System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving and storing documents, images, and video data of a deceased person; means for analyzing the stored data and generating an artificial intelligence model for learning characteristics of the deceased person; interface means for interacting with the generated artificial intelligence model; means for cooperating with a messaging application via communication means and collecting data of interactions with the deceased person; and means for updating and improving the artificial intelligence model using the collected data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, digital technology for remembering the deceased has been developing, but traditional methods have focused on memorial portraits and video messages, with limited means for interactive communication. As a result, it is difficult to deepen bonds with the deceased. Furthermore, there is a lack of means to accurately recreate the personality and behavior of the deceased, making it difficult for bereaved family and friends to find comfort and encouragement through dialogue with the deceased. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes: means for receiving and storing document, image, and video data of the deceased; means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased; interface means for interacting with the generated AI model; means for linking with a messaging application via a communication means to collect data on interactions with the deceased; and means for updating and improving the AI ​​model using the collected data. This allows users to experience a conversation with the deceased, making it possible to more faithfully reproduce the personality and behavior of the deceased. Voice and text input is possible through the interface means, and the digital portrait generates responses based on the AI ​​model, achieving a realistic dialogue.

[0006] The term "deceased" refers to an individual who has died and is important to family and friends.

[0007] "Documents" include text data such as letters and notes written by the deceased.

[0008] "Images" include visual data such as photographs or drawings of the deceased.

[0009] "Video" includes video data that records the movements and sounds of the deceased.

[0010] "Preservation" refers to the safekeeping of digital data on electronic media.

[0011] "Analysis" involves detailed analysis of the deceased's documents and image data to extract characteristics and patterns.

[0012] An "artificial intelligence model" is a machine learning model that learns from large amounts of data to perform specific tasks.

[0013] An "interface" is a means by which a user interacts with a system, and has the ability to accept voice and text input.

[0014] A "communication means" is a system that includes the technologies and protocols for sending and receiving data.

[0015] A "messaging application" is software or a service that allows users to send and receive messages.

[0016] "Collection" is the process of gathering and storing the necessary data.

[0017] "Update" refers to improving existing data or models with new information.

[0018] "Improvement" refers to increasing the performance or accuracy of a system or model.

[0019] A "digital memorial portrait" is a memorial portrait that is displayed electronically based on an image or video of the deceased.

[0020] "Response" refers to a reply or reaction to a question from a user.

[0021] "Voice input" is a means of capturing the user's speech into the system.

[0022] "Text input" is the means by which a user inputs characters. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0025] First, the terms used in the following description will be explained.

[0026] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0027] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0028] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0029] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0030] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0034] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0035] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0036] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0037] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0038] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0041] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0042] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0043] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0044] This invention is a system that vividly recreates the personality and memories of a deceased person by receiving and storing document, image, and video data of the deceased, analyzing that data, and generating an AI model that has learned the characteristics of the deceased. Specific embodiments are described below.

[0045] 1. Data collection and storage

[0046] Users can digitize letters, notes, photos, video messages, and other documents from the deceased and upload them to the server via a dedicated application or web portal. For example, users can take a photo of a letter from the deceased with their smartphone and upload the image to the server.

[0047] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into text using voice recognition technology.

[0048] 2. Data collection through LINE integration

[0049] The user authorizes integration with the messaging application. This integration is achieved by the user providing account information and granting access to the system. For example, the user logs in to their LINE account and grants permission for the system to obtain data.

[0050] The server collects chat history and message data from authorized messaging applications, creating a database of interactions and conversation styles with the deceased.

[0051] 3. Generating AI models

[0052] The server analyzes the collected data. Specifically, it uses natural language processing (NLP) algorithms to extract keywords, frequently occurring phrases, and speech patterns from the text. Based on the results of this analysis, an AI model that learns the characteristics of the deceased is generated.

[0053] The resulting AI model is then used to recreate the writing style and speaking patterns of the deceased. For example, if it is determined that the deceased frequently used the word "thank you," the model will reflect that same tendency.

[0054] 4. Dialogue with a digital portrait

[0055] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0056] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0057] The terminal displays the response from the server and continues the dialogue with the user. This interactive experience allows the user to reaffirm their bond with their deceased loved one.

[0058] 5. Update and improve AI models

[0059] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model, which allows the system to continually improve and increase its ability to provide more natural responses.

[0060] For example, when a user asks the system, "How are you doing lately?", the system extracts the appropriate context from past data and generates a response such as, "I've been a little busy lately, but I'm doing well."

[0061] The above is a specific embodiment for carrying out the present invention. As a tool for remembering the deceased, the system can ease the user's grief and provide comfort through dialogue with the deceased.

[0062] The processing flow will be explained below.

[0063] Step 1: Data collection

[0064] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal.

[0065] The server receives the uploaded data and stores it electronically.

[0066] Step 2: Data conversion

[0067] The server converts the image data into text data using OCR (optical character recognition) technology.

[0068] Example: Converting an image of a letter to text.

[0069] The server converts the video data into text using voice recognition technology.

[0070] Example: Converting audio to text for video messages.

[0071] Step 3: LINE integration

[0072] The user allows collaboration with the messaging application.

[0073] The server collects chat history and message data from authorized messaging applications.

[0074] Step 4: Data analysis

[0075] The server analyzes the collected text data using natural language processing (NLP) technology.

[0076] The server extracts keywords, frequent phrases, and speaking patterns from the text.

[0077] Step 5: Artificial Intelligence Model Generation

[0078] Based on the analysis results, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0079] The server integrates the generated artificial intelligence model into the digital memorial portrait system.

[0080] Step 6: Provide a conversational interface

[0081] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0082] The user speaks to the deceased via voice or text.

[0083] Step 7: Submitting input data

[0084] The terminal transmits the input data from the user to the server.

[0085] Step 8: Response Generation

[0086] The server uses artificial intelligence models to generate appropriate responses based on the received user input data.

[0087] Step 9: View the response

[0088] The terminal displays the response from the server to the user and continues the dialogue.

[0089] Step 10: Update and improve the AI ​​model

[0090] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0091] The server redeploys the updated AI model and reflects it throughout the system.

[0092] The above is the specific processing flow of the system.

[0093] Example 1

[0094] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0095] While there are many ways to commemorate the deceased, existing technologies have difficulty vividly recreating the deceased's personality and memories. In particular, there are few systems that can recreate an individual's writing style and speaking style and allow users to feel a connection with the deceased through conversation. Furthermore, the lack of specific technological means to efficiently and accurately collect and analyze the deceased's data and generate artificial intelligence models risks degrading the quality of the conversation experience with the deceased.

[0096] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0097] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for converting image data into character data using optical character recognition technology, means for converting voice data into text data using voice recognition technology, means for analyzing the stored data and extracting keywords and frequently occurring phrases from the data using natural language processing technology to generate an AI model, interface means for interacting with the generated AI model, means for linking with a message application via communication means to collect data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for displaying the generated responses to the user. This allows the personality and memories of the deceased to be vividly reproduced, making it possible to feel a bond with the deceased through interaction.

[0098] "Documents of the deceased" refers to text data such as letters, notes, memos, and diaries written by the deceased during their lifetime.

[0099] "Image data" refers to still image data that has been digitized from photographs or handwritten text of the deceased.

[0100] "Video data" refers to video data that records the deceased's video messages and daily activities.

[0101] "Means for receiving and storing" refers to the function of digitally capturing documents, image data, and video data of the deceased person provided by the user and storing them on a server.

[0102] Optical character recognition (OCR) is a technology that automatically reads characters contained in image data and converts them into text data.

[0103] "Speech recognition technology" is a technology that analyzes the audio contained in video data and converts it into text data.

[0104] "Means for analysis" refers to a function that uses natural language processing technology to extract keywords and frequently occurring phrases from stored data and analyze the characteristics of the deceased.

[0105] An "artificial intelligence model" is a computer program that learns the writing style and speaking style of the deceased from collected and analyzed data.

[0106] "Interface means" refers to input and output functions that allow a user to interact with an artificial intelligence model using voice or text.

[0107] "Communication means" refers to the ability to send and receive data to and from message applications via the Internet or other communications networks.

[0108] A "messaging application" is software for chatting and exchanging messages.

[0109] "Means of updating and improving" refers to the ability to use new data collected to improve the accuracy of the artificial intelligence model and enable it to generate more natural responses.

[0110] The "means for generating a response" is a function that creates an appropriate response to an input from a user based on the generated artificial intelligence model.

[0111] The "means for displaying" is a function that provides the response from the server to the user visually or audibly.

[0112] This invention is a system for recreating the personality and memories of a deceased person by receiving and storing documents, images, and video data of the deceased, analyzing the data, and generating an artificial intelligence model. Specific embodiments are described below.

[0113] 1. Data collection and storage

[0114] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0115] The server receives and stores the uploaded data. When storing, image data is converted to text data using Tesseract OCR, and video messages are converted to text data using the Google Speech-to-Text API.

[0116] 2. Data collection through LINE integration

[0117] The user authorizes integration with a messaging application. The user provides account information and completes the procedure to allow access to the system. For example, the user logs in to their LINE account and gives the system permission to obtain data.

[0118] The server collects chat history and message data from authorized messaging applications, which is used to model interactions and conversational styles with the deceased.

[0119] 3. Generating AI models

[0120] The server analyzes the collected data using Python's natural language processing libraries, NLTK and SpaCy. This extracts keywords, frequent phrases, and speech patterns from the text, generating an AI model that learns the characteristics of the deceased. For example, if the deceased frequently used the word "thank you," this will be reflected in the model.

[0121] 4. Dialogue with a digital portrait

[0122] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0123] The server receives input from the user and uses the generated artificial intelligence model to generate an appropriate response. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0124] The terminal displays the response from the server and continues the dialogue with the user, allowing the user to enjoy the experience of interacting with the deceased.

[0125] 5. Update and improve AI models

[0126] The server analyzes records of user interactions and performs updates to improve the accuracy of the artificial intelligence model. This allows the system to continuously improve and become more capable of providing more natural responses. For example, if the system is asked by a user, "How are you doing lately?", it can extract appropriate context from past data and generate a response such as, "I've been a little busy lately, but I'm doing well."

[0127] Specific examples

[0128] For example, if a user uploads letters and photos of their deceased grandfather, the system analyzes them and learns the grandfather's characteristic speaking style and vocabulary. Based on this learning result, when a user asks, "Grandpa, how are you?", the system can generate a response such as, "I'm fine, thank you!"

[0129] Prompt Sentence Examples

[0130] "I've uploaded a letter from a deceased person. Please analyze it and extract features."

[0131] "Since you have authorized the integration of LINE messages, please collect chat data with the deceased person and learn their conversation style."

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1: Upload your data

[0134] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0135] Input: Digitized image and video data

[0136] Output: Raw data stored on the server

[0137] Specific operation: The user launches the app on their smartphone, presses the upload button, and selects the data they want to save. The app then sends the data to the server, which receives and saves it.

[0138] Step 2: Transform the data

[0139] The server converts uploaded image data into text data using Tesseract OCR, and converts video messages into text data using the Google Speech-to-Text API.

[0140] Input: Uploaded raw data (image data and video data)

[0141] Output: Parsed text data

[0142] Specific operation: The server launches Tesseract OCR, receives image data as input, and generates text data. Similarly, it inputs video data into the Google Speech-to-Text API and converts the audio into text data.

[0143] Step 3: Collecting data from messaging applications

[0144] The user authorizes integration with a messaging application (e.g., LINE). The user provides account information and completes the procedure to authorize access to the system.

[0145] The server collects chat history and message data from authorized messaging applications.

[0146] Input: Account information that is allowed to be linked

[0147] Output: Captured chat history and message data

[0148] Specific operation: The user logs in to their LINE account and grants permission to the system to retrieve data. The server uses the API to collect past chat history from LINE and saves it in a database.

[0149] Step 4: Analyze the data and generate an artificial intelligence model

[0150] The server analyzes the collected data, using Python natural language processing libraries NLTK and SpaCy to extract keywords, frequent phrases, and speaking patterns from the text.

[0151] Input: Parsed text data and chat history

[0152] Output: AI model that has learned the characteristics of the deceased

[0153] How it works: The server uses NLTK or SpaCy to analyze text data and extract distinctive writing styles and keywords. It then uses machine learning algorithms to generate an AI model based on these features.

[0154] Step 5: User interaction

[0155] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0156] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model.

[0157] The terminal displays the response from the server and continues the dialogue with the user.

[0158] Input: User voice or text input

[0159] Output: The generated response message

[0160] How it works: When a user speaks to the device, the device converts the speech into text and sends it to the server. The server then inputs the resulting text into an artificial intelligence model to generate a response. The generated response is then sent back to the device and displayed to the user.

[0161] Step 6: Analyze interaction data and update the model

[0162] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0163] Input: Record of user interaction

[0164] Output: Updated artificial intelligence model

[0165] How it works: The server analyzes user interaction records to learn frequent patterns and new keywords, then retrains the existing AI model with the new information to improve its accuracy.

[0166] The above are the specific processing steps of this system.

[0167] (Application example 1)

[0168] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0169] Tools for remembering the deceased are limited to physical possessions and photographs, making it difficult to converse with the deceased or reminisce about memories. Furthermore, there are still no systems in place that use digitized information to recreate the personality and characteristics of the deceased and provide an interactive experience. There is a need for a system that allows people to converse with the deceased and relive memories in physical stores.

[0170] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0171] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for providing an interactive interface with the deceased in a physical store, and means for updating and improving the AI ​​model using the collected data. This allows users to interactively experience memories with the deceased even in a physical store, enriching their interactions with the deceased and recreating their memories.

[0172] "Documents, images and video data of the deceased" refers to various forms of digitized information left behind by the deceased during their lifetime, such as handwritten letters, diaries, photographs and video messages.

[0173] "Means for receiving and storing" refers to the technology and systems that allow the server to receive digital data uploaded by users and store it electronically.

[0174] "Means for analyzing and generating an AI model that learns the characteristics of the deceased" refers to technology that analyzes stored digital data using natural language processing and image recognition algorithms to create an AI model that reproduces the speech, behavior, and style of the deceased.

[0175] "Interface means" refers to the input and output devices through which a user interacts with an artificial intelligence model, and the software that manages that interaction.

[0176] "Linking with a messaging application via a communication means" refers to technology that links a user's messaging application account with the system using the Internet or other communication protocols.

[0177] "Data of interactions with the deceased" refers to message exchanges and chat history between the user and the deceased while they were alive.

[0178] "Means for providing an interactive interface with the deceased in a physical store" refers to hardware and software for providing an environment in which users can interact with an artificial intelligence model of the deceased through terminals or kiosks installed in a physical store.

[0179] "Means of updating and improving" refers to technologies for improving the accuracy of AI models and the naturalness of their responses based on new collected data and user interaction logs.

[0180] This invention is an interactive system that recreates the personality and memories of a deceased person by using documents, images, and video data of the deceased to generate an artificial intelligence model and provide an interactive interface in a physical store.

[0181] Data collection and storage

[0182] Users upload digital data such as letters, records, photos, and video messages from the deceased to the server using dedicated terminals in the store. Optical character recognition (OCR) and voice recognition technologies are used to convert image and audio data into text data, which is then saved as text. The server receives the uploaded data and stores it electronically.

[0183] Generating AI models

[0184] The server analyzes the stored data and uses natural language processing (NLP) algorithms to generate an AI model that learns the characteristics of the deceased, such as extracting keywords, frequent phrases, and speech patterns from the text. The generated AI model is then used to recreate the writing style and speaking style of the deceased.

[0185] Providing interactive interfaces in physical stores

[0186] The terminal installed in the store acts as a digital memory consultant, providing an interface that allows users to interact with the deceased. Users can speak to the deceased by voice or text. This input is sent to the server via the interface. The server uses the generated artificial intelligence model to generate an appropriate response and sends it back to the terminal. Users can view this response and enjoy interacting with the deceased.

[0187] AI model updates and improvements

[0188] The server analyzes the conversation records and continuously updates the AI ​​model to improve its accuracy. This allows the system to provide more natural responses over time. For example, if a user asks, "How are you doing lately?", the system can extract appropriate context from past data and generate a response such as, "I've been a bit busy lately, but I'm doing well."

[0189] Specific examples

[0190] For example, if a user asks, "Dad, how was your day?", the system will respond, "I worked in the garden all day today. The flowers are blooming beautifully." An example of a prompt sentence is, "If a user asks about the deceased's hobbies, please provide appropriate context and generate a response. For example, in response to a user question: 'Dad, what are your hobbies these days?', the deceased's response would be, 'I've been into photography lately. I take pictures in various places while walking.'"

[0191] Through this system, users can interactively experience memories of the deceased even in a physical store, allowing them to enjoy interacting with the deceased and reliving memories in a richer way.

[0192] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0193] Step 1:

[0194] The user uploads the document, image, and video data of the deceased person to the server using a terminal in the store. This uploaded data is received by the server and stored electronically. The input is digitized document, image, and video data, which the server converts into a data format for storage and stores on the file server. Specifically, the user uses the upload function of the terminal to select the data file of the deceased person and presses the "upload" button.

[0195] Step 2:

[0196] The server applies OCR or speech recognition technology to the uploaded data, converting image data or audio data into text data. This process uses OCR software (e.g., Tesseract OCR) or speech recognition software (e.g., Google Cloud Speech-to-Text). The input is image data or audio data, and the output is text data obtained by analyzing it. Specifically, the server passes an image file to the OCR software and receives the text as a processing result, or passes an audio file to speech recognition software and converts it into a string of characters.

[0197] Step 3:

[0198] The server analyzes the stored text data using a natural language processing (NLP) algorithm to generate an AI model that learns the characteristics of the deceased. Specifically, it uses Hugging Face's Transformer library, taking text data as input and outputting a generative AI model that reflects the deceased's behavior and conversation style. Specifically, it preprocesses the text data, inputs it into an NLP module, and trains the model.

[0199] Step 4:

[0200] The user uses an interface through a terminal to interact with an AI model of the deceased person. The user inputs voice or text, which is then sent to a server. The server analyzes the voice or text input and uses the AI ​​model to generate an appropriate response. Specifically, the user asks a question into a microphone, and the voice is converted into text and sent to the server.

[0201] Step 5:

[0202] The server generates a response based on the generated AI model and sends it back to the device. The input is the analysis result of the user's question, and the output is a response text that reproduces the deceased's writing style and speaking manner. Specifically, the server generates a prompt based on the dialogue log, inputs it into the AI ​​model to generate a text response, and sends it to the device.

