital information to the server. The input is electronic information stored on the user's device, and the output is information transferred to the server. Transmission occurs automatically via Wi-Fi or a mobile network.

[0570] Step 3:

[0571] The server stores the received electronic information and begins analysis using natural language processing techniques. The input is the transmitted electronic information, and the output is data representing emotion scores and emotional states. The server applies pattern recognition to extract keywords from text and audio and evaluate emotions.

[0572] Step 4:

[0573] The server uses a generative AI model to integrate analyzed sentiment data with chronologically organized activity logs. The input consists of sentiment scores and activity logs, while the output is a narrative containing emotional insights. The generative AI model generates text based on the extracted sentiments to form the narrative.

[0574] Step 5:

[0575] The terminal displays narratives sent from the server on the user interface. The input is the narrative received from the server, and the output is information visually presented on the terminal. The user can view this and reflect on past emotions.

[0576] Step 6:

[0577] Users input feedback and additional sentiment information about the narrative on their device. The input consists of user feedback and additional information, while the output is data that will be reflected in the next journal generation. This allows for a more personalized generation process.

[0578] (Application Example 2)

[0579] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0580] In today's world, users are exposed to a vast amount of content daily, yet there is a lack of effective means to properly record and reflect on their viewing experiences. Traditional recording methods only provide a basic viewing history, making it difficult to reflect on emotional responses and the feelings experienced during viewing. Therefore, a system is needed that provides emotional insights based on viewing experiences, enabling users to engage in more profound reflection.

[0581] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0582] In this invention, the server includes means for collecting data from the user's information processing device, means for analyzing the collected data and generating chronologically recorded information, and means for evaluating emotional responses and generating a narrative based on them. This makes it possible to review emotional insights obtained from the user's viewing experience as a narrative.

[0583] An "information processing device" is an electronic device used to collect and analyze user data and provide information based on that data.

[0584] "Data" refers to a collection of user-related information, including visual and auditory information.

[0585] "Recorded information" refers to information that is structured by arranging collected data chronologically.

[0586] A "story" is a narrative in natural language generated based on data and emotional responses.

[0587] "Emotional response" refers to data that indicates the user's emotional state, analyzed from the user's visual and auditory information.

[0588] "Visual information" refers to visual data such as images and videos.

[0589] "Audio information" refers to data collected from audio and is the subject of analysis.

[0590] The system implementing this invention operates primarily through the collaboration of a server, an information processing terminal, and a user. The server is responsible for collecting data transmitted from the user and performing analysis and integration based on that data. Specifically, the server is equipped with the latest data analysis technology and uses NVIDIA's CUDA to quickly and efficiently evaluate emotional responses from image and audio data.

[0591] The analyzed data is processed on a large scale using Apache Hadoop to generate a time-series record that takes into account the context of viewing and experience. This record is structured to gain deep insights into the viewing experience. For specific narrative generation, OpenAI's GPT model is used, and a personalized natural language story is automatically generated based on the evaluated emotional responses.

[0592] The device acts as an interface that delivers these stories to the user. The generated narratives are sent to the device, and the user can provide feedback with emotional insights based on their viewing experience.

[0593] For example, based on the surprise and emotion a user felt while watching a movie on their day off, the server generates a narrative such as "A holiday spent overwhelmed by a magnificent story." This process is instructed to the model in the form of a prompt message such as, "The content the user watched was a movie, and the main emotions were surprise and emotion. Please generate a narrative of the viewing experience based on these emotions."

[0594] In this way, it becomes possible to reflect on the viewing experience with emotional insights, allowing users to have a richer experience.

[0595] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0596] Step 1:

[0597] The server receives visual and audio information as data from the user's information processing terminal. This data includes information about the content the user has viewed. The server receives this data as input and prepares it for analysis.

[0598] Step 2:

[0599] The server uses NVIDIA's CUDA to analyze emotional responses to the received visual and auditory information. This analysis involves image processing and audio analysis to quantify specific emotional states (e.g., surprise, emotion). The output of this step is the evaluation result of the emotional state.

