system

Abstract

We provide the system. [Solution] A means of inputting data to recreate the personality of the deceased, A method for fine-tuning the personality and behavioral characteristics of a deceased person using a generative model, A means of analyzing emotions based on user input and generating an appropriate response, Means for providing the generated response to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The strong sense of loss and loneliness that people who have lost their beloved deceased relatives may have can sometimes interfere with their daily lives. In such a state, people often try to organize their emotions in their own way, but it is difficult to obtain the necessary psychological support. Furthermore, professional counseling is expensive and there is a psychological and economic burden in using it. Therefore, there is a need for a more affordable and sustainable care method that can provide healing through interaction with the deceased.

Means for Solving the Problems

[0005] This invention utilizes digital data to recreate the personality of a deceased person. This provides a technology that realistically fine-tunes the personality and behavioral characteristics of the deceased through a generative model. By analyzing the emotions behind user messages and generating corresponding responses, users can interact with the deceased and process their emotions. Furthermore, the generated responses are protected with digital watermarking technology to ensure security, allowing users to receive psychological support with peace of mind.

[0006] The term "deceased person" refers to a specific individual who has passed away and who had a significant impact on their surviving family and loved ones.

[0007] "Personality" refers to the totality of an individual's character, emotional expression, and behavioral patterns, which give them a unique individuality that distinguishes them from others.

[0008] A "generative model" is an algorithm that uses artificial intelligence technology to generate new information or content from given data.

[0009] "Fine-tuning" is the process of making minor adjustments to a base model using specific data to improve its performance for a particular application or accuracy.

[0010] "Sentiment analysis" is the process of extracting and classifying emotions from text and audio using natural language processing and data mining techniques.

[0011] A "response" is the answer or reaction that a system provides to a user's input or inquiry.

[0012] "Digital watermarking" is a technology that embeds identification information into digital content and is used to protect data copyright and prevent tampering. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The system in this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. Specific embodiments are described below.

[0035] Data collection and input

[0036] The user inputs digital data about the deceased into the device. This data includes text messages, voice recordings, and images, and forms the basis of the deceased's personality. This data must be information authorized by the deceased during their lifetime. The user selects the data through the device's interface and sends it to the server.

[0037] Fine-tuning of the generative model

[0038] The server analyzes the received digital data and fine-tunes a generative model that reflects the deceased's speech patterns and behavioral patterns. This model is designed to reproduce the deceased's unique communication style.

[0039] Emotion analysis and response generation

[0040] The user initiates a conversation with the deceased AI through their device. The server receives the user's input messages and performs sentiment analysis. Based on the analysis results, the generative model generates the optimal response. This allows the user to continue the conversation as if the deceased were still alive.

[0041] Providing a response

[0042] The generated response is secured by watermarking technology. The server sends this response to the user's device, and the user receives the deceased AI's response, provided as a text message or voice message. This allows the user to relive time with the deceased.

[0043] Specific example

[0044] For example, suppose a user sends a message to a deceased AI saying, "I want to talk about recent events." The server analyzes this message to understand the user's current emotional state. The deceased AI might then respond, "What do you mean? I'd love to hear more." Seeing this response, the user can experience what it's like to actually talk to the deceased, which can help them process their emotions.

[0045] Thus, the present invention enables the realistic reproduction of a deceased person's personality using a generative model, providing users with a new way to reconnect with someone important to them.

[0046] The following describes the processing flow.

[0047] Step 1:

[0048] The user prepares digital data related to the deceased, such as text messages, voice recordings, and images, on their device. The device provides an interface for uploading this data, and the user sends the selected data to the server.

[0049] Step 2:

[0050] The server receives digital data sent from the user. The server checks the data format and quality, and performs data analysis to extract the deceased person's personality and past behavioral characteristics.

[0051] Step 3:

[0052] The server begins fine-tuning the generative model based on the received data. In this process, it learns the deceased person's unique communication style and voice characteristics, building a customized AI model.

[0053] Step 4:

[0054] The user initiates a conversation with the deceased AI via their device. The conversation progresses as the user sends input (text or voice) to the server.

[0055] Step 5:

[0056] The server analyzes user input in real time and uses natural language processing to evaluate intent and emotion. Based on this evaluation, the server uses a generative model to generate appropriate responses that reflect the deceased person's personality.

[0057] Step 6:

[0058] The server applies watermarking technology to secure the response it generates. Once the response is ready, the server sends it to the user's terminal.

[0059] Step 7:

[0060] The device displays a response to the user and plays an audio response if available. The user receives this response and can continue the conversation as needed.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] The aim is to recreate the personality of a deceased person using information technology, thereby providing emotional healing to users. However, this process requires protecting privacy based on the deceased's permission, showing consideration for the user's feelings, and improving the safety and quality of the responses provided.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] In this invention, the server includes a device for inputting information, a device for adjusting personality and behavioral characteristics using a generated knowledge model, a device for analyzing emotions based on user input and generating appropriate responses, and a device for applying technology to keep the generated responses secure. This allows users to find emotional healing through dialogue that recreates the personality of the deceased.

[0066] "Information input device" refers to hardware or software that allows users to provide digital information about the deceased to the system.

[0067] A "generated knowledge model" refers to the data structure of artificial intelligence that is created to reproduce the personality and behavioral characteristics of a deceased person based on the input digital information.

[0068] A "device for adjusting personality and behavioral characteristics" refers to a device that performs a process of fine-tuning the generated knowledge model to achieve a representation that is true to the deceased person.

[0069] A "device that analyzes emotions based on user input and generates appropriate responses" refers to a system component that receives user input, understands their emotional state, and devises a suitable response.

[0070] "Technologies to keep generated responses secure" refers to security technologies that prevent unauthorized access by third parties to data during transmission and storage.

[0071] The system of this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. A specific embodiment of this system is described below.

[0072] First, the terminal receives digital data about the deceased provided by the user. This data includes text messages, voice recordings, and image files, and is used as basic information to recreate the deceased's personality. Through the terminal's interface, the user can input data and send it to the server.

[0073] Next, the server uses the received digital data to fine-tune the generative AI model. Here, natural language processing (NLP) techniques are employed to analyze the deceased person's speech patterns and behavioral patterns, and incorporate them into the generated knowledge model. This generative AI model reproduces the deceased person's unique communication style, enabling dialogue that is faithful to that style.

[0074] When a user actually begins interacting with the AI ​​representing the deceased, they can input a message through their device. The server receives this input and performs sentiment analysis. Based on the analysis results, the model generates the optimal response.

[0075] As a concrete example, let's say a user sends a message to the deceased AI saying, "I want to talk about recent events." The server analyzes the content of this message to understand the user's emotional state and generates a response such as, "What do you mean? I'd love to hear more." This response is securely protected by watermarking technology and sent from the server to the user's device. The user can receive this response from the deceased AI via text message or voice, allowing them to experience what it's like to actually converse with the deceased.

[0076] A concrete example of a prompt message would be something like, "To recreate the deceased's personality, please train a generative model using the following data: text messages, voice recordings, images, etc."

[0077] Thus, this invention is a system that provides users with new opportunities for communication with their deceased loved ones and brings about emotional healing.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The user inputs digital data about the deceased into the terminal. Specifically, the user provides data in the form of text messages, voice recordings, image files, etc., and uploads it through the terminal's designated interface. After input, the terminal checks the data format to ensure it is correct. Next, it converts the data into a format ready for transmission to the server. The input consists of various digital data about the deceased, and the output is the digital data ready for transmission to the server.

[0081] Step 2:

[0082] The server receives digital data transmitted from the terminal. It verifies the format and integrity of the received data and then uses it as input for fine-tuning the generative AI model. Specifically, it analyzes the data using natural language processing (NLP) techniques to extract the deceased person's language patterns and behavioral characteristics. At this point, the input is formatted digital data, and the output is information for adjusting the generative model.

[0083] Step 3:

[0084] The generative AI model is fine-tuned using the deceased's characteristic information obtained from the server. In this process, the existing AI model is input with the deceased's unique linguistic expressions and response patterns, and the model is then fine-tuned based on this input. This reproduces the deceased's characteristic communication style. The input is data for tuning the model, and the output is a personalized generative AI model.

[0085] Step 4:

[0086] The user initiates a conversation with the deceased AI through their device. Specifically, they open the conversation interface on their device and enter a message for the deceased AI. This message is sent to the server as input. The input is the message sent by the user and includes the processing details that the server uses to analyze it.

[0087] Step 5:

[0088] The server analyzes the message received from the user and performs sentiment analysis to understand the intent and emotional state of the input data. Based on the analysis results, it generates the optimal response using a generative AI model. The specific processes here involve the application of sentiment analysis algorithms and the utilization of generative models. The input is the user's message, and the output is the generated response.

[0089] Step 6:

[0090] The generated response is securely transmitted from the server to the terminal using watermarking technology. The terminal interprets the received response and presents it to the user in text or audio. This allows the user to experience a conversation as if they were talking to a deceased person. The input is a pre-generated, secure response, and the output is the dialogue content presented to the end user.

[0091] (Application Example 1)

[0092] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0093] In modern society, there are many ways to remember the deceased, but methods that realistically recreate the personality and memories of the deceased, allowing users to find solace through natural dialogue with them, are limited. Furthermore, conventional interaction methods in virtual spaces have the problem of making it difficult for users to enjoy friendly communication with AI representations of the deceased. As a result, users are missing out on opportunities to experience new forms of interaction with their loved ones.

[0094] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0095] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for fine-tuning the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This enables the user to have a natural conversation with the deceased AI in a virtual space and experience a friendly interaction with the deceased.

[0096] "Information for recreating the deceased's personality" refers to digital data such as text messages, audio recordings, and images related to the deceased, which form the basis for recreating the deceased's unique communication style.