[0203] Step 6:

[0204] The server analyzes the dialogue log with the user and updates the AI ​​model to improve its accuracy. The input is the dialogue log with the user, and the output is the updated AI model. Specifically, the server analyzes the dialogue log and re-learns frequently used phrases and patterns.

[0205] In this way, a system has been created that provides an interactive experience that recreates memories and conversations with the deceased, enabling rich dialogue even in physical stores.

[0206] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0207] This invention provides a system that vividly recreates the personality and memories of a deceased person and further recognizes the user's emotions and adjusts responses accordingly. This system receives and stores document, image, and video data of the deceased, analyzes the data, and generates an artificial intelligence model that learns the characteristics of the deceased. Furthermore, by combining it with an emotion engine, it is possible to recognize the user's emotional state and generate responses accordingly. Specific embodiments are described below.

[0208] 1. Data collection and storage

[0209] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to a server through a dedicated application or web portal. This uploading is done to permanently preserve memories of the deceased as digital data. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file to the server.

[0210] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into audio data using voice recognition technology.

[0211] 2. Data collection through LINE integration

[0212] The user allows the system to connect to a messaging application. This connection allows the system to collect chat history and message data with the deceased. For example, the system can obtain messages exchanged between the deceased and the user on LINE.

[0213] The server collects chat history and message data from authorized messaging applications and stores it in a database, which allows for a better understanding of the conversation style and language used with the deceased.

[0214] 3. Generating AI models

[0215] The server analyzes the collected data using natural language processing (NLP) technology. Specifically, it extracts keywords and frequently occurring phrases in the text, as well as speech patterns. For example, if the deceased frequently used the word "thank you," that tendency can also be learned.

[0216] Based on the analysis results, the server generates an AI model that learns the characteristics of the deceased. This model is used to recreate the deceased's writing style and speaking style. The AI ​​model is then integrated into the digital memorial portrait system.

[0217] 4. Incorporating an Emotional Engine

[0218] The server uses an emotion engine to analyze the user's voice and text data and recognize their emotions. For example, if a user says "I feel lonely" in a sad voice, the emotion engine will recognize that emotion as "sadness."

[0219] Based on the recognized emotion, the server adjusts the response generated by the AI ​​model. For example, if the user speaks to the deceased in a sad voice, the AI ​​model of the deceased person will offer comforting words such as, "It's okay, I'm always here for you."

[0220] 5. Dialogue with a digital portrait

[0221] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0222] The server receives input data from the user and uses artificial intelligence models and emotion engines to generate appropriate responses. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay."

[0223] The terminal displays the response from the server to the user and continues the dialogue, allowing the user to enjoy an interactive dialogue with the deceased.

[0224] 6. Update and improve AI models

[0225] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0226] As a concrete example, consider a situation where a user asks, "How are you doing lately?" In this case, if the emotion engine recognizes the user's emotion as "relief" or "curiosity," the server will respond with, "I'm fine, how are you?"

[0227] The above is a specific embodiment of the present invention. As a tool for remembering the deceased, the present system aims to provide a richer interactive experience while deeply understanding the user's emotions.

[0228] The processing flow will be explained below.

[0229] Step 1: Data collection

[0230] Users digitize letters, notes, photos, and video messages from the deceased and upload them to a server through a dedicated application or web portal.

[0231] The server receives the uploaded digital data and stores it in secure electronic storage.

[0232] Step 2: Data conversion

[0233] The server converts the stored image data into text data using OCR (optical character recognition) technology.

[0234] Example: Scan an image of a letter and convert the text written on it into text data.

[0235] The server converts the audio of the stored video data into text using voice recognition technology.

[0236] Example: Analyzing the audio portion of a video message and converting its content into text data.

[0237] Step 3: LINE integration

[0238] The user allows the messaging application to link with the system.

[0239] The server collects chat history and message data from authorized messaging applications.

[0240] Example: Obtain chat history between the deceased and the user from LINE and save it as text data.

[0241] Step 4: Data analysis

[0242] The server analyzes the collected text data of the deceased using natural language processing (NLP) technology.

[0243] Example: Extracting frequent phrases and keywords from text data and analyzing the tone and style of writing.

[0244] Based on the analysis results, the server incorporates the characteristics of the deceased into a model.

[0245] Step 5: Artificial Intelligence Model Generation

[0246] Based on the results of the data analysis, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0247] For example, learning the speech habits and specific expressions of the deceased and incorporating them into the model.

[0248] The server prepares the generated AI model for integration into the digital memorial portrait system.

[0249] Step 6: Incorporating the Emotion Engine

[0250] The server incorporates an emotion engine that analyzes the user's voice or text data and recognizes emotions.

[0251] For example: If a user says "I feel sad...", the emotion engine will recognize the emotion "sad".

[0252] The server adjusts the response of the artificial intelligence model based on the recognized emotion.

[0253] For example, if the user is feeling sad, the AI ​​model responds, "Don't worry, I'll always be here for you."

[0254] Step 7: Providing a conversational interface

[0255] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0256] Example: A user opens an interactive screen that displays a digital portrait of a deceased person.

[0257] Users can speak to the deceased through voice or text.

[0258] Step 8: Submitting input data

[0259] The terminal transmits voice or text input data from the user to the server.

[0260] Step 9: Response Generation

[0261] The server uses an AI model to generate an appropriate response based on the received user input data and emotion recognition results.

[0262] For example, if a user says, "I miss you," the AI ​​model will consider the emotion and respond, "I miss you too. But it's okay, we'll be together."

[0263] Step 10: View the response

[0264] The terminal displays the response from the server to the user and continues the dialogue.

[0265] Step 11: Update and improve the AI ​​model

[0266] The server analyzes the dialogue records and performs updates to improve the accuracy of the AI ​​model and emotion engine.

[0267] Example: Improving AI models based on user feedback and new interaction data.

[0268] The server redeploys the updated AI model and reflects it throughout the system.

[0269] The above is the specific processing flow of the system.

[0270] Example 2

[0271] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0272] There is a need for a system that can vividly recreate memories of the deceased while recognizing the user's emotions and adjusting its responses. However, conventional systems have not only struggled to accurately reproduce the characteristics and speaking style of the deceased, but also failed to generate responses that correspond to the user's emotional state. This has prevented users from having a natural conversational experience with the deceased, making it difficult to achieve emotional satisfaction.

[0273] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for recognizing the user's emotions and adjusting responses using an emotion engine. This enables a natural interaction experience with the deceased, and provides the user with emotional satisfaction.

[0274] "Deceased documents, images and video data" refers to information stored in digital form that contains personal memories and recollections, such as letters, diaries, photographs and video messages left by the deceased during their lifetime.

[0275] "Means for receiving and storing" refers to a mechanism for receiving digital data provided by a user and storing it in an appropriate form, using a server, database, etc.

[0276] "Means for analyzing and generating an artificial intelligence model that learns the characteristics of the deceased" refers to technology that analyzes collected data using natural language processing and machine learning techniques to model the speaking style and vocabulary of the deceased.

[0277] An "interface means" is a combination of software and hardware that allows a user to interact with a system through voice and / or text.

[0278] "Linking with a messaging application via a communication means" refers to the function of exchanging data with a messaging application using the Internet or other communication protocols.

[0279] "Means of collecting data on interactions with the deceased" refers to methods for importing past chat history and message content into the system through LINE or other messaging applications.

[0280] "Means of updating and improving artificial intelligence models using collected data" refers to a method for improving the accuracy and response capabilities of artificial intelligence by analyzing records of interactions with users and applying new information to the model.

[0281] "Means for recognizing user emotions and adjusting responses using an emotion engine" is a technology for analyzing the emotional state of a user from their voice or text and optimizing the system response based on that.

[0282] This invention provides a system that recreates the personality and memories of a deceased person, recognizes the user's emotions, and adjusts responses accordingly. This system receives and stores documents, images, and video data of the deceased, analyzes them, and generates an artificial intelligence model. It also uses an emotion engine to recognize the user's emotions and adjust responses accordingly. Specific embodiments are described below.

[0283] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file using a dedicated application.

[0284] The server receives the uploaded data and stores it in a database. During this data storage process, image data is converted into text data using "Tesseract OCR." For video data, audio data is converted into text using "Google Speech-to-Text." This makes it possible to process the stored data as text.

[0285] By allowing the user to connect to a messaging application (e.g., LINE), the system can import chat history and past message data with the deceased person. The server then collects the chat history and message data from the authorized messaging application and stores them in a database. This allows for the reproduction of more natural conversations.

[0286] The server then analyzes the collected data using natural language processing (NLP) techniques. Specifically, it uses libraries such as SpaCy and NLTK to extract keywords, frequent phrases, and speech patterns from the text. Based on the results of this analysis, the server uses generative AI models such as GPT-3 and BERT to generate an AI model that reflects the characteristics of the deceased.

[0287] The server then uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to create an emotion engine. This engine analyzes the user's voice and text data to recognize emotions. Once the user's emotion is recognized, the server can adjust the response provided by the generated AI model based on that emotion. For example, if the user sadly says "I'm lonely," the emotion engine will recognize that emotion as "sadness" and provide comforting words.

[0288] The device displays a digital portrait and provides an interface that allows users to interact with the deceased. When the user speaks to the deceased by voice or text, the input data is sent via the device to the server. The server uses an artificial intelligence model and emotion engine to generate an appropriate response based on the received data. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay," and sends it to the device. The device then displays this response to the user, allowing the conversation to continue.

[0289] Finally, the server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0290] Examples of concrete examples and prompts

[0291] A user takes a photo of a letter from a deceased person and uploads it through the app:

[0292] "Please take a photo of the letter from the deceased person with your smartphone and upload this image file using a dedicated application."

[0293] Situations where the user allows integration with the LINE app:

[0294] "Please allow the LINE app to connect and import the chat history with the deceased person into the system."

[0295] The server generates an AI model of the deceased person:

[0296] "The collected data is used to generate an artificial intelligence model that learns the characteristics of the deceased."

[0297] A scene where the server recognizes emotions and adjusts responses:

[0298] "If the user speaks in a sad voice, it will recognize that emotion and offer words of comfort."

[0299] A scene where you interact with a digital portrait:

[0300] "Interact with the digital portrait via voice or text and enjoy the responses."

[0301] In this way, it is possible to vividly recreate memories of the deceased and provide natural dialogue that matches the user's emotions.

[0302] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0303] Step 1: Collect and store data

[0304] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. The input data is image files of letters and video files. The server receives this data and stores it in a database. For image data, it uses "Tesseract OCR" to convert it into text data, and for video data, it uses "Google Speech-to-Text" to convert audio data into text. The output is text data. For example, if a user uploads a photo of a letter, the server analyzes the image and saves it as text data.

[0305] Step 2: Data collection through LINE integration

[0306] The user allows integration with a messaging application. The input is permission to integrate with a messaging application such as LINE. The server collects chat history and message data from the authorized messaging application and stores it in a database. The output is chat history in text format. As a specific example, when the user allows integration with LINE, the server obtains past message data with the deceased person and stores it.

[0307] Step 3: Generate an artificial intelligence model

[0308] The server uses natural language processing (NLP) technology to analyze the data collected in steps 1 and 2. The input is text data. Specifically, it uses "SpaCy" or "NLTK" to extract keywords, frequently occurring phrases, and speaking patterns within the text. Based on the analysis results, the server generates an artificial intelligence model using "GPT-3" or "BERT." The output is an AI model that reproduces the writing style and speaking style of the deceased. For example, it learns phrases frequently used by the deceased and generates an AI model that reflects them.

[0309] Step 4: Incorporating the Emotion Engine

[0310] The server uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to analyze the user's voice and text data and recognize emotions. The input is voice and text data containing the user's emotions. The emotion engine performs the analysis, and the server adjusts the response generated by the AI ​​model based on the recognized emotion. The output is a response text appropriate to the emotion. For example, if a user sadly says "I'm lonely," the emotion engine will recognize the emotion as "sadness" and respond with "It's okay, I'm always here for you."

[0311] Step 5: Interact with the digital portrait

[0312] The terminal displays the digital portrait and provides an interface that allows interaction with the user. Input is voice or text data from the user. The server receives the input data from the user and generates an appropriate response using the generated artificial intelligence model and emotion engine. The output is a dialogue-style response text. The terminal displays this response to the user, and the dialogue continues through the interface. For example, if the user says "I miss you," the server responds "I miss you too, but it's okay," and the terminal displays it.

[0313] Step 6: Update and improve the AI ​​model

[0314] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model and emotion engine. The input is the dialogue records. Based on these records, machine learning technology is used to improve the model. Specifically, when a user asks "How are you doing lately?", the response is evaluated and improvements are made. The output is an AI model with improved accuracy.

[0315] (Application example 2)

[0316] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0317] To remember a deceased loved one, it is important to not only look back at photos and videos of that person, but also to be able to interactively experience deeper memories. However, current systems have difficulty not only reproducing the characteristics of the deceased, but also accurately recognizing the user's emotions and responding accordingly. Furthermore, there are not enough systems in place to allow users to enjoy conversations with the deceased in physical settings such as brick-and-mortar stores.

[0318] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0319] In this invention, the server includes: means for receiving and storing document, image, and video data of the deceased; means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased; interface means for interacting with the generated AI model; means for linking with a message application via communication means and collecting data on interactions with the deceased; means for updating and improving the AI ​​model using the collected data; means for allowing a user to enjoy interactive conversations with the deceased using smart glasses or a head-mounted display; and means including an emotion engine that recognizes the user's emotions and reflects them in responses. This allows a user to have a deeper, more emotional experience interacting with the deceased, making it possible to enjoy interactive conversations even in physical stores.

[0320] "Documents" are text data such as letters and notes written by the deceased.

[0321] "Images" are visual data such as photographs or illustrations of the deceased.

[0322] "Video data" refers to video or recorded footage of the deceased.

[0323] "Means of receiving and storing" refers to the mechanisms and software that capture data on digital devices or servers and store it securely.

[0324] "Analysis" is the process of extracting features and patterns from received and stored data.

[0325] An "artificial intelligence model" is an AI system that learns and reproduces the characteristics of the deceased.

[0326] "Means of generation" refers to the process of creating an artificial intelligence model based on the results of data analysis.

[0327] An "interface means" is an input and output mechanism by which a user interacts with a system.

[0328] "Communication means" refers to the technology that allows a system to exchange data with other devices and applications.

[0329] A "messaging application" is a software application that allows for sending and receiving messages.

[0330] "Means of collection" are the methods or techniques used to obtain data from messaging applications.

[0331] "Means of updating and improving" refers to the way new data collected is used to optimize and improve the AI ​​model.

[0332] "Smart glasses" are wearable eyeglass-type devices that have the ability to display information.

[0333] A "head-mounted display" is a device worn on the head that displays images in the field of vision.

[0334] "Interactive dialogue" refers to a form in which the user and the system interact with each other and respond in real time.

[0335] An "emotion engine" is a system that recognizes emotions from a user's voice or text and generates a response accordingly.

[0336] MODE FOR CARRYING OUT THE INVENTION

[0337] In an embodiment of the present invention, documents, images, and video data of the deceased person are first digitized and sent to a server. The server receives and stores the data using the following hardware and software:

[0338] Hardware: Digital devices, servers

[0339] Software: Data storage system

[0340] The server then analyzes the stored data and uses natural language processing (NLP) techniques to learn the characteristics of the deceased, using the following software:

[0341] Software: Natural language processing technology

[0342] The analyzed data is used to generate an artificial intelligence model, which is then used to recreate the writing style and speaking style of the deceased. The server also communicates with messaging applications to collect data on past interactions with the deceased, which is then stored for further analysis.

[0343] Next, the interface means to enable interactive dialogue are important. The following devices and applications are used as interface means:

[0344] Hardware: Smart glasses, head-mounted displays

[0345] Software: User Interface Application

[0346] The user wears smart glasses or a head-mounted display and interacts with a digital portrait of the deceased. The user's voice and text input is received and transmitted to the server through an interface. The server uses an emotion engine to analyze the user's emotions and adjusts responses accordingly. The emotion engine uses the following software:

[0347] Software: DeepFace, GPT-3

[0348] If a user says "I'm lonely," the emotion engine will recognize this as "sadness" and create a response that reassures the user, such as "Don't worry, I'm always here for you."

[0349] The server also continuously analyzes the dialogue records and updates and improves the AI ​​model and emotion engine to improve their accuracy, enabling more natural dialogue and emotion recognition.

[0350] For example, consider a situation where a user asks, "How are you doing lately?" In this case, the server analyzes the user's emotions and, if it recognizes them as, for example, "relief" or "curiosity," generates a response such as, "I'm fine, how are you?" An example prompt would be:

[0351] The user's emotion is sadness. As the deceased, respond to the following statement: I miss you

[0352] This system allows users to enjoy interactive dialogue with the deceased while creating a deep emotional connection.

[0353] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0354] Step 1:

[0355] Collection and storage of deceased data

[0356] Users digitize letters, photos, videos, etc. of the deceased and upload them to the server using a dedicated application on their device. The server receives and stores this data. It takes the digital data uploaded by the user as input and generates an organized database on the server as output.

[0357] Step 2:

[0358] Analyzing data and generating artificial intelligence models

[0359] The server analyzes the stored data using natural language processing (NLP) techniques to extract the characteristics of the deceased. This data analysis includes tokenizing text data, extracting keywords, and analyzing frequently occurring phrases. It receives the stored data as input and outputs a trained feature set. It then generates an artificial intelligence model based on this feature set.

[0360] Step 3:

[0361] Integration with messaging applications

[0362] The user allows integration with the messaging application. The server retrieves chat history with the deceased person from the messaging application and collects additional data. The server takes the chat history as input and outputs an additional dataset after analysis.

[0363] Step 4:

[0364] Updates and improvements to AI models

[0365] The server uses all collected data to update the existing AI model and improve its accuracy. Here, newly acquired data is added to the model and re-training is performed. This re-training includes optimizing the model, and the output is an updated AI model.

[0366] Step 5:

[0367] Interaction through interface means

[0368] The user wears smart glasses or a head-mounted display and initiates a dialogue with the AI ​​model via the device, which accepts voice or text data as input, analyzes it, and generates an appropriate response, providing the user's visual or audio feedback as output.

[0369] Step 6:

[0370] Emotion recognition and response generation using an emotion engine

[0371] The server analyzes the user's voice and text data using an emotion engine to recognize emotions. It receives the user's response as input and outputs an appropriate response generated by the AI ​​model based on that emotional data. For example, if the user says "I'm lonely," the emotion engine recognizes this as "sadness" and generates a response such as "It's okay, I'm always here for you."