[0600] Step 3:

[0601] The server uses Apache Hadoop to perform large-scale data processing and integrate analysis results and viewing data. In particular, each emotional state is arranged as time-series data and associated with background information of the viewing experience. This process generates time-series recorded information.

[0602] Step 4:

[0603] The server uses OpenAI's generative AI model, GPT, to automatically generate narratives based on the generated time-series recording information. This model converts emotion evaluation results and viewing information into narratives based on prompt text. The output is a natural language story that includes emotional elements.

[0604] Step 5:

[0605] The server sends the generated narrative to the user's device. The device receives this and functions as an interface to visually present it to the user. The user can use this narrative to emotionally reflect on their viewing experience.

[0606] Step 6:

[0607] Users send feedback on the narrative to the server via their device. The server collects this feedback as new input data and uses it to improve the next analysis and narrative generation process. This improves the overall accuracy and personalization of the system.

[0608] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0609] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0610] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0611] [Fourth Embodiment]

[0612] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0613] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0614] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0615] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0616] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0617] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0618] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0619] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0620] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0621] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0622] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0623] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0624] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0625] This invention provides a system that effectively records and facilitates the review of users' daily and work activities. The system analyzes digital information collected from the user's electronic device and generates a highly personalized journal. This allows users to eliminate manual record-keeping and improve the quality of activity statistics and reviews.

[0626] Server roles and functions

[0627] The server, as the core of the system, manages and processes digital information. First, the server acquires digital information such as photos, videos, calendars, and activity logs from the user's terminal. The acquired information is analyzed within the server, and an activity timeline is generated based on location and time information. Furthermore, natural language processing technology is used to convert the timeline into a human-readable narrative. This allows the server to provide information to the user in an easy-to-use format.

[0628] Terminal roles and functions

[0629] The user's device displays information provided by the server, allowing the user to review and edit their activities. The device receives journal entries from the server and displays them on the screen in a visualized format. This allows users to easily access data as a diary or daily work report. In addition, it includes a function for users to add comments and supplementary information, which can then be sent back to the server as feedback.

[0630] User interaction and experience

[0631] Users can use the system simply by setting it up and allowing the collection of digital information to the extent necessary. No special operation is required, as the system automatically records activities and events that the user wishes to document. The activity logs and narratives provided by the system are based on the user's past data, making them tailored to individual experiences. For example, if travel photos are registered as data, the server will construct context from the location and time the photos were taken and automatically generate a travelogue.

[0632] As a concrete example, consider a user who goes mountain climbing on a holiday. If the user takes photos and collects activity logs, the server analyzes this data and generates a diary that includes details such as the time it took to reach the summit and the route taken. The photos taken are also used as part of the narrative, providing a visual story of the activity. Later, the user can refer to this digital diary to vividly recall the memories of the day and use that information to plan their next trip.

[0633] Thus, the present invention provides an efficient and high-quality journal, enabling users to record their daily lives while saving them time and effort.

[0634] The following describes the processing flow.

[0635] Step 1:

[0636] The server sends a data collection request to the user's device. At this time, the user specifies the type of digital information to be collected, such as photos, videos, activity logs, and calendar information.

[0637] Step 2:

[0638] The device retrieves the specified digital information from a local database and sends the collected data to the server. This process may include location information and social media information.

[0639] Step 3:

[0640] The server analyzes the received digital information. First, it extracts metadata to obtain the date and time of shooting and location information, and then compares it with activity logs and calendar information to determine the relationships between them.

[0641] Step 4:

[0642] The server generates a timeline of activities in chronological order from the analyzed data. This generated timeline serves as the foundation for organizing the user's activities as a series of stories.

[0643] Step 5:

[0644] The server utilizes AI to construct narratives based on timelines. It uses natural language processing technology to generate text that is easy for users to understand.

[0645] Step 6:

[0646] The server personalizes the generated narrative based on the user's past records and preferences. It selects and highlights important events, completing the content with individual adjustments.

[0647] Step 7:

[0648] The server sends the completed narrative to the user's device. The device receives this data and displays it in its viewing interface.