[0097] A "generative model" is an AI model that analyzes received digital data to reflect the personality and behavioral characteristics of the deceased, enabling realistic interaction with the user.

[0098] "Fine-tuning" is the process of adjusting a generative model based on the deceased person's digital data to reproduce their speech patterns and behavioral patterns.

[0099] "Means for analyzing emotions and generating appropriate responses" refers to technology that analyzes the user's emotional state based on input messages from the user, generates the optimal response, and provides it to the user.

[0100] "A means of providing a virtual space to facilitate interaction between users and the deceased AI" refers to a system that allows users to interact with the deceased AI in a virtual environment via a smart device, enabling friendly and approachable communication.

[0101] "Information based on permission given during the deceased's lifetime" refers to information for which the deceased consented to the use of digital data during their lifetime, and which will be used in a manner that respects privacy and consent.

[0102] "Information concealment technology" is a technique applied to ensure the security of generated responses, with the aim of protecting the response content from tampering and unauthorized access.

[0103] The system for realizing this invention includes a terminal for inputting the deceased's digital data, a server for processing the data, and an environment for enabling interaction with the user. First, the user uses the terminal to input information about the deceased, such as text messages, voice recordings, and images. This information is sent to the server as basic data for recreating the deceased's personality.

[0104] The server uses the received information to fine-tune the generated AI model. This process is necessary to reflect the deceased person's unique speech patterns and behavioral patterns in the model. The server also uses Google Cloud's Dialogflow or similar natural language processing technologies to analyze user messages and perform sentiment analysis to generate appropriate responses.

[0105] The generated responses are delivered to the user through a virtual space. In this process, smart devices play a role in facilitating the interaction between the user and the deceased AI. Users can interact with the deceased AI in a virtual environment via their smartphones or smart glasses, enjoying a new form of communication.

[0106] For example, if a user types "Tell me about your recent trip" into the device, the server analyzes their emotions and interests and generates a natural response from the AI, such as "What moments from that trip were particularly memorable?"

[0107] An example of a prompt in a generative AI model is an instruction such as, "When a user asks about the features of a product, how would the AI ​​explain it?" This helps ensure that the generated response is user-friendly and meaningful.

[0108] Through this invention, users can initiate friendly conversations with deceased AI figures in a virtual space and find emotional healing.

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The user inputs digital data about the deceased into the terminal. The input data consists of text messages, voice recordings, images, etc., and the terminal sends this information to the server. The input here is the basic data for recreating the personality of the deceased, and the output is the transmission of data to the server.

[0112] Step 2:

[0113] The server analyzes the received digital data and fine-tunes the generative AI model. Specifically, the server learns the deceased person's speech patterns and behavioral patterns based on the digital data and optimizes the model. The input is the received digital data, and the output is the fine-tuned generative model.

[0114] Step 3:

[0115] The user initiates a conversation with the deceased AI via a terminal. The terminal sends input messages from the user to the server. The input is a text message from the user, which is then output to the server.

[0116] Step 4:

[0117] The server receives messages from users and performs sentiment analysis. Specifically, it uses sentiment recognition algorithms to determine the user's emotional state. The input is the user's text message, and the output is the sentiment analysis result.

[0118] Step 5:

[0119] The server generates an appropriate response using a generative model based on the sentiment analysis results. The model utilizes prompt text to recreate the deceased person's communication style. Inputs are the sentiment analysis results and text prompts, while output is the generated response.

[0120] Step 6:

[0121] The server applies information concealment techniques to the generated response and sends it to the terminal. Specifically, the response message is processed to protect it from unauthorized access and tampering. The input is the generated response, and the output is the secure response message.

[0122] Step 7:

[0123] The terminal provides the user with responses generated in a virtual space. Specifically, the interaction with the deceased AI is visually and audibly reproduced through the device the user uses. The input is a safe response message, and the output is visual and audible feedback to the user.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention is a system that combines an emotional engine that recreates the personality of a deceased person with an emotional engine that understands the user's emotions. Through this system, the user can process their emotions and find emotional healing through dialogue with the deceased. Specific embodiments are described below.

[0126] Data collection and input

[0127] The user prepares digital data (text, audio, images, etc.) about the deceased on their device. This data forms the basis for recreating the deceased's personality. The user selects this data through their device and sends it to the server. This step requires the use of only data for which permission was obtained from the deceased during their lifetime.

[0128] Fine-tuning of the generative model

[0129] The server analyzes data sent by the user and fine-tunes a generative model to recreate the deceased person's personality and behavioral characteristics. This model has the ability to learn the deceased person's distinctive communication style and generate personalized responses.

[0130] Analysis using an emotion engine

[0131] The server has an emotion engine built in, which analyzes the input messages in real time once the user starts a conversation. The emotion engine recognizes the user's emotional state from their text and voice, and the generative model adjusts the response accordingly.

[0132] Response generation and provision

[0133] The server generates an appropriate response that reflects the deceased person's characteristics using a generative model. This response is tailored to the user's current emotions by an emotion engine, and its security is ensured by watermarking technology. The generated response is sent to the user's terminal, and the user confirms the response through the terminal.

[0134] Specific example

[0135] For example, if a user sends a text message saying, "Life has been tough lately," the server uses its emotion engine to recognize the user's emotion as "sadness." Based on this, the generative model generates a response in an encouraging tone, providing a message such as, "That must have been difficult. But I'm always rooting for you." Through this response, the user can feel as if they are actually being encouraged by the deceased, and it provides emotional support.

[0136] Thus, the present invention is a system that recreates communication with a deceased person in a new form and provides emotional support to the user.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The user gathers text, audio, and image data related to the deceased on their device and prepares to input it into the system. The device has an interface for sending this data to a server, and the user uploads the data they have selected.

[0140] Step 2:

[0141] The server receives data sent from the user. The server verifies the format and integrity of the data and performs data analysis to extract the information necessary to recreate the deceased person's personality.

[0142] Step 3:

[0143] The server fine-tunes the generative model based on the extracted information. This model is adjusted to reproduce the deceased person's unique speech patterns and behavioral characteristics. The model is optimized according to the user's individual needs.

[0144] Step 4:

[0145] The user initiates interaction via a terminal and sends a message to the system. The server receives this message and prepares to process it.

[0146] Step 5:

[0147] The server uses an emotion engine to analyze user messages and recognize their emotional state. The emotion engine uses natural language processing and emotion classification techniques to evaluate the user's emotions in real time.

[0148] Step 6:

[0149] Based on the results of the emotion engine, the server generates a response using a generative model. This response corresponds to the user's current emotional state and is tailored to reflect the deceased person's communication style.

[0150] Step 7:

[0151] The server applies watermarking technology to the generated response to ensure its security. The response is then sent to the user's terminal, allowing the conversation to continue.

[0152] Step 8:

[0153] The device displays a response to the user and, if necessary, plays it back as audio. The user receives this response and can continue the conversation.

[0154] (Example 2)

[0155] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0156] There is a need to maintain an emotional connection through records of the deceased, but conventional technologies are insufficient in recreating the personality of the deceased, recognizing the user's emotions, and providing appropriate responses. To solve this problem, it is necessary to more accurately recreate the characteristics of the deceased and generate appropriate responses that correspond to the user's emotions.

[0157] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0158] In this invention, the server includes means for inputting information related to the deceased, means for adjusting the characteristics of the deceased using a generative artificial intelligence model, and means for analyzing user input, recognizing emotions, and adjusting responses. This enables natural and emotional dialogue with the deceased and provides emotional support to the user.

[0159] "Information related to the deceased" refers to digital data such as text, audio, and images necessary to recreate the deceased's personality and behavioral characteristics.

[0160] A "generative artificial intelligence model" is a machine learning model that has the ability to learn the characteristics of a person based on input data and generate personalized responses.

[0161] "User input" refers to text and voice data that users provide to the server through interaction.

[0162] An "emotion engine" is a technology that analyzes user input in real time and recognizes the emotions behind it.

[0163] "Digital watermarking technology" is a technique used to ensure the security of digital data, and it involves embedding an invisible mark into the data.

[0164] "Adjusting the response" refers to optimizing the tone and content of the generated response based on the perceived emotions.

[0165] The embodiments for carrying out the present invention are described below.

[0166] In the system for implementing the invention, the user, terminal, and server play key roles. First, the user inputs information into the terminal to recreate the deceased person's personality. This information includes text, audio, and images related to the deceased, and only data permitted during their lifetime must be used. The terminal has the function of transmitting this data to the server.

[0167] The server analyzes the received data and uses a generative artificial intelligence model to fine-tune the model in order to recreate the deceased person's personality and behavioral characteristics. The generative artificial intelligence model used here is based on a large-scale machine learning framework and makes extensive use of natural language processing (NLP) techniques.

[0168] Next, the server is equipped with an emotion engine that analyzes the user's input through dialogue in real time. The emotion engine recognizes emotions from the user's input and can adjust the response output by the generating AI model to correspond to those emotions. The response is protected by watermarking technology to ensure security and is sent to the user's device.

[0169] For example, if a user sends a message from their device saying, "Life has been tough lately," the server uses an emotion engine to recognize the emotion as "sadness" and provides a response based on that, such as, "That must have been difficult. But I'm always rooting for you." This allows the user to feel as if the deceased person is actually encouraging them.

[0170] An example of a prompt might be: "The user is feeling sad about something that happened recently. Understand this emotion and generate a gentle, encouraging response."

[0171] In this way, a system is created that provides emotional support to users through dialogue with the deceased.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] The user prepares information related to the deceased. Specifically, they select digital data such as text, audio, and images using their device. This data must be authorized by the deceased during their lifetime. The prepared data becomes the input data sent from the device to the server.