[0372] Step 7:

[0373] Recording interactions and continuously improving the model

[0374] The server records the conversation between the user and the AI ​​model and later analyzes it. This allows further model updates and emotion engine improvements based on new data. It receives the conversation recording data as input, analyzes it, and outputs updates to the model and emotion engine.

[0375] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0376] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0377] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0378] [Second embodiment]

[0379] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0380] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0381] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0382] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0383] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0384] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0385] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0386] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0387] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0388] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0389] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0390] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0391] This invention is a system that vividly recreates the personality and memories of a deceased person by receiving and storing document, image, and video data of the deceased, analyzing that data, and generating an AI model that has learned the characteristics of the deceased. Specific embodiments are described below.

[0392] 1. Data collection and storage

[0393] Users can digitize letters, notes, photos, video messages, and other documents from the deceased and upload them to the server via a dedicated application or web portal. For example, users can take a photo of a letter from the deceased with their smartphone and upload the image to the server.

[0394] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into text using voice recognition technology.

[0395] 2. Data collection through LINE integration

[0396] The user authorizes integration with the messaging application. This integration is achieved by the user providing account information and granting access to the system. For example, the user logs in to their LINE account and grants permission for the system to obtain data.

[0397] The server collects chat history and message data from authorized messaging applications, creating a database of interactions and conversation styles with the deceased.

[0398] 3. Generating AI models

[0399] The server analyzes the collected data. Specifically, it uses natural language processing (NLP) algorithms to extract keywords, frequently occurring phrases, and speech patterns from the text. Based on the results of this analysis, an AI model that learns the characteristics of the deceased is generated.

[0400] The resulting AI model is then used to recreate the writing style and speaking patterns of the deceased. For example, if it is determined that the deceased frequently used the word "thank you," the model will reflect that same tendency.

[0401] 4. Dialogue with a digital portrait

[0402] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0403] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0404] The terminal displays the response from the server and continues the dialogue with the user. This interactive experience allows the user to reaffirm their bond with their deceased loved one.

[0405] 5. Update and improve AI models

[0406] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model, which allows the system to continually improve and increase its ability to provide more natural responses.

[0407] For example, when a user asks the system, "How are you doing lately?", the system extracts the appropriate context from past data and generates a response such as, "I've been a little busy lately, but I'm doing well."

[0408] The above is a specific embodiment for carrying out the present invention. As a tool for remembering the deceased, the system can ease the user's grief and provide comfort through dialogue with the deceased.

[0409] The processing flow will be explained below.

[0410] Step 1: Data collection

[0411] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal.

[0412] The server receives the uploaded data and stores it electronically.

[0413] Step 2: Data conversion

[0414] The server converts the image data into text data using OCR (optical character recognition) technology.

[0415] Example: Converting an image of a letter to text.

[0416] The server converts the video data into text using voice recognition technology.

[0417] Example: Converting audio to text for video messages.

[0418] Step 3: LINE integration

[0419] The user allows collaboration with the messaging application.

[0420] The server collects chat history and message data from authorized messaging applications.

[0421] Step 4: Data analysis

[0422] The server analyzes the collected text data using natural language processing (NLP) technology.

[0423] The server extracts keywords, frequent phrases, and speaking patterns from the text.

[0424] Step 5: Artificial Intelligence Model Generation

[0425] Based on the analysis results, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0426] The server integrates the generated artificial intelligence model into the digital memorial portrait system.

[0427] Step 6: Provide a conversational interface

[0428] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0429] The user speaks to the deceased via voice or text.

[0430] Step 7: Submitting input data

[0431] The terminal transmits the input data from the user to the server.

[0432] Step 8: Response Generation

[0433] The server uses artificial intelligence models to generate appropriate responses based on the received user input data.

[0434] Step 9: View the response

[0435] The terminal displays the response from the server to the user and continues the dialogue.

[0436] Step 10: Update and improve the AI ​​model

[0437] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0438] The server redeploys the updated AI model and reflects it throughout the system.

[0439] The above is the specific processing flow of the system.

[0440] Example 1

[0441] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0442] While there are many ways to commemorate the deceased, existing technologies have difficulty vividly recreating the deceased's personality and memories. In particular, there are few systems that can recreate an individual's writing style and speaking style and allow users to feel a connection with the deceased through conversation. Furthermore, the lack of specific technological means to efficiently and accurately collect and analyze the deceased's data and generate artificial intelligence models risks degrading the quality of the conversation experience with the deceased.

[0443] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0444] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for converting image data into character data using optical character recognition technology, means for converting voice data into text data using voice recognition technology, means for analyzing the stored data and extracting keywords and frequently occurring phrases from the data using natural language processing technology to generate an AI model, interface means for interacting with the generated AI model, means for linking with a message application via communication means to collect data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for displaying the generated responses to the user. This allows the personality and memories of the deceased to be vividly reproduced, making it possible to feel a bond with the deceased through interaction.

[0445] "Documents of the deceased" refers to text data such as letters, notes, memos, and diaries written by the deceased during their lifetime.

[0446] "Image data" refers to still image data that has been digitized from photographs or handwritten text of the deceased.

[0447] "Video data" refers to video data that records the deceased's video messages and daily activities.

[0448] "Means for receiving and storing" refers to the function of digitally capturing documents, image data, and video data of the deceased person provided by the user and storing them on a server.

[0449] Optical character recognition (OCR) is a technology that automatically reads characters contained in image data and converts them into text data.

[0450] "Speech recognition technology" is a technology that analyzes the audio contained in video data and converts it into text data.

[0451] "Means for analysis" refers to a function that uses natural language processing technology to extract keywords and frequently occurring phrases from stored data and analyze the characteristics of the deceased.

[0452] An "artificial intelligence model" is a computer program that learns the writing style and speaking style of the deceased from collected and analyzed data.

[0453] "Interface means" refers to input and output functions that allow a user to interact with an artificial intelligence model using voice or text.

[0454] "Communication means" refers to the ability to send and receive data to and from message applications via the Internet or other communications networks.

[0455] A "messaging application" is software for chatting and exchanging messages.

[0456] "Means of updating and improving" refers to the ability to use new data collected to improve the accuracy of the artificial intelligence model and enable it to generate more natural responses.

[0457] The "means for generating a response" is a function that creates an appropriate response to an input from a user based on the generated artificial intelligence model.

[0458] The "means for displaying" is a function that provides the response from the server to the user visually or audibly.

[0459] This invention is a system for recreating the personality and memories of a deceased person by receiving and storing documents, images, and video data of the deceased, analyzing the data, and generating an artificial intelligence model. Specific embodiments are described below.

[0460] 1. Data collection and storage

[0461] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0462] The server receives and stores the uploaded data. When storing, image data is converted to text data using Tesseract OCR, and video messages are converted to text data using the Google Speech-to-Text API.

[0463] 2. Data collection through LINE integration

[0464] The user authorizes integration with a messaging application. The user provides account information and completes the procedure to allow access to the system. For example, the user logs in to their LINE account and gives the system permission to obtain data.

[0465] The server collects chat history and message data from authorized messaging applications, which is used to model interactions and conversational styles with the deceased.

[0466] 3. Generating AI models

[0467] The server analyzes the collected data using Python's natural language processing libraries, NLTK and SpaCy. This extracts keywords, frequent phrases, and speech patterns from the text, generating an AI model that learns the characteristics of the deceased. For example, if the deceased frequently used the word "thank you," this will be reflected in the model.

[0468] 4. Dialogue with a digital portrait

[0469] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0470] The server receives input from the user and uses the generated artificial intelligence model to generate an appropriate response. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0471] The terminal displays the response from the server and continues the dialogue with the user, allowing the user to enjoy the experience of interacting with the deceased.

[0472] 5. Update and improve AI models

[0473] The server analyzes records of user interactions and performs updates to improve the accuracy of the artificial intelligence model. This allows the system to continuously improve and become more capable of providing more natural responses. For example, if the system is asked by a user, "How are you doing lately?", it can extract appropriate context from past data and generate a response such as, "I've been a little busy lately, but I'm doing well."

[0474] Specific examples

[0475] For example, if a user uploads letters and photos of their deceased grandfather, the system analyzes them and learns the grandfather's characteristic speaking style and vocabulary. Based on this learning result, when a user asks, "Grandpa, how are you?", the system can generate a response such as, "I'm fine, thank you!"

[0476] Prompt Sentence Examples

[0477] "I've uploaded a letter from a deceased person. Please analyze it and extract features."

[0478] "Since you have authorized the integration of LINE messages, please collect chat data with the deceased person and learn their conversation style."

[0479] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0480] Step 1: Upload your data

[0481] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0482] Input: Digitized image and video data

[0483] Output: Raw data stored on the server

[0484] Specific operation: The user launches the app on their smartphone, presses the upload button, and selects the data they want to save. The app then sends the data to the server, which receives and saves it.

[0485] Step 2: Transform the data

[0486] The server converts uploaded image data into text data using Tesseract OCR, and converts video messages into text data using the Google Speech-to-Text API.

[0487] Input: Uploaded raw data (image data and video data)

[0488] Output: Parsed text data

[0489] Specific operation: The server launches Tesseract OCR, receives image data as input, and generates text data. Similarly, it inputs video data into the Google Speech-to-Text API and converts the audio into text data.

[0490] Step 3: Collecting data from messaging applications

[0491] The user authorizes integration with a messaging application (e.g., LINE). The user provides account information and completes the procedure to authorize access to the system.

[0492] The server collects chat history and message data from authorized messaging applications.

[0493] Input: Account information that is allowed to be linked

[0494] Output: Captured chat history and message data

[0495] Specific operation: The user logs in to their LINE account and grants permission to the system to retrieve data. The server uses the API to collect past chat history from LINE and saves it in a database.

[0496] Step 4: Analyze the data and generate an artificial intelligence model

[0497] The server analyzes the collected data, using Python natural language processing libraries NLTK and SpaCy to extract keywords, frequent phrases, and speaking patterns from the text.

[0498] Input: Parsed text data and chat history

[0499] Output: AI model that has learned the characteristics of the deceased

[0500] How it works: The server uses NLTK or SpaCy to analyze text data and extract distinctive writing styles and keywords. It then uses machine learning algorithms to generate an AI model based on these features.

[0501] Step 5: User interaction

[0502] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0503] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model.

[0504] The terminal displays the response from the server and continues the dialogue with the user.

[0505] Input: User voice or text input

[0506] Output: The generated response message

[0507] How it works: When a user speaks to the device, the device converts the speech into text and sends it to the server. The server then inputs the resulting text into an artificial intelligence model to generate a response. The generated response is then sent back to the device and displayed to the user.

[0508] Step 6: Analyze interaction data and update the model

[0509] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0510] Input: Record of user interaction

[0511] Output: Updated artificial intelligence model

[0512] How it works: The server analyzes user interaction records to learn frequent patterns and new keywords, then retrains the existing AI model with the new information to improve its accuracy.

[0513] The above are the specific processing steps of this system.

[0514] (Application example 1)

[0515] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0516] Tools for remembering the deceased are limited to physical possessions and photographs, making it difficult to converse with the deceased or reminisce about memories. Furthermore, there are still no systems in place that use digitized information to recreate the personality and characteristics of the deceased and provide an interactive experience. There is a need for a system that allows people to converse with the deceased and relive memories in physical stores.

[0517] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0518] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for providing an interactive interface with the deceased in a physical store, and means for updating and improving the AI ​​model using the collected data. This allows users to interactively experience memories with the deceased even in a physical store, enriching their interactions with the deceased and recreating their memories.

[0519] "Documents, images and video data of the deceased" refers to various forms of digitized information left behind by the deceased during their lifetime, such as handwritten letters, diaries, photographs and video messages.

[0520] "Means for receiving and storing" refers to the technology and systems that allow the server to receive digital data uploaded by users and store it electronically.

[0521] "Means for analyzing and generating an AI model that learns the characteristics of the deceased" refers to technology that analyzes stored digital data using natural language processing and image recognition algorithms to create an AI model that reproduces the speech, behavior, and style of the deceased.

[0522] "Interface means" refers to the input and output devices through which a user interacts with an artificial intelligence model, and the software that manages that interaction.

[0523] "Linking with a messaging application via a communication means" refers to technology that links a user's messaging application account with the system using the Internet or other communication protocols.

[0524] "Data of interactions with the deceased" refers to message exchanges and chat history between the user and the deceased while they were alive.

[0525] "Means for providing an interactive interface with the deceased in a physical store" refers to hardware and software for providing an environment in which users can interact with an artificial intelligence model of the deceased through terminals or kiosks installed in a physical store.

[0526] "Means of updating and improving" refers to technologies for improving the accuracy of AI models and the naturalness of their responses based on new collected data and user interaction logs.

[0527] This invention is an interactive system that recreates the personality and memories of a deceased person by using documents, images, and video data of the deceased to generate an artificial intelligence model and provide an interactive interface in a physical store.

[0528] Data collection and storage

[0529] Users upload digital data such as letters, records, photos, and video messages from the deceased to the server using dedicated terminals in the store. Optical character recognition (OCR) and voice recognition technologies are used to convert image and audio data into text data, which is then saved as text. The server receives the uploaded data and stores it electronically.

[0530] Generating AI models

[0531] The server analyzes the stored data and uses natural language processing (NLP) algorithms to generate an AI model that learns the characteristics of the deceased, such as extracting keywords, frequent phrases, and speech patterns from the text. The generated AI model is then used to recreate the writing style and speaking style of the deceased.

[0532] Providing interactive interfaces in physical stores

[0533] The terminal installed in the store acts as a digital memory consultant, providing an interface that allows users to interact with the deceased. Users can speak to the deceased by voice or text. This input is sent to the server via the interface. The server uses the generated artificial intelligence model to generate an appropriate response and sends it back to the terminal. Users can view this response and enjoy interacting with the deceased.

[0534] AI model updates and improvements

[0535] The server analyzes the conversation records and continuously updates the AI ​​model to improve its accuracy. This allows the system to provide more natural responses over time. For example, if a user asks, "How are you doing lately?", the system can extract appropriate context from past data and generate a response such as, "I've been a bit busy lately, but I'm doing well."

[0536] Specific examples

[0537] For example, if a user asks, "Dad, how was your day?", the system will respond, "I worked in the garden all day today. The flowers are blooming beautifully." An example of a prompt sentence is, "If a user asks about the deceased's hobbies, please provide appropriate context and generate a response. For example, in response to a user question: 'Dad, what are your hobbies these days?', the deceased's response would be, 'I've been into photography lately. I take pictures in various places while walking.'"

[0538] Through this system, users can interactively experience memories of the deceased even in a physical store, allowing them to enjoy interacting with the deceased and reliving memories in a richer way.

[0539] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0540] Step 1:

[0541] The user uploads the document, image, and video data of the deceased person to the server using a terminal in the store. This uploaded data is received by the server and stored electronically. The input is digitized document, image, and video data, which the server converts into a data format for storage and stores on the file server. Specifically, the user uses the upload function of the terminal to select the data file of the deceased person and presses the "upload" button.

[0542] Step 2:

[0543] The server applies OCR or speech recognition technology to the uploaded data, converting image data or audio data into text data. This process uses OCR software (e.g., Tesseract OCR) or speech recognition software (e.g., Google Cloud Speech-to-Text). The input is image data or audio data, and the output is text data obtained by analyzing it. Specifically, the server passes an image file to the OCR software and receives the text as a processing result, or passes an audio file to speech recognition software and converts it into a string of characters.

[0544] Step 3:

[0545] The server analyzes the stored text data using a natural language processing (NLP) algorithm to generate an AI model that learns the characteristics of the deceased. Specifically, it uses Hugging Face's Transformer library, taking text data as input and outputting a generative AI model that reflects the deceased's behavior and conversation style. Specifically, it preprocesses the text data, inputs it into an NLP module, and trains the model.

[0546] Step 4:

[0547] The user uses an interface through a terminal to interact with an AI model of the deceased person. The user inputs voice or text, which is then sent to a server. The server analyzes the voice or text input and uses the AI ​​model to generate an appropriate response. Specifically, the user asks a question into a microphone, and the voice is converted into text and sent to the server.

[0548] Step 5:

[0549] The server generates a response based on the generated AI model and sends it back to the device. The input is the analysis result of the user's question, and the output is a response text that reproduces the deceased's writing style and speaking manner. Specifically, the server generates a prompt based on the dialogue log, inputs it into the AI ​​model to generate a text response, and sends it to the device.

[0550] Step 6:

[0551] The server analyzes the dialogue log with the user and updates the AI ​​model to improve its accuracy. The input is the dialogue log with the user, and the output is the updated AI model. Specifically, the server analyzes the dialogue log and re-learns frequently used phrases and patterns.

[0552] In this way, a system has been created that provides an interactive experience that recreates memories and conversations with the deceased, enabling rich dialogue even in physical stores.

[0553] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0554] This invention provides a system that vividly recreates the personality and memories of a deceased person and further recognizes the user's emotions and adjusts responses accordingly. This system receives and stores document, image, and video data of the deceased, analyzes the data, and generates an artificial intelligence model that learns the characteristics of the deceased. Furthermore, by combining it with an emotion engine, it is possible to recognize the user's emotional state and generate responses accordingly. Specific embodiments are described below.

[0555] 1. Data collection and storage

[0556] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to a server through a dedicated application or web portal. This uploading is done to permanently preserve memories of the deceased as digital data. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file to the server.

[0557] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into audio data using voice recognition technology.

[0558] 2. Data collection through LINE integration

[0559] The user allows the system to connect to a messaging application. This connection allows the system to collect chat history and message data with the deceased. For example, the system can obtain messages exchanged between the deceased and the user on LINE.

[0560] The server collects chat history and message data from authorized messaging applications and stores it in a database, which allows for a better understanding of the conversation style and language used with the deceased.

[0561] 3. Generating AI models

[0562] The server analyzes the collected data using natural language processing (NLP) technology. Specifically, it extracts keywords and frequently occurring phrases in the text, as well as speech patterns. For example, if the deceased frequently used the word "thank you," that tendency can also be learned.

[0563] Based on the analysis results, the server generates an AI model that learns the characteristics of the deceased. This model is used to recreate the deceased's writing style and speaking style. The AI ​​model is then integrated into the digital memorial portrait system.

[0564] 4. Incorporating an Emotional Engine

[0565] The server uses an emotion engine to analyze the user's voice and text data and recognize their emotions. For example, if a user says "I feel lonely" in a sad voice, the emotion engine will recognize that emotion as "sadness."

[0566] Based on the recognized emotion, the server adjusts the response generated by the AI ​​model. For example, if the user speaks to the deceased in a sad voice, the AI ​​model of the deceased person will offer comforting words such as, "It's okay, I'm always here for you."