[0649] Step 8:

[0650] Users view the narrative on their devices and add comments and notes as needed. This feedback information is sent to the server and used for subsequent analytics and content improvement.

[0651] (Example 1)

[0652] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] In today's world, information about daily activities and work is increasingly digitized, and data is generated from diverse sources. In this environment, people may face decreased productivity and loss of important information due to overlooked or misinterpreted records. To solve this, a system is needed that automatically generates accurate and personalized activity records with minimal effort and provides them in an easy-to-understand format.

[0654] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0655] In this invention, the server includes means for collecting information from the user's information processing device, means for analyzing and integrating the collected information to generate a time-series activity record, and means for generating natural language text from the integrated activity record. This enables the user to efficiently review their activities and make decisions based on the necessary information.

[0656] A "user" refers to a person or organization that uses this system to generate activity records.

[0657] An "information processing device" refers to an electronic device owned or used by a user that has the function of collecting and transmitting digital information.

[0658] "Information" refers to digital data related to user activities, including photos, videos, calendar events, and activity logs.

[0659] A "server" refers to a computer system that receives and analyzes information, and generates and transmits activity records and documents.

[0660] "Activity log" refers to data that summarizes a user's actions and events over a certain period of time in chronological order.

[0661] "Natural language" refers to texts written in the language that humans use on a daily basis.

[0662] "Generating text" means creating a narrative written in natural language from the information received.

[0663] A "generative AI model" refers to an artificial intelligence model trained using machine learning, which analyzes data and generates output suitable for the user.

[0664] This invention supports the automatic recording and review of user activities through a system including a user information processing device and a server. Specifically, the information processing device is an electronic device owned by the user, such as a smartphone or tablet, and these devices first collect various digital information such as photos, videos, calendar information, and activity logs. The information processing device temporarily stores this data and transmits it to the server in a secure manner.

[0665] The server analyzes the received digital information and uses location and time data to generate a timeline of activities. This uses a general database management system and a generative AI model for natural language processing. The generative AI model is equipped with natural language processing technology such as that provided by OpenAI, and is capable of generating a human-readable narrative from activity records.

[0666] The generated narrative is optimized for each individual user and sent to the information processing device. The information processing device visually displays this narrative, allowing users to easily review their activities. For example, if a user goes mountain climbing on a holiday, the server generates a timeline of the climb based on data such as photos, videos, and GPS logs, and displays it as a travelogue in natural language.

[0667] An example of a prompt would be: "Generate a digital diary about last weekend's mountain climbing. Include information about the climbing route and arrival time from photos and activity logs."

[0668] By building the system in this way, users can efficiently obtain high-quality activity records without requiring any special operations.

[0669] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0670] Step 1:

[0671] The device collects photos, videos, calendar information, and activity logs with the user's permission. This digital information is collected as input and temporarily stored on the device. Specific operations include using the device's camera app and location services to obtain necessary data.

[0672] Step 2:

[0673] The terminal transmits the collected digital information to the server using a secure communication method. The data stored in step 1 is used as input, and the data is sent to the server as output. Specifically, the HTTPS protocol is used for secure data transfer.

[0674] Step 3:

[0675] The server analyzes the received digital information and organizes the data based on time and location information. It receives data transmitted from terminals as input and generates an activity timeline as output. Specifically, it identifies the start and end times of events from location and time information and creates a logical timeline.

[0676] Step 4:

[0677] The server uses a generative AI model to convert the timeline into a natural language narrative. The input is the timeline generated in step 3, and the output is human-readable text. Specifically, the AI ​​model utilizes text generation prompts to describe the activities in easily understandable language.

[0678] Step 5:

[0679] The server sends the generated narrative to the terminal. The input is the narrative generated in step 4, and the output is the data sent to the terminal. Specifically, this involves delivering the narrative data to the user's terminal using a secure communication protocol.

[0680] Step 6:

[0681] The terminal visually displays the received narrative, allowing the user to review it. The input is the narrative received from the server, and the output is displayed on the user's screen. Specifically, the terminal's display interface visualizes the text, allowing the user to scroll and edit it.