[0175] Step 2:

[0176] The server analyzes the received data. Specifically, it classifies the data according to its format (text, audio, and image) and extracts key phrases from the text data using natural language processing. It also analyzes characteristic speech patterns from the audio data and uses this extracted information to fine-tune the parameters of the generative artificial intelligence model. This generates output that reproduces the personality and behavioral characteristics of the deceased.

[0177] Step 3:

[0178] The server analyzes user input in real time. It receives messages sent by the user through dialogue and recognizes the emotions using its emotion engine. For example, if the input message is "Life has been difficult lately," the server classifies this emotion as "sadness" and outputs parameters to adjust the response.

[0179] Step 4:

[0180] Based on emotional data obtained by the emotion engine, the server uses a generative AI model to generate an appropriate response. The generated response is adjusted to match the user's emotional state, and may include encouraging words such as, "That must have been tough, but I'm always rooting for you." This response is watermarked to ensure security.

[0181] Step 5:

[0182] The generated response is sent from the server to the user's terminal. The user receives the response on the terminal and can view it on the screen. Through this process, the system is designed to help the user reconstruct their emotional connection with the deceased.

[0183] (Application Example 2)

[0184] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0185] For users seeking emotional healing through dialogue with the deceased, there is a need for a system that faithfully reproduces the personality of the deceased while providing appropriate responses in real time that respond to the user's emotions. Furthermore, ensuring the safety and integrity of the generated responses and providing the dialogue experience to users through readily accessible mobile devices and display devices is a challenge.

[0186] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0187] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for optimizing the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This allows users to safely receive personalized responses from the deceased, thereby achieving emotional healing.

[0188] "Information for recreating the deceased's personality" refers to digital data (such as voice, text, and images) from the deceased's lifetime, which is used to recreate the deceased's personality and communication style.

[0189] A "generative model" is a collection of algorithms designed to analyze data using machine learning and, through learning, reproduce the characteristics of the target.

[0190] "Optimization methods" refer to the process of adjusting the parameters of a generative model based on input information to precisely reproduce the desired characteristics.

[0191] "Means for analyzing emotions and generating appropriate responses" refers to technology that emotionally analyzes user input (text or voice) in real time and generates responses tailored to that state.

[0192] "Technologies for ensuring data integrity" refer to technologies that guarantee that generated responses and data have not been tampered with, and include technologies such as digital watermarking.

[0193] "Through mobile devices and display devices" indicates that the system can be used through devices such as smartphones and smart glasses.

[0194] This invention is a system that recreates the personality of a deceased person and provides emotional healing to the user through dialogue. The system includes the processes of data input, optimization of the generative model, emotion analysis, and response generation. First, the user's terminal sends information about the deceased (voice, text, images, etc.) to the server. This information is used as basic data to recreate the personality of the deceased.

[0195] The server analyzes the transmitted information using a generative model (e.g., OpenAI® GPT-4®) and optimizes the model to reproduce the deceased person's personality and behavioral characteristics. Next, the user transmits what they say to the server in real time through input devices such as the terminal's microphone. The server has emotion recognition software (e.g., Microsoft® Azure® Emotion API) built in to analyze the user's emotional state. Based on this analysis, the generative model generates the optimal response.

[0196] The server applies digital watermarking technology to the generated response to ensure data integrity. This response is then sent to the user's device, allowing the user to experience what it's like to converse with a deceased person. The device could be a smartphone or smart glasses.

[0197] For example, if a user says, "Today I want to celebrate a special day with someone important to me," the sentiment analysis software understands that wish, and the generative model generates a response such as, "Those memories will always be precious to you, enjoy them to the fullest."

[0198] An example of a prompt message is, "When the user feels emotionally lonely, generate kind words of encouragement from the deceased." This allows the system to provide a personalized conversational experience that responds to the user's emotions.

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] The terminal inputs audio, text, and image data related to the deceased and sends it to the server. The input data includes information to reconstruct the deceased's personality and communication style. The server receives this data and stores it in a database.

[0202] Step 2:

[0203] The server optimizes the generative AI model using the stored data. Specifically, it analyzes the data using machine learning algorithms to learn the characteristics of the deceased. This process results in a dialogue model that reflects the personality of the deceased. The input is the data of the deceased received by the server, and the output is the optimized generative model.

[0204] Step 3:

[0205] The user initiates a conversation through a terminal. User input (text or voice) is converted into a digital signal by the terminal and transmitted to the server in real time. The server uses the input signal to analyze the user's emotional state. This includes data processing using emotion recognition software. The input is the user's speech data, and the output is the analyzed emotion data.

[0206] Step 4:

[0207] The server uses the analyzed sentiment data to generate an appropriate response from an optimized generative model. A message tailored to the user's emotions is generated, and data integrity is ensured through watermarking technology. The input is sentiment data, and the output is a secure response message.

[0208] Step 5:

[0209] The generated response message is sent from the server to the terminal. The terminal displays this response to the user. Through this, the user can have an experience as if they were conversing with a deceased person. The input is the message sent from the server, and the output is the response information that the user confirms.

[0210] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0211] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0212] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0213] [Second Embodiment]

[0214] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0215] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0216] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0217] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0218] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0219] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0220] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0221] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0222] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0223] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0224] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0225] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0226] The system in this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. Specific embodiments are described below.

[0227] Data collection and input

[0228] The user inputs digital data about the deceased into the device. This data includes text messages, voice recordings, and images, and forms the basis of the deceased's personality. This data must be information authorized by the deceased during their lifetime. The user selects the data through the device's interface and sends it to the server.

[0229] Fine-tuning of the generative model

[0230] The server analyzes the received digital data and fine-tunes a generative model that reflects the deceased's speech patterns and behavioral patterns. This model is designed to reproduce the deceased's unique communication style.

[0231] Emotion analysis and response generation

[0232] The user initiates a conversation with the deceased AI through their device. The server receives the user's input messages and performs sentiment analysis. Based on the analysis results, the generative model generates the optimal response. This allows the user to continue the conversation as if the deceased were still alive.

[0233] Providing a response

[0234] The generated response is secured by digital watermarking technology. The server sends this response to the user's device, and the user receives the deceased AI's response, provided as a text message or voice message. This allows the user to relive time with the deceased.

[0235] Specific example

[0236] For example, suppose a user sends a message to a deceased AI saying, "I want to talk about recent events." The server analyzes this message to understand the user's current emotional state. The deceased AI might then respond, "What do you mean? I'd love to hear more." Seeing this response, the user can experience what it's like to actually talk to the deceased, which can help them process their emotions.

[0237] Thus, the present invention enables the realistic reproduction of a deceased person's personality using a generative model, providing users with a new way to reconnect with someone important to them.

[0238] The following describes the processing flow.

[0239] Step 1:

[0240] The user prepares digital data related to the deceased, such as text messages, voice recordings, and images, on their device. The device provides an interface for uploading this data, and the user sends the selected data to the server.

[0241] Step 2:

[0242] The server receives digital data sent from the user. The server checks the data format and quality, and performs data analysis to extract the deceased person's personality and past behavioral characteristics.

[0243] Step 3:

[0244] The server begins fine-tuning the generative model based on the received data. In this process, it learns the deceased person's unique communication style and voice characteristics, building a customized AI model.

[0245] Step 4:

[0246] The user initiates a conversation with the deceased AI via their device. The conversation progresses as the user sends input (text or voice) to the server.

[0247] Step 5:

[0248] The server analyzes user input in real time and uses natural language processing to evaluate intent and emotion. Based on this evaluation, the server uses a generative model to generate appropriate responses that reflect the deceased person's personality.

[0249] Step 6:

[0250] The server applies watermarking technology to secure the response it generates. Once the response is ready, the server sends it to the user's terminal.

[0251] Step 7:

[0252] The device displays a response to the user and plays an audio response if available. The user receives this response and can continue the conversation as needed.

[0253] (Example 1)

[0254] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0255] The aim is to recreate the personality of a deceased person using information technology, thereby providing emotional healing to users. However, this process requires protecting privacy based on the deceased's permission, showing consideration for the user's feelings, and improving the safety and quality of the responses provided.

[0256] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0257] In this invention, the server includes a device for inputting information, a device for adjusting personality and behavioral characteristics using a generated knowledge model, a device for analyzing emotions based on user input and generating appropriate responses, and a device for applying technology to keep the generated responses secure. This allows users to find emotional healing through dialogue that recreates the personality of the deceased.

[0258] "Information input device" refers to hardware or software that allows users to provide digital information about the deceased to the system.

[0259] A "generated knowledge model" refers to the data structure of artificial intelligence that is created to reproduce the personality and behavioral characteristics of a deceased person based on the input digital information.

[0260] A "device for adjusting personality and behavioral characteristics" refers to a device that performs a process of fine-tuning the generated knowledge model to achieve a representation that is true to the deceased person.

[0261] A "device that analyzes emotions based on user input and generates appropriate responses" refers to a system component that receives user input, understands their emotional state, and devises a suitable response.

[0262] "Technologies to keep generated responses secure" refers to security technologies that prevent unauthorized access by third parties to data during transmission and storage.

[0263] The system of this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. A specific embodiment of this system is described below.

[0264] First, the terminal receives digital data about the deceased provided by the user. This data includes text messages, voice recordings, and image files, and is used as basic information to recreate the deceased's personality. Through the terminal's interface, the user can input data and send it to the server.

[0265] Next, the server uses the received digital data to fine-tune the generative AI model. Here, natural language processing (NLP) techniques are employed to analyze the deceased person's speech patterns and behavioral patterns, and incorporate them into the generated knowledge model. This generative AI model reproduces the deceased person's unique communication style, enabling dialogue that is faithful to that style.

