system

Abstract

We provide the system. [Solution] A means of automatically acquiring multiple types of digital data from personal electronic devices, A means of analyzing acquired digital data to extract people, places, and emotions, A means to recognize related events based on the extracted information and tag the data, A means of generating personally viewable content using tagged data, A means of providing generated content to individuals and enabling them to re-experience it, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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 modern times, the digital data generated by individuals daily is enormous, and it is difficult to appropriately organize and manage them. Also, there is a problem that it is not sufficiently possible to relive special moments and share emotions due to time and technical constraints. In addition, there is a lack of a system for efficiently looking back on personal memories and experiences, and support by technical means is demanded.

Means for Solving the Problems

[0005] This invention provides a system that automatically acquires and analyzes digital data from personal electronic devices. It extracts information such as people, places, and emotions from the acquired data, recognizes related events, tags the data, and facilitates organization. Furthermore, it generates personalized content based on the tagged data and provides it to the user, enabling them to efficiently relive special moments. This system also includes the ability to display the generated content in a virtual reality or augmented reality environment, further enhancing the user experience.

[0006] "Electronic devices" are devices owned by individuals that enable the creation, storage, and communication of digital data, and include smartphones, tablets, PCs, etc.

[0007] "Digital data" refers to information created or stored on electronic devices, including in the form of photographs, videos, voice memos, and text messages.

[0008] "Analysis" refers to the process of analyzing digital data using computer programs to identify or extract elements (people, places, emotions).

[0009] "Extraction" is the act of identifying and removing specific information from analyzed digital data.

[0010] An "event" refers to a significant occurrence or activity at a specific date or time or period, and includes things like trips, birthdays, and anniversaries.

[0011] "Tagging" refers to the process of assigning relevant information or categories as labels to digital data.

[0012] "Generation" refers to the process of creating new content or products based on digital data.

[0013] "Content" refers to digital information provided in a format that users can view or experience.

[0014] "Virtual reality" refers to a technology that uses digital technology to provide users with visual or sensory experiences different from the real world.

[0015] "Augmented reality" is a technology that superimposes digital information on the vision of the real world and is used for the purpose of improving the user's real-world experience.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in 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 the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory where information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention provides a system that effectively organizes personal experiences as digital data, allowing users to relive special moments. Specifically, the system starts operating via a dedicated application running on the user's personal electronic device. With the user's permission, this application collects digital data such as photos, videos, voice memos, text messages, and GPS information, and periodically uploads this data to a cloud server.

[0038] After receiving the uploaded data, the server performs analysis. This analysis uses image recognition technology to identify people and places from photos and videos, and sentiment analysis technology to extract the emotions contained within each piece of content. Each data item is tagged with relevant tags and classified as an event. For example, photos and videos related to travel are tagged with "travel," "tourist destination," and "family."

[0039] The server generates content using tagged data periodically or upon user request. The generated content takes the form of slideshows or storyboards, used to relive special moments in the user's life. The content may also include machine learning-generated voice narration and background music. Users can also experience this content through AR (augmented reality) and VR (virtual reality) devices for a more immersive re-experience.

[0040] For example, if a user wants to look back on their birthdays over several years, the device uploads relevant data from that period to a server, which then generates birthday-themed content based on that data. This content can include a dynamic slideshow based on past birthday photos and automatically generated narration, providing the user with a moving retrospective experience.

[0041] Thus, the present invention implements a system configuration that organically combines the roles of terminals, servers, and users in order to improve the management and experience of digital data.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The device launches applications on the user's electronic device and collects digital data such as photos, videos, voice memos, and GPS information in the background, to the extent permitted by the user. The frequency and timing of collection are adjusted based on network conditions and battery usage.

[0045] Step 2:

[0046] The device uploads the collected data to a cloud server. Encryption technology is applied to the upload to ensure data security and efficiency. The system is configured to transfer data only when communication conditions are optimal (e.g., when connected to Wi-Fi).

[0047] Step 3:

[0048] The server first saves the received data to storage. Next, it starts analyzing the data using machine learning algorithms, performing image recognition to identify people, places, and emotions during emergencies from photos and videos.

[0049] Step 4:

[0050] Based on the server's analysis, tags related to the data are assigned. These tags include extracted emotions and specific event information, and are used as foundational data for subsequent event recognition.

[0051] Step 5:

[0052] The server creates an event list using tagged data. Here, date and location information is integrated to recognize and classify specific past events (e.g., travel, birthdays).

[0053] Step 6:

[0054] The server generates content by combining tagged data based on user requests or a recurring schedule. This process is carried out using AI technology in the form of slideshows, videos, or content with audio.

[0055] Step 7:

[0056] Users view content provided from the server via a dedicated app and experience it through viewing or AR / VR devices. The generated content recreates special moments from the past, providing users with a new and moving experience.

[0057] (Example 1)

[0058] 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."

[0059] In today's world, many people generate a vast amount of digital data on a daily basis, but effectively organizing this information and making it meaningful for individuals to re-experience is challenging. Furthermore, extracting special moments from this massive amount of data and conducting emotionally-based evaluations is also difficult. Moreover, there is a need for means to experience generated content in a more immersive way.

[0060] 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.

[0061] In this invention, the server includes means for continuously collecting diverse information from an individual's information processing device, means for analyzing the collected information and extracting subjects, locations, and emotions, means for recognizing related events based on the extracted identification information and classifying the information by identifiers, and means for generating individual viewable information representations using the information classified by identifiers. This makes it possible to organize an individual's special moments and provide emotionally valuable re-experiences.

[0062] An "information processing device" is a machine or device used to process and manage digital data, and usually refers to a computer or smartphone.

[0063] "Information" refers to digital data generated by individuals, encompassing a wide range of data including photographs, videos, voice memos, text, and location information.

[0064] "Collection" refers to the act of gathering information for a specific purpose, and in this invention, it refers to the automatic or manual acquisition of personal digital data.

[0065] "Analysis" is the process of examining collected information in detail to reveal its meaning and characteristics, and includes identifying people and places and evaluating emotions.

[0066] "Subject" refers to an object that appears in a photograph or video, and in this invention, it is identified by image recognition technology.

[0067] "Location" refers to the geographical location to which the collected information is related, and is usually specified by GPS data.

[0068] "Emotion" refers to the emotional elements contained within information, including emotional states such as positive, negative, and neutral, which can be extracted from text or audio.

[0069] An "identifier" refers to a label or tag used to classify or organize information, and is assigned to information based on related events or themes.

[0070] "Information representation" refers to content generated based on collected and analyzed information, and specific examples include slideshows and storyboard-style materials.

[0071] "Re-experiencing" refers to reliving past experiences or events, and in this invention, it is achieved through the generated information representation.

[0072] This invention enables the continuous collection of diverse information using a personal information processing device, allowing for the effective organization and re-experience of special moments. Specifically, the device launches a dedicated application running on the personal information processing device and, with the user's consent, collects digital data such as photos, videos, voice memos, text messages, and GPS information. Portable information processing devices, such as smartphones, are primarily used.

[0073] The data collected by the device is encrypted before being transferred to the cloud server and securely uploaded using security protocols such as TLS. When the server analyzes the received data, it uses image recognition and natural language processing technologies to identify subjects and locations from photos and videos, and extract emotions from text messages. The analyzed data is automatically assigned identifiers and organized into related events.

[0074] The server generates viewable informational representations based on data classified by this identifier. These representations include slideshow-style videos and storyboard-style materials, to which automatically generated voice narration and background music are added using a generative AI model. This allows users to relive special moments in a more emotionally impactful way.

[0075] For example, if a user wants to look back on their birthday records over several years, the device uploads the relevant data to a server. Based on this, the server automatically generates content including a slideshow and narration based on past birthday photos, providing the user with a moving retrospective experience.

[0076] An example of a prompt using a generative AI model is, "Collect data related to a specific trip and create narrated VR content based on it." This allows the server to construct a specific scenario from the tagged data and provide the user with a unique experience.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The terminal launches a dedicated application. The user opens the application, logs in, and grants permission for data collection. This action causes the application to enter data collection mode. The input is the user's authentication information, and the output is the acquisition of user permission for data collection.

[0080] Step 2:

[0081] The device collects digital data from the user's electronic devices. This process involves recording photos, videos, and voice memos using cameras and microphones, and obtaining location data using GPS functionality. These data serve as inputs, and the output is a collection of diverse digital data.

[0082] Step 3:

[0083] The device encrypts the data it collects and uploads it to a cloud server. The data is securely transferred using security protocols such as TLS. The input is the collected raw data, and the output is the encrypted data stored on the server.

[0084] Step 4:

[0085] The server analyzes the data it receives. First, it uses image recognition technology to identify subjects and locations from photos and videos. It also uses natural language processing technology to extract emotions from text messages. The input is data stored on the server, and the output is the identified subjects, locations, emotions, and identifiers assigned based on them.

[0086] Step 5:

[0087] The server generates informational representations based on data classified by identifiers. This process uses a generative AI model to add voice narration and background music, creating content in slideshow or storyboard format. The input is the analyzed data, and the output is the completed informational representation content.

[0088] Step 6:

[0089] Users view generated information representations. Users can play content on their devices and further enhance their experience using AR / VR devices. The input is the generated information representation, and the output is the information experienced through the user's sight and hearing.

[0090] (Application Example 1)

[0091] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0092] People save many special moments in their daily lives as digital information, but they lacked a way to effectively organize and provide them in a format that allows them to relive those experiences at any time. In particular, there was a lack of systems that could visually recreate individual experiences and allow them to be experienced in an emotionally rich way.

[0093] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0094] In this invention, the server includes means for automatically collecting data from multiple digital information sources, means for analyzing the collected data to extract subjects, locations, and emotions, and means for displaying the generated visual information using a projection device. This allows users to effectively relive special moments from the past and engage in emotionally rich reflection in their daily lives.

[0095] "Digital information sources" refer to a variety of digital data generated from personal electronic devices and online platforms, such as photos, videos, voice memos, text messages, and GPS information.

[0096] "Collecting" refers to the process of automatically retrieving data from digital sources and consistently storing it using a dedicated system or application.

[0097] "Analyzing and extracting" means processing collected digital data and identifying and extracting specific information such as people, places, and emotions from it.

[0098] "Tagging" refers to the process of classifying extracted data into appropriate categories or themes and assigning identifiable information to them.

[0099] "Generating visual information" means using tagged data to create easy-to-understand slideshows or video content.

[0100] "Displaying using projection equipment" refers to a method of projecting generated visual information into a physical space via a projector or display system to make it visible.

[0101] This invention provides a system that effectively allows users to re-experience individual digital experiences. The system collects data from various digital sources, analyzes it to generate visual content, and presents it using a projection device. This allows users to immersively revisit special moments.

[0102] The system first collects digital information through the device with the user's permission. Specifically, it automatically acquires photos, videos, voice memos, text messages, and location information using smartphones, cameras, and GPS sensors. The collected data is uploaded to a cloud server.

[0103] The server analyzes the uploaded data. Using image recognition technology (e.g., OpenCV) and sentiment analysis engines (e.g., Azure Cognitive Services), it identifies subjects and locations from photos and videos and extracts emotions contained in the digital information. This allows for tagging based on people, places, and emotions, and classifying them as appropriate events.

[0104] Tagged information is compiled into visual content using a machine learning model. A slideshow video is generated using a video editing library (e.g., FFmpeg), and voice narration and background music are added. The generated content is then delivered to the user via projection equipment or a display system.

[0105] For example, when a user wants to relive travel memories, they can simply tell their device, "Show me photos from last summer's trip," and all photos, videos, and voice memos related to that period will be organized and displayed as an emotionally engaging slideshow. This allows the user to relive those moments with family and friends.

[0106] Examples of prompt messages are as follows:

[0107] "Please share your memories of my birthday in February 2019. Create a slideshow using relevant photos and videos. If possible, please include narration and background music that recreates the feelings I had at that time."

[0108] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0109] Step 1:

[0110] With the user's permission, the device automatically retrieves photos, videos, voice memos, text messages, and location information from digital sources using the smartphone, camera, and GPS sensor. This data is temporarily stored in local storage for analysis in later processes.

[0111] Step 2:

[0112] The terminal uploads the collected digital data to a cloud server. At this stage, the terminal standardizes the data format and adds metadata to enable efficient analysis on the server. The input is local digital data on the terminal, and the output is standardized format data uploaded to the cloud server.