[0567] 5. Dialogue with a digital portrait

[0568] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0569] The server receives input data from the user and uses artificial intelligence models and emotion engines to generate appropriate responses. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay."

[0570] The terminal displays the response from the server to the user and continues the dialogue, allowing the user to enjoy an interactive dialogue with the deceased.

[0571] 6. Update and improve AI models

[0572] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0573] As a concrete example, consider a situation where a user asks, "How are you doing lately?" In this case, if the emotion engine recognizes the user's emotion as "relief" or "curiosity," the server will respond with, "I'm fine, how are you?"

[0574] The above is a specific embodiment of the present invention. As a tool for remembering the deceased, the present system aims to provide a richer interactive experience while deeply understanding the user's emotions.

[0575] The processing flow will be explained below.

[0576] Step 1: Data collection

[0577] Users digitize letters, notes, photos, and video messages from the deceased and upload them to a server through a dedicated application or web portal.

[0578] The server receives the uploaded digital data and stores it in secure electronic storage.

[0579] Step 2: Data conversion

[0580] The server converts the stored image data into text data using OCR (optical character recognition) technology.

[0581] Example: Scan an image of a letter and convert the text written on it into text data.

[0582] The server converts the audio of the stored video data into text using voice recognition technology.

[0583] Example: Analyzing the audio portion of a video message and converting its content into text data.

[0584] Step 3: LINE integration

[0585] The user allows the messaging application to link with the system.

[0586] The server collects chat history and message data from authorized messaging applications.

[0587] Example: Obtain chat history between the deceased and the user from LINE and save it as text data.

[0588] Step 4: Data analysis

[0589] The server analyzes the collected text data of the deceased using natural language processing (NLP) technology.

[0590] Example: Extracting frequent phrases and keywords from text data and analyzing the tone and style of writing.

[0591] Based on the analysis results, the server incorporates the characteristics of the deceased into a model.

[0592] Step 5: Artificial Intelligence Model Generation

[0593] Based on the results of the data analysis, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0594] For example, learning the speech habits and specific expressions of the deceased and incorporating them into the model.

[0595] The server prepares the generated AI model for integration into the digital memorial portrait system.

[0596] Step 6: Incorporating the Emotion Engine

[0597] The server incorporates an emotion engine that analyzes the user's voice or text data and recognizes emotions.

[0598] For example: If a user says "I feel sad...", the emotion engine will recognize the emotion "sad".

[0599] The server adjusts the response of the artificial intelligence model based on the recognized emotion.

[0600] For example, if the user is feeling sad, the AI ​​model responds, "Don't worry, I'll always be here for you."

[0601] Step 7: Providing a conversational interface

[0602] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0603] Example: A user opens an interactive screen that displays a digital portrait of a deceased person.

[0604] Users can speak to the deceased through voice or text.

[0605] Step 8: Submitting input data

[0606] The terminal transmits voice or text input data from the user to the server.

[0607] Step 9: Response Generation

[0608] The server uses an AI model to generate an appropriate response based on the received user input data and emotion recognition results.

[0609] For example, if a user says, "I miss you," the AI ​​model will consider the emotion and respond, "I miss you too. But it's okay, we'll be together."

[0610] Step 10: View the response

[0611] The terminal displays the response from the server to the user and continues the dialogue.

[0612] Step 11: Update and improve the AI ​​model

[0613] The server analyzes the dialogue records and performs updates to improve the accuracy of the AI ​​model and emotion engine.

[0614] Example: Improving AI models based on user feedback and new interaction data.

[0615] The server redeploys the updated AI model and reflects it throughout the system.

[0616] The above is the specific processing flow of the system.

[0617] Example 2

[0618] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0619] There is a need for a system that can vividly recreate memories of the deceased while recognizing the user's emotions and adjusting its responses. However, conventional systems have not only struggled to accurately reproduce the characteristics and speaking style of the deceased, but also failed to generate responses that correspond to the user's emotional state. This has prevented users from having a natural conversational experience with the deceased, making it difficult to achieve emotional satisfaction.

[0620] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for recognizing the user's emotions and adjusting responses using an emotion engine. This enables a natural interaction experience with the deceased, and provides the user with emotional satisfaction.

[0621] "Deceased documents, images and video data" refers to information stored in digital form that contains personal memories and recollections, such as letters, diaries, photographs and video messages left by the deceased during their lifetime.

[0622] "Means for receiving and storing" refers to a mechanism for receiving digital data provided by a user and storing it in an appropriate form, using a server, database, etc.

[0623] "Means for analyzing and generating an artificial intelligence model that learns the characteristics of the deceased" refers to technology that analyzes collected data using natural language processing and machine learning techniques to model the speaking style and vocabulary of the deceased.

[0624] An "interface means" is a combination of software and hardware that allows a user to interact with a system through voice and / or text.

[0625] "Linking with a messaging application via a communication means" refers to the function of exchanging data with a messaging application using the Internet or other communication protocols.

[0626] "Means of collecting data on interactions with the deceased" refers to methods for importing past chat history and message content into the system through LINE or other messaging applications.

[0627] "Means of updating and improving artificial intelligence models using collected data" refers to a method for improving the accuracy and response capabilities of artificial intelligence by analyzing records of interactions with users and applying new information to the model.

[0628] "Means for recognizing user emotions and adjusting responses using an emotion engine" is a technology for analyzing the emotional state of a user from their voice or text and optimizing the system response based on that.

[0629] This invention provides a system that recreates the personality and memories of a deceased person, recognizes the user's emotions, and adjusts responses accordingly. This system receives and stores documents, images, and video data of the deceased, analyzes them, and generates an artificial intelligence model. It also uses an emotion engine to recognize the user's emotions and adjust responses accordingly. Specific embodiments are described below.

[0630] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file using a dedicated application.

[0631] The server receives the uploaded data and stores it in a database. During this data storage process, image data is converted into text data using "Tesseract OCR." For video data, audio data is converted into text using "Google Speech-to-Text." This makes it possible to process the stored data as text.

[0632] By allowing the user to connect to a messaging application (e.g., LINE), the system can import chat history and past message data with the deceased person. The server then collects the chat history and message data from the authorized messaging application and stores them in a database. This allows for the reproduction of more natural conversations.

[0633] The server then analyzes the collected data using natural language processing (NLP) techniques. Specifically, it uses libraries such as SpaCy and NLTK to extract keywords, frequent phrases, and speech patterns from the text. Based on the results of this analysis, the server uses generative AI models such as GPT-3 and BERT to generate an AI model that reflects the characteristics of the deceased.

[0634] The server then uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to create an emotion engine. This engine analyzes the user's voice and text data to recognize emotions. Once the user's emotion is recognized, the server can adjust the response provided by the generated AI model based on that emotion. For example, if the user sadly says "I'm lonely," the emotion engine will recognize that emotion as "sadness" and provide comforting words.

[0635] The device displays a digital portrait and provides an interface that allows users to interact with the deceased. When the user speaks to the deceased by voice or text, the input data is sent via the device to the server. The server uses an artificial intelligence model and emotion engine to generate an appropriate response based on the received data. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay," and sends it to the device. The device then displays this response to the user, allowing the conversation to continue.

[0636] Finally, the server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0637] Examples of concrete examples and prompts

[0638] A user takes a photo of a letter from a deceased person and uploads it through the app:

[0639] "Please take a photo of the letter from the deceased person with your smartphone and upload this image file using a dedicated application."

[0640] Situations where the user allows integration with the LINE app:

[0641] "Please allow the LINE app to connect and import the chat history with the deceased person into the system."

[0642] The server generates an AI model of the deceased person:

[0643] "The collected data is used to generate an artificial intelligence model that learns the characteristics of the deceased."

[0644] A scene where the server recognizes emotions and adjusts responses:

[0645] "If the user speaks in a sad voice, it will recognize that emotion and offer words of comfort."

[0646] A scene where you interact with a digital portrait:

[0647] "Interact with the digital portrait via voice or text and enjoy the responses."

[0648] In this way, it is possible to vividly recreate memories of the deceased and provide natural dialogue that matches the user's emotions.

[0649] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0650] Step 1: Collect and store data

[0651] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. The input data is image files of letters and video files. The server receives this data and stores it in a database. For image data, it uses "Tesseract OCR" to convert it into text data, and for video data, it uses "Google Speech-to-Text" to convert audio data into text. The output is text data. For example, if a user uploads a photo of a letter, the server analyzes the image and saves it as text data.

[0652] Step 2: Data collection through LINE integration

[0653] The user allows integration with a messaging application. The input is permission to integrate with a messaging application such as LINE. The server collects chat history and message data from the authorized messaging application and stores it in a database. The output is chat history in text format. As a specific example, when the user allows integration with LINE, the server obtains past message data with the deceased person and stores it.

[0654] Step 3: Generate an artificial intelligence model

[0655] The server uses natural language processing (NLP) technology to analyze the data collected in steps 1 and 2. The input is text data. Specifically, it uses "SpaCy" or "NLTK" to extract keywords, frequently occurring phrases, and speaking patterns within the text. Based on the analysis results, the server generates an artificial intelligence model using "GPT-3" or "BERT." The output is an AI model that reproduces the writing style and speaking style of the deceased. For example, it learns phrases frequently used by the deceased and generates an AI model that reflects them.

[0656] Step 4: Incorporating the Emotion Engine

[0657] The server uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to analyze the user's voice and text data and recognize emotions. The input is voice and text data containing the user's emotions. The emotion engine performs the analysis, and the server adjusts the response generated by the AI ​​model based on the recognized emotion. The output is a response text appropriate to the emotion. For example, if a user sadly says "I'm lonely," the emotion engine will recognize the emotion as "sadness" and respond with "It's okay, I'm always here for you."

[0658] Step 5: Interact with the digital portrait

[0659] The terminal displays the digital portrait and provides an interface that allows interaction with the user. Input is voice or text data from the user. The server receives the input data from the user and generates an appropriate response using the generated artificial intelligence model and emotion engine. The output is a dialogue-style response text. The terminal displays this response to the user, and the dialogue continues through the interface. For example, if the user says "I miss you," the server responds "I miss you too, but it's okay," and the terminal displays it.

[0660] Step 6: Update and improve the AI ​​model

[0661] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model and emotion engine. The input is the dialogue records. Based on these records, machine learning technology is used to improve the model. Specifically, when a user asks "How are you doing lately?", the response is evaluated and improvements are made. The output is an AI model with improved accuracy.

[0662] (Application example 2)

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

[0664] To remember a deceased loved one, it is important to not only look back at photos and videos of that person, but also to be able to interactively experience deeper memories. However, current systems have difficulty not only reproducing the characteristics of the deceased, but also accurately recognizing the user's emotions and responding accordingly. Furthermore, there are not enough systems in place to allow users to enjoy conversations with the deceased in physical settings such as brick-and-mortar stores.

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

[0666] In this invention, the server includes: means for receiving and storing document, image, and video data of the deceased; means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased; interface means for interacting with the generated AI model; means for linking with a message application via communication means and collecting data on interactions with the deceased; means for updating and improving the AI ​​model using the collected data; means for allowing a user to enjoy interactive conversations with the deceased using smart glasses or a head-mounted display; and means including an emotion engine that recognizes the user's emotions and reflects them in responses. This allows a user to have a deeper, more emotional experience interacting with the deceased, making it possible to enjoy interactive conversations even in physical stores.

[0667] "Documents" are text data such as letters and notes written by the deceased.

[0668] "Images" are visual data such as photographs or illustrations of the deceased.

[0669] "Video data" refers to video or recorded footage of the deceased.

[0670] "Means of receiving and storing" refers to the mechanisms and software that capture data on digital devices or servers and store it securely.

[0671] "Analysis" is the process of extracting features and patterns from received and stored data.

[0672] An "artificial intelligence model" is an AI system that learns and reproduces the characteristics of the deceased.

[0673] "Means of generation" refers to the process of creating an artificial intelligence model based on the results of data analysis.

[0674] An "interface means" is an input and output mechanism by which a user interacts with a system.

[0675] "Communication means" refers to the technology that allows a system to exchange data with other devices and applications.

[0676] A "messaging application" is a software application that allows for sending and receiving messages.

[0677] "Means of collection" are the methods or techniques used to obtain data from messaging applications.

[0678] "Means of updating and improving" refers to the way new data collected is used to optimize and improve the AI ​​model.

[0679] "Smart glasses" are wearable eyeglass-type devices that have the ability to display information.

[0680] A "head-mounted display" is a device worn on the head that displays images in the field of vision.

[0681] "Interactive dialogue" refers to a form in which the user and the system interact with each other and respond in real time.

[0682] An "emotion engine" is a system that recognizes emotions from a user's voice or text and generates a response accordingly.

[0683] MODE FOR CARRYING OUT THE INVENTION

[0684] In an embodiment of the present invention, documents, images, and video data of the deceased person are first digitized and sent to a server. The server receives and stores the data using the following hardware and software:

[0685] Hardware: Digital devices, servers

[0686] Software: Data storage system

[0687] The server then analyzes the stored data and uses natural language processing (NLP) techniques to learn the characteristics of the deceased, using the following software:

[0688] Software: Natural language processing technology

[0689] The analyzed data is used to generate an artificial intelligence model, which is then used to recreate the writing style and speaking style of the deceased. The server also communicates with messaging applications to collect data on past interactions with the deceased, which is then stored for further analysis.

[0690] Next, the interface means to enable interactive dialogue are important. The following devices and applications are used as interface means:

[0691] Hardware: Smart glasses, head-mounted displays

[0692] Software: User Interface Application

[0693] The user wears smart glasses or a head-mounted display and interacts with a digital portrait of the deceased. The user's voice and text input is received and transmitted to the server through an interface. The server uses an emotion engine to analyze the user's emotions and adjusts responses accordingly. The emotion engine uses the following software:

[0694] Software: DeepFace, GPT-3

[0695] If a user says "I'm lonely," the emotion engine will recognize this as "sadness" and create a response that reassures the user, such as "Don't worry, I'm always here for you."

[0696] The server also continuously analyzes the dialogue records and updates and improves the AI ​​model and emotion engine to improve their accuracy, enabling more natural dialogue and emotion recognition.

[0697] For example, consider a situation where a user asks, "How are you doing lately?" In this case, the server analyzes the user's emotions and, if it recognizes them as, for example, "relief" or "curiosity," generates a response such as, "I'm fine, how are you?" An example prompt would be:

[0698] The user's emotion is sadness. As the deceased, respond to the following statement: I miss you

[0699] This system allows users to enjoy interactive dialogue with the deceased while creating a deep emotional connection.

[0700] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0701] Step 1:

[0702] Collection and storage of deceased data

[0703] Users digitize letters, photos, videos, etc. of the deceased and upload them to the server using a dedicated application on their device. The server receives and stores this data. It takes the digital data uploaded by the user as input and generates an organized database on the server as output.

[0704] Step 2:

[0705] Analyzing data and generating artificial intelligence models

[0706] The server analyzes the stored data using natural language processing (NLP) techniques to extract the characteristics of the deceased. This data analysis includes tokenizing text data, extracting keywords, and analyzing frequently occurring phrases. It receives the stored data as input and outputs a trained feature set. It then generates an artificial intelligence model based on this feature set.

[0707] Step 3:

[0708] Integration with messaging applications

[0709] The user allows integration with the messaging application. The server retrieves chat history with the deceased person from the messaging application and collects additional data. The server takes the chat history as input and outputs an additional dataset after analysis.

[0710] Step 4:

[0711] Updates and improvements to AI models

[0712] The server uses all collected data to update the existing AI model and improve its accuracy. Here, newly acquired data is added to the model and re-training is performed. This re-training includes optimizing the model, and the output is an updated AI model.

[0713] Step 5:

[0714] Interaction through interface means

[0715] The user wears smart glasses or a head-mounted display and initiates a dialogue with the AI ​​model via the device, which accepts voice or text data as input, analyzes it, and generates an appropriate response, providing the user's visual or audio feedback as output.

[0716] Step 6:

[0717] Emotion recognition and response generation using an emotion engine

[0718] The server analyzes the user's voice and text data using an emotion engine to recognize emotions. It receives the user's response as input and outputs an appropriate response generated by the AI ​​model based on that emotional data. For example, if the user says "I'm lonely," the emotion engine recognizes this as "sadness" and generates a response such as "It's okay, I'm always here for you."

[0719] Step 7:

[0720] Recording interactions and continuously improving the model

[0721] The server records the conversation between the user and the AI ​​model and later analyzes it. This allows further model updates and emotion engine improvements based on new data. It receives the conversation recording data as input, analyzes it, and outputs updates to the model and emotion engine.

[0722] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0723] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0724] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0725] [Third embodiment]

[0726] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0727] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0728] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0729] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0730] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0731] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0732] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0733] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0734] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0735] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0736] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0737] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0738] This invention is a system that vividly recreates the personality and memories of a deceased person by receiving and storing document, image, and video data of the deceased, analyzing that data, and generating an AI model that has learned the characteristics of the deceased. Specific embodiments are described below.

[0739] 1. Data collection and storage

[0740] Users can digitize letters, notes, photos, video messages, and other documents from the deceased and upload them to the server via a dedicated application or web portal. For example, users can take a photo of a letter from the deceased with their smartphone and upload the image to the server.

[0741] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into text using voice recognition technology.

[0742] 2. Data collection through LINE integration

[0743] The user authorizes integration with the messaging application. This integration is achieved by the user providing account information and granting access to the system. For example, the user logs in to their LINE account and grants permission for the system to obtain data.

[0744] The server collects chat history and message data from authorized messaging applications, creating a database of interactions and conversation styles with the deceased.

[0745] 3. Generating AI models

[0746] The server analyzes the collected data. Specifically, it uses natural language processing (NLP) algorithms to extract keywords, frequently occurring phrases, and speech patterns from the text. Based on the results of this analysis, an AI model that learns the characteristics of the deceased is generated.

[0747] The resulting AI model is then used to recreate the writing style and speaking patterns of the deceased. For example, if it is determined that the deceased frequently used the word "thank you," the model will reflect that same tendency.

[0748] 4. Dialogue with a digital portrait

[0749] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0750] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0751] The terminal displays the response from the server and continues the dialogue with the user. This interactive experience allows the user to reaffirm their bond with their deceased loved one.

[0752] 5. Update and improve AI models

[0753] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model, which allows the system to continually improve and increase its ability to provide more natural responses.

[0754] For example, when a user asks the system, "How are you doing lately?", the system extracts the appropriate context from past data and generates a response such as, "I've been a little busy lately, but I'm doing well."

[0755] The above is a specific embodiment for carrying out the present invention. As a tool for remembering the deceased, the system can ease the user's grief and provide comfort through dialogue with the deceased.