[0682] Step 7:

[0683] Users can add comments and supplementary information to the displayed narrative. Input includes user feedback and additional information, which is saved on the device as output. Specifically, this involves users adding information via text or voice to input fields on the device.

[0684] Step 8:

[0685] The terminal sends additional information from the user to the server as feedback. The input is the feedback information generated in step 7, and the output is data sent to the server. Specifically, the operation is to send the data back using the same protocol as the one used to send it earlier.

[0686] (Application Example 1)

[0687] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0688] In today's commercial environment, there is a demand for quick and individualized responses to diverse customer needs. However, it is difficult for store staff to manually understand customer interests and behavior and make appropriate product recommendations, hindering improvements in customer experience and optimization of sales opportunities. To solve this problem, there is a need for technology that automatically understands customer behavior and interests, enabling store staff to respond immediately.

[0689] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0690] In this invention, the server includes means for collecting information data from the user's information processing device, means for analyzing and integrating the collected information data to generate a time-series activity history, and means for displaying customer interest information on a store employee's visual support device. This enables store employees to grasp customer interests and behavior in the store in real time and quickly make optimal product suggestions.

[0691] A "user information processing device" is a device used by a user to collect, display, and edit data, and includes smartphones, tablets, and computers.

[0692] "Information data" refers to electronic data collected from user activities and environment, including photos, videos, calendar information, and activity logs.

[0693] "Activity history" is a record of a user's activities, constructed chronologically, and is generated by analyzing information data.

[0694] A "narrative in natural language" is a description in a user-friendly text format, generated based on the activity history analyzed by the system.

[0695] "Visual assistance devices" are devices used by store employees to visually confirm customer information, and include smart glasses and tablets.

[0696] This invention is a system implemented using a user information processing device, a server, and a visual assistance device. The system is configured as follows:

[0697] First, the user's information processing device plays the role of collecting informational data such as photos, videos, calendar information, and activity logs. This data is fundamental information for recording the user's daily activities and interests.

[0698] Next, the server receives and analyzes the information data sent from the user's information processing device. Specifically, the server uses advanced natural language processing techniques to integrate the information data as a chronological activity history. This analysis utilizes natural language processing engines such as the Google Cloud Natural Language API.

[0699] The analyzed activity history is generated as a narrative in natural language and presented in a user-friendly format. Users can add comments and feedback to this narrative, which are then used to further refine the activity history.

[0700] Furthermore, the server displays portions of the generated story on the store clerk's visual assistance device. This device (e.g., smart glasses) provides the clerk with information about the customer's interests, enabling them to make optimal product recommendations in real time.

[0701] As a concrete example, consider a scenario where a store employee wears smart glasses while patrolling the store. Based on data collected by in-store sensors and cameras, a server analyzes and notifies the employee of information about products the customer has shown interest in. For example, a message such as, "This customer is interested in running shoes. Please suggest some new products," might be displayed on the glasses.

[0702] An example of a prompt for a generative AI model is: "Based on historical data and behavioral analysis of the products this customer is most interested in, generate a product description that is best suited to this customer." This allows store employees to provide even more personalized service to customers.

[0703] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0704] Step 1:

[0705] The user's information processing device collects information data such as photos, videos, calendar information, and activity logs. At this stage, the information data is entered, and the user's daily activities are recorded chronologically. The collected data is then sent to the server.

[0706] Step 2:

[0707] The server receives information data transmitted from the user's information processing device. The input here consists of various digital data from the user, which the server receives for analysis. The server then integrates and organizes this data to generate a chronological activity history. Metadata such as photo timestamps and location information is utilized during this process.

[0708] Step 3:

[0709] The server generates a story in natural language based on the integrated activity history. In this step, natural language processing techniques are applied to the integrated data as input. The generated story is output in a human-readable format for the user. The text is generated using tools such as the Google Cloud Natural Language API.

[0710] Step 4:

[0711] The server extracts customer interest information from the generated stories and sends it to the store clerk's visual assistance device. Here, information about a specific customer's interests is the input, and the data is converted into an appropriate format for display on the visual assistance device. The output information is presented to the store clerk in real time.