[0113] Step 3:

[0114] The server receives uploaded data and analyzes it using image recognition technology (e.g., OpenCV) and sentiment analysis engine (e.g., Azure Cognitive Services). Input is digital data in a unified format, and output is extracted subject, location, and sentiment data. Specifically, it identifies people and locations from photographs and extracts sentiment from text messages and voice memos.

[0115] Step 4:

[0116] The server classifies the information based on the analysis results and assigns relevant tags to the data. The input is extracted data, and the output is tagged data. The tags classify the data based on themes such as "travel," "family," and "emotional experiences," organizing them as unified events.

[0117] Step 5:

[0118] The server uses tagged data and leverages a video editing library (e.g., FFmpeg) to generate slideshow-style visual content. The input is tagged data, and the output is visual content. The generated content includes voice narration and background music generated by a generative AI model.

[0119] Step 6:

[0120] The user requests the terminal to display a specific past moment using a prompt. In response to the request, the terminal displays the generated visual content via a projection device or display. The input consists of the user's prompt and the generated visual content; the output is the video displayed on the projection device.

[0121] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0122] This invention combines a system that organizes personal digital data and allows users to relive special moments with an emotion engine that recognizes the user's feelings. The terminal operates on the user's personal electronic devices and, with the user's permission, has the function of automatically acquiring various digital data (photos, videos, voice memos, text messages, GPS information).

[0123] This device uploads collected digital data to a cloud server. The server applies machine learning algorithms to the data, and an emotion engine is activated to analyze the emotions of people, places, and situations extracted from the data. The emotion engine identifies the user's emotions from images and audio and assigns emotion tags to the data based on the information.

[0124] Furthermore, the server recognizes relevant events based on the extracted information and generates personalized, viewable content based on tagged data. In this process, it can incorporate the user's emotional information recognized by the emotion engine, tailoring the viewing experience to be more emotionally engaging. The generated content is created and provided to the user in formats such as slideshows, videos, and audio presentations.

[0125] For example, if a user wants to relive memories of a past trip, the device uploads data acquired during that trip (photos, videos, GPS information related to the travel locations). The server uses an emotion engine to identify the user's emotions during the trip (joy, surprise, etc.) and assigns emotion tags to each data item based on that. Then, using the tagged data, the entire trip is recreated in a narrative format, generating content that resonates with the user's emotions.

[0126] Users can view content provided through a dedicated app and also have a more immersive experience through virtual reality (VR) and augmented reality (AR) devices. In this way, the present invention enhances the re-experience of personal special moments and provides a deeper emotional impact through a system configuration that takes user emotions into consideration.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The device launches a dedicated application on the user's personal electronic device and automatically acquires digital data with the user's permission. This includes photos, videos, voice memos, GPS information, etc. The device then prepares to upload the acquired data to a cloud server at defined intervals while maintaining security.

[0130] Step 2:

[0131] The server receives the digital data uploaded from the terminal, first checks the data format, and then saves it to storage in a standardized format.

[0132] Step 3:

[0133] An emotion engine on the server operates, performing image recognition on received photo and video data and analyzing the facial expressions of the people contained within. Furthermore, it analyzes the tone and speed of voices from audio data to identify emotions.

[0134] Step 4:

[0135] The server assigns appropriate emotion tags to the digital data based on the extracted emotion information. This allows the data to be classified according to the user's emotions.

[0136] Step 5:

[0137] The server uses tagged data to identify relevant and important events. Here, events are automatically categorized based on the duration of the trip or specific dates.

[0138] Step 6:

[0139] When the server generates content for the user based on classified data, it incorporates previously recognized emotional information into the presentation. This results in video content with music and narration that aligns with the user's emotions.

[0140] Step 7:

[0141] Users view the generated content through a dedicated app. Furthermore, by using VR and AR devices, they can enjoy a more immersive experience and interactively relive special moments from the past.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0144] In today's information society, individuals generate vast amounts of electronic data in their daily lives, making it difficult to organize and utilize this data. In particular, there is a growing demand to relive special moments and memories, but a lack of appropriate systems to meet this need. Therefore, there is a need for systems that can organize data while taking individual emotions into account, and that can provide emotionally resonant re-experiences.

[0145] 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.

[0146] In this invention, the server includes means for automatically collecting various electronic data from a personal terminal, means for analyzing the collected electronic data and extracting the subject, location, and emotion, and means for recognizing related events based on the extracted information and attaching emotion tags to the data. This makes it possible to re-experience a person's special moments while being emotionally connected to them.

[0147] A "personal device" is an electronic device used by an individual, and is a device used for data collection and information processing.

[0148] "Electronic data" refers to information stored in digital format, including photographs, videos, audio, text, and location information.

[0149] An "emotion tag" is an identification piece of information attached to electronic data that indicates the emotional state contained within the data.

[0150] "Experiential content" refers to content that allows users to gain emotional value through viewing or experiencing it, and includes slideshows and video presentations.

[0151] A "virtual image environment" is a technology that provides a realistic experience through computer-generated images and information.

[0152] An "augmented video environment" is a technology that overlays digital information onto real-world images, providing users with an enhanced experience of interacting with the real world.

[0153] This invention is a system that makes it possible to relive special personal moments, and it consists of the interaction between a server, a terminal, and the user.

[0154] First, the device is a personal electronic device (e.g., a smartphone or tablet) that, with the user's permission, automatically collects various types of electronic data, such as photos, videos, voice memos, texts, and location information. This data is managed while monitoring the device's storage usage to prevent excessive data usage.

[0155] The collected electronic data is uploaded from the terminal to the server via a secure network connection. The server receives the collected data and performs analysis using machine learning algorithms. This includes processes that use image recognition and speech recognition technologies to identify objects, locations, and emotions. This process can utilize AI technologies from common cloud service providers.

[0156] After data analysis, the server uses an emotion engine to assign emotion tags to the data. The emotion engine analyzes images and audio based on the emotional states extracted from the data. As a result, the data is organized using emotion tags.

[0157] The server then generates personalized, interactive content based on the tagged data. This content takes the form of slideshows, videos, and audio presentations, enhancing the user's emotional experience. Generative AI models are used to create prompts and express the user's past events in an emotionally resonant way.

[0158] For example, if a user wants to relive a past trip, the device collects photos, videos, and location information recorded during that trip and uploads them to a server. The server analyzes this data, uses an emotion engine to identify emotions such as "fun" and "surprise," and assigns emotion tags. Next, the tagged data is used to recreate the travel experience in narrative form, providing the user with an emotionally engaging viewing experience. Users can view the generated content through a dedicated application.

[0159] An example of a prompt message could be: "Recreate the user's past travel memories as an emotionally engaging, narrative-style slideshow using emotional data. Based on the user's emotional information, create a presentation that highlights enjoyable and surprising moments during their travels."

[0160] This system allows users to deeply relive special moments and have a moving experience.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The device collects various electronic data from personal electronic devices with the user's permission. This data includes photos, videos, voice memos, texts, and location information. This data is appropriately categorized into folders, and after checking the storage status, important data is selected and temporarily stored on the device.

[0164] Step 2:

[0165] The device uploads the collected electronic data to the server via a secure network connection. The input is temporarily stored electronic data, while the output is saved to a database on the server. The upload process starts automatically when Wi-Fi is available, but users can also start the upload manually.

[0166] Step 3:

[0167] The server analyzes the received electronic data and processes it using image recognition and speech recognition technologies. The input is electronic data stored on the server, and the output is subject, location information, and sentiment data extracted from the data. Specifically, cloud-based machine learning algorithms are used to analyze the data and extract information from images and audio.

[0168] Step 4:

[0169] The server uses an emotion engine to tag the data with emotion based on the analyzed information. The input is the extracted emotion data, and the output is the data with emotion tags. This adds emotion labels to the data, making subsequent processing easier.

[0170] Step 5:

[0171] The server uses tagged data to generate personalized, interactive content. Input is data containing emotion tags, and output is content in the form of slideshows or video presentations that resonate with the user's emotions. A generative AI model is used to create narrative-style content based on prompt text.

[0172] Step 6:

[0173] Users view experiential content generated through a dedicated application. The input is the generated content, and the output is the emotionally engaging viewing experience derived from the played content. In this step, users can relive special moments by viewing the output content.

[0174] (Application Example 2)

[0175] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0176] When individuals wish to relive special moments, it is necessary to properly organize the digital data and efficiently perform emotionally-driven visualizations. However, conventional technologies simply play back large amounts of digital data, which is insufficient to provide the emotional re-experience that users desire. Furthermore, there is a lack of home systems that allow users to freely and deeply relive past moments.

[0177] 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.

[0178] In this invention, the server includes means for automatically collecting various digital information from personal information devices, means for analyzing the collected digital information and extracting the subject, location, and emotion, and means for acquiring emotion-tagged data in response to voice commands and presenting the experience using visualization and audio technologies. This makes it possible for users to easily access special moments from the past via voice commands and enjoy visual and audio re-experiences based on emotions.

[0179] "Personal information devices" are electronic devices owned by individuals and used for collecting and managing digital information.

[0180] "Digital information" refers to data expressed in electronic form, including images, audio, and location information.

[0181] "Analysis" is the process of extracting meaningful information from collected digital data, and it is achieved using machine learning algorithms and emotion recognition technologies.

[0182] "Extracting subjects, locations, and emotions" means identifying and extracting location information of people, objects, and places, as well as the emotions associated with them, contained within digital information.

[0183] "Voice commands" refer to an input method that uses voice to transmit commands to information devices and cause them to perform specific operations.

[0184] "Emotionally tagged data" refers to data that has been tagged based on emotional information extracted from digital information.

[0185] "Visualization technology" refers to technologies that visually represent digital information and facilitate re-experience.

[0186] "Voice technology" refers to technologies that reproduce digital information as sound and enable voice-based interaction.

[0187] "Presenting an experience" is the process of enabling users to gain new experiences by viewing and listening to digital information.

[0188] In the system for implementing this invention, the user's information device plays a central role. This information device includes smartphones and home assistant devices, which automatically collect various digital information from the user's daily life. This information is diverse, including images, audio, and location information, and after collection, it is uploaded to a cloud server.

[0189] The server applies machine learning algorithms to this digital information and uses image analysis techniques to extract the subject, location, and emotion. For emotion recognition, libraries such as OpenCV can be used, and for speech processing, speech synthesis libraries such as pyttsx3 can be combined. Based on the extracted emotion information, emotion tags are assigned to the data, and relevant content is generated based on the specified identification information.

[0190] Users can access this content using voice commands. For example, by sending a voice command such as "Show me the smiling photos from last year's trip" to a home device, the necessary emotion-tagged data is retrieved from the server and projected onto the wall via visualization technology (e.g., a projector). Voice technology is also used to output personalized audio guides, enhancing the quality of the re-experience.

[0191] An example of a prompt message might be: "Create a slideshow of past travel photos tailored to the user based on sentiment tags, add relevant music and narration, and explain it clearly to the user." This allows the user to have a more personal and immersive experience.

[0192] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0193] Step 1:

[0194] The device automatically collects digital information such as images, audio, and GPS data generated in the user's daily life. The input is raw data stored on the device. The collected data is uploaded to a cloud server with the user's permission. The output is the digital information uploaded to the server.

[0195] Step 2:

[0196] The server receives uploaded digital information and performs image and audio analysis. The input is the collected digital information. Using libraries such as OpenCV, it detects people and objects from images and extracts the user's emotions from facial expressions and audio using emotion recognition algorithms. This process yields data with emotion tags as output.

[0197] Step 3:

[0198] The server recognizes relevant events based on extracted sentiment-tagged data and generates content tailored to user specifications. The input is sentiment-tagged data. Prompt text is input to the generating AI model, which creates slideshows and narrations related to the user's past special moments. This step outputs content for presentation to the user.

[0199] Step 4:

[0200] The user inputs voice commands into the terminal. These inputs are the user's voice data. The terminal analyzes these voice commands and sends a request for relevant content to the server. This process prepares the server to select and output the appropriate content.

[0201] Step 5:

[0202] The server retrieves content based on voice commands and sends it to the terminal. The input is the user's request data. The terminal uses the retrieved data and plays the content using visualization and audio technologies. The output of this step is the content presented visually and audibly on the user's device.