[0756] The processing flow will be explained below.

[0757] Step 1: Data collection

[0758] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal.

[0759] The server receives the uploaded data and stores it electronically.

[0760] Step 2: Data conversion

[0761] The server converts the image data into text data using OCR (optical character recognition) technology.

[0762] Example: Converting an image of a letter to text.

[0763] The server converts the video data into text using voice recognition technology.

[0764] Example: Converting audio to text for video messages.

[0765] Step 3: LINE integration

[0766] The user allows collaboration with the messaging application.

[0767] The server collects chat history and message data from authorized messaging applications.

[0768] Step 4: Data analysis

[0769] The server analyzes the collected text data using natural language processing (NLP) technology.

[0770] The server extracts keywords, frequent phrases, and speaking patterns from the text.

[0771] Step 5: Artificial Intelligence Model Generation

[0772] Based on the analysis results, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0773] The server integrates the generated artificial intelligence model into the digital memorial portrait system.

[0774] Step 6: Provide a conversational interface

[0775] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0776] The user speaks to the deceased via voice or text.

[0777] Step 7: Submitting input data

[0778] The terminal transmits the input data from the user to the server.

[0779] Step 8: Response Generation

[0780] The server uses artificial intelligence models to generate appropriate responses based on the received user input data.

[0781] Step 9: View the response

[0782] The terminal displays the response from the server to the user and continues the dialogue.

[0783] Step 10: Update and improve the AI ​​model

[0784] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0785] The server redeploys the updated AI model and reflects it throughout the system.

[0786] The above is the specific processing flow of the system.

[0787] Example 1

[0788] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0789] While there are many ways to commemorate the deceased, existing technologies have difficulty vividly recreating the deceased's personality and memories. In particular, there are few systems that can recreate an individual's writing style and speaking style and allow users to feel a connection with the deceased through conversation. Furthermore, the lack of specific technological means to efficiently and accurately collect and analyze the deceased's data and generate artificial intelligence models risks degrading the quality of the conversation experience with the deceased.

[0790] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0791] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for converting image data into character data using optical character recognition technology, means for converting voice data into text data using voice recognition technology, means for analyzing the stored data and extracting keywords and frequently occurring phrases from the data using natural language processing technology to generate an AI model, interface means for interacting with the generated AI model, means for linking with a message application via communication means to collect data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for displaying the generated responses to the user. This allows the personality and memories of the deceased to be vividly reproduced, making it possible to feel a bond with the deceased through interaction.

[0792] "Documents of the deceased" refers to text data such as letters, notes, memos, and diaries written by the deceased during their lifetime.

[0793] "Image data" refers to still image data that has been digitized from photographs or handwritten text of the deceased.

[0794] "Video data" refers to video data that records the deceased's video messages and daily activities.

[0795] "Means for receiving and storing" refers to the function of digitally capturing documents, image data, and video data of the deceased person provided by the user and storing them on a server.

[0796] Optical character recognition (OCR) is a technology that automatically reads characters contained in image data and converts them into text data.

[0797] "Speech recognition technology" is a technology that analyzes the audio contained in video data and converts it into text data.

[0798] "Means for analysis" refers to a function that uses natural language processing technology to extract keywords and frequently occurring phrases from stored data and analyze the characteristics of the deceased.

[0799] An "artificial intelligence model" is a computer program that learns the writing style and speaking style of the deceased from collected and analyzed data.

[0800] "Interface means" refers to input and output functions that allow a user to interact with an artificial intelligence model using voice or text.

[0801] "Communication means" refers to the ability to send and receive data to and from message applications via the Internet or other communications networks.

[0802] A "messaging application" is software for chatting and exchanging messages.

[0803] "Means of updating and improving" refers to the ability to use new data collected to improve the accuracy of the artificial intelligence model and enable it to generate more natural responses.

[0804] The "means for generating a response" is a function that creates an appropriate response to an input from a user based on the generated artificial intelligence model.

[0805] The "means for displaying" is a function that provides the response from the server to the user visually or audibly.

[0806] This invention is a system for recreating the personality and memories of a deceased person by receiving and storing documents, images, and video data of the deceased, analyzing the data, and generating an artificial intelligence model. Specific embodiments are described below.

[0807] 1. Data collection and storage

[0808] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0809] The server receives and stores the uploaded data. When storing, image data is converted to text data using Tesseract OCR, and video messages are converted to text data using the Google Speech-to-Text API.

[0810] 2. Data collection through LINE integration

[0811] The user authorizes integration with a messaging application. The user provides account information and completes the procedure to allow access to the system. For example, the user logs in to their LINE account and gives the system permission to obtain data.

[0812] The server collects chat history and message data from authorized messaging applications, which is used to model interactions and conversational styles with the deceased.

[0813] 3. Generating AI models

[0814] The server analyzes the collected data using Python's natural language processing libraries, NLTK and SpaCy. This extracts keywords, frequent phrases, and speech patterns from the text, generating an AI model that learns the characteristics of the deceased. For example, if the deceased frequently used the word "thank you," this will be reflected in the model.

[0815] 4. Dialogue with a digital portrait

[0816] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0817] The server receives input from the user and uses the generated artificial intelligence model to generate an appropriate response. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[0818] The terminal displays the response from the server and continues the dialogue with the user, allowing the user to enjoy the experience of interacting with the deceased.

[0819] 5. Update and improve AI models

[0820] The server analyzes records of user interactions and performs updates to improve the accuracy of the artificial intelligence model. This allows the system to continuously improve and become more capable of providing more natural responses. For example, if the system is asked by a user, "How are you doing lately?", it can extract appropriate context from past data and generate a response such as, "I've been a little busy lately, but I'm doing well."

[0821] Specific examples

[0822] For example, if a user uploads letters and photos of their deceased grandfather, the system analyzes them and learns the grandfather's characteristic speaking style and vocabulary. Based on this learning result, when a user asks, "Grandpa, how are you?", the system can generate a response such as, "I'm fine, thank you!"

[0823] Prompt Sentence Examples

[0824] "I've uploaded a letter from a deceased person. Please analyze it and extract features."

[0825] "Since you have authorized the integration of LINE messages, please collect chat data with the deceased person and learn their conversation style."

[0826] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0827] Step 1: Upload your data

[0828] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[0829] Input: Digitized image and video data

[0830] Output: Raw data stored on the server

[0831] Specific operation: The user launches the app on their smartphone, presses the upload button, and selects the data they want to save. The app then sends the data to the server, which receives and saves it.

[0832] Step 2: Transform the data

[0833] The server converts uploaded image data into text data using Tesseract OCR, and converts video messages into text data using the Google Speech-to-Text API.

[0834] Input: Uploaded raw data (image data and video data)

[0835] Output: Parsed text data

[0836] Specific operation: The server launches Tesseract OCR, receives image data as input, and generates text data. Similarly, it inputs video data into the Google Speech-to-Text API and converts the audio into text data.

[0837] Step 3: Collecting data from messaging applications

[0838] The user authorizes integration with a messaging application (e.g., LINE). The user provides account information and completes the procedure to authorize access to the system.

[0839] The server collects chat history and message data from authorized messaging applications.

[0840] Input: Account information that is allowed to be linked

[0841] Output: Captured chat history and message data

[0842] Specific operation: The user logs in to their LINE account and grants permission to the system to retrieve data. The server uses the API to collect past chat history from LINE and saves it in a database.

[0843] Step 4: Analyze the data and generate an artificial intelligence model

[0844] The server analyzes the collected data, using Python natural language processing libraries NLTK and SpaCy to extract keywords, frequent phrases, and speaking patterns from the text.

[0845] Input: Parsed text data and chat history

[0846] Output: AI model that has learned the characteristics of the deceased

[0847] How it works: The server uses NLTK or SpaCy to analyze text data and extract distinctive writing styles and keywords. It then uses machine learning algorithms to generate an AI model based on these features.

[0848] Step 5: User interaction

[0849] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[0850] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model.

[0851] The terminal displays the response from the server and continues the dialogue with the user.

[0852] Input: User voice or text input

[0853] Output: The generated response message

[0854] How it works: When a user speaks to the device, the device converts the speech into text and sends it to the server. The server then inputs the resulting text into an artificial intelligence model to generate a response. The generated response is then sent back to the device and displayed to the user.

[0855] Step 6: Analyze interaction data and update the model

[0856] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[0857] Input: Record of user interaction

[0858] Output: Updated artificial intelligence model

[0859] How it works: The server analyzes user interaction records to learn frequent patterns and new keywords, then retrains the existing AI model with the new information to improve its accuracy.

[0860] The above are the specific processing steps of this system.

[0861] (Application example 1)

[0862] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0863] Tools for remembering the deceased are limited to physical possessions and photographs, making it difficult to converse with the deceased or reminisce about memories. Furthermore, there are still no systems in place that use digitized information to recreate the personality and characteristics of the deceased and provide an interactive experience. There is a need for a system that allows people to converse with the deceased and relive memories in physical stores.

[0864] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0865] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for providing an interactive interface with the deceased in a physical store, and means for updating and improving the AI ​​model using the collected data. This allows users to interactively experience memories with the deceased even in a physical store, enriching their interactions with the deceased and recreating their memories.

[0866] "Documents, images and video data of the deceased" refers to various forms of digitized information left behind by the deceased during their lifetime, such as handwritten letters, diaries, photographs and video messages.

[0867] "Means for receiving and storing" refers to the technology and systems that allow the server to receive digital data uploaded by users and store it electronically.

[0868] "Means for analyzing and generating an AI model that learns the characteristics of the deceased" refers to technology that analyzes stored digital data using natural language processing and image recognition algorithms to create an AI model that reproduces the speech, behavior, and style of the deceased.

[0869] "Interface means" refers to the input and output devices through which a user interacts with an artificial intelligence model, and the software that manages that interaction.

[0870] "Linking with a messaging application via a communication means" refers to technology that links a user's messaging application account with the system using the Internet or other communication protocols.

[0871] "Data of interactions with the deceased" refers to message exchanges and chat history between the user and the deceased while they were alive.

[0872] "Means for providing an interactive interface with the deceased in a physical store" refers to hardware and software for providing an environment in which users can interact with an artificial intelligence model of the deceased through terminals or kiosks installed in a physical store.

[0873] "Means of updating and improving" refers to technologies for improving the accuracy of AI models and the naturalness of their responses based on new collected data and user interaction logs.

[0874] This invention is an interactive system that recreates the personality and memories of a deceased person by using documents, images, and video data of the deceased to generate an artificial intelligence model and provide an interactive interface in a physical store.

[0875] Data collection and storage

[0876] Users upload digital data such as letters, records, photos, and video messages from the deceased to the server using dedicated terminals in the store. Optical character recognition (OCR) and voice recognition technologies are used to convert image and audio data into text data, which is then saved as text. The server receives the uploaded data and stores it electronically.

[0877] Generating AI models

[0878] The server analyzes the stored data and uses natural language processing (NLP) algorithms to generate an AI model that learns the characteristics of the deceased, such as extracting keywords, frequent phrases, and speech patterns from the text. The generated AI model is then used to recreate the writing style and speaking style of the deceased.

[0879] Providing interactive interfaces in physical stores

[0880] The terminal installed in the store acts as a digital memory consultant, providing an interface that allows users to interact with the deceased. Users can speak to the deceased by voice or text. This input is sent to the server via the interface. The server uses the generated artificial intelligence model to generate an appropriate response and sends it back to the terminal. Users can view this response and enjoy interacting with the deceased.

[0881] AI model updates and improvements

[0882] The server analyzes the conversation records and continuously updates the AI ​​model to improve its accuracy. This allows the system to provide more natural responses over time. For example, if a user asks, "How are you doing lately?", the system can extract appropriate context from past data and generate a response such as, "I've been a bit busy lately, but I'm doing well."

[0883] Specific examples

[0884] For example, if a user asks, "Dad, how was your day?", the system will respond, "I worked in the garden all day today. The flowers are blooming beautifully." An example of a prompt sentence is, "If a user asks about the deceased's hobbies, please provide appropriate context and generate a response. For example, in response to a user question: 'Dad, what are your hobbies these days?', the deceased's response would be, 'I've been into photography lately. I take pictures in various places while walking.'"

[0885] Through this system, users can interactively experience memories of the deceased even in a physical store, allowing them to enjoy interacting with the deceased and reliving memories in a richer way.

[0886] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0887] Step 1:

[0888] The user uploads the document, image, and video data of the deceased person to the server using a terminal in the store. This uploaded data is received by the server and stored electronically. The input is digitized document, image, and video data, which the server converts into a data format for storage and stores on the file server. Specifically, the user uses the upload function of the terminal to select the data file of the deceased person and presses the "upload" button.

[0889] Step 2:

[0890] The server applies OCR or speech recognition technology to the uploaded data, converting image data or audio data into text data. This process uses OCR software (e.g., Tesseract OCR) or speech recognition software (e.g., Google Cloud Speech-to-Text). The input is image data or audio data, and the output is text data obtained by analyzing it. Specifically, the server passes an image file to the OCR software and receives the text as a processing result, or passes an audio file to speech recognition software and converts it into a string of characters.

[0891] Step 3:

[0892] The server analyzes the stored text data using a natural language processing (NLP) algorithm to generate an AI model that learns the characteristics of the deceased. Specifically, it uses Hugging Face's Transformer library, taking text data as input and outputting a generative AI model that reflects the deceased's behavior and conversation style. Specifically, it preprocesses the text data, inputs it into an NLP module, and trains the model.

[0893] Step 4:

[0894] The user uses an interface through a terminal to interact with an AI model of the deceased person. The user inputs voice or text, which is then sent to a server. The server analyzes the voice or text input and uses the AI ​​model to generate an appropriate response. Specifically, the user asks a question into a microphone, and the voice is converted into text and sent to the server.

[0895] Step 5:

[0896] The server generates a response based on the generated AI model and sends it back to the device. The input is the analysis result of the user's question, and the output is a response text that reproduces the deceased's writing style and speaking manner. Specifically, the server generates a prompt based on the dialogue log, inputs it into the AI ​​model to generate a text response, and sends it to the device.

[0897] Step 6:

[0898] The server analyzes the dialogue log with the user and updates the AI ​​model to improve its accuracy. The input is the dialogue log with the user, and the output is the updated AI model. Specifically, the server analyzes the dialogue log and re-learns frequently used phrases and patterns.

[0899] In this way, a system has been created that provides an interactive experience that recreates memories and conversations with the deceased, enabling rich dialogue even in physical stores.

[0900] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0901] This invention provides a system that vividly recreates the personality and memories of a deceased person and further recognizes the user's emotions and adjusts responses accordingly. This system receives and stores document, image, and video data of the deceased, analyzes the data, and generates an artificial intelligence model that learns the characteristics of the deceased. Furthermore, by combining it with an emotion engine, it is possible to recognize the user's emotional state and generate responses accordingly. Specific embodiments are described below.

[0902] 1. Data collection and storage

[0903] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to a server through a dedicated application or web portal. This uploading is done to permanently preserve memories of the deceased as digital data. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file to the server.

[0904] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into audio data using voice recognition technology.

[0905] 2. Data collection through LINE integration

[0906] The user allows the system to connect to a messaging application. This connection allows the system to collect chat history and message data with the deceased. For example, the system can obtain messages exchanged between the deceased and the user on LINE.

[0907] The server collects chat history and message data from authorized messaging applications and stores it in a database, which allows for a better understanding of the conversation style and language used with the deceased.

[0908] 3. Generating AI models

[0909] The server analyzes the collected data using natural language processing (NLP) technology. Specifically, it extracts keywords and frequently occurring phrases in the text, as well as speech patterns. For example, if the deceased frequently used the word "thank you," that tendency can also be learned.

[0910] Based on the analysis results, the server generates an AI model that learns the characteristics of the deceased. This model is used to recreate the deceased's writing style and speaking style. The AI ​​model is then integrated into the digital memorial portrait system.

[0911] 4. Incorporating an Emotional Engine

[0912] The server uses an emotion engine to analyze the user's voice and text data and recognize their emotions. For example, if a user says "I feel lonely" in a sad voice, the emotion engine will recognize that emotion as "sadness."

[0913] Based on the recognized emotion, the server adjusts the response generated by the AI ​​model. For example, if the user speaks to the deceased in a sad voice, the AI ​​model of the deceased person will offer comforting words such as, "It's okay, I'm always here for you."

[0914] 5. Dialogue with a digital portrait

[0915] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[0916] The server receives input data from the user and uses artificial intelligence models and emotion engines to generate appropriate responses. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay."

[0917] The terminal displays the response from the server to the user and continues the dialogue, allowing the user to enjoy an interactive dialogue with the deceased.

[0918] 6. Update and improve AI models

[0919] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0920] As a concrete example, consider a situation where a user asks, "How are you doing lately?" In this case, if the emotion engine recognizes the user's emotion as "relief" or "curiosity," the server will respond with, "I'm fine, how are you?"

[0921] The above is a specific embodiment of the present invention. As a tool for remembering the deceased, the present system aims to provide a richer interactive experience while deeply understanding the user's emotions.

[0922] The processing flow will be explained below.

[0923] Step 1: Data collection

[0924] Users digitize letters, notes, photos, and video messages from the deceased and upload them to a server through a dedicated application or web portal.

[0925] The server receives the uploaded digital data and stores it in secure electronic storage.

[0926] Step 2: Data conversion

[0927] The server converts the stored image data into text data using OCR (optical character recognition) technology.

[0928] Example: Scan an image of a letter and convert the text written on it into text data.

[0929] The server converts the audio of the stored video data into text using voice recognition technology.

[0930] Example: Analyzing the audio portion of a video message and converting its content into text data.

[0931] Step 3: LINE integration

[0932] The user allows the messaging application to link with the system.

[0933] The server collects chat history and message data from authorized messaging applications.

[0934] Example: Obtain chat history between the deceased and the user from LINE and save it as text data.

[0935] Step 4: Data analysis

[0936] The server analyzes the collected text data of the deceased using natural language processing (NLP) technology.

[0937] Example: Extracting frequent phrases and keywords from text data and analyzing the tone and style of writing.

[0938] Based on the analysis results, the server incorporates the characteristics of the deceased into a model.

[0939] Step 5: Artificial Intelligence Model Generation

[0940] Based on the results of the data analysis, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[0941] For example, learning the speech habits and specific expressions of the deceased and incorporating them into the model.

[0942] The server prepares the generated AI model for integration into the digital memorial portrait system.

[0943] Step 6: Incorporating the Emotion Engine

[0944] The server incorporates an emotion engine that analyzes the user's voice or text data and recognizes emotions.