[0712] Step 5:

[0713] Users enter comments and feedback on the provided stories and send them to the server. This input constitutes user feedback, which the server receives. This information is used to improve future activity history and story adjustments. User feedback contributes to improving the system's accuracy.

[0714] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0715] This invention provides a journal generation system that takes into account the user's emotional state, thereby enabling the addition of emotional insights to daily activity records. In addition to collecting, analyzing, and integrating digital information, the system has the function of analyzing the user's emotional responses using an emotion engine.

[0716] Server roles and functions

[0717] The server analyzes photos, videos, activity logs, and calendar information collected from the user's device and uses an emotion engine to evaluate the user's emotions. The emotion engine extracts emotions from the context and text within the collected digital information and quantifies or qualitatively evaluates how the user felt. Based on this information, the server integrates time-series activity records and emotion data to generate a narrative.

[0718] Terminal roles and functions

[0719] The device displays a journal that includes sentiment analysis sent from the server. The displayed narrative reflects the emotional tone, allowing the user to reflect on their own feelings about past events. Users can also add feedback and new sentiment information, and this data will be used to generate the next journal.

[0720] User interaction and experience

[0721] The invention allows users to reflect on their emotions along with recording their daily lives. For example, if a user spends time with friends over the weekend, the joy and happiness they felt at that time are recognized by the emotion engine and reflected in the narrative. Later, the user can recall the event along with the emotions they felt at the time through this journal.

[0722] For example, if the surprise or satisfaction a user felt during their trip is detected from photos and activity logs, the server generates emotional narratives such as "a wonderful adventure" or "an unexpected encounter" based on those emotions. This allows users to digitally recreate deeper, emotion-based experiences that go beyond mere records of events.

[0723] The system realized by this invention enriches the user experience and enables further personalization through emotion recognition. In this way, users can record their daily lives in a more meaningful way and have more fulfilling recollections on an emotional level.

[0724] The following describes the processing flow.

[0725] Step 1:

[0726] The server periodically sends requests to collect digital information from the user's electronic device. This includes photos, videos, activity logs, and calendar information.

[0727] Step 2:

[0728] The terminal retrieves the specified digital information from local storage and sends it to the server. During this process, a prompt will appear to obtain permission from the user if necessary.

[0729] Step 3:

[0730] The server analyzes the received digital information. It extracts date, time, and location information from the metadata of photos and videos, and integrates activity records using activity logs and calendar information.

[0731] Step 4:

[0732] The server uses an emotion engine to analyze the user's emotional state from text and images within digital information. The emotion engine utilizes natural language processing and image analysis to quantify the user's emotional responses.

[0733] Step 5:

[0734] The server generates natural language narratives based on analyzed sentiment data and integrated activity records. During generation, it reflects the sentiment data and constructs the text in a tone that matches the user's experience.

[0735] Step 6:

[0736] The server considers the user's past activity history and emotional tendencies to individually personalize the generated narrative. This adjustment also utilizes previous feedback.

[0737] Step 7:

[0738] The server sends the final narrative to the user's terminal. The terminal displays this journal in a user-friendly interface.

[0739] Step 8:

[0740] Users can view the narrative generated on their device and add comments and sentimental feedback as needed. This feedback is then sent back to the server and used for future analysis and content generation.

[0741] (Example 2)

[0742] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0743] When recording users' daily activities, there is a need to go beyond a mere list of facts and provide deeper insights that reflect the user's own emotions. Traditional recording methods have made it difficult to consider users' emotions, making meaningful reflection difficult for users. Therefore, the challenge is to provide a richer experience by analyzing users' emotions and adding emotional insights to activity records.

[0744] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0745] In this invention, the server includes means for collecting electronic information from the user's information processing device, means for analyzing the collected electronic information and using natural language processing technology to evaluate emotions, and means for integrating the evaluated emotion information and activity records in chronological order and generating text in natural language using generative AI technology. This adds emotional insight to the user's activity records, enabling more meaningful reflection for the user.