[0203] Through these steps, users can immersively relive special moments based on their emotions.

[0204] 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.

[0205] 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.

[0206] 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.

[0207] [Second Embodiment]

[0208] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0209] 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.

[0210] 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).

[0211] 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.

[0212] 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.

[0213] 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).

[0214] 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.

[0215] 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.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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".

[0220] This invention provides a system that effectively organizes personal experiences as digital data, allowing users to relive special moments. Specifically, the system starts operating via a dedicated application running on the user's personal electronic device. With the user's permission, this application collects digital data such as photos, videos, voice memos, text messages, and GPS information, and periodically uploads this data to a cloud server.

[0221] After receiving the uploaded data, the server performs analysis. This analysis uses image recognition technology to identify people and places from photos and videos, and sentiment analysis technology to extract the emotions contained within each piece of content. Each data item is tagged with relevant tags and classified as an event. For example, photos and videos related to travel are tagged with "travel," "tourist destination," and "family."

[0222] The server generates content using tagged data periodically or upon user request. The generated content takes the form of slideshows or storyboards, used to relive special moments in the user's life. The content may also include machine learning-generated voice narration and background music. Users can also experience this content through AR (augmented reality) and VR (virtual reality) devices for a more immersive re-experience.

[0223] For example, if a user wants to look back on their birthdays over several years, the device uploads relevant data from that period to a server, which then generates birthday-themed content based on that data. This content can include a dynamic slideshow based on past birthday photos and automatically generated narration, providing the user with a moving retrospective experience.

[0224] Thus, the present invention implements a system configuration that organically combines the roles of terminals, servers, and users in order to improve the management and experience of digital data.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] The device launches applications on the user's electronic device and collects digital data such as photos, videos, voice memos, and GPS information in the background, to the extent permitted by the user. The frequency and timing of collection are adjusted based on network conditions and battery usage.

[0228] Step 2:

[0229] The device uploads the collected data to a cloud server. Encryption technology is applied to the upload to ensure data security and efficiency. The system is configured to transfer data only when communication conditions are optimal (e.g., when connected to Wi-Fi).

[0230] Step 3:

[0231] The server first saves the received data to storage. Next, it starts analyzing the data using machine learning algorithms, performing image recognition to identify people, places, and emotions during emergencies from photos and videos.

[0232] Step 4:

[0233] Based on the server's analysis, tags related to the data are assigned. These tags include extracted emotions and specific event information, and are used as foundational data for subsequent event recognition.

[0234] Step 5:

[0235] The server creates an event list using tagged data. Here, date and location information is integrated to recognize and classify specific past events (e.g., travel, birthdays).

[0236] Step 6:

[0237] The server generates content by combining tagged data based on user requests or a recurring schedule. This process is carried out using AI technology in the form of slideshows, videos, or content with audio.

[0238] Step 7:

[0239] Users view content provided from the server via a dedicated app and experience it through viewing or AR / VR devices. The generated content recreates special moments from the past, providing users with a new and moving experience.

[0240] (Example 1)

[0241] 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."

[0242] In today's world, many people generate a vast amount of digital data on a daily basis, but effectively organizing this information and making it meaningful for individuals to re-experience is challenging. Furthermore, extracting special moments from this massive amount of data and conducting emotionally-based evaluations is also difficult. Moreover, there is a need for means to experience generated content in a more immersive way.

[0243] 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.

[0244] In this invention, the server includes means for continuously collecting diverse information from an individual's information processing device, means for analyzing the collected information and extracting subjects, locations, and emotions, means for recognizing related events based on the extracted identification information and classifying the information by identifiers, and means for generating individual viewable information representations using the information classified by identifiers. This makes it possible to organize an individual's special moments and provide emotionally valuable re-experiences.

[0245] An "information processing device" is a machine or device used to process and manage digital data, and usually refers to a computer or smartphone.

[0246] "Information" refers to digital data generated by individuals, encompassing a wide range of data including photographs, videos, voice memos, text, and location information.

[0247] "Collection" refers to the act of gathering information for a specific purpose, and in this invention, it refers to the automatic or manual acquisition of personal digital data.

[0248] "Analysis" is the process of examining collected information in detail to reveal its meaning and characteristics, and includes identifying people and places and evaluating emotions.

[0249] "Subject" refers to an object that appears in a photograph or video, and in this invention, it is identified by image recognition technology.

[0250] "Location" refers to the geographical location to which the collected information is related, and is usually specified by GPS data.

[0251] "Emotion" refers to the emotional elements contained within information, including emotional states such as positive, negative, and neutral, which can be extracted from text or audio.

[0252] An "identifier" refers to a label or tag used to classify or organize information, and is assigned to information based on related events or themes.

[0253] "Information representation" refers to content generated based on collected and analyzed information, and specific examples include slideshows and storyboard-style materials.

[0254] "Re-experiencing" refers to reliving past experiences or events, and in this invention, it is achieved through the generated information representation.

[0255] This invention enables the continuous collection of diverse information using a personal information processing device, allowing for the effective organization and re-experience of special moments. Specifically, the device launches a dedicated application running on the personal information processing device and, with the user's consent, collects digital data such as photos, videos, voice memos, text messages, and GPS information. Portable information processing devices, such as smartphones, are primarily used.

[0256] The data collected by the device is encrypted before being transferred to the cloud server and securely uploaded using security protocols such as TLS. When the server analyzes the received data, it uses image recognition and natural language processing technologies to identify subjects and locations from photos and videos, and extract emotions from text messages. The analyzed data is automatically assigned identifiers and organized into related events.

[0257] The server generates viewable informational representations based on data classified by this identifier. These representations include slideshow-style videos and storyboard-style materials, to which automatically generated voice narration and background music are added using a generative AI model. This allows users to relive special moments in a more emotionally impactful way.

[0258] For example, if a user wants to look back on their birthday records over several years, the device uploads the relevant data to a server. Based on this, the server automatically generates content including a slideshow and narration based on past birthday photos, providing the user with a moving retrospective experience.

[0259] An example of a prompt using a generative AI model is, "Collect data related to a specific trip and create narrated VR content based on it." This allows the server to construct a specific scenario from the tagged data and provide the user with a unique experience.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The terminal launches a dedicated application. The user opens the application, logs in, and grants permission for data collection. This action causes the application to enter data collection mode. The input is the user's authentication information, and the output is the acquisition of user permission for data collection.

[0263] Step 2:

[0264] The device collects digital data from the user's electronic devices. This process involves recording photos, videos, and voice memos using cameras and microphones, and obtaining location data using GPS functionality. These data serve as inputs, and the output is a collection of diverse digital data.

[0265] Step 3:

[0266] The device encrypts the data it collects and uploads it to a cloud server. The data is securely transferred using security protocols such as TLS. The input is the collected raw data, and the output is the encrypted data stored on the server.

[0267] Step 4:

[0268] The server analyzes the data it receives. First, it uses image recognition technology to identify subjects and locations from photos and videos. It also uses natural language processing technology to extract emotions from text messages. The input is data stored on the server, and the output is the identified subjects, locations, emotions, and identifiers assigned based on them.

[0269] Step 5:

[0270] The server generates informational representations based on data classified by identifiers. This process uses a generative AI model to add voice narration and background music, creating content in slideshow or storyboard format. The input is the analyzed data, and the output is the completed informational representation content.

[0271] Step 6:

[0272] Users view generated information representations. Users can play content on their devices and further enhance their experience using AR / VR devices. The input is the generated information representation, and the output is the information experienced through the user's sight and hearing.

[0273] (Application Example 1)

[0274] 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."

[0275] People save many special moments in their daily lives as digital information, but they lacked a way to effectively organize and provide them in a format that allows them to relive those experiences at any time. In particular, there was a lack of systems that could visually recreate individual experiences and allow them to be experienced in an emotionally rich way.

[0276] 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.

[0277] In this invention, the server includes means for automatically collecting data from multiple digital information sources, means for analyzing the collected data to extract subjects, locations, and emotions, and means for displaying the generated visual information using a projection device. This allows users to effectively relive special moments from the past and engage in emotionally rich reflection in their daily lives.

[0278] The "digital information source" refers to various digital data such as photos, videos, voice memos, text messages, GPS information, etc. generated from personal electronic devices and online platforms.

[0279] "Collect" refers to the process of automatically importing data from a digital information source and consistently storing it by a dedicated system or application.

[0280] "Analyze and extract" means processing the collected digital data and identifying and extracting specific information such as people, places, emotions, etc. from it.

[0281] "Tagging" refers to the operation of classifying the data into appropriate categories or themes based on the extracted information and assigning identifiable information.

[0282] "Generate visual information" means using the tagged data to compose it into an easy-to-understand slide show or video content.

[0283] "Display using a projection device" is a method of projecting the generated visual information onto the physical space via a projector or display system to make it visible.

[0284] This invention provides a system for effectively re-experiencing individual digital experiences. The system collects data from various digital information sources, analyzes it to generate visual content, and presents it using a projection device. Thereby, users can immersive revisit special moments.

[0285] The system first collects digital information through the terminal with the user's permission. Specifically, it automatically acquires photos, videos, voice memos, text messages, location information, etc. using a smartphone, camera, GPS sensor. The collected data is uploaded to the cloud server.

[0286] The server analyzes the uploaded data. Using image recognition technology (e.g., OpenCV) and sentiment analysis engines (e.g., Azure Cognitive Services), it identifies objects and locations from photos and videos and extracts the sentiment contained in the digital information. As a result, tagging is performed based on people, places, and sentiment, and it is classified as an appropriate event.

[0287] The tagged information is composed as visual content using a machine learning model. A slide show format video is generated by a video editing library (e.g., FFmpeg), and voice narration and BGM are added. The generated content is provided to the user via a projection device or display system.

[0288] As a specific example, when a user wants to relive the memories of a trip, if they instruct the terminal to "show me the photos of last summer's trip", all the related photos, videos, and voice memos from that period are organized and displayed as an emotional slide show. Thus, the user can once again enjoy that moment with family and friends.

[0289] Examples of prompt sentences are as follows.

[0290] "Please tell me about the memories of my birthday in February 2019. Create a slide show using related photos and videos. If possible, also include a narration and BGM that reproduce the feelings of that time."

[0291] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0292] Step 1:

[0293] With the user's permission, the device automatically retrieves photos, videos, voice memos, text messages, and location information from digital sources using the smartphone, camera, and GPS sensor. This data is temporarily stored in local storage for analysis in later processes.

[0294] Step 2:

[0295] The terminal uploads the collected digital data to a cloud server. At this stage, the terminal standardizes the data format and adds metadata to enable efficient analysis on the server. The input is local digital data on the terminal, and the output is standardized format data uploaded to the cloud server.

[0296] Step 3:

[0297] The server receives uploaded data and analyzes it using image recognition technology (e.g., OpenCV) and sentiment analysis engine (e.g., Azure Cognitive Services). Input is digital data in a unified format, and output is extracted subject, location, and sentiment data. Specifically, it identifies people and locations from photographs and extracts sentiment from text messages and voice memos.

[0298] Step 4:

[0299] The server classifies the information based on the analysis results and assigns relevant tags to the data. The input is extracted data, and the output is tagged data. The tags classify the data based on themes such as "travel," "family," and "emotional experiences," organizing them as unified events.

[0300] Step 5:

[0301] The server uses tagged data and leverages a video editing library (e.g., FFmpeg) to generate slideshow-style visual content. The input is tagged data, and the output is visual content. The generated content includes voice narration and background music generated by a generative AI model.

[0302] Step 6:

[0303] The user requests the terminal to display a specific past moment using a prompt. In response to the request, the terminal displays the generated visual content via a projection device or display. The input consists of the user's prompt and the generated visual content; the output is the video displayed on the projection device.

[0304] 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.

[0305] This invention combines a system that organizes personal digital data and allows users to relive special moments with an emotion engine that recognizes the user's feelings. The terminal operates on the user's personal electronic devices and, with the user's permission, has the function of automatically acquiring various digital data (photos, videos, voice memos, text messages, GPS information).

[0306] This device uploads collected digital data to a cloud server. The server applies machine learning algorithms to the data, and an emotion engine is activated to analyze the emotions of people, places, and situations extracted from the data. The emotion engine identifies the user's emotions from images and audio and assigns emotion tags to the data based on the information.