[0945] For example: If a user says "I feel sad...", the emotion engine will recognize the emotion "sad".

[0946] The server adjusts the response of the artificial intelligence model based on the recognized emotion.

[0947] For example, if the user is feeling sad, the AI ​​model responds, "Don't worry, I'll always be here for you."

[0948] Step 7: Providing a conversational interface

[0949] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[0950] Example: A user opens an interactive screen that displays a digital portrait of a deceased person.

[0951] Users can speak to the deceased through voice or text.

[0952] Step 8: Submitting input data

[0953] The terminal transmits voice or text input data from the user to the server.

[0954] Step 9: Response Generation

[0955] The server uses an AI model to generate an appropriate response based on the received user input data and emotion recognition results.

[0956] For example, if a user says, "I miss you," the AI ​​model will consider the emotion and respond, "I miss you too. But it's okay, we'll be together."

[0957] Step 10: View the response

[0958] The terminal displays the response from the server to the user and continues the dialogue.

[0959] Step 11: Update and improve the AI ​​model

[0960] The server analyzes the dialogue records and performs updates to improve the accuracy of the AI ​​model and emotion engine.

[0961] Example: Improving AI models based on user feedback and new interaction data.

[0962] The server redeploys the updated AI model and reflects it throughout the system.

[0963] The above is the specific processing flow of the system.

[0964] Example 2

[0965] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0966] There is a need for a system that can vividly recreate memories of the deceased while recognizing the user's emotions and adjusting its responses. However, conventional systems have not only struggled to accurately reproduce the characteristics and speaking style of the deceased, but also failed to generate responses that correspond to the user's emotional state. This has prevented users from having a natural conversational experience with the deceased, making it difficult to achieve emotional satisfaction.

[0967] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for recognizing the user's emotions and adjusting responses using an emotion engine. This enables a natural interaction experience with the deceased, and provides the user with emotional satisfaction.

[0968] "Deceased documents, images and video data" refers to information stored in digital form that contains personal memories and recollections, such as letters, diaries, photographs and video messages left by the deceased during their lifetime.

[0969] "Means for receiving and storing" refers to a mechanism for receiving digital data provided by a user and storing it in an appropriate form, using a server, database, etc.

[0970] "Means for analyzing and generating an artificial intelligence model that learns the characteristics of the deceased" refers to technology that analyzes collected data using natural language processing and machine learning techniques to model the speaking style and vocabulary of the deceased.

[0971] An "interface means" is a combination of software and hardware that allows a user to interact with a system through voice and / or text.

[0972] "Linking with a messaging application via a communication means" refers to the function of exchanging data with a messaging application using the Internet or other communication protocols.

[0973] "Means of collecting data on interactions with the deceased" refers to methods for importing past chat history and message content into the system through LINE or other messaging applications.

[0974] "Means of updating and improving artificial intelligence models using collected data" refers to a method for improving the accuracy and response capabilities of artificial intelligence by analyzing records of interactions with users and applying new information to the model.

[0975] "Means for recognizing user emotions and adjusting responses using an emotion engine" is a technology for analyzing the emotional state of a user from their voice or text and optimizing the system response based on that.

[0976] This invention provides a system that recreates the personality and memories of a deceased person, recognizes the user's emotions, and adjusts responses accordingly. This system receives and stores documents, images, and video data of the deceased, analyzes them, and generates an artificial intelligence model. It also uses an emotion engine to recognize the user's emotions and adjust responses accordingly. Specific embodiments are described below.

[0977] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file using a dedicated application.

[0978] The server receives the uploaded data and stores it in a database. During this data storage process, image data is converted into text data using "Tesseract OCR." For video data, audio data is converted into text using "Google Speech-to-Text." This makes it possible to process the stored data as text.

[0979] By allowing the user to connect to a messaging application (e.g., LINE), the system can import chat history and past message data with the deceased person. The server then collects the chat history and message data from the authorized messaging application and stores them in a database. This allows for the reproduction of more natural conversations.

[0980] The server then analyzes the collected data using natural language processing (NLP) techniques. Specifically, it uses libraries such as SpaCy and NLTK to extract keywords, frequent phrases, and speech patterns from the text. Based on the results of this analysis, the server uses generative AI models such as GPT-3 and BERT to generate an AI model that reflects the characteristics of the deceased.

[0981] The server then uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to create an emotion engine. This engine analyzes the user's voice and text data to recognize emotions. Once the user's emotion is recognized, the server can adjust the response provided by the generated AI model based on that emotion. For example, if the user sadly says "I'm lonely," the emotion engine will recognize that emotion as "sadness" and provide comforting words.

[0982] The device displays a digital portrait and provides an interface that allows users to interact with the deceased. When the user speaks to the deceased by voice or text, the input data is sent via the device to the server. The server uses an artificial intelligence model and emotion engine to generate an appropriate response based on the received data. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay," and sends it to the device. The device then displays this response to the user, allowing the conversation to continue.

[0983] Finally, the server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[0984] Examples of concrete examples and prompts

[0985] A user takes a photo of a letter from a deceased person and uploads it through the app:

[0986] "Please take a photo of the letter from the deceased person with your smartphone and upload this image file using a dedicated application."

[0987] Situations where the user allows integration with the LINE app:

[0988] "Please allow the LINE app to connect and import the chat history with the deceased person into the system."

[0989] The server generates an AI model of the deceased person:

[0990] "The collected data is used to generate an artificial intelligence model that learns the characteristics of the deceased."

[0991] A scene where the server recognizes emotions and adjusts responses:

[0992] "If the user speaks in a sad voice, it will recognize that emotion and offer words of comfort."

[0993] A scene where you interact with a digital portrait:

[0994] "Interact with the digital portrait via voice or text and enjoy the responses."

[0995] In this way, it is possible to vividly recreate memories of the deceased and provide natural dialogue that matches the user's emotions.

[0996] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0997] Step 1: Collect and store data

[0998] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. The input data is image files of letters and video files. The server receives this data and stores it in a database. For image data, it uses "Tesseract OCR" to convert it into text data, and for video data, it uses "Google Speech-to-Text" to convert audio data into text. The output is text data. For example, if a user uploads a photo of a letter, the server analyzes the image and saves it as text data.

[0999] Step 2: Data collection through LINE integration

[1000] The user allows integration with a messaging application. The input is permission to integrate with a messaging application such as LINE. The server collects chat history and message data from the authorized messaging application and stores it in a database. The output is chat history in text format. As a specific example, when the user allows integration with LINE, the server obtains past message data with the deceased person and stores it.

[1001] Step 3: Generate an artificial intelligence model

[1002] The server uses natural language processing (NLP) technology to analyze the data collected in steps 1 and 2. The input is text data. Specifically, it uses "SpaCy" or "NLTK" to extract keywords, frequently occurring phrases, and speaking patterns within the text. Based on the analysis results, the server generates an artificial intelligence model using "GPT-3" or "BERT." The output is an AI model that reproduces the writing style and speaking style of the deceased. For example, it learns phrases frequently used by the deceased and generates an AI model that reflects them.

[1003] Step 4: Incorporating the Emotion Engine

[1004] The server uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to analyze the user's voice and text data and recognize emotions. The input is voice and text data containing the user's emotions. The emotion engine performs the analysis, and the server adjusts the response generated by the AI ​​model based on the recognized emotion. The output is a response text appropriate to the emotion. For example, if a user sadly says "I'm lonely," the emotion engine will recognize the emotion as "sadness" and respond with "It's okay, I'm always here for you."

[1005] Step 5: Interact with the digital portrait

[1006] The terminal displays the digital portrait and provides an interface that allows interaction with the user. Input is voice or text data from the user. The server receives the input data from the user and generates an appropriate response using the generated artificial intelligence model and emotion engine. The output is a dialogue-style response text. The terminal displays this response to the user, and the dialogue continues through the interface. For example, if the user says "I miss you," the server responds "I miss you too, but it's okay," and the terminal displays it.

[1007] Step 6: Update and improve the AI ​​model

[1008] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model and emotion engine. The input is the dialogue records. Based on these records, machine learning technology is used to improve the model. Specifically, when a user asks "How are you doing lately?", the response is evaluated and improvements are made. The output is an AI model with improved accuracy.

[1009] (Application example 2)

[1010] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1011] To remember a deceased loved one, it is important to not only look back at photos and videos of that person, but also to be able to interactively experience deeper memories. However, current systems have difficulty not only reproducing the characteristics of the deceased, but also accurately recognizing the user's emotions and responding accordingly. Furthermore, there are not enough systems in place to allow users to enjoy conversations with the deceased in physical settings such as brick-and-mortar stores.

[1012] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1013] In this invention, the server includes: means for receiving and storing document, image, and video data of the deceased; means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased; interface means for interacting with the generated AI model; means for linking with a message application via communication means and collecting data on interactions with the deceased; means for updating and improving the AI ​​model using the collected data; means for allowing a user to enjoy interactive conversations with the deceased using smart glasses or a head-mounted display; and means including an emotion engine that recognizes the user's emotions and reflects them in responses. This allows a user to have a deeper, more emotional experience interacting with the deceased, making it possible to enjoy interactive conversations even in physical stores.

[1014] "Documents" are text data such as letters and notes written by the deceased.

[1015] "Images" are visual data such as photographs or illustrations of the deceased.

[1016] "Video data" refers to video or recorded footage of the deceased.

[1017] "Means of receiving and storing" refers to the mechanisms and software that capture data on digital devices or servers and store it securely.

[1018] "Analysis" is the process of extracting features and patterns from received and stored data.

[1019] An "artificial intelligence model" is an AI system that learns and reproduces the characteristics of the deceased.

[1020] "Means of generation" refers to the process of creating an artificial intelligence model based on the results of data analysis.

[1021] An "interface means" is an input and output mechanism by which a user interacts with a system.

[1022] "Communication means" refers to the technology that allows a system to exchange data with other devices and applications.

[1023] A "messaging application" is a software application that allows for sending and receiving messages.

[1024] "Means of collection" are the methods or techniques used to obtain data from messaging applications.

[1025] "Means of updating and improving" refers to the way new data collected is used to optimize and improve the AI ​​model.

[1026] "Smart glasses" are wearable eyeglass-type devices that have the ability to display information.

[1027] A "head-mounted display" is a device worn on the head that displays images in the field of vision.

[1028] "Interactive dialogue" refers to a form in which the user and the system interact with each other and respond in real time.

[1029] An "emotion engine" is a system that recognizes emotions from a user's voice or text and generates a response accordingly.

[1030] MODE FOR CARRYING OUT THE INVENTION

[1031] In an embodiment of the present invention, documents, images, and video data of the deceased person are first digitized and sent to a server. The server receives and stores the data using the following hardware and software:

[1032] Hardware: Digital devices, servers

[1033] Software: Data storage system

[1034] The server then analyzes the stored data and uses natural language processing (NLP) techniques to learn the characteristics of the deceased, using the following software:

[1035] Software: Natural language processing technology

[1036] The analyzed data is used to generate an artificial intelligence model, which is then used to recreate the writing style and speaking style of the deceased. The server also communicates with messaging applications to collect data on past interactions with the deceased, which is then stored for further analysis.

[1037] Next, the interface means to enable interactive dialogue are important. The following devices and applications are used as interface means:

[1038] Hardware: Smart glasses, head-mounted displays

[1039] Software: User Interface Application

[1040] The user wears smart glasses or a head-mounted display and interacts with a digital portrait of the deceased. The user's voice and text input is received and transmitted to the server through an interface. The server uses an emotion engine to analyze the user's emotions and adjusts responses accordingly. The emotion engine uses the following software:

[1041] Software: DeepFace, GPT-3

[1042] If a user says "I'm lonely," the emotion engine will recognize this as "sadness" and create a response that reassures the user, such as "Don't worry, I'm always here for you."

[1043] The server also continuously analyzes the dialogue records and updates and improves the AI ​​model and emotion engine to improve their accuracy, enabling more natural dialogue and emotion recognition.

[1044] For example, consider a situation where a user asks, "How are you doing lately?" In this case, the server analyzes the user's emotions and, if it recognizes them as, for example, "relief" or "curiosity," generates a response such as, "I'm fine, how are you?" An example prompt would be:

[1045] The user's emotion is sadness. As the deceased, respond to the following statement: I miss you

[1046] This system allows users to enjoy interactive dialogue with the deceased while creating a deep emotional connection.

[1047] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1048] Step 1:

[1049] Collection and storage of deceased data

[1050] Users digitize letters, photos, videos, etc. of the deceased and upload them to the server using a dedicated application on their device. The server receives and stores this data. It takes the digital data uploaded by the user as input and generates an organized database on the server as output.

[1051] Step 2:

[1052] Analyzing data and generating artificial intelligence models

[1053] The server analyzes the stored data using natural language processing (NLP) techniques to extract the characteristics of the deceased. This data analysis includes tokenizing text data, extracting keywords, and analyzing frequently occurring phrases. It receives the stored data as input and outputs a trained feature set. It then generates an artificial intelligence model based on this feature set.

[1054] Step 3:

[1055] Integration with messaging applications

[1056] The user allows integration with the messaging application. The server retrieves chat history with the deceased person from the messaging application and collects additional data. The server takes the chat history as input and outputs an additional dataset after analysis.

[1057] Step 4:

[1058] Updates and improvements to AI models

[1059] The server uses all collected data to update the existing AI model and improve its accuracy. Here, newly acquired data is added to the model and re-training is performed. This re-training includes optimizing the model, and the output is an updated AI model.

[1060] Step 5:

[1061] Interaction through interface means

[1062] The user wears smart glasses or a head-mounted display and initiates a dialogue with the AI ​​model via the device, which accepts voice or text data as input, analyzes it, and generates an appropriate response, providing the user's visual or audio feedback as output.

[1063] Step 6:

[1064] Emotion recognition and response generation using an emotion engine

[1065] The server analyzes the user's voice and text data using an emotion engine to recognize emotions. It receives the user's response as input and outputs an appropriate response generated by the AI ​​model based on that emotional data. For example, if the user says "I'm lonely," the emotion engine recognizes this as "sadness" and generates a response such as "It's okay, I'm always here for you."

[1066] Step 7:

[1067] Recording interactions and continuously improving the model

[1068] The server records the conversation between the user and the AI ​​model and later analyzes it. This allows further model updates and emotion engine improvements based on new data. It receives the conversation recording data as input, analyzes it, and outputs updates to the model and emotion engine.

[1069] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1070] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1071] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1072] [Fourth embodiment]

[1073] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1074] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1075] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1076] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1077] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1078] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1079] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1080] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1081] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1082] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1083] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1084] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1085] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1086] This invention is a system that vividly recreates the personality and memories of a deceased person by receiving and storing document, image, and video data of the deceased, analyzing that data, and generating an AI model that has learned the characteristics of the deceased. Specific embodiments are described below.

[1087] 1. Data collection and storage

[1088] Users can digitize letters, notes, photos, video messages, and other documents from the deceased and upload them to the server via a dedicated application or web portal. For example, users can take a photo of a letter from the deceased with their smartphone and upload the image to the server.

[1089] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into text using voice recognition technology.

[1090] 2. Data collection through LINE integration

[1091] The user authorizes integration with the messaging application. This integration is achieved by the user providing account information and granting access to the system. For example, the user logs in to their LINE account and grants permission for the system to obtain data.

[1092] The server collects chat history and message data from authorized messaging applications, creating a database of interactions and conversation styles with the deceased.

[1093] 3. Generating AI models

[1094] The server analyzes the collected data. Specifically, it uses natural language processing (NLP) algorithms to extract keywords, frequently occurring phrases, and speech patterns from the text. Based on the results of this analysis, an AI model that learns the characteristics of the deceased is generated.

[1095] The resulting AI model is then used to recreate the writing style and speaking patterns of the deceased. For example, if it is determined that the deceased frequently used the word "thank you," the model will reflect that same tendency.

[1096] 4. Dialogue with a digital portrait

[1097] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[1098] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[1099] The terminal displays the response from the server and continues the dialogue with the user. This interactive experience allows the user to reaffirm their bond with their deceased loved one.

[1100] 5. Update and improve AI models

[1101] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model, which allows the system to continually improve and increase its ability to provide more natural responses.

[1102] For example, when a user asks the system, "How are you doing lately?", the system extracts the appropriate context from past data and generates a response such as, "I've been a little busy lately, but I'm doing well."

[1103] The above is a specific embodiment for carrying out the present invention. As a tool for remembering the deceased, the system can ease the user's grief and provide comfort through dialogue with the deceased.

[1104] The processing flow will be explained below.

[1105] Step 1: Data collection

[1106] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal.

[1107] The server receives the uploaded data and stores it electronically.

[1108] Step 2: Data conversion

[1109] The server converts the image data into text data using OCR (optical character recognition) technology.

[1110] Example: Converting an image of a letter to text.

[1111] The server converts the video data into text using voice recognition technology.

[1112] Example: Converting audio to text for video messages.

[1113] Step 3: LINE integration

[1114] The user allows collaboration with the messaging application.

[1115] The server collects chat history and message data from authorized messaging applications.

[1116] Step 4: Data analysis

[1117] The server analyzes the collected text data using natural language processing (NLP) technology.

[1118] The server extracts keywords, frequent phrases, and speaking patterns from the text.

[1119] Step 5: Artificial Intelligence Model Generation

[1120] Based on the analysis results, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[1121] The server integrates the generated artificial intelligence model into the digital memorial portrait system.

[1122] Step 6: Provide a conversational interface

[1123] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[1124] The user speaks to the deceased via voice or text.

[1125] Step 7: Submitting input data

[1126] The terminal transmits the input data from the user to the server.

[1127] Step 8: Response Generation

[1128] The server uses artificial intelligence models to generate appropriate responses based on the received user input data.

[1129] Step 9: View the response

[1130] The terminal displays the response from the server to the user and continues the dialogue.

[1131] Step 10: Update and improve the AI ​​model

[1132] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[1133] The server redeploys the updated AI model and reflects it throughout the system.

[1134] The above is the specific processing flow of the system.

[1135] Example 1

[1136] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1137] While there are many ways to commemorate the deceased, existing technologies have difficulty vividly recreating the deceased's personality and memories. In particular, there are few systems that can recreate an individual's writing style and speaking style and allow users to feel a connection with the deceased through conversation. Furthermore, the lack of specific technological means to efficiently and accurately collect and analyze the deceased's data and generate artificial intelligence models risks degrading the quality of the conversation experience with the deceased.