[0746] An "information processing device" is an electronic device used by users on a daily basis, which collects and displays digital information.

[0747] "Electronic information" refers to all data that represents a user's activities and status in digital format, such as photographs, videos, activity logs, and calendar information.

[0748] "Evaluating emotions" means analyzing a user's emotional state from collected digital information and understanding it either numerically or qualitatively.

[0749] "Natural language processing technology" refers to computational methods for understanding the meaning of information through the analysis of text data and for extracting useful information from that data.

[0750] "Generative AI technology" is a technology that uses artificial intelligence to automatically generate text and other content, and is used to generate text based on the user's emotional state and behavioral logs.

[0751] "Integrating chronologically" is the process of organizing user activity and emotional data in chronological order and combining related information.

[0752] "Natural language text" refers to text expressed in a language format that humans normally use, and is intended to provide information in a way that is easy for users to understand.

[0753] In this invention, users record electronic information using an information processing device on a daily basis. This information processing device refers to, for example, a mobile device such as a smartphone or tablet, which has the function of accumulating daily data such as photos, videos, activity logs, and calendar information. This digital information is transmitted to a server via a wireless network.

[0754] The server is equipped with a large-capacity storage system for receiving and storing large amounts of digital information. The server uses natural language processing technology to analyze the received data. Specifically, this technology is used to analyze collected text and audio data, extracting keywords from them to evaluate the user's emotional state.

[0755] The emotion engine operates based on a generative AI model, integrating emotional information evaluated from analyzed data with activity logs in a time-series manner. This AI model has the ability to determine emotions from text data, qualitatively or numerically evaluate the user's emotions, and utilizes the resulting emotion score to enable narrative generation.

[0756] The terminal displays a generated narrative retrieved from the server to the user. The user reviews the displayed narrative and reflects on their emotions regarding past events. Furthermore, feedback and additional information from the user are collected and incorporated into the next journal generation. The user interface is intuitive and designed to allow users to easily add emotional information.

[0757] For example, when a user uploads photos from their trip, the server detects feelings of surprise and satisfaction from those photos. A generative AI model then generates a narrative of "a wonderful adventure" based on these emotions and displays it on the user's device. This allows users to not only record their trip but also relive the emotions they felt at the time, enabling a deeper reflection.

[0758] An example of a prompt statement can be written as follows:

[0759] "If a user provides a log of their activities over the past week, how can we extract the key events and associated sentiments from that data?"

[0760] "Identify the emotions experienced during a trip from travel photos uploaded by the user, and generate a narrative based on those emotions."

[0761] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0762] Step 1:

[0763] Users use an information processing device to record their daily activities as photos, videos, activity logs, and calendar information. The input is this electronic information, and the output is data ready to be sent from the terminal to the server. This involves data format conversion and necessary tagging.

[0764] Step 2:

[0765] The device periodically transmits digital information to the server. The input is electronic information stored on the user's device, and the output is information transferred to the server. Transmission occurs automatically via Wi-Fi or a mobile network.

[0766] Step 3:

[0767] The server stores the received electronic information and begins analysis using natural language processing techniques. The input is the transmitted electronic information, and the output is data representing emotion scores and emotional states. The server applies pattern recognition to extract keywords from text and audio and evaluate emotions.

[0768] Step 4:

[0769] The server uses a generative AI model to integrate analyzed sentiment data with chronologically organized activity logs. The input consists of sentiment scores and activity logs, while the output is a narrative containing emotional insights. The generative AI model generates text based on the extracted sentiments to form the narrative.

[0770] Step 5:

[0771] The terminal displays narratives sent from the server on the user interface. The input is the narrative received from the server, and the output is information visually presented on the terminal. The user can view this and reflect on past emotions.

[0772] Step 6:

[0773] Users input feedback and additional sentiment information about the narrative on their device. The input consists of user feedback and additional information, while the output is data that will be reflected in the next journal generation. This allows for a more personalized generation process.