[0307] Furthermore, the server recognizes related events based on the extracted information and generates personalized viewable content based on the tagged data. At this time, it is possible to reflect the user's emotional information recognized by the emotion engine and adjust the viewing experience to be more moving. The generated content is created in the form of a slideshow, video, audio presentation, etc. and provided to the user.

[0308] As a specific example, when the user wants to relive the memories of a past trip, the terminal uploads the data (photos, videos, GPS information related to the travel destination) obtained during that trip. The server identifies the user's emotions (happiness, surprise, etc.) during the trip through the emotion engine and assigns emotion tags to each data based on that. After that, the tagged data is used to reproduce the entire trip in a narrative form and generate content that conforms to the user's emotions.

[0309] The user can view the content provided through a dedicated app and can also have a more immersive experience through virtual reality (VR) or augmented reality (AR) devices. In this way, the present invention enhances the re-experience of a person's special moments and provides a deeper sense of emotion through a system configuration that takes into account the user's emotions.

[0310] The processing flow will be described below.

[0311] Step 1:

[0312] The terminal, which is a personal electronic device, launches a dedicated application and automatically acquires digital data for which the user has given permission. This includes photos, videos, voice memos, GPS information, etc. The terminal prepares to upload the acquired data to the cloud server at defined intervals while maintaining security.

[0313] Step 2:

[0314] The server receives the digital data uploaded from the terminal, first checks the data format, and then saves it to storage in a standardized format.

[0315] Step 3:

[0316] An emotion engine on the server operates, performing image recognition on received photo and video data and analyzing the facial expressions of the people contained within. Furthermore, it analyzes the tone and speed of voices from audio data to identify emotions.

[0317] Step 4:

[0318] The server assigns appropriate emotion tags to the digital data based on the extracted emotion information. This allows the data to be classified according to the user's emotions.

[0319] Step 5:

[0320] The server uses tagged data to identify relevant and important events. Here, events are automatically categorized based on the duration of the trip or specific dates.

[0321] Step 6:

[0322] When the server generates content for the user based on classified data, it incorporates previously recognized emotional information into the presentation. This results in video content with music and narration that aligns with the user's emotions.

[0323] Step 7:

[0324] Users view the generated content through a dedicated app. Furthermore, by using VR and AR devices, they can enjoy a more immersive experience and interactively relive special moments from the past.

[0325] (Example 2)

[0326] 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".

[0327] In today's information society, individuals generate vast amounts of electronic data in their daily lives, making it difficult to organize and utilize this data. In particular, there is a growing demand to relive special moments and memories, but a lack of appropriate systems to meet this need. Therefore, there is a need for systems that can organize data while taking individual emotions into account, and that can provide emotionally resonant re-experiences.

[0328] 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.

[0329] In this invention, the server includes means for automatically collecting various electronic data from a personal terminal, means for analyzing the collected electronic data and extracting the subject, location, and emotion, and means for recognizing related events based on the extracted information and attaching emotion tags to the data. This makes it possible to re-experience a person's special moments while being emotionally connected to them.

[0330] A "personal device" is an electronic device used by an individual, and is a device used for data collection and information processing.

[0331] "Electronic data" refers to information stored in digital format, including photographs, videos, audio, text, and location information.

[0332] An "emotion tag" is an identification piece of information attached to electronic data that indicates the emotional state contained within the data.

[0333] "Experiential content" refers to content that allows users to gain emotional value through viewing or experiencing it, and includes slideshows and video presentations.

[0334] A "virtual image environment" is a technology that provides a realistic experience through computer-generated images and information.

[0335] An "augmented video environment" is a technology that overlays digital information onto real-world images, providing users with an enhanced experience of interacting with the real world.

[0336] This invention is a system that makes it possible to relive special personal moments, and it consists of the interaction between a server, a terminal, and the user.

[0337] First, the device is a personal electronic device (e.g., a smartphone or tablet) that, with the user's permission, automatically collects various types of electronic data, such as photos, videos, voice memos, texts, and location information. This data is managed while monitoring the device's storage usage to prevent excessive data usage.

[0338] The collected electronic data is uploaded from the terminal to the server via a secure network connection. The server receives the collected data and performs analysis using machine learning algorithms. This includes processes that use image recognition and speech recognition technologies to identify objects, locations, and emotions. This process can utilize AI technologies from common cloud service providers.

[0339] After data analysis, the server uses an emotion engine to assign emotion tags to the data. The emotion engine analyzes images and audio based on the emotional states extracted from the data. As a result, the data is organized using emotion tags.

[0340] The server then generates personalized, interactive content based on the tagged data. This content takes the form of slideshows, videos, and audio presentations, enhancing the user's emotional experience. Generative AI models are used to create prompts and express the user's past events in an emotionally resonant way.

[0341] For example, if a user wants to relive a past trip, the device collects photos, videos, and location information recorded during that trip and uploads them to a server. The server analyzes this data, uses an emotion engine to identify emotions such as "fun" and "surprise," and assigns emotion tags. Next, the tagged data is used to recreate the travel experience in narrative form, providing the user with an emotionally engaging viewing experience. Users can view the generated content through a dedicated application.

[0342] An example of a prompt message could be: "Recreate the user's past travel memories as an emotionally engaging, narrative-style slideshow using emotional data. Based on the user's emotional information, create a presentation that highlights enjoyable and surprising moments during their travels."

[0343] This system allows users to deeply relive special moments and have a moving experience.

[0344] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0345] Step 1:

[0346] The device collects various electronic data from personal electronic devices with the user's permission. This data includes photos, videos, voice memos, texts, and location information. This data is appropriately categorized into folders, and after checking the storage status, important data is selected and temporarily stored on the device.

[0347] Step 2:

[0348] The device uploads the collected electronic data to the server via a secure network connection. The input is temporarily stored electronic data, while the output is saved to a database on the server. The upload process starts automatically when Wi-Fi is available, but users can also start the upload manually.

[0349] Step 3:

[0350] The server analyzes the received electronic data and processes it using image recognition and speech recognition technologies. The input is electronic data stored on the server, and the output is subject, location information, and sentiment data extracted from the data. Specifically, cloud-based machine learning algorithms are used to analyze the data and extract information from images and audio.

[0351] Step 4:

[0352] The server uses an emotion engine to tag the data with emotion based on the analyzed information. The input is the extracted emotion data, and the output is the data with emotion tags. This adds emotion labels to the data, making subsequent processing easier.

[0353] Step 5:

[0354] The server uses tagged data to generate personalized, interactive content. Input is data containing emotion tags, and output is content in the form of slideshows or video presentations that resonate with the user's emotions. A generative AI model is used to create narrative-style content based on prompt text.

[0355] Step 6:

[0356] Users view experiential content generated through a dedicated application. The input is the generated content, and the output is the emotionally engaging viewing experience derived from the played content. In this step, users can relive special moments by viewing the output content.

[0357] (Application Example 2)

[0358] 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."

[0359] When individuals wish to relive special moments, it is necessary to properly organize the digital data and efficiently perform emotionally-driven visualizations. However, conventional technologies simply play back large amounts of digital data, which is insufficient to provide the emotional re-experience that users desire. Furthermore, there is a lack of home systems that allow users to freely and deeply relive past moments.

[0360] 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.

[0361] In this invention, the server includes means for automatically collecting various digital information from personal information devices, means for analyzing the collected digital information and extracting the subject, location, and emotion, and means for acquiring emotion-tagged data in response to voice commands and presenting the experience using visualization and audio technologies. This makes it possible for users to easily access special moments from the past via voice commands and enjoy visual and audio re-experiences based on emotions.

[0362] "Personal information devices" are electronic devices owned by individuals and used for collecting and managing digital information.

[0363] "Digital information" refers to data expressed in electronic form, including images, audio, and location information.

[0364] "Analysis" is the process of extracting meaningful information from collected digital data, and it is achieved using machine learning algorithms and emotion recognition technologies.

[0365] "Extracting subjects, locations, and emotions" means identifying and extracting location information of people, objects, and places, as well as the emotions associated with them, contained within digital information.

[0366] "Voice commands" refer to an input method that uses voice to transmit commands to information devices and cause them to perform specific operations.

[0367] "Emotionally tagged data" refers to data that has been tagged based on emotional information extracted from digital information.

[0368] "Visualization technology" refers to technologies that visually represent digital information and facilitate re-experience.

[0369] "Voice technology" refers to technologies that reproduce digital information as sound and enable voice-based interaction.

[0370] "Presenting an experience" is the process of enabling users to gain new experiences by viewing and listening to digital information.

[0371] In the system for implementing this invention, the user's information device plays a central role. This information device includes smartphones and home assistant devices, which automatically collect various digital information from the user's daily life. This information is diverse, including images, audio, and location information, and after collection, it is uploaded to a cloud server.

[0372] The server applies machine learning algorithms to this digital information and uses image analysis techniques to extract the subject, location, and emotion. For emotion recognition, libraries such as OpenCV can be used, and for speech processing, speech synthesis libraries such as pyttsx3 can be combined. Based on the extracted emotion information, emotion tags are assigned to the data, and relevant content is generated based on the specified identification information.

[0373] Users can access this content using voice commands. For example, by sending a voice command such as "Show me the smiling photos from last year's trip" to a home device, the necessary emotion-tagged data is retrieved from the server and projected onto the wall via visualization technology (e.g., a projector). Voice technology is also used to output personalized audio guides, enhancing the quality of the re-experience.

[0374] An example of a prompt message might be: "Create a slideshow of past travel photos tailored to the user based on sentiment tags, add relevant music and narration, and explain it clearly to the user." This allows the user to have a more personal and immersive experience.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The device automatically collects digital information such as images, audio, and GPS data generated in the user's daily life. The input is raw data stored on the device. The collected data is uploaded to a cloud server with the user's permission. The output is the digital information uploaded to the server.

[0378] Step 2:

[0379] The server receives uploaded digital information and performs image and audio analysis. The input is the collected digital information. Using libraries such as OpenCV, it detects people and objects from images and extracts the user's emotions from facial expressions and audio using emotion recognition algorithms. This process yields data with emotion tags as output.

[0380] Step 3:

[0381] The server recognizes relevant events based on extracted sentiment-tagged data and generates content tailored to user specifications. The input is sentiment-tagged data. Prompt text is input to the generating AI model, which creates slideshows and narrations related to the user's past special moments. This step outputs content for presentation to the user.

[0382] Step 4:

[0383] The user inputs voice commands into the terminal. These inputs are the user's voice data. The terminal analyzes these voice commands and sends a request for relevant content to the server. This process prepares the server to select and output the appropriate content.

[0384] Step 5:

[0385] The server retrieves content based on voice commands and sends it to the terminal. The input is the user's request data. The terminal uses the retrieved data and plays the content using visualization and audio technologies. The output of this step is the content presented visually and audibly on the user's device.

[0386] Through these steps, users can immersively relive special moments based on their emotions.

[0387] 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.

[0388] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0389] 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.

[0390] [Third Embodiment]

[0391] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0392] 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.

[0393] 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).

[0394] 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.

[0395] 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.

[0396] 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).

[0397] 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.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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".

[0403] This invention provides a system that effectively organizes personal experiences as digital data, allowing users to relive special moments. Specifically, the system starts operating via a dedicated application running on the user's personal electronic device. With the user's permission, this application collects digital data such as photos, videos, voice memos, text messages, and GPS information, and periodically uploads this data to a cloud server.

[0404] After receiving the uploaded data, the server performs analysis. This analysis uses image recognition technology to identify people and places from photos and videos, and sentiment analysis technology to extract the emotions contained within each piece of content. Each data item is tagged with relevant tags and classified as an event. For example, photos and videos related to travel are tagged with "travel," "tourist destination," and "family."

[0405] The server generates content using tagged data periodically or upon user request. The generated content takes the form of slideshows or storyboards, used to relive special moments in the user's life. The content may also include machine learning-generated voice narration and background music. Users can also experience this content through AR (augmented reality) and VR (virtual reality) devices for a more immersive re-experience.

[0406] For example, if a user wants to look back on their birthdays over several years, the device uploads relevant data from that period to a server, which then generates birthday-themed content based on that data. This content can include a dynamic slideshow based on past birthday photos and automatically generated narration, providing the user with a moving retrospective experience.