[1138] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1139] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for converting image data into character data using optical character recognition technology, means for converting voice data into text data using voice recognition technology, means for analyzing the stored data and extracting keywords and frequently occurring phrases from the data using natural language processing technology to generate an AI model, interface means for interacting with the generated AI model, means for linking with a message application via communication means to collect data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for displaying the generated responses to the user. This allows the personality and memories of the deceased to be vividly reproduced, making it possible to feel a bond with the deceased through interaction.

[1140] "Documents of the deceased" refers to text data such as letters, notes, memos, and diaries written by the deceased during their lifetime.

[1141] "Image data" refers to still image data that has been digitized from photographs or handwritten text of the deceased.

[1142] "Video data" refers to video data that records the deceased's video messages and daily activities.

[1143] "Means for receiving and storing" refers to the function of digitally capturing documents, image data, and video data of the deceased person provided by the user and storing them on a server.

[1144] Optical character recognition (OCR) is a technology that automatically reads characters contained in image data and converts them into text data.

[1145] "Speech recognition technology" is a technology that analyzes the audio contained in video data and converts it into text data.

[1146] "Means for analysis" refers to a function that uses natural language processing technology to extract keywords and frequently occurring phrases from stored data and analyze the characteristics of the deceased.

[1147] An "artificial intelligence model" is a computer program that learns the writing style and speaking style of the deceased from collected and analyzed data.

[1148] "Interface means" refers to input and output functions that allow a user to interact with an artificial intelligence model using voice or text.

[1149] "Communication means" refers to the ability to send and receive data to and from message applications via the Internet or other communications networks.

[1150] A "messaging application" is software for chatting and exchanging messages.

[1151] "Means of updating and improving" refers to the ability to use new data collected to improve the accuracy of the artificial intelligence model and enable it to generate more natural responses.

[1152] The "means for generating a response" is a function that creates an appropriate response to an input from a user based on the generated artificial intelligence model.

[1153] The "means for displaying" is a function that provides the response from the server to the user visually or audibly.

[1154] This invention is a system for recreating the personality and memories of a deceased person by receiving and storing documents, images, and video data of the deceased, analyzing the data, and generating an artificial intelligence model. Specific embodiments are described below.

[1155] 1. Data collection and storage

[1156] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[1157] The server receives and stores the uploaded data. When storing, image data is converted to text data using Tesseract OCR, and video messages are converted to text data using the Google Speech-to-Text API.

[1158] 2. Data collection through LINE integration

[1159] The user authorizes integration with a messaging application. The user provides account information and completes the procedure to allow access to the system. For example, the user logs in to their LINE account and gives the system permission to obtain data.

[1160] The server collects chat history and message data from authorized messaging applications, which is used to model interactions and conversational styles with the deceased.

[1161] 3. Generating AI models

[1162] The server analyzes the collected data using Python's natural language processing libraries, NLTK and SpaCy. This extracts keywords, frequent phrases, and speech patterns from the text, generating an AI model that learns the characteristics of the deceased. For example, if the deceased frequently used the word "thank you," this will be reflected in the model.

[1163] 4. Dialogue with a digital portrait

[1164] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[1165] The server receives input from the user and uses the generated artificial intelligence model to generate an appropriate response. For example, if the user asks, "How are you?", the server generates a response such as, "I'm fine, thank you!" and sends it to the device.

[1166] The terminal displays the response from the server and continues the dialogue with the user, allowing the user to enjoy the experience of interacting with the deceased.

[1167] 5. Update and improve AI models

[1168] The server analyzes records of user interactions and performs updates to improve the accuracy of the artificial intelligence model. This allows the system to continuously improve and become more capable of providing more natural responses. For example, if the system is asked by a user, "How are you doing lately?", it can extract appropriate context from past data and generate a response such as, "I've been a little busy lately, but I'm doing well."

[1169] Specific examples

[1170] For example, if a user uploads letters and photos of their deceased grandfather, the system analyzes them and learns the grandfather's characteristic speaking style and vocabulary. Based on this learning result, when a user asks, "Grandpa, how are you?", the system can generate a response such as, "I'm fine, thank you!"

[1171] Prompt Sentence Examples

[1172] "I've uploaded a letter from a deceased person. Please analyze it and extract features."

[1173] "Since you have authorized the integration of LINE messages, please collect chat data with the deceased person and learn their conversation style."

[1174] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1175] Step 1: Upload your data

[1176] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server via a dedicated application or web portal. For example, a user can take a photo of a letter with their smartphone and upload the image via the app.

[1177] Input: Digitized image and video data

[1178] Output: Raw data stored on the server

[1179] Specific operation: The user launches the app on their smartphone, presses the upload button, and selects the data they want to save. The app then sends the data to the server, which receives and saves it.

[1180] Step 2: Transform the data

[1181] The server converts uploaded image data into text data using Tesseract OCR, and converts video messages into text data using the Google Speech-to-Text API.

[1182] Input: Uploaded raw data (image data and video data)

[1183] Output: Parsed text data

[1184] Specific operation: The server launches Tesseract OCR, receives image data as input, and generates text data. Similarly, it inputs video data into the Google Speech-to-Text API and converts the audio into text data.

[1185] Step 3: Collecting data from messaging applications

[1186] The user authorizes integration with a messaging application (e.g., LINE). The user provides account information and completes the procedure to authorize access to the system.

[1187] The server collects chat history and message data from authorized messaging applications.

[1188] Input: Account information that is allowed to be linked

[1189] Output: Captured chat history and message data

[1190] Specific operation: The user logs in to their LINE account and grants permission to the system to retrieve data. The server uses the API to collect past chat history from LINE and saves it in a database.

[1191] Step 4: Analyze the data and generate an artificial intelligence model

[1192] The server analyzes the collected data, using Python natural language processing libraries NLTK and SpaCy to extract keywords, frequent phrases, and speaking patterns from the text.

[1193] Input: Parsed text data and chat history

[1194] Output: AI model that has learned the characteristics of the deceased

[1195] How it works: The server uses NLTK or SpaCy to analyze text data and extract distinctive writing styles and keywords. It then uses machine learning algorithms to generate an AI model based on these features.

[1196] Step 5: User interaction

[1197] The terminal displays the digital portrait and provides an interface that allows interaction with the user, who speaks to the deceased by voice or text, and whose input is transmitted to the server via the interface.

[1198] The server receives input from the user and generates an appropriate response using the generated artificial intelligence model.

[1199] The terminal displays the response from the server and continues the dialogue with the user.

[1200] Input: User voice or text input

[1201] Output: The generated response message

[1202] How it works: When a user speaks to the device, the device converts the speech into text and sends it to the server. The server then inputs the resulting text into an artificial intelligence model to generate a response. The generated response is then sent back to the device and displayed to the user.

[1203] Step 6: Analyze interaction data and update the model

[1204] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model.

[1205] Input: Record of user interaction

[1206] Output: Updated artificial intelligence model

[1207] How it works: The server analyzes user interaction records to learn frequent patterns and new keywords, then retrains the existing AI model with the new information to improve its accuracy.

[1208] The above are the specific processing steps of this system.

[1209] (Application example 1)

[1210] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1211] Tools for remembering the deceased are limited to physical possessions and photographs, making it difficult to converse with the deceased or reminisce about memories. Furthermore, there are still no systems in place that use digitized information to recreate the personality and characteristics of the deceased and provide an interactive experience. There is a need for a system that allows people to converse with the deceased and relive memories in physical stores.

[1212] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1213] In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for providing an interactive interface with the deceased in a physical store, and means for updating and improving the AI ​​model using the collected data. This allows users to interactively experience memories with the deceased even in a physical store, enriching their interactions with the deceased and recreating their memories.

[1214] "Documents, images and video data of the deceased" refers to various forms of digitized information left behind by the deceased during their lifetime, such as handwritten letters, diaries, photographs and video messages.

[1215] "Means for receiving and storing" refers to the technology and systems that allow the server to receive digital data uploaded by users and store it electronically.

[1216] "Means for analyzing and generating an AI model that learns the characteristics of the deceased" refers to technology that analyzes stored digital data using natural language processing and image recognition algorithms to create an AI model that reproduces the speech, behavior, and style of the deceased.

[1217] "Interface means" refers to the input and output devices through which a user interacts with an artificial intelligence model, and the software that manages that interaction.

[1218] "Linking with a messaging application via a communication means" refers to technology that links a user's messaging application account with the system using the Internet or other communication protocols.

[1219] "Data of interactions with the deceased" refers to message exchanges and chat history between the user and the deceased while they were alive.

[1220] "Means for providing an interactive interface with the deceased in a physical store" refers to hardware and software for providing an environment in which users can interact with an artificial intelligence model of the deceased through terminals or kiosks installed in a physical store.

[1221] "Means of updating and improving" refers to technologies for improving the accuracy of AI models and the naturalness of their responses based on new collected data and user interaction logs.

[1222] This invention is an interactive system that recreates the personality and memories of a deceased person by using documents, images, and video data of the deceased to generate an artificial intelligence model and provide an interactive interface in a physical store.

[1223] Data collection and storage

[1224] Users upload digital data such as letters, records, photos, and video messages from the deceased to the server using dedicated terminals in the store. Optical character recognition (OCR) and voice recognition technologies are used to convert image and audio data into text data, which is then saved as text. The server receives the uploaded data and stores it electronically.

[1225] Generating AI models

[1226] The server analyzes the stored data and uses natural language processing (NLP) algorithms to generate an AI model that learns the characteristics of the deceased, such as extracting keywords, frequent phrases, and speech patterns from the text. The generated AI model is then used to recreate the writing style and speaking style of the deceased.

[1227] Providing interactive interfaces in physical stores

[1228] The terminal installed in the store acts as a digital memory consultant, providing an interface that allows users to interact with the deceased. Users can speak to the deceased by voice or text. This input is sent to the server via the interface. The server uses the generated artificial intelligence model to generate an appropriate response and sends it back to the terminal. Users can view this response and enjoy interacting with the deceased.

[1229] AI model updates and improvements

[1230] The server analyzes the conversation records and continuously updates the AI ​​model to improve its accuracy. This allows the system to provide more natural responses over time. For example, if a user asks, "How are you doing lately?", the system can extract appropriate context from past data and generate a response such as, "I've been a bit busy lately, but I'm doing well."

[1231] Specific examples

[1232] For example, if a user asks, "Dad, how was your day?", the system will respond, "I worked in the garden all day today. The flowers are blooming beautifully." An example of a prompt sentence is, "If a user asks about the deceased's hobbies, please provide appropriate context and generate a response. For example, in response to a user question: 'Dad, what are your hobbies these days?', the deceased's response would be, 'I've been into photography lately. I take pictures in various places while walking.'"

[1233] Through this system, users can interactively experience memories of the deceased even in a physical store, allowing them to enjoy interacting with the deceased and reliving memories in a richer way.

[1234] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1235] Step 1:

[1236] The user uploads the document, image, and video data of the deceased person to the server using a terminal in the store. This uploaded data is received by the server and stored electronically. The input is digitized document, image, and video data, which the server converts into a data format for storage and stores on the file server. Specifically, the user uses the upload function of the terminal to select the data file of the deceased person and presses the "upload" button.

[1237] Step 2:

[1238] The server applies OCR or speech recognition technology to the uploaded data, converting image data or audio data into text data. This process uses OCR software (e.g., Tesseract OCR) or speech recognition software (e.g., Google Cloud Speech-to-Text). The input is image data or audio data, and the output is text data obtained by analyzing it. Specifically, the server passes an image file to the OCR software and receives the text as a processing result, or passes an audio file to speech recognition software and converts it into a string of characters.

[1239] Step 3:

[1240] The server analyzes the stored text data using a natural language processing (NLP) algorithm to generate an AI model that learns the characteristics of the deceased. Specifically, it uses Hugging Face's Transformer library, taking text data as input and outputting a generative AI model that reflects the deceased's behavior and conversation style. Specifically, it preprocesses the text data, inputs it into an NLP module, and trains the model.

[1241] Step 4:

[1242] The user uses an interface through a terminal to interact with an AI model of the deceased person. The user inputs voice or text, which is then sent to a server. The server analyzes the voice or text input and uses the AI ​​model to generate an appropriate response. Specifically, the user asks a question into a microphone, and the voice is converted into text and sent to the server.

[1243] Step 5:

[1244] The server generates a response based on the generated AI model and sends it back to the device. The input is the analysis result of the user's question, and the output is a response text that reproduces the deceased's writing style and speaking manner. Specifically, the server generates a prompt based on the dialogue log, inputs it into the AI ​​model to generate a text response, and sends it to the device.

[1245] Step 6:

[1246] The server analyzes the dialogue log with the user and updates the AI ​​model to improve its accuracy. The input is the dialogue log with the user, and the output is the updated AI model. Specifically, the server analyzes the dialogue log and re-learns frequently used phrases and patterns.

[1247] In this way, a system has been created that provides an interactive experience that recreates memories and conversations with the deceased, enabling rich dialogue even in physical stores.

[1248] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1249] This invention provides a system that vividly recreates the personality and memories of a deceased person and further recognizes the user's emotions and adjusts responses accordingly. This system receives and stores document, image, and video data of the deceased, analyzes the data, and generates an artificial intelligence model that learns the characteristics of the deceased. Furthermore, by combining it with an emotion engine, it is possible to recognize the user's emotional state and generate responses accordingly. Specific embodiments are described below.

[1250] 1. Data collection and storage

[1251] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to a server through a dedicated application or web portal. This uploading is done to permanently preserve memories of the deceased as digital data. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file to the server.

[1252] The server receives the uploaded data and stores it electronically. At this time, image data is converted into text data using OCR (Optical Character Recognition) technology, and video data is converted into audio data using voice recognition technology.

[1253] 2. Data collection through LINE integration

[1254] The user allows the system to connect to a messaging application. This connection allows the system to collect chat history and message data with the deceased. For example, the system can obtain messages exchanged between the deceased and the user on LINE.

[1255] The server collects chat history and message data from authorized messaging applications and stores it in a database, which allows for a better understanding of the conversation style and language used with the deceased.

[1256] 3. Generating AI models

[1257] The server analyzes the collected data using natural language processing (NLP) technology. Specifically, it extracts keywords and frequently occurring phrases in the text, as well as speech patterns. For example, if the deceased frequently used the word "thank you," that tendency can also be learned.

[1258] Based on the analysis results, the server generates an AI model that learns the characteristics of the deceased. This model is used to recreate the deceased's writing style and speaking style. The AI ​​model is then integrated into the digital memorial portrait system.

[1259] 4. Incorporating an Emotional Engine

[1260] The server uses an emotion engine to analyze the user's voice and text data and recognize their emotions. For example, if a user says "I feel lonely" in a sad voice, the emotion engine will recognize that emotion as "sadness."

[1261] Based on the recognized emotion, the server adjusts the response generated by the AI ​​model. For example, if the user speaks to the deceased in a sad voice, the AI ​​model of the deceased person will offer comforting words such as, "It's okay, I'm always here for you."

[1262] 5. Dialogue with a digital portrait

[1263] The terminal displays the digital portrait and provides an interface that allows interaction with the user: the user can speak to the deceased by voice or text, and their input is transmitted to the server via the interface.

[1264] The server receives input data from the user and uses artificial intelligence models and emotion engines to generate appropriate responses. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay."

[1265] The terminal displays the response from the server to the user and continues the dialogue, allowing the user to enjoy an interactive dialogue with the deceased.

[1266] 6. Update and improve AI models

[1267] The server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[1268] As a concrete example, consider a situation where a user asks, "How are you doing lately?" In this case, if the emotion engine recognizes the user's emotion as "relief" or "curiosity," the server will respond with, "I'm fine, how are you?"

[1269] The above is a specific embodiment of the present invention. As a tool for remembering the deceased, the present system aims to provide a richer interactive experience while deeply understanding the user's emotions.

[1270] The processing flow will be explained below.

[1271] Step 1: Data collection

[1272] Users digitize letters, notes, photos, and video messages from the deceased and upload them to a server through a dedicated application or web portal.

[1273] The server receives the uploaded digital data and stores it in secure electronic storage.

[1274] Step 2: Data conversion

[1275] The server converts the stored image data into text data using OCR (optical character recognition) technology.

[1276] Example: Scan an image of a letter and convert the text written on it into text data.

[1277] The server converts the audio of the stored video data into text using voice recognition technology.

[1278] Example: Analyzing the audio portion of a video message and converting its content into text data.

[1279] Step 3: LINE integration

[1280] The user allows the messaging application to link with the system.

[1281] The server collects chat history and message data from authorized messaging applications.

[1282] Example: Obtain chat history between the deceased and the user from LINE and save it as text data.

[1283] Step 4: Data analysis

[1284] The server analyzes the collected text data of the deceased using natural language processing (NLP) technology.

[1285] Example: Extracting frequent phrases and keywords from text data and analyzing the tone and style of writing.

[1286] Based on the analysis results, the server incorporates the characteristics of the deceased into a model.

[1287] Step 5: Artificial Intelligence Model Generation

[1288] Based on the results of the data analysis, the server generates an artificial intelligence model that learns the characteristics of the deceased.

[1289] For example, learning the speech habits and specific expressions of the deceased and incorporating them into the model.

[1290] The server prepares the generated AI model for integration into the digital memorial portrait system.

[1291] Step 6: Incorporating the Emotion Engine

[1292] The server incorporates an emotion engine that analyzes the user's voice or text data and recognizes emotions.

[1293] For example: If a user says "I feel sad...", the emotion engine will recognize the emotion "sad".

[1294] The server adjusts the response of the artificial intelligence model based on the recognized emotion.

[1295] For example, if the user is feeling sad, the AI ​​model responds, "Don't worry, I'll always be here for you."

[1296] Step 7: Providing a conversational interface

[1297] The terminal displays the digital portrait and provides an interface that allows interaction with the user.

[1298] Example: A user opens an interactive screen that displays a digital portrait of a deceased person.

[1299] Users can speak to the deceased through voice or text.

[1300] Step 8: Submitting input data

[1301] The terminal transmits voice or text input data from the user to the server.

[1302] Step 9: Response Generation

[1303] The server uses an AI model to generate an appropriate response based on the received user input data and emotion recognition results.

[1304] For example, if a user says, "I miss you," the AI ​​model will consider the emotion and respond, "I miss you too. But it's okay, we'll be together."

[1305] Step 10: View the response

[1306] The terminal displays the response from the server to the user and continues the dialogue.

[1307] Step 11: Update and improve the AI ​​model

[1308] The server analyzes the dialogue records and performs updates to improve the accuracy of the AI ​​model and emotion engine.

[1309] Example: Improving AI models based on user feedback and new interaction data.

[1310] The server redeploys the updated AI model and reflects it throughout the system.

[1311] The above is the specific processing flow of the system.