[0774] (Application Example 2)

[0775] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0776] In today's world, users are exposed to a vast amount of content daily, yet there is a lack of effective means to properly record and reflect on their viewing experiences. Traditional recording methods only provide a basic viewing history, making it difficult to reflect on emotional responses and the feelings experienced during viewing. Therefore, a system is needed that provides emotional insights based on viewing experiences, enabling users to engage in more profound reflection.

[0777] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0778] In this invention, the server includes means for collecting data from the user's information processing device, means for analyzing the collected data and generating chronologically recorded information, and means for evaluating emotional responses and generating a narrative based on them. This makes it possible to review emotional insights obtained from the user's viewing experience as a narrative.

[0779] An "information processing device" is an electronic device used to collect and analyze user data and provide information based on that data.

[0780] "Data" refers to a collection of user-related information, including visual and auditory information.

[0781] "Recorded information" refers to information that is structured by arranging collected data chronologically.

[0782] A "story" is a narrative in natural language generated based on data and emotional responses.

[0783] "Emotional response" refers to data that indicates the user's emotional state, analyzed from the user's visual and auditory information.

[0784] "Visual information" refers to visual data such as images and videos.

[0785] "Audio information" refers to data collected from audio and is the subject of analysis.

[0786] The system implementing this invention operates primarily through the collaboration of a server, an information processing terminal, and a user. The server is responsible for collecting data transmitted from the user and performing analysis and integration based on that data. Specifically, the server is equipped with the latest data analysis technology and uses NVIDIA's CUDA to quickly and efficiently evaluate emotional responses from image and audio data.

[0787] The analyzed data is processed on a large scale using Apache Hadoop to generate a time-series record that takes into account the context of viewing and experience. This record is structured to gain deep insights into the viewing experience. For specific narrative generation, OpenAI's GPT model is used, and a personalized natural language story is automatically generated based on the evaluated emotional responses.

[0788] The device acts as an interface that delivers these stories to the user. The generated narratives are sent to the device, and the user can provide feedback with emotional insights based on their viewing experience.

[0789] For example, based on the surprise and emotion a user felt while watching a movie on their day off, the server generates a narrative such as "A holiday spent overwhelmed by a magnificent story." This process is instructed to the model in the form of a prompt message such as, "The content the user watched was a movie, and the main emotions were surprise and emotion. Please generate a narrative of the viewing experience based on these emotions."

[0790] In this way, it becomes possible to reflect on the viewing experience with emotional insights, allowing users to have a richer experience.

[0791] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0792] Step 1:

[0793] The server receives visual and audio information as data from the user's information processing terminal. This data includes information about the content the user has viewed. The server receives this data as input and prepares it for analysis.

[0794] Step 2:

[0795] The server uses NVIDIA's CUDA to analyze emotional responses to the received visual and auditory information. This analysis involves image processing and audio analysis to quantify specific emotional states (e.g., surprise, emotion). The output of this step is the evaluation result of the emotional state.

[0796] Step 3:

[0797] The server uses Apache Hadoop to perform large-scale data processing and integrate analysis results and viewing data. In particular, each emotional state is arranged as time-series data and associated with background information of the viewing experience. This process generates time-series recorded information.

[0798] Step 4:

[0799] The server uses OpenAI's generative AI model, GPT, to automatically generate narratives based on the generated time-series recording information. This model converts emotion evaluation results and viewing information into narratives based on prompt text. The output is a natural language story that includes emotional elements.

[0800] Step 5:

[0801] The server sends the generated narrative to the user's device. The device receives this and functions as an interface to visually present it to the user. The user can use this narrative to emotionally reflect on their viewing experience.

[0802] Step 6:

[0803] Users send feedback on the narrative to the server via their device. The server collects this feedback as new input data and uses it to improve the next analysis and narrative generation process. This improves the overall accuracy and personalization of the system.

[0804] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0805] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0806] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0807] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0808] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0809] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0810] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0811] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0812] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0813] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0814] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0815] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0816] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0817] 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.

[0818] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0819] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0820] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0821] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0822] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0823] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0824] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0825] The following is further disclosed regarding the embodiments described above.