[0407] Thus, the present invention implements a system configuration that organically combines the roles of terminals, servers, and users in order to improve the management and experience of digital data.

[0408] The following describes the processing flow.

[0409] Step 1:

[0410] The device launches applications on the user's electronic device and collects digital data such as photos, videos, voice memos, and GPS information in the background, to the extent permitted by the user. The frequency and timing of collection are adjusted based on network conditions and battery usage.

[0411] Step 2:

[0412] The device uploads the collected data to a cloud server. Encryption technology is applied to the upload to ensure data security and efficiency. The system is configured to transfer data only when communication conditions are optimal (e.g., when connected to Wi-Fi).

[0413] Step 3:

[0414] The server first saves the received data to storage. Next, it starts analyzing the data using machine learning algorithms, performing image recognition to identify people, places, and emotions during emergencies from photos and videos.

[0415] Step 4:

[0416] Based on the server's analysis, tags related to the data are assigned. These tags include extracted emotions and specific event information, and are used as foundational data for subsequent event recognition.

[0417] Step 5:

[0418] The server creates an event list using tagged data. Here, date and location information is integrated to recognize and classify specific past events (e.g., travel, birthdays).

[0419] Step 6:

[0420] The server generates content by combining tagged data based on user requests or a recurring schedule. This process is carried out using AI technology in the form of slideshows, videos, or content with audio.

[0421] Step 7:

[0422] Users view content provided from the server via a dedicated app and experience it through viewing or AR / VR devices. The generated content recreates special moments from the past, providing users with a new and moving experience.

[0423] (Example 1)

[0424] 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."

[0425] In today's world, many people generate a vast amount of digital data on a daily basis, but effectively organizing this information and making it meaningful for individuals to re-experience is challenging. Furthermore, extracting special moments from this massive amount of data and conducting emotionally-based evaluations is also difficult. Moreover, there is a need for means to experience generated content in a more immersive way.

[0426] 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.

[0427] In this invention, the server includes means for continuously collecting diverse information from an individual's information processing device, means for analyzing the collected information and extracting subjects, locations, and emotions, means for recognizing related events based on the extracted identification information and classifying the information by identifiers, and means for generating individual viewable information representations using the information classified by identifiers. This makes it possible to organize an individual's special moments and provide emotionally valuable re-experiences.

[0428] An "information processing device" is a machine or device used to process and manage digital data, and usually refers to a computer or smartphone.

[0429] "Information" refers to digital data generated by individuals, encompassing a wide range of data including photographs, videos, voice memos, text, and location information.

[0430] "Collection" refers to the act of gathering information for a specific purpose, and in this invention, it refers to the automatic or manual acquisition of personal digital data.

[0431] "Analysis" is the process of examining collected information in detail to reveal its meaning and characteristics, and includes identifying people and places and evaluating emotions.

[0432] "Subject" refers to an object that appears in a photograph or video, and in this invention, it is identified by image recognition technology.

[0433] "Location" refers to the geographical location to which the collected information is related, and is usually specified by GPS data.

[0434] "Emotion" refers to the emotional elements contained within information, including emotional states such as positive, negative, and neutral, which can be extracted from text or audio.

[0435] An "identifier" refers to a label or tag used to classify or organize information, and is assigned to information based on related events or themes.

[0436] "Information representation" refers to content generated based on collected and analyzed information, and specific examples include slideshows and storyboard-style materials.

[0437] "Re-experiencing" refers to reliving past experiences or events, and in this invention, it is achieved through the generated information representation.

[0438] This invention enables the continuous collection of diverse information using a personal information processing device, allowing for the effective organization and re-experience of special moments. Specifically, the device launches a dedicated application running on the personal information processing device and, with the user's consent, collects digital data such as photos, videos, voice memos, text messages, and GPS information. Portable information processing devices, such as smartphones, are primarily used.

[0439] The data collected by the device is encrypted before being transferred to the cloud server and securely uploaded using security protocols such as TLS. When the server analyzes the received data, it uses image recognition and natural language processing technologies to identify subjects and locations from photos and videos, and extract emotions from text messages. The analyzed data is automatically assigned identifiers and organized into related events.

[0440] The server generates viewable informational representations based on data classified by this identifier. These representations include slideshow-style videos and storyboard-style materials, to which automatically generated voice narration and background music are added using a generative AI model. This allows users to relive special moments in a more emotionally impactful way.

[0441] For example, if a user wants to look back on their birthday records over several years, the device uploads the relevant data to a server. Based on this, the server automatically generates content including a slideshow and narration based on past birthday photos, providing the user with a moving retrospective experience.

[0442] An example of a prompt using a generative AI model is, "Collect data related to a specific trip and create narrated VR content based on it." This allows the server to construct a specific scenario from the tagged data and provide the user with a unique experience.

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The terminal launches a dedicated application. The user opens the application, logs in, and grants permission for data collection. This action causes the application to enter data collection mode. The input is the user's authentication information, and the output is the acquisition of user permission for data collection.

[0446] Step 2:

[0447] The device collects digital data from the user's electronic devices. This process involves recording photos, videos, and voice memos using cameras and microphones, and obtaining location data using GPS functionality. These data serve as inputs, and the output is a collection of diverse digital data.

[0448] Step 3:

[0449] The device encrypts the data it collects and uploads it to a cloud server. The data is securely transferred using security protocols such as TLS. The input is the collected raw data, and the output is the encrypted data stored on the server.

[0450] Step 4:

[0451] The server analyzes the data it receives. First, it uses image recognition technology to identify subjects and locations from photos and videos. It also uses natural language processing technology to extract emotions from text messages. The input is data stored on the server, and the output is the identified subjects, locations, emotions, and identifiers assigned based on them.

[0452] Step 5:

[0453] The server generates informational representations based on data classified by identifiers. This process uses a generative AI model to add voice narration and background music, creating content in slideshow or storyboard format. The input is the analyzed data, and the output is the completed informational representation content.

[0454] Step 6:

[0455] Users view generated information representations. Users can play content on their devices and further enhance their experience using AR / VR devices. The input is the generated information representation, and the output is the information experienced through the user's sight and hearing.

[0456] (Application Example 1)

[0457] 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."

[0458] People save many special moments in their daily lives as digital information, but they lacked a way to effectively organize and provide them in a format that allows them to relive those experiences at any time. In particular, there was a lack of systems that could visually recreate individual experiences and allow them to be experienced in an emotionally rich way.

[0459] 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.

[0460] In this invention, the server includes means for automatically collecting data from multiple digital information sources, means for analyzing the collected data to extract subjects, locations, and emotions, and means for displaying the generated visual information using a projection device. This allows users to effectively relive special moments from the past and engage in emotionally rich reflection in their daily lives.

[0461] "Digital information sources" refer to a variety of digital data generated from personal electronic devices and online platforms, such as photos, videos, voice memos, text messages, and GPS information.

[0462] "Collecting" refers to the process of automatically retrieving data from digital sources and consistently storing it using a dedicated system or application.

[0463] "Analyzing and extracting" means processing collected digital data and identifying and extracting specific information such as people, places, and emotions from it.

[0464] "Tagging" refers to the process of classifying extracted data into appropriate categories or themes and assigning identifiable information to them.

[0465] "Generating visual information" means using tagged data to create easy-to-understand slideshows or video content.

[0466] "Displaying using projection equipment" refers to a method of projecting generated visual information into a physical space via a projector or display system to make it visible.

[0467] This invention provides a system that effectively allows users to re-experience individual digital experiences. The system collects data from various digital sources, analyzes it to generate visual content, and presents it using a projection device. This allows users to immersively revisit special moments.

[0468] The system first collects digital information through the device with the user's permission. Specifically, it automatically acquires photos, videos, voice memos, text messages, and location information using smartphones, cameras, and GPS sensors. The collected data is uploaded to a cloud server.

[0469] The server analyzes the uploaded data. Using image recognition technology (e.g., OpenCV) and sentiment analysis engines (e.g., Azure Cognitive Services), it identifies subjects and locations from photos and videos and extracts emotions contained in the digital information. This allows for tagging based on people, places, and emotions, and classifying the data as appropriate events.

[0470] Tagged information is compiled into visual content using a machine learning model. A slideshow video is generated using a video editing library (e.g., FFmpeg), and voice narration and background music are added. The generated content is then delivered to the user via projection equipment or a display system.

[0471] For example, when a user wants to relive travel memories, they can simply tell their device, "Show me photos from last summer's trip," and all photos, videos, and voice memos related to that period will be organized and displayed as an emotionally engaging slideshow. This allows the user to relive those moments with family and friends.

[0472] Examples of prompt messages are as follows:

[0473] "Please share your memories of my birthday in February 2019. Create a slideshow using relevant photos and videos. If possible, please include narration and background music that recreates the feelings I had at that time."

[0474] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0475] Step 1:

[0476] With the user's permission, the device automatically retrieves photos, videos, voice memos, text messages, and location information from digital sources using the smartphone, camera, and GPS sensor. This data is temporarily stored in local storage for analysis in later processes.

[0477] Step 2:

[0478] The terminal uploads the collected digital data to a cloud server. At this stage, the terminal standardizes the data format and adds metadata to enable efficient analysis on the server. The input is local digital data on the terminal, and the output is standardized format data uploaded to the cloud server.

[0479] Step 3:

[0480] The server receives uploaded data and analyzes it using image recognition technology (e.g., OpenCV) and sentiment analysis engine (e.g., Azure Cognitive Services). Input is digital data in a unified format, and output is extracted subject, location, and sentiment data. Specifically, it identifies people and locations from photographs and extracts sentiment from text messages and voice memos.

[0481] Step 4:

[0482] The server classifies the information based on the analysis results and assigns relevant tags to the data. The input is extracted data, and the output is tagged data. The tags classify the data based on themes such as "travel," "family," and "emotional experiences," organizing them as unified events.

[0483] Step 5:

[0484] The server uses tagged data and leverages a video editing library (e.g., FFmpeg) to generate slideshow-style visual content. The input is tagged data, and the output is visual content. The generated content includes voice narration and background music generated by a generative AI model.

[0485] Step 6:

[0486] The user requests the terminal to display a specific past moment using a prompt. In response to the request, the terminal displays the generated visual content via a projection device or display. The input consists of the user's prompt and the generated visual content; the output is the video displayed on the projection device.

[0487] 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.

[0488] This invention combines a system that organizes personal digital data and allows users to relive special moments with an emotion engine that recognizes the user's feelings. The terminal operates on the user's personal electronic devices and, with the user's permission, has the function of automatically acquiring various digital data (photos, videos, voice memos, text messages, GPS information).

[0489] This device uploads collected digital data to a cloud server. The server applies machine learning algorithms to the data, and an emotion engine is activated to analyze the emotions of people, places, and situations extracted from the data. The emotion engine identifies the user's emotions from images and audio and assigns emotion tags to the data based on the information.

[0490] Furthermore, the server recognizes relevant events based on the extracted information and generates personalized, viewable content based on tagged data. In this process, it can incorporate the user's emotional information recognized by the emotion engine, tailoring the viewing experience to be more emotionally engaging. The generated content is created and provided to the user in formats such as slideshows, videos, and audio presentations.

[0491] For example, if a user wants to relive memories of a past trip, the device uploads data acquired during that trip (photos, videos, GPS information related to the travel locations). The server uses an emotion engine to identify the user's emotions during the trip (joy, surprise, etc.) and assigns emotion tags to each data item based on that. Then, using the tagged data, the entire trip is recreated in a narrative format, generating content that resonates with the user's emotions.

[0492] Users can view content provided through a dedicated app and also have a more immersive experience through virtual reality (VR) and augmented reality (AR) devices. In this way, the present invention enhances the re-experience of personal special moments and provides a deeper emotional impact through a system configuration that takes user emotions into consideration.

[0493] The following describes the processing flow.

[0494] Step 1:

[0495] The device launches a dedicated application on the user's personal electronic device and automatically acquires digital data with the user's permission. This includes photos, videos, voice memos, GPS information, etc. The device then prepares to upload the acquired data to a cloud server at defined intervals while maintaining security.

[0496] Step 2:

[0497] The server receives the digital data uploaded from the terminal, first checks the data format, and then saves it to storage in a standardized format.