[0266] When a user actually begins interacting with the AI ​​representing the deceased, they can input a message through their device. The server receives this input and performs sentiment analysis. Based on the analysis results, the model generates the optimal response.

[0267] As a concrete example, let's say a user sends a message to the deceased AI saying, "I want to talk about recent events." The server analyzes the content of this message to understand the user's emotional state and generates a response such as, "What do you mean? I'd love to hear more." This response is securely protected by watermarking technology and sent from the server to the user's device. The user can receive this response from the deceased AI via text message or voice, allowing them to experience what it's like to actually converse with the deceased.

[0268] A concrete example of a prompt message would be something like, "To recreate the deceased's personality, please train a generative model using the following data: text messages, voice recordings, images, etc."

[0269] Thus, this invention is a system that provides users with new opportunities for communication with their deceased loved ones and brings about emotional healing.

[0270] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0271] Step 1:

[0272] The user inputs digital data about the deceased into the terminal. Specifically, the user provides data in the form of text messages, voice recordings, image files, etc., and uploads it through the terminal's designated interface. After input, the terminal checks the data format to ensure it is correct. Next, it converts the data into a format ready for transmission to the server. The input consists of various digital data about the deceased, and the output is the digital data ready for transmission to the server.

[0273] Step 2:

[0274] The server receives digital data transmitted from the terminal. It verifies the format and integrity of the received data and then uses it as input for fine-tuning the generative AI model. Specifically, it analyzes the data using natural language processing (NLP) techniques to extract the deceased person's language patterns and behavioral characteristics. At this point, the input is formatted digital data, and the output is information for adjusting the generative model.

[0275] Step 3:

[0276] The generative AI model is fine-tuned using the deceased's characteristic information obtained from the server. In this process, the existing AI model is input with the deceased's unique linguistic expressions and response patterns, and the model is then fine-tuned based on this input. This reproduces the deceased's characteristic communication style. The input is data for tuning the model, and the output is a personalized generative AI model.

[0277] Step 4:

[0278] The user initiates a conversation with the deceased AI through their device. Specifically, they open the conversation interface on their device and enter a message for the deceased AI. This message is sent to the server as input. The input is the message sent by the user and includes the processing details that the server uses to analyze it.

[0279] Step 5:

[0280] The server analyzes the message received from the user and performs sentiment analysis to understand the intent and emotional state of the input data. Based on the analysis results, it generates the optimal response using a generative AI model. The specific processes here involve the application of sentiment analysis algorithms and the utilization of generative models. The input is the user's message, and the output is the generated response.

[0281] Step 6:

[0282] The generated response is securely transmitted from the server to the terminal using steganography technology. The terminal interprets the received response and presents it to the user in text or voice. Through this, the user can experience as if they are having a conversation with the deceased. The input is the generated response with security, and the output is the dialogue content presented to the end-user.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In modern society, there are various ways to remember the deceased, but the methods of realistically reproducing the personality and memories of the deceased and allowing users to obtain mental healing through natural conversations with the deceased are limited. Also, in conventional interaction methods in virtual spaces, there is a problem that it is difficult for users to enjoy a friendly communication with the deceased AI. As a result, users are missing the opportunity to experience a new form of communication with the deceased.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes means for inputting information for reproducing the personality of the deceased, means for fine-tuning the personality and behavioral characteristics of the deceased by a generation model, and means for analyzing emotions based on the input from the user and generating an appropriate response. Thereby, the user can have a natural conversation with the deceased AI in the virtual space and experience a friendly communication with the deceased.

[0288] The "information for reproducing the personality of the deceased" is digital data such as text messages, voice recordings, and images related to the deceased, and is the basis for reproducing the unique communication style of the deceased.

[0289] A "generative model" is an AI model that analyzes received digital data to reflect the personality and behavioral characteristics of the deceased, enabling realistic interaction with the user.

[0290] "Fine-tuning" is the process of adjusting a generative model based on the deceased person's digital data to reproduce their speech patterns and behavioral patterns.

[0291] "Means for analyzing emotions and generating appropriate responses" refers to technology that analyzes the user's emotional state based on input messages from the user, generates the optimal response, and provides it to the user.

[0292] "A means of providing a virtual space to facilitate interaction between users and the deceased AI" refers to a system that allows users to interact with the deceased AI in a virtual environment via a smart device, enabling friendly and approachable communication.

[0293] "Information based on permission given during the deceased's lifetime" refers to information for which the deceased consented to the use of digital data during their lifetime, and which will be used in a manner that respects privacy and consent.

[0294] "Information concealment technology" is a technique applied to ensure the security of generated responses, with the aim of protecting the response content from tampering and unauthorized access.

[0295] The system for realizing this invention includes a terminal for inputting the deceased's digital data, a server for processing the data, and an environment for enabling interaction with the user. First, the user uses the terminal to input information about the deceased, such as text messages, voice recordings, and images. This information is sent to the server as basic data for recreating the deceased's personality.

[0296] The server uses the received information to fine-tune the generated AI model. This process is necessary to reflect the deceased person's unique speech patterns and behavioral patterns in the model. The server also uses Google Cloud's Dialogflow or similar natural language processing technologies to analyze user messages and perform sentiment analysis to generate appropriate responses.

[0297] The generated responses are delivered to the user through a virtual space. In this process, smart devices play a role in facilitating the interaction between the user and the deceased AI. Users can interact with the deceased AI in a virtual environment via their smartphones or smart glasses, enjoying a new form of communication.

[0298] For example, if a user types "Tell me about your recent trip" into the device, the server analyzes their emotions and interests and generates a natural response from the AI, such as "What moments from that trip were particularly memorable?"

[0299] An example of a prompt in a generative AI model is an instruction such as, "When a user asks about the features of a product, how would the AI ​​explain it?" This helps ensure that the generated response is user-friendly and meaningful.

[0300] Through this invention, users can initiate friendly conversations with deceased AI figures in a virtual space and find emotional healing.

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] The user inputs digital data about the deceased into the terminal. The input data consists of text messages, voice recordings, images, etc., and the terminal sends this information to the server. The input here is the basic data for recreating the personality of the deceased, and the output is the transmission of data to the server.

[0304] Step 2:

[0305] The server analyzes the received digital data and performs fine-tuning of the generated AI model. As a specific operation, the server learns the speech patterns and behavioral patterns of the deceased based on the digital data and optimizes the model. The input is the received digital data, and the output is the fine-tuned generation model.

[0306] Step 3:

[0307] The user starts a conversation with the deceased AI via the terminal. The terminal sends the input message from the user to the server. The input is the text message from the user, and this is output in the form passed to the server.

[0308] Step 4:

[0309] The server receives the message from the user and performs sentiment analysis. As a specific operation, it discriminates the user's emotional state using an emotion recognition algorithm. The input is the user's text message, and the output is the sentiment analysis result.

[0310] Step 5:

[0311] Based on the sentiment analysis result, the server generates an appropriate response using the generation model. To reproduce the communication style of the deceased, it utilizes prompt sentences. The input is the sentiment analysis result and the text prompt, and the output is the generated response.

[0312] Step 6:

[0313] The server applies information hiding technology to the generated response and sends it to the terminal. Specifically, the response message is processed so as to be protected from unauthorized access and tampering. The input is the generated response, and the output is a secure response message.

[0314] Step 7:

[0315] The terminal provides the user with responses generated in a virtual space. Specifically, the interaction with the deceased AI is visually and audibly reproduced through the device the user uses. The input is a safe response message, and the output is visual and audible feedback to the user.

[0316] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0317] This invention is a system that combines an emotional engine that recreates the personality of a deceased person with an emotional engine that understands the user's emotions. Through this system, the user can process their emotions and find emotional healing through dialogue with the deceased. Specific embodiments are described below.

[0318] Data collection and input

[0319] The user prepares digital data (text, audio, images, etc.) about the deceased on their device. This data forms the basis for recreating the deceased's personality. The user selects this data through their device and sends it to the server. This step requires the use of only data for which permission was obtained from the deceased during their lifetime.

[0320] Fine-tuning of the generative model

[0321] The server analyzes data sent by the user and fine-tunes a generative model to recreate the deceased person's personality and behavioral characteristics. This model has the ability to learn the deceased person's distinctive communication style and generate personalized responses.

[0322] Analysis using an emotion engine

[0323] The server has an emotion engine built in, which analyzes the input messages in real time once the user starts a conversation. The emotion engine recognizes the user's emotional state from their text and voice, and the generative model adjusts the response accordingly.

[0324] Response generation and provision

[0325] The server generates an appropriate response that reflects the deceased person's characteristics using a generative model. This response is tailored to the user's current emotions by an emotion engine, and its security is ensured by watermarking technology. The generated response is sent to the user's terminal, and the user confirms the response through the terminal.

[0326] Specific example

[0327] For example, if a user sends a text message saying, "Life has been tough lately," the server uses its emotion engine to recognize the user's emotion as "sadness." Based on this, the generative model generates a response in an encouraging tone, providing a message such as, "That must have been difficult. But I'm always rooting for you." Through this response, the user can feel as if they are actually being encouraged by the deceased, and it provides emotional support.

[0328] Thus, the present invention is a system that recreates communication with a deceased person in a new form and provides emotional support to the user.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] The user gathers text, audio, and image data related to the deceased on their device and prepares to input it into the system. The device has an interface for sending this data to a server, and the user uploads the data they have selected.

[0332] Step 2:

[0333] The server receives data sent from the user. The server verifies the format and integrity of the data and performs data analysis to extract the information necessary to recreate the deceased person's personality.

[0334] Step 3:

[0335] The server fine-tunes the generative model based on the extracted information. This model is adjusted to reproduce the deceased person's unique speech patterns and behavioral characteristics. The model is optimized according to the user's individual needs.