[1312] Example 2

[1313] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1314] There is a need for a system that can vividly recreate memories of the deceased while recognizing the user's emotions and adjusting its responses. However, conventional systems have not only struggled to accurately reproduce the characteristics and speaking style of the deceased, but also failed to generate responses that correspond to the user's emotional state. This has prevented users from having a natural conversational experience with the deceased, making it difficult to achieve emotional satisfaction.

[1315] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving and storing document, image, and video data of the deceased, means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased, interface means for interacting with the generated AI model, means for linking with a message application via communication means and collecting data on interactions with the deceased, means for updating and improving the AI ​​model using the collected data, and means for recognizing the user's emotions and adjusting responses using an emotion engine. This enables a natural interaction experience with the deceased, and provides the user with emotional satisfaction.

[1316] "Deceased documents, images and video data" refers to information stored in digital form that contains personal memories and recollections, such as letters, diaries, photographs and video messages left by the deceased during their lifetime.

[1317] "Means for receiving and storing" refers to a mechanism for receiving digital data provided by a user and storing it in an appropriate form, using a server, database, etc.

[1318] "Means for analyzing and generating an artificial intelligence model that learns the characteristics of the deceased" refers to technology that analyzes collected data using natural language processing and machine learning techniques to model the speaking style and vocabulary of the deceased.

[1319] An "interface means" is a combination of software and hardware that allows a user to interact with a system through voice and / or text.

[1320] "Linking with a messaging application via a communication means" refers to the function of exchanging data with a messaging application using the Internet or other communication protocols.

[1321] "Means of collecting data on interactions with the deceased" refers to methods for importing past chat history and message content into the system through LINE or other messaging applications.

[1322] "Means of updating and improving artificial intelligence models using collected data" refers to a method for improving the accuracy and response capabilities of artificial intelligence by analyzing records of interactions with users and applying new information to the model.

[1323] "Means for recognizing user emotions and adjusting responses using an emotion engine" is a technology for analyzing the emotional state of a user from their voice or text and optimizing the system response based on that.

[1324] This invention provides a system that recreates the personality and memories of a deceased person, recognizes the user's emotions, and adjusts responses accordingly. This system receives and stores documents, images, and video data of the deceased, analyzes them, and generates an artificial intelligence model. It also uses an emotion engine to recognize the user's emotions and adjust responses accordingly. Specific embodiments are described below.

[1325] Users can digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. For example, a user can take a photo of a letter from the deceased with their smartphone and upload the image file using a dedicated application.

[1326] The server receives the uploaded data and stores it in a database. During this data storage process, image data is converted into text data using "Tesseract OCR." For video data, audio data is converted into text using "Google Speech-to-Text." This makes it possible to process the stored data as text.

[1327] By allowing the user to connect to a messaging application (e.g., LINE), the system can import chat history and past message data with the deceased person. The server then collects the chat history and message data from the authorized messaging application and stores them in a database. This allows for the reproduction of more natural conversations.

[1328] The server then analyzes the collected data using natural language processing (NLP) techniques. Specifically, it uses libraries such as SpaCy and NLTK to extract keywords, frequent phrases, and speech patterns from the text. Based on the results of this analysis, the server uses generative AI models such as GPT-3 and BERT to generate an AI model that reflects the characteristics of the deceased.

[1329] The server then uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to create an emotion engine. This engine analyzes the user's voice and text data to recognize emotions. Once the user's emotion is recognized, the server can adjust the response provided by the generated AI model based on that emotion. For example, if the user sadly says "I'm lonely," the emotion engine will recognize that emotion as "sadness" and provide comforting words.

[1330] The device displays a digital portrait and provides an interface that allows users to interact with the deceased. When the user speaks to the deceased by voice or text, the input data is sent via the device to the server. The server uses an artificial intelligence model and emotion engine to generate an appropriate response based on the received data. For example, if the user says "I miss you," the server generates a response such as "I miss you too, but it's okay," and sends it to the device. The device then displays this response to the user, allowing the conversation to continue.

[1331] Finally, the server analyzes the dialogue recordings and performs updates to improve the accuracy of the artificial intelligence model and emotion engine, allowing the system to continuously improve and enable more natural responses and emotion recognition.

[1332] Examples of concrete examples and prompts

[1333] A user takes a photo of a letter from a deceased person and uploads it through the app:

[1334] "Please take a photo of the letter from the deceased person with your smartphone and upload this image file using a dedicated application."

[1335] Situations where the user allows integration with the LINE app:

[1336] "Please allow the LINE app to connect and import the chat history with the deceased person into the system."

[1337] The server generates an AI model of the deceased person:

[1338] "The collected data is used to generate an artificial intelligence model that learns the characteristics of the deceased."

[1339] A scene where the server recognizes emotions and adjusts responses:

[1340] "If the user speaks in a sad voice, it will recognize that emotion and offer words of comfort."

[1341] A scene where you interact with a digital portrait:

[1342] "Interact with the digital portrait via voice or text and enjoy the responses."

[1343] In this way, it is possible to vividly recreate memories of the deceased and provide natural dialogue that matches the user's emotions.

[1344] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1345] Step 1: Collect and store data

[1346] Users digitize letters, notes, photos, video messages, etc. from the deceased and upload them to the server through a dedicated application or web portal. The input data is image files of letters and video files. The server receives this data and stores it in a database. For image data, it uses "Tesseract OCR" to convert it into text data, and for video data, it uses "Google Speech-to-Text" to convert audio data into text. The output is text data. For example, if a user uploads a photo of a letter, the server analyzes the image and saves it as text data.

[1347] Step 2: Data collection through LINE integration

[1348] The user allows integration with a messaging application. The input is permission to integrate with a messaging application such as LINE. The server collects chat history and message data from the authorized messaging application and stores it in a database. The output is chat history in text format. As a specific example, when the user allows integration with LINE, the server obtains past message data with the deceased person and stores it.

[1349] Step 3: Generate an artificial intelligence model

[1350] The server uses natural language processing (NLP) technology to analyze the data collected in steps 1 and 2. The input is text data. Specifically, it uses "SpaCy" or "NLTK" to extract keywords, frequently occurring phrases, and speaking patterns within the text. Based on the analysis results, the server generates an artificial intelligence model using "GPT-3" or "BERT." The output is an AI model that reproduces the writing style and speaking style of the deceased. For example, it learns phrases frequently used by the deceased and generates an AI model that reflects them.

[1351] Step 4: Incorporating the Emotion Engine

[1352] The server uses IBM Watson Tone Analyzer and Microsoft Azure Emotion API to analyze the user's voice and text data and recognize emotions. The input is voice and text data containing the user's emotions. The emotion engine performs the analysis, and the server adjusts the response generated by the AI ​​model based on the recognized emotion. The output is a response text appropriate to the emotion. For example, if a user sadly says "I'm lonely," the emotion engine will recognize the emotion as "sadness" and respond with "It's okay, I'm always here for you."

[1353] Step 5: Interact with the digital portrait

[1354] The terminal displays the digital portrait and provides an interface that allows interaction with the user. Input is voice or text data from the user. The server receives the input data from the user and generates an appropriate response using the generated artificial intelligence model and emotion engine. The output is a dialogue-style response text. The terminal displays this response to the user, and the dialogue continues through the interface. For example, if the user says "I miss you," the server responds "I miss you too, but it's okay," and the terminal displays it.

[1355] Step 6: Update and improve the AI ​​model

[1356] The server analyzes the dialogue records and performs updates to improve the accuracy of the artificial intelligence model and emotion engine. The input is the dialogue records. Based on these records, machine learning technology is used to improve the model. Specifically, when a user asks "How are you doing lately?", the response is evaluated and improvements are made. The output is an AI model with improved accuracy.

[1357] (Application example 2)

[1358] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1359] To remember a deceased loved one, it is important to not only look back at photos and videos of that person, but also to be able to interactively experience deeper memories. However, current systems have difficulty not only reproducing the characteristics of the deceased, but also accurately recognizing the user's emotions and responding accordingly. Furthermore, there are not enough systems in place to allow users to enjoy conversations with the deceased in physical settings such as brick-and-mortar stores.

[1360] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1361] In this invention, the server includes: means for receiving and storing document, image, and video data of the deceased; means for analyzing the stored data and generating an AI model that learns the characteristics of the deceased; interface means for interacting with the generated AI model; means for linking with a message application via communication means and collecting data on interactions with the deceased; means for updating and improving the AI ​​model using the collected data; means for allowing a user to enjoy interactive conversations with the deceased using smart glasses or a head-mounted display; and means including an emotion engine that recognizes the user's emotions and reflects them in responses. This allows a user to have a deeper, more emotional experience interacting with the deceased, making it possible to enjoy interactive conversations even in physical stores.

[1362] "Documents" are text data such as letters and notes written by the deceased.

[1363] "Images" are visual data such as photographs or illustrations of the deceased.

[1364] "Video data" refers to video or recorded footage of the deceased.

[1365] "Means of receiving and storing" refers to the mechanisms and software that capture data on digital devices or servers and store it securely.

[1366] "Analysis" is the process of extracting features and patterns from received and stored data.

[1367] An "artificial intelligence model" is an AI system that learns and reproduces the characteristics of the deceased.

[1368] "Means of generation" refers to the process of creating an artificial intelligence model based on the results of data analysis.

[1369] An "interface means" is an input and output mechanism by which a user interacts with a system.

[1370] "Communication means" refers to the technology that allows a system to exchange data with other devices and applications.

[1371] A "messaging application" is a software application that allows for sending and receiving messages.

[1372] "Means of collection" are the methods or techniques used to obtain data from messaging applications.

[1373] "Means of updating and improving" refers to the way new data collected is used to optimize and improve the AI ​​model.

[1374] "Smart glasses" are wearable eyeglass-type devices that have the ability to display information.

[1375] A "head-mounted display" is a device worn on the head that displays images in the field of vision.

[1376] "Interactive dialogue" refers to a form in which the user and the system interact with each other and respond in real time.

[1377] An "emotion engine" is a system that recognizes emotions from a user's voice or text and generates a response accordingly.

[1378] MODE FOR CARRYING OUT THE INVENTION

[1379] In an embodiment of the present invention, documents, images, and video data of the deceased person are first digitized and sent to a server. The server receives and stores the data using the following hardware and software:

[1380] Hardware: Digital devices, servers

[1381] Software: Data storage system

[1382] The server then analyzes the stored data and uses natural language processing (NLP) techniques to learn the characteristics of the deceased, using the following software:

[1383] Software: Natural language processing technology

[1384] The analyzed data is used to generate an artificial intelligence model, which is then used to recreate the writing style and speaking style of the deceased. The server also communicates with messaging applications to collect data on past interactions with the deceased, which is then stored for further analysis.

[1385] Next, the interface means to enable interactive dialogue are important. The following devices and applications are used as interface means:

[1386] Hardware: Smart glasses, head-mounted displays

[1387] Software: User Interface Application

[1388] The user wears smart glasses or a head-mounted display and interacts with a digital portrait of the deceased. The user's voice and text input is received and transmitted to the server through an interface. The server uses an emotion engine to analyze the user's emotions and adjusts responses accordingly. The emotion engine uses the following software:

[1389] Software: DeepFace, GPT-3

[1390] If a user says "I'm lonely," the emotion engine will recognize this as "sadness" and create a response that reassures the user, such as "Don't worry, I'm always here for you."

[1391] The server also continuously analyzes the dialogue records and updates and improves the AI ​​model and emotion engine to improve their accuracy, enabling more natural dialogue and emotion recognition.

[1392] For example, consider a situation where a user asks, "How are you doing lately?" In this case, the server analyzes the user's emotions and, if it recognizes them as, for example, "relief" or "curiosity," generates a response such as, "I'm fine, how are you?" An example prompt would be:

[1393] The user's emotion is sadness. As the deceased, respond to the following statement: I miss you

[1394] This system allows users to enjoy interactive dialogue with the deceased while creating a deep emotional connection.

[1395] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1396] Step 1:

[1397] Collection and storage of deceased data

[1398] Users digitize letters, photos, videos, etc. of the deceased and upload them to the server using a dedicated application on their device. The server receives and stores this data. It takes the digital data uploaded by the user as input and generates an organized database on the server as output.

[1399] Step 2:

[1400] Analyzing data and generating artificial intelligence models

[1401] The server analyzes the stored data using natural language processing (NLP) techniques to extract the characteristics of the deceased. This data analysis includes tokenizing text data, extracting keywords, and analyzing frequently occurring phrases. It receives the stored data as input and outputs a trained feature set. It then generates an artificial intelligence model based on this feature set.

[1402] Step 3:

[1403] Integration with messaging applications

[1404] The user allows integration with the messaging application. The server retrieves chat history with the deceased person from the messaging application and collects additional data. The server takes the chat history as input and outputs an additional dataset after analysis.

[1405] Step 4:

[1406] Updates and improvements to AI models

[1407] The server uses all collected data to update the existing AI model and improve its accuracy. Here, newly acquired data is added to the model and re-training is performed. This re-training includes optimizing the model, and the output is an updated AI model.

[1408] Step 5:

[1409] Interaction through interface means

[1410] The user wears smart glasses or a head-mounted display and initiates a dialogue with the AI ​​model via the device, which accepts voice or text data as input, analyzes it, and generates an appropriate response, providing the user's visual or audio feedback as output.

[1411] Step 6:

[1412] Emotion recognition and response generation using an emotion engine

[1413] The server analyzes the user's voice and text data using an emotion engine to recognize emotions. It receives the user's response as input and outputs an appropriate response generated by the AI ​​model based on that emotional data. For example, if the user says "I'm lonely," the emotion engine recognizes this as "sadness" and generates a response such as "It's okay, I'm always here for you."

[1414] Step 7:

[1415] Recording interactions and continuously improving the model

[1416] The server records the conversation between the user and the AI ​​model and later analyzes it. This allows further model updates and emotion engine improvements based on new data. It receives the conversation recording data as input, analyzes it, and outputs updates to the model and emotion engine.

[1417] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1418] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1419] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1420] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1421] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1422] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1423] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1424] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1425] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1426] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1427] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1428] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1429] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1430] 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.

[1431] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1432] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1433] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1434] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1435] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1436] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1437] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1438] The following is further disclosed regarding the above embodiment.

[1439] (Claim 1)

[1440] means for receiving and storing documents, images, and video data of the deceased;

[1441] means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased;

[1442] an interface means for interacting with the generated artificial intelligence model;

[1443] A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means;

[1444] A means of updating and improving the artificial intelligence model using the collected data; and

[1445] A system including:

[1446] (Claim 2)

[1447] 2. The system according to claim 1, wherein the interface means is capable of accepting voice input and text input and conducting a dialogue.

[1448] (Claim 3)

[1449] The system of claim 1, wherein responses are generated when the digital portrait interacts with the deceased based on the generated artificial intelligence model.

[1450] "Example 1"

[1451] (Claim 1)

[1452] means for receiving and storing documents, images, and video data of the deceased;

[1453] means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased;

[1454] an interface means for interacting with the generated artificial intelligence model;

[1455] A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means;

[1456] A means of updating and improving the artificial intelligence model using the collected data; and

[1457] means for converting image data into character data using optical character recognition technology;

[1458] A means for converting voice data into text data using voice recognition technology;

[1459] A means for extracting keywords and frequently occurring phrases from the analyzed data using natural language processing technology and generating an artificial intelligence model;

[1460] means for displaying the generated response to the user;

[1461] A system including:

[1462] (Claim 2)

[1463] 2. The system according to claim 1, wherein the interface means is capable of accepting voice input and text input and conducting a dialogue.

[1464] (Claim 3)

[1465] The system of claim 1, wherein responses are generated when the digital portrait interacts with the deceased based on the generated artificial intelligence model.

[1466] "Application Example 1"

[1467] (Claim 1)

[1468] means for receiving and storing documents, images, and video data of the deceased;

[1469] means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased;

[1470] an interface means for interacting with the generated artificial intelligence model;

[1471] A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means;

[1472] means for providing an interactive interface with the deceased person at a physical store;

[1473] A means of updating and improving the artificial intelligence model using the collected data; and

[1474] A system including:

[1475] (Claim 2)

[1476] 2. The system according to claim 1, wherein the interface means is capable of accepting voice input and text input and conducting a dialogue.

[1477] (Claim 3)

[1478] The system of claim 1, wherein a terminal installed in a physical store generates responses when interacting with the deceased based on the generated artificial intelligence model.

[1479] "Example 2: Combining Emotion Engines"

[1480] (Claim 1)

[1481] means for receiving and storing documents, images, and video data of the deceased;

[1482] means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased;

[1483] an interface means for interacting with the generated artificial intelligence model;

[1484] A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means;

[1485] A means of updating and improving the artificial intelligence model using the collected data; and

[1486] means for recognizing a user's emotions and adjusting a response using an emotion engine;

[1487] A system including:

[1488] (Claim 2)

[1489] 2. The system according to claim 1, wherein the interface means is capable of accepting voice input and text input and conducting a dialogue.

[1490] (Claim 3)

[1491] The system according to claim 1, wherein a response based on the analysis results of the emotion engine is generated based on the generated artificial intelligence model.

[1492] "Application example 2 when combining emotion engines"

[1493] New Claims

[1494] (Claim 1)

[1495] means for receiving and storing documents, images, and video data of the deceased;

[1496] means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased;

[1497] an interface means for interacting with the generated artificial intelligence model;

[1498] A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means;

[1499] A means of updating and improving the artificial intelligence model using the collected data; and

[1500] A means for users to enjoy interactive dialogue with the deceased using smart glasses or a head-mounted display;

[1501] means including an emotion engine for recognizing the emotion of the user and reflecting it in a response;

[1502] A system including:

[1503] (Claim 2)

[1504] 10. The system of claim 1, wherein the interface means is capable of accepting voice and text inputs, conducting dialogue, and providing an interactive visual experience.

[1505] (Claim 3)

[1506] The system of claim 1, wherein the generated artificial intelligence model is used to generate responses for the digital portrait when interacting with the deceased, and the responses are adjusted based on the user's emotional state. [Explanation of symbols]

[1507] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving and storing documents, images, and video data of the deceased; means for analyzing the stored data and generating an artificial intelligence model that learns characteristics of the deceased; an interface means for interacting with the generated artificial intelligence model; A means for collecting data on interactions with the deceased person by linking with a messaging application via a communication means; A means of using the collected data to update and improve the artificial intelligence model; and A system including:

2. 2. The system according to claim 1, wherein the interface means is capable of accepting voice input and text input and conducting a dialogue.

3. The system according to claim 1, wherein responses are generated when the digital portrait interacts with the deceased based on the generated artificial intelligence model.

Images