[0498] Step 3:

[0499] An emotion engine on the server operates, performing image recognition on received photo and video data and analyzing the facial expressions of the people contained within. Furthermore, it analyzes the tone and speed of voices from audio data to identify emotions.

[0500] Step 4:

[0501] The server assigns appropriate emotion tags to the digital data based on the extracted emotion information. This allows the data to be classified according to the user's emotions.

[0502] Step 5:

[0503] The server uses tagged data to identify relevant and important events. Here, events are automatically categorized based on the duration of the trip or specific dates.

[0504] Step 6:

[0505] When the server generates content for the user based on classified data, it incorporates previously recognized emotional information into the presentation. This results in video content with music and narration that aligns with the user's emotions.

[0506] Step 7:

[0507] Users view the generated content through a dedicated app. Furthermore, by using VR and AR devices, they can enjoy a more immersive experience and interactively relive special moments from the past.

[0508] (Example 2)

[0509] 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."

[0510] In today's information society, individuals generate vast amounts of electronic data in their daily lives, making it difficult to organize and utilize this data. In particular, there is a growing demand to relive special moments and memories, but a lack of appropriate systems to meet this need. Therefore, there is a need for systems that can organize data while taking individual emotions into account, and that can provide emotionally resonant re-experiences.

[0511] 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.

[0512] In this invention, the server includes means for automatically collecting various electronic data from a personal terminal, means for analyzing the collected electronic data and extracting the subject, location, and emotion, and means for recognizing related events based on the extracted information and attaching emotion tags to the data. This makes it possible to re-experience a person's special moments while being emotionally connected to them.

[0513] A "personal device" is an electronic device used by an individual, and is a device used for data collection and information processing.

[0514] "Electronic data" refers to information stored in digital format, including photographs, videos, audio, text, and location information.

[0515] An "emotion tag" is an identification piece of information attached to electronic data that indicates the emotional state contained within the data.

[0516] "Experiential content" refers to content that allows users to gain emotional value through viewing or experiencing it, and includes slideshows and video presentations.

[0517] A "virtual image environment" is a technology that provides a realistic experience through computer-generated images and information.

[0518] An "augmented video environment" is a technology that overlays digital information onto real-world images, providing users with an enhanced experience of interacting with the real world.

[0519] This invention is a system that makes it possible to relive special personal moments, and it consists of the interaction between a server, a terminal, and the user.

[0520] First, the device is a personal electronic device (e.g., a smartphone or tablet) that, with the user's permission, automatically collects various types of electronic data, such as photos, videos, voice memos, texts, and location information. This data is managed while monitoring the device's storage usage to prevent excessive data usage.

[0521] The collected electronic data is uploaded from the terminal to the server via a secure network connection. The server receives the collected data and performs analysis using machine learning algorithms. This includes processes that use image recognition and speech recognition technologies to identify objects, locations, and emotions. This process can utilize AI technologies from common cloud service providers.

[0522] After data analysis, the server uses an emotion engine to assign emotion tags to the data. The emotion engine analyzes images and audio based on the emotional states extracted from the data. As a result, the data is organized using emotion tags.

[0523] The server then generates personalized, interactive content based on the tagged data. This content takes the form of slideshows, videos, and audio presentations, enhancing the user's emotional experience. Generative AI models are used to create prompts and express the user's past events in an emotionally resonant way.

[0524] For example, if a user wants to relive a past trip, the device collects photos, videos, and location information recorded during that trip and uploads them to a server. The server analyzes this data, uses an emotion engine to identify emotions such as "fun" and "surprise," and assigns emotion tags. Next, the tagged data is used to recreate the travel experience in narrative form, providing the user with an emotionally engaging viewing experience. Users can view the generated content through a dedicated application.

[0525] An example of a prompt message could be: "Recreate the user's past travel memories as an emotionally engaging, narrative-style slideshow using emotional data. Based on the user's emotional information, create a presentation that highlights enjoyable and surprising moments during their travels."

[0526] This system allows users to deeply relive special moments and have a moving experience.

[0527] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0528] Step 1:

[0529] The device collects various electronic data from personal electronic devices with the user's permission. This data includes photos, videos, voice memos, texts, and location information. This data is appropriately categorized into folders, and after checking the storage status, important data is selected and temporarily stored on the device.

[0530] Step 2:

[0531] The device uploads the collected electronic data to the server via a secure network connection. The input is temporarily stored electronic data, while the output is saved to a database on the server. The upload process starts automatically when Wi-Fi is available, but users can also start the upload manually.

[0532] Step 3:

[0533] The server analyzes the received electronic data and processes it using image recognition and speech recognition technologies. The input is electronic data stored on the server, and the output is subject, location information, and sentiment data extracted from the data. Specifically, cloud-based machine learning algorithms are used to analyze the data and extract information from images and audio.

[0534] Step 4:

[0535] The server uses an emotion engine to tag the data with emotion based on the analyzed information. The input is the extracted emotion data, and the output is the data with emotion tags. This adds emotion labels to the data, making subsequent processing easier.

[0536] Step 5:

[0537] The server uses tagged data to generate personalized, interactive content. Input is data containing emotion tags, and output is content in the form of slideshows or video presentations that resonate with the user's emotions. A generative AI model is used to create narrative-style content based on prompt text.

[0538] Step 6:

[0539] Users view experiential content generated through a dedicated application. The input is the generated content, and the output is the emotionally engaging viewing experience derived from the played content. In this step, users can relive special moments by viewing the output content.

[0540] (Application Example 2)

[0541] 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."

[0542] When individuals wish to relive special moments, it is necessary to properly organize the digital data and efficiently perform emotionally-driven visualizations. However, conventional technologies simply play back large amounts of digital data, which is insufficient to provide the emotional re-experience that users desire. Furthermore, there is a lack of home systems that allow users to freely and deeply relive past moments.

[0543] 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.

[0544] In this invention, the server includes means for automatically collecting various digital information from personal information devices, means for analyzing the collected digital information and extracting the subject, location, and emotion, and means for acquiring emotion-tagged data in response to voice commands and presenting the experience using visualization and audio technologies. This makes it possible for users to easily access special moments from the past via voice commands and enjoy visual and audio re-experiences based on emotions.

[0545] "Personal information devices" are electronic devices owned by individuals and used for collecting and managing digital information.

[0546] "Digital information" refers to data expressed in electronic form, including images, audio, and location information.

[0547] "Analysis" is the process of extracting meaningful information from collected digital data, and it is achieved using machine learning algorithms and emotion recognition technologies.

[0548] "Extracting subjects, locations, and emotions" means identifying and extracting location information of people, objects, and places, as well as the emotions associated with them, contained within digital information.

[0549] "Voice commands" refer to an input method that uses voice to transmit commands to information devices and cause them to perform specific operations.

[0550] "Emotionally tagged data" refers to data that has been tagged based on emotional information extracted from digital information.

[0551] "Visualization technology" refers to technologies that visually represent digital information and facilitate re-experience.

[0552] "Voice technology" refers to technologies that reproduce digital information as sound and enable voice-based interaction.

[0553] "Presenting an experience" is the process of enabling users to gain new experiences by viewing and listening to digital information.

[0554] In the system for implementing this invention, the user's information device plays a central role. This information device includes smartphones and home assistant devices, which automatically collect various digital information from the user's daily life. This information is diverse, including images, audio, and location information, and after collection, it is uploaded to a cloud server.

[0555] The server applies machine learning algorithms to this digital information and uses image analysis techniques to extract the subject, location, and emotion. For emotion recognition, libraries such as OpenCV can be used, and for speech processing, speech synthesis libraries such as pyttsx3 can be combined. Based on the extracted emotion information, emotion tags are assigned to the data, and relevant content is generated based on the specified identification information.

[0556] Users can access this content using voice commands. For example, by sending a voice command such as "Show me the smiling photos from last year's trip" to a home device, the necessary emotion-tagged data is retrieved from the server and projected onto the wall via visualization technology (e.g., a projector). Voice technology is also used to output personalized audio guides, enhancing the quality of the re-experience.

[0557] An example of a prompt message might be: "Create a slideshow of past travel photos tailored to the user based on sentiment tags, add relevant music and narration, and explain it clearly to the user." This allows the user to have a more personal and immersive experience.

[0558] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0559] Step 1:

[0560] The device automatically collects digital information such as images, audio, and GPS data generated in the user's daily life. The input is raw data stored on the device. The collected data is uploaded to a cloud server with the user's permission. The output is the digital information uploaded to the server.

[0561] Step 2:

[0562] The server receives uploaded digital information and performs image and audio analysis. The input is the collected digital information. Using libraries such as OpenCV, it detects people and objects from images and extracts the user's emotions from facial expressions and audio using emotion recognition algorithms. This process yields data with emotion tags as output.

[0563] Step 3:

[0564] The server recognizes relevant events based on extracted sentiment-tagged data and generates content tailored to user specifications. The input is sentiment-tagged data. Prompt text is input to the generating AI model, which creates slideshows and narrations related to the user's past special moments. This step outputs content for presentation to the user.

[0565] Step 4:

[0566] The user inputs voice commands into the terminal. These inputs are the user's voice data. The terminal analyzes these voice commands and sends a request for relevant content to the server. This process prepares the server to select and output the appropriate content.

[0567] Step 5:

[0568] The server retrieves content based on voice commands and sends it to the terminal. The input is the user's request data. The terminal uses the retrieved data and plays the content using visualization and audio technologies. The output of this step is the content presented visually and audibly on the user's device.

[0569] Through these steps, users can immersively relive special moments based on their emotions.

[0570] 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.

[0571] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0572] 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.

[0573] [Fourth Embodiment]

[0574] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0575] 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.

[0576] 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).

[0577] 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.

[0578] 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.

[0579] 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).

[0580] 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.

[0581] 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.

[0582] 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.

[0583] 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.

[0584] 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.

[0585] 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.

[0586] 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".

[0587] This invention provides a system that effectively organizes personal experiences as digital data, allowing users to relive special moments. Specifically, the system starts operating via a dedicated application running on the user's personal electronic device. With the user's permission, this application collects digital data such as photos, videos, voice memos, text messages, and GPS information, and periodically uploads this data to a cloud server.

[0588] After receiving the uploaded data, the server performs analysis. This analysis uses image recognition technology to identify people and places from photos and videos, and sentiment analysis technology to extract the emotions contained within each piece of content. Each data item is tagged with relevant tags and classified as an event. For example, photos and videos related to travel are tagged with "travel," "tourist destination," and "family."

[0589] The server generates content using tagged data periodically or upon user request. The generated content takes the form of slideshows or storyboards, used to relive special moments in the user's life. The content may also include machine learning-generated voice narration and background music. Users can also experience this content through AR (augmented reality) and VR (virtual reality) devices for a more immersive re-experience.

[0590] For example, if a user wants to look back on their birthdays over several years, the device uploads relevant data from that period to a server, which then generates birthday-themed content based on that data. This content can include a dynamic slideshow based on past birthday photos and automatically generated narration, providing the user with a moving retrospective experience.

[0591] Thus, the present invention implements a system configuration that organically combines the roles of terminals, servers, and users in order to improve the management and experience of digital data.

[0592] The following describes the processing flow.

[0593] Step 1:

[0594] The device launches applications on the user's electronic device and collects digital data such as photos, videos, voice memos, and GPS information in the background, to the extent permitted by the user. The frequency and timing of collection are adjusted based on network conditions and battery usage.

[0595] Step 2:

[0596] The device uploads the collected data to a cloud server. Encryption technology is applied to the upload to ensure data security and efficiency. The system is configured to transfer data only when communication conditions are optimal (e.g., when connected to Wi-Fi).

[0597] Step 3:

[0598] The server first saves the received data to storage. Next, it starts analyzing the data using machine learning algorithms, performing image recognition to identify people, places, and emotions during emergencies from photos and videos.

[0599] Step 4:

[0600] Based on the server's analysis, tags related to the data are assigned. These tags include extracted emotions and specific event information, and are used as foundational data for subsequent event recognition.

[0601] Step 5:

[0602] The server creates an event list using tagged data. Here, date and location information is integrated to recognize and classify specific past events (e.g., travel, birthdays).

[0603] Step 6:

[0604] The server generates content by combining tagged data based on user requests or a recurring schedule. This process is carried out using AI technology in the form of slideshows, videos, or content with audio.