[0336] Step 4:

[0337] The user initiates interaction via a terminal and sends a message to the system. The server receives this message and prepares to process it.

[0338] Step 5:

[0339] The server uses an emotion engine to analyze user messages and recognize their emotional state. The emotion engine uses natural language processing and emotion classification techniques to evaluate the user's emotions in real time.

[0340] Step 6:

[0341] Based on the results of the emotion engine, the server generates a response using a generative model. This response corresponds to the user's current emotional state and is tailored to reflect the deceased person's communication style.

[0342] Step 7:

[0343] The server applies watermarking technology to the generated response to ensure its security. The response is then sent to the user's terminal, allowing the conversation to continue.

[0344] Step 8:

[0345] The device displays a response to the user and, if necessary, plays it back as audio. The user receives this response and can continue the conversation.

[0346] (Example 2)

[0347] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0348] There is a need to maintain an emotional connection through records of the deceased, but conventional technologies are insufficient in recreating the personality of the deceased, recognizing the user's emotions, and providing appropriate responses. To solve this problem, it is necessary to more accurately recreate the characteristics of the deceased and generate appropriate responses that correspond to the user's emotions.

[0349] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0350] In this invention, the server includes means for inputting information related to the deceased, means for adjusting the characteristics of the deceased using a generative artificial intelligence model, and means for analyzing user input, recognizing emotions, and adjusting responses. This enables natural and emotional dialogue with the deceased and provides emotional support to the user.

[0351] "Information related to the deceased" refers to digital data such as text, audio, and images necessary to recreate the deceased's personality and behavioral characteristics.

[0352] A "generative artificial intelligence model" is a machine learning model that has the ability to learn the characteristics of a person based on input data and generate personalized responses.

[0353] "User input" refers to text and voice data that users provide to the server through interaction.

[0354] An "emotion engine" is a technology that analyzes user input in real time and recognizes the emotions behind it.

[0355] "Digital watermarking technology" is a technique used to ensure the security of digital data, and it involves embedding an invisible mark into the data.

[0356] "Adjusting the response" refers to optimizing the tone and content of the generated response based on the perceived emotions.

[0357] The embodiments for carrying out the present invention are described below.

[0358] In the system for implementing the invention, the user, terminal, and server play key roles. First, the user inputs information into the terminal to recreate the deceased person's personality. This information includes text, audio, and images related to the deceased, and only data permitted during their lifetime must be used. The terminal has the function of transmitting this data to the server.

[0359] The server analyzes the received data and uses a generative artificial intelligence model to fine-tune the model in order to recreate the deceased person's personality and behavioral characteristics. The generative artificial intelligence model used here is based on a large-scale machine learning framework and makes extensive use of natural language processing (NLP) techniques.

[0360] Next, the server is equipped with an emotion engine that analyzes the user's input through dialogue in real time. The emotion engine recognizes emotions from the user's input and can adjust the response output by the generating AI model to correspond to those emotions. The response is protected by watermarking technology to ensure security and is sent to the user's device.

[0361] For example, if a user sends a message from their device saying, "Life has been tough lately," the server uses an emotion engine to recognize the emotion as "sadness" and provides a response based on that, such as, "That must have been difficult. But I'm always rooting for you." This allows the user to feel as if the deceased person is actually encouraging them.

[0362] An example of a prompt might be: "The user is feeling sad about something that happened recently. Understand this emotion and generate a gentle, encouraging response."

[0363] In this way, a system is created that provides emotional support to users through dialogue with the deceased.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The user prepares information related to the deceased. Specifically, they select digital data such as text, audio, and images using their device. This data must be authorized by the deceased during their lifetime. The prepared data becomes the input data sent from the device to the server.

[0367] Step 2:

[0368] The server analyzes the received data. Specifically, it classifies the data according to its format (text, audio, and image) and extracts key phrases from the text data using natural language processing. It also analyzes characteristic speech patterns from the audio data and uses this extracted information to fine-tune the parameters of the generative artificial intelligence model. This generates output that reproduces the personality and behavioral characteristics of the deceased.

[0369] Step 3:

[0370] The server analyzes user input in real time. It receives messages sent by the user through dialogue and recognizes the emotions using its emotion engine. For example, if the input message is "Life has been difficult lately," the server classifies this emotion as "sadness" and outputs parameters to adjust the response.

[0371] Step 4:

[0372] Based on emotional data obtained by the emotion engine, the server uses a generative AI model to generate an appropriate response. The generated response is adjusted to match the user's emotional state, and may include encouraging words such as, "That must have been tough, but I'm always rooting for you." This response is watermarked to ensure security.

[0373] Step 5:

[0374] The generated response is sent from the server to the user's terminal. The user receives the response on the terminal and can view it on the screen. Through this process, the system is designed to help the user reconstruct their emotional connection with the deceased.

[0375] (Application Example 2)

[0376] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0377] For users seeking emotional healing through dialogue with the deceased, there is a need for a system that faithfully reproduces the personality of the deceased while providing appropriate responses in real time that respond to the user's emotions. Furthermore, ensuring the safety and integrity of the generated responses and providing the dialogue experience to users through readily accessible mobile devices and display devices is a challenge.

[0378] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0379] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for optimizing the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This allows users to safely receive personalized responses from the deceased, thereby achieving emotional healing.

[0380] "Information for recreating the deceased's personality" refers to digital data (such as voice, text, and images) from the deceased's lifetime, which is used to recreate the deceased's personality and communication style.

[0381] A "generative model" is a collection of algorithms designed to analyze data using machine learning and, through learning, reproduce the characteristics of the target.

[0382] "Optimization methods" refer to the process of adjusting the parameters of a generative model based on input information to precisely reproduce the desired characteristics.

[0383] "Means for analyzing emotions and generating appropriate responses" refers to technology that emotionally analyzes user input (text or voice) in real time and generates responses tailored to that state.

[0384] "Technologies for ensuring data integrity" refer to technologies that guarantee that generated responses and data have not been tampered with, and include technologies such as digital watermarking.

[0385] "Through mobile devices and display devices" indicates that the system can be used through devices such as smartphones and smart glasses.

[0386] This invention is a system that recreates the personality of a deceased person and provides emotional healing to the user through dialogue. The system includes the processes of data input, optimization of the generative model, emotion analysis, and response generation. First, the user's terminal sends information about the deceased (voice, text, images, etc.) to the server. This information is used as basic data to recreate the personality of the deceased.

[0387] The server analyzes the transmitted information using a generative model (e.g., OpenAI GPT-4) and optimizes the model to reproduce the deceased person's personality and behavioral characteristics. Next, the user's speech is transmitted to the server in real time through the input device, such as the terminal's microphone. The server has emotion recognition software (e.g., Microsoft Azure Emotion API) built in to analyze the user's emotional state. Based on this analysis, the generative model generates the optimal response.

[0388] The server applies digital watermarking technology to the generated response to ensure data integrity. This response is then sent to the user's device, allowing the user to experience what it's like to converse with a deceased person. The device could be a smartphone or smart glasses.

[0389] For example, if a user says, "Today I want to celebrate a special day with someone important to me," the sentiment analysis software understands that wish, and the generative model generates a response such as, "Those memories will always be precious to you, enjoy them to the fullest."

[0390] An example of a prompt message is, "When the user feels emotionally lonely, generate kind words of encouragement from the deceased." This allows the system to provide a personalized conversational experience that responds to the user's emotions.

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] The terminal inputs audio, text, and image data related to the deceased and sends it to the server. The input data includes information to reconstruct the deceased's personality and communication style. The server receives this data and stores it in a database.

[0394] Step 2:

[0395] The server optimizes the generative AI model using the stored data. Specifically, it analyzes the data using machine learning algorithms to learn the characteristics of the deceased. This process results in a dialogue model that reflects the personality of the deceased. The input is the data of the deceased received by the server, and the output is the optimized generative model.

[0396] Step 3:

[0397] The user initiates a conversation through a terminal. User input (text or voice) is converted into a digital signal by the terminal and transmitted to the server in real time. The server uses the input signal to analyze the user's emotional state. This includes data processing using emotion recognition software. The input is the user's speech data, and the output is the analyzed emotion data.

[0398] Step 4:

[0399] The server uses the analyzed sentiment data to generate an appropriate response from an optimized generative model. A message tailored to the user's emotions is generated, and data integrity is ensured through watermarking technology. The input is sentiment data, and the output is a secure response message.

[0400] Step 5:

[0401] The generated response message is sent from the server to the terminal. The terminal displays this response to the user. Through this, the user can have an experience as if they were conversing with a deceased person. The input is the message sent from the server, and the output is the response information that the user confirms.

[0402] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0403] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0404] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0408] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0409] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0410] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0411] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0412] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0413] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0414] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0415] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0416] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0417] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0418] The system in this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. Specific embodiments are described below.

[0419] Data collection and input

[0420] The user inputs digital data about the deceased into the device. This data includes text messages, voice recordings, and images, and forms the basis of the deceased's personality. This data must be information authorized by the deceased during their lifetime. The user selects the data through the device's interface and sends it to the server.

[0421] Fine-tuning of the generative model

[0422] The server analyzes the received digital data and fine-tunes a generative model that reflects the deceased's speech patterns and behavioral patterns. This model is designed to reproduce the deceased's unique communication style.

[0423] Emotion analysis and response generation

[0424] The user initiates a conversation with the deceased AI through their device. The server receives the user's input messages and performs sentiment analysis. Based on the analysis results, the generative model generates the optimal response. This allows the user to continue the conversation as if the deceased were still alive.

[0425] Providing a response

[0426] The generated response is secured by watermarking technology. The server sends this response to the user's device, and the user receives the deceased AI's response, provided as a text message or voice message. This allows the user to relive time with the deceased.