[0826] (Claim 1)

[0827] Means for collecting digital information from users' electronic devices,

[0828] A means for analyzing and integrating collected digital information to generate a chronological record of activities,

[0829] A means of generating a natural language narrative from an integrated activity log,

[0830] A means of individually adjusting the narrative based on the user's past activity record,

[0831] A means for transmitting the adjusted narrative to the user's electronic device,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which analyzes user activity logs and location information and utilizes them to generate activity records.

[0835] (Claim 3)

[0836] The system according to claim 1, which collects user feedback and incorporates it into adjusting activity records or narratives.

[0837] "Example 1"

[0838] (Claim 1)

[0839] Means for collecting information from a user's information processing device,

[0840] A means for analyzing and integrating collected information to generate a time-series activity record,

[0841] A means of generating natural language text from integrated activity records,

[0842] A means of individually adjusting text based on the user's past activity record,

[0843] A means for transmitting the adjusted text to the user's information processing device,

[0844] A means of collecting information added by the user to the text displayed on the user's information processing device and sending it back to the server,

[0845] Means for adjusting the aforementioned activities and texts using a generative AI model,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, which analyzes the user's behavior history and location information and utilizes it to generate activity records.

[0849] (Claim 3)

[0850] The system according to claim 1, which collects user feedback and reflects it in adjusting activity records or text.

[0851] "Application Example 1"

[0852] (Claim 1)

[0853] A means for collecting information data from a user's information processing device,

[0854] A means for analyzing and integrating collected information data to generate a time-series activity history,

[0855] A means of generating a natural language narrative from an integrated activity history,

[0856] A means of individually tailoring the story based on the user's past activity history,

[0857] A means for transmitting the adjusted story to the user's information processing device,

[0858] A means of displaying customer interest information on a visual assistance device for store employees,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, which analyzes information from environmental sensors and utilizes it to generate an activity history.

[0862] (Claim 3)

[0863] The system according to claim 1, which collects feedback information from users or the environment and reflects it in adjusting the activity history or narrative.

[0864] "Example 2 of combining an emotion engine"

[0865] (Claim 1)

[0866] Means for collecting electronic information from a user's information processing device,

[0867] A means of analyzing collected electronic information and using natural language processing techniques to evaluate emotions,

[0868] A means of integrating evaluated emotional information and activity records in chronological order and generating natural language text using generative AI technology,

[0869] A means of reflecting emotional insights based on the generated text and individually adjusting it in relation to the user's past activities,

[0870] A means for displaying the adjusted text on the user's information processing device,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, which analyzes the user's behavior history and location data and utilizes it to generate emotion evaluations and activity records.

[0874] (Claim 3)

[0875] The system according to claim 1, which collects user feedback and reflects it in adjusting the generated activity log or text.

[0876] "Application example 2 when combining with an emotional engine"

[0877] (Claim 1)

[0878] A means of collecting data from a user's information processing device,

[0879] A means for analyzing and integrating collected data to generate time-series record information,

[0880] A means of generating a story in natural language from integrated recorded information,

[0881] A means of individually adjusting the story based on the user's past recorded information,

[0882] A means of analyzing visual information, including images and sounds, and evaluating emotional responses,

[0883] A means of reinforcing the narrative as an emotional element based on evaluated emotional responses,

[0884] A means for transmitting the adjusted story to the user's information processing device,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, which analyzes the user's behavior history and location information and utilizes it to generate recorded information.

[0888] (Claim 3)

[0889] The system according to claim 1, which collects user response information and reflects it in adjusting recorded information or a narrative. [Explanation of symbols]

[0890] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for collecting digital information from users' electronic devices, A means for analyzing and integrating collected digital information to generate a chronological record of activities, A means of generating a natural language narrative from an integrated activity log, A means of individually adjusting the narrative based on the user's past activity record, A means for transmitting the adjusted narrative to the user's electronic device, A system that includes this.

2. The system according to claim 1, which analyzes user activity logs and location information and utilizes them to generate activity records.

3. The system according to claim 1, which collects user feedback and reflects it in adjusting activity records or narratives.

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