[0605] Step 7:

[0606] Users view content provided from the server via a dedicated app and experience it through viewing or AR / VR devices. The generated content recreates special moments from the past, providing users with a new and moving experience.

[0607] (Example 1)

[0608] 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".

[0609] In today's world, many people generate a vast amount of digital data on a daily basis, but effectively organizing this information and making it meaningful for individuals to re-experience is challenging. Furthermore, extracting special moments from this massive amount of data and conducting emotionally-based evaluations is also difficult. Moreover, there is a need for means to experience generated content in a more immersive way.

[0610] 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.

[0611] In this invention, the server includes means for continuously collecting diverse information from an individual's information processing device, means for analyzing the collected information and extracting subjects, locations, and emotions, means for recognizing related events based on the extracted identification information and classifying the information by identifiers, and means for generating individual viewable information representations using the information classified by identifiers. This makes it possible to organize an individual's special moments and provide emotionally valuable re-experiences.

[0612] An "information processing device" is a machine or device used to process and manage digital data, and usually refers to a computer or smartphone.

[0613] "Information" refers to digital data generated by individuals, encompassing a wide range of data including photographs, videos, voice memos, text, and location information.

[0614] "Collection" refers to the act of gathering information for a specific purpose, and in this invention, it refers to the automatic or manual acquisition of personal digital data.

[0615] "Analysis" is the process of examining collected information in detail to reveal its meaning and characteristics, and includes identifying people and places and evaluating emotions.

[0616] "Subject" refers to an object that appears in a photograph or video, and in this invention, it is identified by image recognition technology.

[0617] "Location" refers to the geographical location to which the collected information is related, and is usually specified by GPS data.

[0618] "Emotion" refers to the emotional elements contained within information, including emotional states such as positive, negative, and neutral, which can be extracted from text or audio.

[0619] An "identifier" refers to a label or tag used to classify or organize information, and is assigned to information based on related events or themes.

[0620] "Information representation" refers to content generated based on collected and analyzed information, and specific examples include slideshows and storyboard-style materials.

[0621] "Re-experiencing" refers to reliving past experiences or events, and in this invention, it is achieved through the generated information representation.

[0622] This invention enables the continuous collection of diverse information using a personal information processing device, allowing for the effective organization and re-experience of special moments. Specifically, the device launches a dedicated application running on the personal information processing device and, with the user's consent, collects digital data such as photos, videos, voice memos, text messages, and GPS information. Portable information processing devices, such as smartphones, are primarily used.

[0623] The data collected by the device is encrypted before being transferred to the cloud server and securely uploaded using security protocols such as TLS. When the server analyzes the received data, it uses image recognition and natural language processing technologies to identify subjects and locations from photos and videos, and extract emotions from text messages. The analyzed data is automatically assigned identifiers and organized into related events.

[0624] The server generates viewable informational representations based on data classified by this identifier. These representations include slideshow-style videos and storyboard-style materials, to which automatically generated voice narration and background music are added using a generative AI model. This allows users to relive special moments in a more emotionally impactful way.

[0625] For example, if a user wants to look back on their birthday records over several years, the device uploads the relevant data to a server. Based on this, the server automatically generates content including a slideshow and narration based on past birthday photos, providing the user with a moving retrospective experience.

[0626] An example of a prompt using a generative AI model is, "Collect data related to a specific trip and create narrated VR content based on it." This allows the server to construct a specific scenario from the tagged data and provide the user with a unique experience.

[0627] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0628] Step 1:

[0629] The terminal launches a dedicated application. The user opens the application, logs in, and grants permission for data collection. This action causes the application to enter data collection mode. The input is the user's authentication information, and the output is the acquisition of user permission for data collection.

[0630] Step 2:

[0631] The device collects digital data from the user's electronic devices. This process involves recording photos, videos, and voice memos using cameras and microphones, and obtaining location data using GPS functionality. These data serve as inputs, and the output is a collection of diverse digital data.

[0632] Step 3:

[0633] The device encrypts the data it collects and uploads it to a cloud server. The data is securely transferred using security protocols such as TLS. The input is the collected raw data, and the output is the encrypted data stored on the server.

[0634] Step 4:

[0635] The server analyzes the data it receives. First, it uses image recognition technology to identify subjects and locations from photos and videos. It also uses natural language processing technology to extract emotions from text messages. The input is data stored on the server, and the output is the identified subjects, locations, emotions, and identifiers assigned based on them.

[0636] Step 5:

[0637] The server generates informational representations based on data classified by identifiers. This process uses a generative AI model to add voice narration and background music, creating content in slideshow or storyboard format. The input is the analyzed data, and the output is the completed informational representation content.

[0638] Step 6:

[0639] Users view generated information representations. Users can play content on their devices and further enhance their experience using AR / VR devices. The input is the generated information representation, and the output is the information experienced through the user's sight and hearing.

[0640] (Application Example 1)

[0641] 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".

[0642] People save many special moments in their daily lives as digital information, but they lacked a way to effectively organize and provide them in a format that allows them to relive those experiences at any time. In particular, there was a lack of systems that could visually recreate individual experiences and allow them to be experienced in an emotionally rich way.

[0643] 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.

[0644] In this invention, the server includes means for automatically collecting data from multiple digital information sources, means for analyzing the collected data to extract subjects, locations, and emotions, and means for displaying the generated visual information using a projection device. This allows users to effectively relive special moments from the past and engage in emotionally rich reflection in their daily lives.

[0645] "Digital information sources" refer to a variety of digital data generated from personal electronic devices and online platforms, such as photos, videos, voice memos, text messages, and GPS information.

[0646] "Collecting" refers to the process of automatically retrieving data from digital sources and consistently storing it using a dedicated system or application.

[0647] "Analyzing and extracting" means processing collected digital data and identifying and extracting specific information such as people, places, and emotions from it.

[0648] "Tagging" refers to the process of classifying extracted data into appropriate categories or themes and assigning identifiable information to them.

[0649] "Generating visual information" means using tagged data to create easy-to-understand slideshows or video content.

[0650] "Displaying using projection equipment" refers to a method of projecting generated visual information into a physical space via a projector or display system to make it visible.

[0651] This invention provides a system that effectively allows users to re-experience individual digital experiences. The system collects data from various digital sources, analyzes it to generate visual content, and presents it using a projection device. This allows users to immersively revisit special moments.

[0652] The system first collects digital information through the device with the user's permission. Specifically, it automatically acquires photos, videos, voice memos, text messages, and location information using smartphones, cameras, and GPS sensors. The collected data is uploaded to a cloud server.

[0653] The server analyzes the uploaded data. Using image recognition technology (e.g., OpenCV) and sentiment analysis engines (e.g., Azure Cognitive Services), it identifies subjects and locations from photos and videos and extracts emotions contained in the digital information. This allows for tagging based on people, places, and emotions, and classifying the data as appropriate events.

[0654] Tagged information is compiled into visual content using a machine learning model. A slideshow video is generated using a video editing library (e.g., FFmpeg), and voice narration and background music are added. The generated content is then delivered to the user via projection equipment or a display system.

[0655] For example, when a user wants to relive travel memories, they can simply tell their device, "Show me photos from last summer's trip," and all photos, videos, and voice memos related to that period will be organized and displayed as an emotionally engaging slideshow. This allows the user to relive those moments with family and friends.

[0656] Examples of prompt messages are as follows:

[0657] "Please share your memories of my birthday in February 2019. Create a slideshow using relevant photos and videos. If possible, please include narration and background music that recreates the feelings I had at that time."

[0658] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0659] Step 1:

[0660] With the user's permission, the device automatically retrieves photos, videos, voice memos, text messages, and location information from digital sources using the smartphone, camera, and GPS sensor. This data is temporarily stored in local storage for analysis in later processes.

[0661] Step 2:

[0662] The terminal uploads the collected digital data to a cloud server. At this stage, the terminal standardizes the data format and adds metadata to enable efficient analysis on the server. The input is local digital data on the terminal, and the output is standardized format data uploaded to the cloud server.

[0663] Step 3:

[0664] The server receives uploaded data and analyzes it using image recognition technology (e.g., OpenCV) and sentiment analysis engine (e.g., Azure Cognitive Services). Input is digital data in a unified format, and output is extracted subject, location, and sentiment data. Specifically, it identifies people and locations from photographs and extracts sentiment from text messages and voice memos.

[0665] Step 4:

[0666] The server classifies the information based on the analysis results and assigns relevant tags to the data. The input is extracted data, and the output is tagged data. The tags classify the data based on themes such as "travel," "family," and "emotional experiences," organizing them as unified events.

[0667] Step 5:

[0668] The server uses tagged data and leverages a video editing library (e.g., FFmpeg) to generate slideshow-style visual content. The input is tagged data, and the output is visual content. The generated content includes voice narration and background music generated by a generative AI model.

[0669] Step 6:

[0670] The user requests the terminal to display a specific past moment using a prompt. In response to the request, the terminal displays the generated visual content via a projection device or display. The input consists of the user's prompt and the generated visual content; the output is the video displayed on the projection device.

[0671] 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.

[0672] This invention combines a system that organizes personal digital data and allows users to relive special moments with an emotion engine that recognizes the user's feelings. The terminal operates on the user's personal electronic devices and, with the user's permission, has the function of automatically acquiring various digital data (photos, videos, voice memos, text messages, GPS information).

[0673] This device uploads collected digital data to a cloud server. The server applies machine learning algorithms to the data, and an emotion engine is activated to analyze the emotions of people, places, and situations extracted from the data. The emotion engine identifies the user's emotions from images and audio and assigns emotion tags to the data based on the information.

[0674] Furthermore, the server recognizes relevant events based on the extracted information and generates personalized, viewable content based on tagged data. In this process, it can incorporate the user's emotional information recognized by the emotion engine, tailoring the viewing experience to be more emotionally engaging. The generated content is created and provided to the user in formats such as slideshows, videos, and audio presentations.

[0675] For example, if a user wants to relive memories of a past trip, the device uploads data acquired during that trip (photos, videos, GPS information related to the travel locations). The server uses an emotion engine to identify the user's emotions during the trip (joy, surprise, etc.) and assigns emotion tags to each data item based on that. Then, using the tagged data, the entire trip is recreated in a narrative format, generating content that resonates with the user's emotions.

[0676] Users can view content provided through a dedicated app and also have a more immersive experience through virtual reality (VR) and augmented reality (AR) devices. In this way, the present invention enhances the re-experience of personal special moments and provides a deeper emotional impact through a system configuration that takes user emotions into consideration.

[0677] The following describes the processing flow.

[0678] Step 1:

[0679] The device launches a dedicated application on the user's personal electronic device and automatically acquires digital data with the user's permission. This includes photos, videos, voice memos, GPS information, etc. The device then prepares to upload the acquired data to a cloud server at defined intervals while maintaining security.

[0680] Step 2:

[0681] The server receives the digital data uploaded from the terminal, first checks the data format, and then saves it to storage in a standardized format.

[0682] Step 3:

[0683] An emotion engine on the server operates, performing image recognition on received photo and video data and analyzing the facial expressions of the people contained within. Furthermore, it analyzes the tone and speed of voices from audio data to identify emotions.

[0684] Step 4:

[0685] The server assigns appropriate emotion tags to the digital data based on the extracted emotion information. This allows the data to be classified according to the user's emotions.

[0686] Step 5:

[0687] The server uses tagged data to identify relevant and important events. Here, events are automatically categorized based on the duration of the trip or specific dates.

[0688] Step 6:

[0689] When the server generates content for the user based on classified data, it incorporates previously recognized emotional information into the presentation. This results in video content with music and narration that aligns with the user's emotions.

[0690] Step 7:

[0691] Users view the generated content through a dedicated app. Furthermore, by using VR and AR devices, they can enjoy a more immersive experience and interactively relive special moments from the past.

[0692] (Example 2)

[0693] 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".

[0694] In today's information society, individuals generate vast amounts of electronic data in their daily lives, making it difficult to organize and utilize this data. In particular, there is a growing demand to relive special moments and memories, but a lack of appropriate systems to meet this need. Therefore, there is a need for systems that can organize data while taking individual emotions into account, and that can provide emotionally resonant re-experiences.

[0695] 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.

[0696] In this invention, the server includes means for automatically collecting various electronic data from a personal terminal, means for analyzing the collected electronic data and extracting the subject, location, and emotion, and means for recognizing related events based on the extracted information and attaching emotion tags to the data. This makes it possible to re-experience a person's special moments while being emotionally connected to them.