[0427] Specific example

[0428] For example, suppose a user sends a message to a deceased AI saying, "I want to talk about recent events." The server analyzes this message to understand the user's current emotional state. The deceased AI might then respond, "What do you mean? I'd love to hear more." Seeing this response, the user can experience what it's like to actually talk to the deceased, which can help them process their emotions.

[0429] Thus, the present invention enables the realistic reproduction of a deceased person's personality using a generative model, providing users with a new way to reconnect with someone important to them.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] The user prepares digital data related to the deceased, such as text messages, voice recordings, and images, on their device. The device provides an interface for uploading this data, and the user sends the selected data to the server.

[0433] Step 2:

[0434] The server receives digital data sent from the user. The server checks the data format and quality, and performs data analysis to extract the deceased person's personality and past behavioral characteristics.

[0435] Step 3:

[0436] The server begins fine-tuning the generative model based on the received data. In this process, it learns the deceased person's unique communication style and voice characteristics, building a customized AI model.

[0437] Step 4:

[0438] The user initiates a conversation with the deceased AI via their device. The conversation progresses as the user sends input (text or voice) to the server.

[0439] Step 5:

[0440] The server analyzes user input in real time and uses natural language processing to evaluate intent and emotion. Based on this evaluation, the server uses a generative model to generate appropriate responses that reflect the deceased person's personality.

[0441] Step 6:

[0442] The server applies watermarking technology to secure the response it generates. Once the response is ready, the server sends it to the user's terminal.

[0443] Step 7:

[0444] The device displays a response to the user and plays an audio response if available. The user receives this response and can continue the conversation as needed.

[0445] (Example 1)

[0446] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0447] The aim is to recreate the personality of a deceased person using information technology, thereby providing emotional healing to users. However, this process requires protecting privacy based on the deceased's permission, showing consideration for the user's feelings, and improving the safety and quality of the responses provided.

[0448] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0449] In this invention, the server includes a device for inputting information, a device for adjusting personality and behavioral characteristics using a generated knowledge model, a device for analyzing emotions based on user input and generating appropriate responses, and a device for applying technology to keep the generated responses secure. This allows users to find emotional healing through dialogue that recreates the personality of the deceased.

[0450] "Information input device" refers to hardware or software that allows users to provide digital information about the deceased to the system.

[0451] A "generated knowledge model" refers to the data structure of artificial intelligence that is created to reproduce the personality and behavioral characteristics of a deceased person based on the input digital information.

[0452] A "device for adjusting personality and behavioral characteristics" refers to a device that performs a process of fine-tuning the generated knowledge model to achieve a representation that is true to the deceased person.

[0453] A "device that analyzes emotions based on user input and generates appropriate responses" refers to a system component that receives user input, understands their emotional state, and devises a suitable response.

[0454] "Technologies to keep generated responses secure" refers to security technologies that prevent unauthorized access by third parties to data during transmission and storage.

[0455] The system of this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. A specific embodiment of this system is described below.

[0456] First, the terminal receives digital data about the deceased provided by the user. This data includes text messages, voice recordings, and image files, and is used as basic information to recreate the deceased's personality. Through the terminal's interface, the user can input data and send it to the server.

[0457] Next, the server uses the received digital data to fine-tune the generative AI model. Here, natural language processing (NLP) techniques are employed to analyze the deceased person's speech patterns and behavioral patterns, and incorporate them into the generated knowledge model. This generative AI model reproduces the deceased person's unique communication style, enabling dialogue that is faithful to that style.

[0458] When a user actually begins interacting with the AI ​​representing the deceased, they can input a message through their device. The server receives this input and performs sentiment analysis. Based on the analysis results, the model generates the optimal response.

[0459] As a concrete example, let's say a user sends a message to the deceased AI saying, "I want to talk about recent events." The server analyzes the content of this message to understand the user's emotional state and generates a response such as, "What do you mean? I'd love to hear more." This response is securely protected by watermarking technology and sent from the server to the user's device. The user can receive this response from the deceased AI via text message or voice, allowing them to experience what it's like to actually converse with the deceased.

[0460] A concrete example of a prompt message would be something like, "To recreate the deceased's personality, please train a generative model using the following data: text messages, voice recordings, images, etc."

[0461] Thus, this invention is a system that provides users with new opportunities for communication with their deceased loved ones and brings about emotional healing.

[0462] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0463] Step 1:

[0464] The user inputs digital data about the deceased into the terminal. Specifically, the user provides data in the form of text messages, voice recordings, image files, etc., and uploads it through the terminal's designated interface. After input, the terminal checks the data format to ensure it is correct. Next, it converts the data into a format ready for transmission to the server. The input consists of various digital data about the deceased, and the output is the digital data ready for transmission to the server.

[0465] Step 2:

[0466] The server receives digital data transmitted from the terminal. It verifies the format and integrity of the received data and then uses it as input for fine-tuning the generative AI model. Specifically, it analyzes the data using natural language processing (NLP) techniques to extract the deceased person's language patterns and behavioral characteristics. At this point, the input is formatted digital data, and the output is information for adjusting the generative model.

[0467] Step 3:

[0468] The generative AI model is fine-tuned using the deceased's characteristic information obtained from the server. In this process, the existing AI model is input with the deceased's unique linguistic expressions and response patterns, and the model is then fine-tuned based on this input. This reproduces the deceased's characteristic communication style. The input is data for tuning the model, and the output is a personalized generative AI model.

[0469] Step 4:

[0470] The user initiates a conversation with the deceased AI through their device. Specifically, they open the conversation interface on their device and enter a message for the deceased AI. This message is sent to the server as input. The input is the message sent by the user and includes the processing details that the server uses to analyze it.

[0471] Step 5:

[0472] The server analyzes the message received from the user and performs sentiment analysis to understand the intent and emotional state of the input data. Based on the analysis results, it generates the optimal response using a generative AI model. The specific processes here involve the application of sentiment analysis algorithms and the utilization of generative models. The input is the user's message, and the output is the generated response.

[0473] Step 6:

[0474] The generated response is securely transmitted from the server to the terminal using watermarking technology. The terminal interprets the received response and presents it to the user in text or audio. This allows the user to experience a conversation as if they were talking to a deceased person. The input is a pre-generated, secure response, and the output is the dialogue content presented to the end user.

[0475] (Application Example 1)

[0476] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0477] In modern society, there are many ways to remember the deceased, but methods that realistically recreate the personality and memories of the deceased, allowing users to find solace through natural dialogue with them, are limited. Furthermore, conventional interaction methods in virtual spaces have the problem of making it difficult for users to enjoy friendly communication with AI representations of the deceased. As a result, users are missing out on opportunities to experience new forms of interaction with their loved ones.

[0478] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0479] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for fine-tuning the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This enables the user to have a natural conversation with the deceased AI in a virtual space and experience a friendly interaction with the deceased.

[0480] "Information for recreating the deceased's personality" refers to digital data such as text messages, audio recordings, and images related to the deceased, which form the basis for recreating the deceased's unique communication style.

[0481] A "generative model" is an AI model that analyzes received digital data to reflect the personality and behavioral characteristics of the deceased, enabling realistic interaction with the user.

[0482] "Fine-tuning" is the process of adjusting a generative model based on the deceased person's digital data to reproduce their speech patterns and behavioral patterns.

[0483] "Means for analyzing emotions and generating appropriate responses" refers to technology that analyzes the user's emotional state based on input messages from the user, generates the optimal response, and provides it to the user.

[0484] "A means of providing a virtual space to facilitate interaction between users and the deceased AI" refers to a system that allows users to interact with the deceased AI in a virtual environment via a smart device, enabling friendly and approachable communication.

[0485] "Information based on permission given during the deceased's lifetime" refers to information for which the deceased consented to the use of digital data during their lifetime, and which will be used in a manner that respects privacy and consent.

[0486] "Information concealment technology" is a technique applied to ensure the security of generated responses, with the aim of protecting the response content from tampering and unauthorized access.

[0487] The system for realizing this invention includes a terminal for inputting the deceased's digital data, a server for processing the data, and an environment for enabling interaction with the user. First, the user uses the terminal to input information about the deceased, such as text messages, voice recordings, and images. This information is sent to the server as basic data for recreating the deceased's personality.

[0488] The server uses the received information to fine-tune the generated AI model. This process is necessary to reflect the deceased person's unique speech patterns and behavioral patterns in the model. The server also uses Google Cloud's Dialogflow or similar natural language processing technologies to analyze user messages and perform sentiment analysis to generate appropriate responses.

[0489] The generated responses are delivered to the user through a virtual space. In this process, smart devices play a role in facilitating the interaction between the user and the deceased AI. Users can interact with the deceased AI in a virtual environment via their smartphones or smart glasses, enjoying a new form of communication.

[0490] For example, if a user types "Tell me about your recent trip" into the device, the server analyzes their emotions and interests and generates a natural response from the AI, such as "What moments from that trip were particularly memorable?"

[0491] An example of a prompt in a generative AI model is an instruction such as, "When a user asks about the features of a product, how would the AI ​​explain it?" This helps ensure that the generated response is user-friendly and meaningful.

[0492] Through this invention, users can initiate friendly conversations with deceased AI figures in a virtual space and find emotional healing.

[0493] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0494] Step 1:

[0495] The user inputs digital data about the deceased into the terminal. The input data consists of text messages, voice recordings, images, etc., and the terminal sends this information to the server. The input here is the basic data for recreating the personality of the deceased, and the output is the transmission of data to the server.

[0496] Step 2:

[0497] The server analyzes the received digital data and fine-tunes the generative AI model. Specifically, the server learns the deceased person's speech patterns and behavioral patterns based on the digital data and optimizes the model. The input is the received digital data, and the output is the fine-tuned generative model.

[0498] Step 3:

[0499] The user initiates a conversation with the deceased AI via a terminal. The terminal sends input messages from the user to the server. The input is a text message from the user, which is then output to the server.

[0500] Step 4:

[0501] The server receives messages from users and performs sentiment analysis. Specifically, it uses sentiment recognition algorithms to determine the user's emotional state. The input is the user's text message, and the output is the sentiment analysis result.

[0502] Step 5:

[0503] The server generates an appropriate response using a generative model based on the sentiment analysis results. The model utilizes prompt text to recreate the deceased person's communication style. Inputs are the sentiment analysis results and text prompts, while output is the generated response.

[0504] Step 6:

[0505] The server applies information concealment techniques to the generated response and sends it to the terminal. Specifically, the response message is processed to protect it from unauthorized access and tampering. The input is the generated response, and the output is the secure response message.

[0506] Step 7:

[0507] The terminal provides the user with responses generated in a virtual space. Specifically, the interaction with the deceased AI is visually and audibly reproduced through the device the user uses. The input is a safe response message, and the output is visual and audible feedback to the user.

[0508] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0509] This invention is a system that combines an emotional engine that recreates the personality of a deceased person with an emotional engine that understands the user's emotions. Through this system, the user can process their emotions and find emotional healing through dialogue with the deceased. Specific embodiments are described below.

[0510] Data collection and input

[0511] The user prepares digital data (text, audio, images, etc.) about the deceased on their device. This data forms the basis for recreating the deceased's personality. The user selects this data through their device and sends it to the server. This step requires the use of only data for which permission was obtained from the deceased during their lifetime.

[0512] Fine-tuning of the generative model

[0513] The server analyzes data sent by the user and fine-tunes a generative model to recreate the deceased person's personality and behavioral characteristics. This model has the ability to learn the deceased person's distinctive communication style and generate personalized responses.

[0514] Analysis using an emotion engine

[0515] The server has an emotion engine built in, which analyzes the input messages in real time once the user starts a conversation. The emotion engine recognizes the user's emotional state from their text and voice, and the generative model adjusts the response accordingly.

[0516] Response generation and provision

[0517] The server generates an appropriate response that reflects the deceased person's characteristics using a generative model. This response is tailored to the user's current emotions by an emotion engine, and its security is ensured by watermarking technology. The generated response is sent to the user's terminal, and the user confirms the response through the terminal.

[0518] Specific example

[0519] For example, if a user sends a text message saying, "Life has been tough lately," the server uses its emotion engine to recognize the user's emotion as "sadness." Based on this, the generative model generates a response in an encouraging tone, providing a message such as, "That must have been difficult. But I'm always rooting for you." Through this response, the user can feel as if they are actually being encouraged by the deceased, and it provides emotional support.

[0520] Thus, the present invention is a system that recreates communication with a deceased person in a new form and provides emotional support to the user.

[0521] The following describes the processing flow.

[0522] Step 1:

[0523] The user gathers text, audio, and image data related to the deceased on their device and prepares to input it into the system. The device has an interface for sending this data to a server, and the user uploads the data they have selected.

[0524] Step 2:

[0525] The server receives data sent from the user. The server verifies the format and integrity of the data and performs data analysis to extract the information necessary to recreate the deceased person's personality.

[0526] Step 3:

[0527] The server fine-tunes the generative model based on the extracted information. This model is adjusted to reproduce the deceased person's unique speech patterns and behavioral characteristics. The model is optimized according to the user's individual needs.

[0528] Step 4:

[0529] The user initiates interaction via a terminal and sends a message to the system. The server receives this message and prepares to process it.

[0530] Step 5:

[0531] The server uses an emotion engine to analyze user messages and recognize their emotional state. The emotion engine uses natural language processing and emotion classification techniques to evaluate the user's emotions in real time.

[0532] Step 6:

[0533] Based on the results of the emotion engine, the server generates a response using a generative model. This response corresponds to the user's current emotional state and is tailored to reflect the deceased person's communication style.

[0534] Step 7:

[0535] The server applies watermarking technology to the generated response to ensure its security. The response is then sent to the user's terminal, allowing the conversation to continue.

[0536] Step 8:

[0537] The device displays a response to the user and, if necessary, plays it back as audio. The user receives this response and can continue the conversation.

[0538] (Example 2)

[0539] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0540] There is a need to maintain an emotional connection through records of the deceased, but conventional technologies are insufficient in recreating the personality of the deceased, recognizing the user's emotions, and providing appropriate responses. To solve this problem, it is necessary to more accurately recreate the characteristics of the deceased and generate appropriate responses that correspond to the user's emotions.

[0541] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0542] In this invention, the server includes means for inputting information related to the deceased, means for adjusting the characteristics of the deceased using a generative artificial intelligence model, and means for analyzing user input, recognizing emotions, and adjusting responses. This enables natural and emotional dialogue with the deceased and provides emotional support to the user.

[0543] "Information related to the deceased" refers to digital data such as text, audio, and images necessary to recreate the deceased's personality and behavioral characteristics.

[0544] A "generative artificial intelligence model" is a machine learning model that has the ability to learn the characteristics of a person based on input data and generate personalized responses.

[0545] "User input" refers to text and voice data that users provide to the server through interaction.

[0546] An "emotion engine" is a technology that analyzes user input in real time and recognizes the emotions behind it.

[0547] "Digital watermarking technology" is a technique used to ensure the security of digital data, and it involves embedding an invisible mark into the data.

[0548] "Adjusting the response" refers to optimizing the tone and content of the generated response based on the perceived emotions.

[0549] The embodiments for carrying out the present invention are described below.

[0550] In the system for implementing the invention, the user, terminal, and server play key roles. First, the user inputs information into the terminal to recreate the deceased person's personality. This information includes text, audio, and images related to the deceased, and only data permitted during their lifetime must be used. The terminal has the function of transmitting this data to the server.

[0551] The server analyzes the received data and uses a generative artificial intelligence model to fine-tune the model in order to recreate the deceased person's personality and behavioral characteristics. The generative artificial intelligence model used here is based on a large-scale machine learning framework and makes extensive use of natural language processing (NLP) techniques.

[0552] Next, the server is equipped with an emotion engine that analyzes the user's input through dialogue in real time. The emotion engine recognizes emotions from the user's input and can adjust the response output by the generating AI model to correspond to those emotions. The response is protected by watermarking technology to ensure security and is sent to the user's device.

[0553] For example, if a user sends a message from their device saying, "Life has been tough lately," the server uses an emotion engine to recognize the emotion as "sadness" and provides a response based on that, such as, "That must have been difficult. But I'm always rooting for you." This allows the user to feel as if the deceased person is actually encouraging them.

[0554] An example of a prompt might be: "The user is feeling sad about something that happened recently. Understand this emotion and generate a gentle, encouraging response."

[0555] In this way, a system is created that provides emotional support to users through dialogue with the deceased.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] The user prepares information related to the deceased. Specifically, they select digital data such as text, audio, and images using their device. This data must be authorized by the deceased during their lifetime. The prepared data becomes the input data sent from the device to the server.

[0559] Step 2:

[0560] The server analyzes the received data. Specifically, it classifies the data according to its format (text, audio, and image) and extracts key phrases from the text data using natural language processing. It also analyzes characteristic speech patterns from the audio data and uses this extracted information to fine-tune the parameters of the generative artificial intelligence model. This generates output that reproduces the personality and behavioral characteristics of the deceased.

[0561] Step 3:

[0562] The server analyzes user input in real time. It receives messages sent by the user through dialogue and recognizes the emotions using its emotion engine. For example, if the input message is "Life has been difficult lately," the server classifies this emotion as "sadness" and outputs parameters to adjust the response.

[0563] Step 4:

[0564] Based on emotional data obtained by the emotion engine, the server uses a generative AI model to generate an appropriate response. The generated response is adjusted to match the user's emotional state, and may include encouraging words such as, "That must have been tough, but I'm always rooting for you." This response is watermarked to ensure security.

[0565] Step 5:

[0566] The generated response is sent from the server to the user's terminal. The user receives the response on the terminal and can view it on the screen. Through this process, the system is designed to help the user reconstruct their emotional connection with the deceased.

[0567] (Application Example 2)

[0568] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0569] For users seeking emotional healing through dialogue with the deceased, there is a need for a system that faithfully reproduces the personality of the deceased while providing appropriate responses in real time that respond to the user's emotions. Furthermore, ensuring the safety and integrity of the generated responses and providing the dialogue experience to users through readily accessible mobile devices and display devices is a challenge.

[0570] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0571] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for optimizing the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This allows users to safely receive personalized responses from the deceased, thereby achieving emotional healing.

[0572] "Information for recreating the deceased's personality" refers to digital data (such as voice, text, and images) from the deceased's lifetime, which is used to recreate the deceased's personality and communication style.

[0573] A "generative model" is a collection of algorithms designed to analyze data using machine learning and, through learning, reproduce the characteristics of the target.

[0574] "Optimization methods" refer to the process of adjusting the parameters of a generative model based on input information to precisely reproduce the desired characteristics.

[0575] "Means for analyzing emotions and generating appropriate responses" refers to technology that emotionally analyzes user input (text or voice) in real time and generates responses tailored to that state.

[0576] "Technologies for ensuring data integrity" refer to technologies that guarantee that generated responses and data have not been tampered with, and include technologies such as digital watermarking.

[0577] "Through mobile devices and display devices" indicates that the system can be used through devices such as smartphones and smart glasses.

[0578] This invention is a system that recreates the personality of a deceased person and provides emotional healing to the user through dialogue. The system includes the processes of data input, optimization of the generative model, emotion analysis, and response generation. First, the user's terminal sends information about the deceased (voice, text, images, etc.) to the server. This information is used as basic data to recreate the personality of the deceased.