[0697] A "personal device" is an electronic device used by an individual, and is a device used for data collection and information processing.

[0698] "Electronic data" refers to information stored in digital format, including photographs, videos, audio, text, and location information.

[0699] An "emotion tag" is an identification piece of information attached to electronic data that indicates the emotional state contained within the data.

[0700] "Experiential content" refers to content that allows users to gain emotional value through viewing or experiencing it, and includes slideshows and video presentations.

[0701] A "virtual image environment" is a technology that provides a realistic experience through computer-generated images and information.

[0702] An "augmented video environment" is a technology that overlays digital information onto real-world images, providing users with an enhanced experience of interacting with the real world.

[0703] This invention is a system that makes it possible to relive special personal moments, and it consists of the interaction between a server, a terminal, and the user.

[0704] First, the device is a personal electronic device (e.g., a smartphone or tablet) that, with the user's permission, automatically collects various types of electronic data, such as photos, videos, voice memos, texts, and location information. This data is managed while monitoring the device's storage usage to prevent excessive data usage.

[0705] The collected electronic data is uploaded from the terminal to the server via a secure network connection. The server receives the collected data and performs analysis using machine learning algorithms. This includes processes that use image recognition and speech recognition technologies to identify objects, locations, and emotions. This process can utilize AI technologies from common cloud service providers.

[0706] After data analysis, the server uses an emotion engine to assign emotion tags to the data. The emotion engine analyzes images and audio based on the emotional states extracted from the data. As a result, the data is organized using emotion tags.

[0707] The server then generates personalized, interactive content based on the tagged data. This content takes the form of slideshows, videos, and audio presentations, enhancing the user's emotional experience. Generative AI models are used to create prompts and express the user's past events in an emotionally resonant way.

[0708] For example, if a user wants to relive a past trip, the device collects photos, videos, and location information recorded during that trip and uploads them to a server. The server analyzes this data, uses an emotion engine to identify emotions such as "fun" and "surprise," and assigns emotion tags. Next, the tagged data is used to recreate the travel experience in narrative form, providing the user with an emotionally engaging viewing experience. Users can view the generated content through a dedicated application.

[0709] An example of a prompt message could be: "Recreate the user's past travel memories as an emotionally engaging, narrative-style slideshow using emotional data. Based on the user's emotional information, create a presentation that highlights enjoyable and surprising moments during their travels."

[0710] This system allows users to deeply relive special moments and have a moving experience.

[0711] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0712] Step 1:

[0713] The device collects various electronic data from personal electronic devices with the user's permission. This data includes photos, videos, voice memos, texts, and location information. This data is appropriately categorized into folders, and after checking the storage status, important data is selected and temporarily stored on the device.

[0714] Step 2:

[0715] The device uploads the collected electronic data to the server via a secure network connection. The input is temporarily stored electronic data, while the output is saved to a database on the server. The upload process starts automatically when Wi-Fi is available, but users can also start the upload manually.

[0716] Step 3:

[0717] The server analyzes the received electronic data and processes it using image recognition and speech recognition technologies. The input is electronic data stored on the server, and the output is subject, location information, and sentiment data extracted from the data. Specifically, cloud-based machine learning algorithms are used to analyze the data and extract information from images and audio.

[0718] Step 4:

[0719] The server uses an emotion engine to tag the data with emotion based on the analyzed information. The input is the extracted emotion data, and the output is the data with emotion tags. This adds emotion labels to the data, making subsequent processing easier.

[0720] Step 5:

[0721] The server uses tagged data to generate personalized, interactive content. Input is data containing emotion tags, and output is content in the form of slideshows or video presentations that resonate with the user's emotions. A generative AI model is used to create narrative-style content based on prompt text.

[0722] Step 6:

[0723] Users view experiential content generated through a dedicated application. The input is the generated content, and the output is the emotionally engaging viewing experience derived from the played content. In this step, users can relive special moments by viewing the output content.

[0724] (Application Example 2)

[0725] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0726] When individuals wish to relive special moments, it is necessary to properly organize the digital data and efficiently perform emotionally-driven visualizations. However, conventional technologies simply play back large amounts of digital data, which is insufficient to provide the emotional re-experience that users desire. Furthermore, there is a lack of home systems that allow users to freely and deeply relive past moments.

[0727] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0728] In this invention, the server includes means for automatically collecting various digital information from personal information devices, means for analyzing the collected digital information and extracting the subject, location, and emotion, and means for acquiring emotion-tagged data in response to voice commands and presenting the experience using visualization and audio technologies. This makes it possible for users to easily access special moments from the past via voice commands and enjoy visual and audio re-experiences based on emotions.

[0729] "Personal information devices" are electronic devices owned by individuals and used for collecting and managing digital information.

[0730] "Digital information" refers to data expressed in electronic form, including images, audio, and location information.

[0731] "Analysis" is the process of extracting meaningful information from collected digital data, and it is achieved using machine learning algorithms and emotion recognition technologies.

[0732] "Extracting subjects, locations, and emotions" means identifying and extracting location information of people, objects, and places, as well as the emotions associated with them, contained within digital information.

[0733] "Voice commands" refer to an input method that uses voice to transmit commands to information devices and cause them to perform specific operations.

[0734] "Emotionally tagged data" refers to data that has been tagged based on emotional information extracted from digital information.

[0735] "Visualization technology" refers to technologies that visually represent digital information and facilitate re-experience.

[0736] "Voice technology" refers to technologies that reproduce digital information as sound and enable voice-based interaction.

[0737] "Presenting an experience" is the process of enabling users to gain new experiences by viewing and listening to digital information.

[0738] In the system for implementing this invention, the user's information device plays a central role. This information device includes smartphones and home assistant devices, which automatically collect various digital information from the user's daily life. This information is diverse, including images, audio, and location information, and after collection, it is uploaded to a cloud server.

[0739] The server applies machine learning algorithms to this digital information and uses image analysis techniques to extract the subject, location, and emotion. For emotion recognition, libraries such as OpenCV can be used, and for speech processing, speech synthesis libraries such as pyttsx3 can be combined. Based on the extracted emotion information, emotion tags are assigned to the data, and relevant content is generated based on the specified identification information.

[0740] Users can access this content using voice commands. For example, by sending a voice command such as "Show me the smiling photos from last year's trip" to a home device, the necessary emotion-tagged data is retrieved from the server and projected onto the wall via visualization technology (e.g., a projector). Voice technology is also used to output personalized audio guides, enhancing the quality of the re-experience.

[0741] An example of a prompt message might be: "Create a slideshow of past travel photos tailored to the user based on sentiment tags, add relevant music and narration, and explain it clearly to the user." This allows the user to have a more personal and immersive experience.

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

[0743] Step 1:

[0744] The device automatically collects digital information such as images, audio, and GPS data generated in the user's daily life. The input is raw data stored on the device. The collected data is uploaded to a cloud server with the user's permission. The output is the digital information uploaded to the server.

[0745] Step 2:

[0746] The server receives uploaded digital information and performs image and audio analysis. The input is the collected digital information. Using libraries such as OpenCV, it detects people and objects from images and extracts the user's emotions from facial expressions and audio using emotion recognition algorithms. This process yields data with emotion tags as output.

[0747] Step 3:

[0748] The server recognizes relevant events based on extracted sentiment-tagged data and generates content tailored to user specifications. The input is sentiment-tagged data. Prompt text is input to the generating AI model, which creates slideshows and narrations related to the user's past special moments. This step outputs content for presentation to the user.

[0749] Step 4:

[0750] The user inputs voice commands into the terminal. These inputs are the user's voice data. The terminal analyzes these voice commands and sends a request for relevant content to the server. This process prepares the server to select and output the appropriate content.

[0751] Step 5:

[0752] The server retrieves content based on voice commands and sends it to the terminal. The input is the user's request data. The terminal uses the retrieved data and plays the content using visualization and audio technologies. The output of this step is the content presented visually and audibly on the user's device.

[0753] Through these steps, users can immersively relive special moments based on their emotions.

[0754] 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.

[0755] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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."

[0763] 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.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0775] The following is further disclosed regarding the embodiments described above.

[0776] (Claim 1)

[0777] A means of automatically acquiring multiple types of digital data from personal electronic devices,

[0778] A means of analyzing acquired digital data to extract people, places, and emotions,

[0779] A means to recognize related events based on the extracted information and tag the data,

[0780] A means of generating personally viewable content using tagged data,

[0781] A means of providing generated content to individuals and enabling them to re-experience it,

[0782] A system that includes this.

[0783] (Claim 2)

[0784] The system according to claim 1, which identifies patterns related to specific events or emotions from acquired digital data and automatically classifies the relevant data.

[0785] (Claim 3)

[0786] The system according to claim 1, which displays generated personal content in a virtual reality or augmented reality environment to enhance the experience.

[0787] "Example 1"

[0788] (Claim 1)

[0789] A means of continuously collecting diverse information from personal information processing devices,

[0790] A means of analyzing the collected information and extracting the subject, location, and emotions,

[0791] A means for recognizing related events based on extracted identification information and classifying the information by identifier,

[0792] A means for generating individual viewable information representations using information classified by identifiers,

[0793] A means of providing the generated information representation to an individual and making it possible to re-experience it,

[0794] A system that includes this.

[0795] (Claim 2)

[0796] The system according to claim 1, which detects patterns related to specific events or emotions from collected information and automatically classifies the information based on those patterns.

[0797] (Claim 3)

[0798] The system according to claim 1, which displays the generated individual information representations in a virtual or extended environment to enhance the user experience.

[0799] "Application Example 1"

[0800] (Claim 1)

[0801] A means of automatically collecting data from multiple digital information sources,

[0802] A means of analyzing the collected data to extract the subject, location, and emotion,

[0803] A means of identifying related events and tagging the data based on the extracted information,

[0804] A means of generating individually designed visual information using tagged data,

[0805] A means of providing generated visual information to an individual and enabling them to recreate past experiences,

[0806] A means for displaying the generated visual information using a projection device,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, which recognizes regularities related to specific events or emotions from collected digital information and automatically organizes related data.

[0810] (Claim 3)

[0811] The system according to claim 1, which presents generated, individually designed visual information in an immersive display system to enhance the experience.

[0812] "Example 2 of combining an emotion engine"

[0813] (Claim 1)

[0814] A means of automatically collecting various electronic data from personal devices,

[0815] A means of analyzing collected electronic data to extract the subject, location, and emotions,

[0816] A means of recognizing related events based on extracted information and assigning sentiment tags to the data,

[0817] A means of generating individual experiential content based on tagged data,

[0818] A means to provide the generated content to the user and enable the reproduction of a specific moment,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, which identifies patterns corresponding to specific events or emotions from collected electronic data and automatically classifies related data.

[0822] (Claim 3)

[0823] The system according to claim 1, which displays the generated individual experiential content in a virtual video environment or an augmented video environment to enhance the experience.

[0824] "Application example 2 when combining with an emotional engine"

[0825] (Claim 1)

[0826] A means of automatically collecting various digital information from personal information devices,

[0827] A means of analyzing collected digital information to extract the subject, location, and emotions,

[0828] A means for recognizing related events based on extracted information and adding identifying information to the data,

[0829] A means for generating individual viewable information using data to which identification information has been added,

[0830] A means of providing generated information individually and enabling a re-experience,

[0831] A means of acquiring emotion-tagged data in response to voice commands and presenting an experience using visualization and voice technologies,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which identifies patterns related to specific events or emotions from acquired digital information and automatically organizes related information.

[0835] (Claim 3)

[0836] The system according to claim 1, which presents the generated individual information in a virtual or alternative reality environment to enhance the experience. [Explanation of Symbols]

[0837] 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. A means of automatically acquiring multiple types of digital data from personal electronic devices, A means of analyzing acquired digital data to extract people, places, and emotions, A means to recognize related events based on the extracted information and tag the data, A means of generating personally viewable content using tagged data, A means of providing generated content to individuals and enabling them to re-experience it, A system that includes this.

2. The system according to claim 1, which identifies patterns related to specific events or emotions from acquired digital data and automatically classifies the relevant data.

3. The system according to claim 1, which displays generated personal content in a virtual reality or augmented reality environment to enhance the experience.

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