[0579] The server analyzes the transmitted information using a generative model (e.g., OpenAI GPT-4) and optimizes the model to reproduce the deceased person's personality and behavioral characteristics. Next, the user's speech is transmitted to the server in real time through the input device, such as the terminal's microphone. The server has emotion recognition software (e.g., Microsoft Azure Emotion API) built in to analyze the user's emotional state. Based on this analysis, the generative model generates the optimal response.

[0580] The server applies digital watermarking technology to the generated response to ensure data integrity. This response is then sent to the user's device, allowing the user to experience what it's like to converse with a deceased person. The device could be a smartphone or smart glasses.

[0581] For example, if a user says, "Today I want to celebrate a special day with someone important to me," the sentiment analysis software understands that wish, and the generative model generates a response such as, "Those memories will always be precious to you, enjoy them to the fullest."

[0582] An example of a prompt message is, "When the user feels emotionally lonely, generate kind words of encouragement from the deceased." This allows the system to provide a personalized conversational experience that responds to the user's emotions.

[0583] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0584] Step 1:

[0585] The terminal inputs audio, text, and image data related to the deceased and sends it to the server. The input data includes information to reconstruct the deceased's personality and communication style. The server receives this data and stores it in a database.

[0586] Step 2:

[0587] The server optimizes the generative AI model using the stored data. Specifically, it analyzes the data using machine learning algorithms to learn the characteristics of the deceased. This process results in a dialogue model that reflects the personality of the deceased. The input is the data of the deceased received by the server, and the output is the optimized generative model.

[0588] Step 3:

[0589] The user initiates a conversation through a terminal. User input (text or voice) is converted into a digital signal by the terminal and transmitted to the server in real time. The server uses the input signal to analyze the user's emotional state. This includes data processing using emotion recognition software. The input is the user's speech data, and the output is the analyzed emotion data.

[0590] Step 4:

[0591] The server uses the analyzed sentiment data to generate an appropriate response from an optimized generative model. A message tailored to the user's emotions is generated, and data integrity is ensured through watermarking technology. The input is sentiment data, and the output is a secure response message.

[0592] Step 5:

[0593] The generated response message is sent from the server to the terminal. The terminal displays this response to the user. Through this, the user can have an experience as if they were conversing with a deceased person. The input is the message sent from the server, and the output is the response information that the user confirms.

[0594] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0595] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0596] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0597] [Fourth Embodiment]

[0598] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0599] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0600] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0601] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0602] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0603] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0604] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0605] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0606] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0607] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0608] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0609] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0610] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0611] The system in this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. Specific embodiments are described below.

[0612] Data collection and input

[0613] The user inputs digital data about the deceased into the device. This data includes text messages, voice recordings, and images, and forms the basis of the deceased's personality. This data must be information authorized by the deceased during their lifetime. The user selects the data through the device's interface and sends it to the server.

[0614] Fine-tuning of the generative model

[0615] The server analyzes the received digital data and fine-tunes a generative model that reflects the deceased's speech patterns and behavioral patterns. This model is designed to reproduce the deceased's unique communication style.

[0616] Emotion analysis and response generation

[0617] The user initiates a conversation with the deceased AI through their device. The server receives the user's input messages and performs sentiment analysis. Based on the analysis results, the generative model generates the optimal response. This allows the user to continue the conversation as if the deceased were still alive.

[0618] Providing a response

[0619] The generated response is secured by digital watermarking technology. The server sends this response to the user's device, and the user receives the deceased AI's response, provided as a text message or voice message. This allows the user to relive time with the deceased.

[0620] Specific example

[0621] For example, suppose a user sends a message to a deceased AI saying, "I want to talk about recent events." The server analyzes this message to understand the user's current emotional state. The deceased AI might then respond, "What do you mean? I'd love to hear more." Seeing this response, the user can experience what it's like to actually talk to the deceased, which can help them process their emotions.

[0622] Thus, the present invention enables the realistic reproduction of a deceased person's personality using a generative model, providing users with a new way to reconnect with someone important to them.

[0623] The following describes the processing flow.

[0624] Step 1:

[0625] The user prepares digital data related to the deceased, such as text messages, voice recordings, and images, on their device. The device provides an interface for uploading this data, and the user sends the selected data to the server.

[0626] Step 2:

[0627] The server receives digital data sent from the user. The server checks the data format and quality, and performs data analysis to extract the deceased person's personality and past behavioral characteristics.

[0628] Step 3:

[0629] The server begins fine-tuning the generative model based on the received data. In this process, it learns the deceased person's unique communication style and voice characteristics, building a customized AI model.

[0630] Step 4:

[0631] The user initiates a conversation with the deceased AI via their device. The conversation progresses as the user sends input (text or voice) to the server.

[0632] Step 5:

[0633] The server analyzes user input in real time and uses natural language processing to evaluate intent and emotion. Based on this evaluation, the server uses a generative model to generate appropriate responses that reflect the deceased person's personality.

[0634] Step 6:

[0635] The server applies watermarking technology to secure the response it generates. Once the response is ready, the server sends it to the user's terminal.

[0636] Step 7:

[0637] The device displays a response to the user and plays an audio response if available. The user receives this response and can continue the conversation as needed.

[0638] (Example 1)

[0639] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0640] The aim is to recreate the personality of a deceased person using information technology, thereby providing emotional healing to users. However, this process requires protecting privacy based on the deceased's permission, showing consideration for the user's feelings, and improving the safety and quality of the responses provided.

[0641] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0642] In this invention, the server includes a device for inputting information, a device for adjusting personality and behavioral characteristics using a generated knowledge model, a device for analyzing emotions based on user input and generating appropriate responses, and a device for applying technology to keep the generated responses secure. This allows users to find emotional healing through dialogue that recreates the personality of the deceased.

[0643] "Information input device" refers to hardware or software that allows users to provide digital information about the deceased to the system.

[0644] A "generated knowledge model" refers to the data structure of artificial intelligence that is created to reproduce the personality and behavioral characteristics of a deceased person based on the input digital information.

[0645] A "device for adjusting personality and behavioral characteristics" refers to a device that performs a process of fine-tuning the generated knowledge model to achieve a representation that is true to the deceased person.

[0646] A "device that analyzes emotions based on user input and generates appropriate responses" refers to a system component that receives user input, understands their emotional state, and devises a suitable response.

[0647] "Technologies to keep generated responses secure" refers to security technologies that prevent unauthorized access by third parties to data during transmission and storage.

[0648] The system of this invention aims to recreate the personality of a deceased person, allowing the user to process their emotions and find solace through dialogue with the deceased. A specific embodiment of this system is described below.

[0649] First, the terminal receives digital data about the deceased provided by the user. This data includes text messages, voice recordings, and image files, and is used as basic information to recreate the deceased's personality. Through the terminal's interface, the user can input data and send it to the server.

[0650] Next, the server uses the received digital data to fine-tune the generative AI model. Here, natural language processing (NLP) techniques are employed to analyze the deceased person's speech patterns and behavioral patterns, and incorporate them into the generated knowledge model. This generative AI model reproduces the deceased person's unique communication style, enabling dialogue that is faithful to that style.

[0651] When a user actually begins interacting with the AI ​​representing the deceased, they can input a message through their device. The server receives this input and performs sentiment analysis. Based on the analysis results, the model generates the optimal response.

[0652] As a concrete example, let's say a user sends a message to the deceased AI saying, "I want to talk about recent events." The server analyzes the content of this message to understand the user's emotional state and generates a response such as, "What do you mean? I'd love to hear more." This response is securely protected by watermarking technology and sent from the server to the user's device. The user can receive this response from the deceased AI via text message or voice, allowing them to experience what it's like to actually converse with the deceased.

[0653] A concrete example of a prompt message would be something like, "To recreate the deceased's personality, please train a generative model using the following data: text messages, voice recordings, images, etc."

[0654] Thus, this invention is a system that provides users with new opportunities for communication with their deceased loved ones and brings about emotional healing.

[0655] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0656] Step 1:

[0657] The user inputs digital data about the deceased into the terminal. Specifically, the user provides data in the form of text messages, voice recordings, image files, etc., and uploads it through the terminal's designated interface. After input, the terminal checks the data format to ensure it is correct. Next, it converts the data into a format ready for transmission to the server. The input consists of various digital data about the deceased, and the output is the digital data ready for transmission to the server.

[0658] Step 2:

[0659] The server receives digital data transmitted from the terminal. It verifies the format and integrity of the received data and then uses it as input for fine-tuning the generative AI model. Specifically, it analyzes the data using natural language processing (NLP) techniques to extract the deceased person's language patterns and behavioral characteristics. At this point, the input is formatted digital data, and the output is information for adjusting the generative model.

[0660] Step 3:

[0661] The generative AI model is fine-tuned using the deceased's characteristic information obtained from the server. In this process, the existing AI model is input with the deceased's unique linguistic expressions and response patterns, and the model is then fine-tuned based on this input. This reproduces the deceased's characteristic communication style. The input is data for tuning the model, and the output is a personalized generative AI model.

[0662] Step 4:

[0663] The user initiates a conversation with the deceased AI through their device. Specifically, they open the conversation interface on their device and enter a message for the deceased AI. This message is sent to the server as input. The input is the message sent by the user and includes the processing details that the server uses to analyze it.

[0664] Step 5:

[0665] The server analyzes the message received from the user and performs sentiment analysis to understand the intent and emotional state of the input data. Based on the analysis results, it generates the optimal response using a generative AI model. The specific processes here involve the application of sentiment analysis algorithms and the utilization of generative models. The input is the user's message, and the output is the generated response.

[0666] Step 6:

[0667] The generated response is securely transmitted from the server to the terminal using watermarking technology. The terminal interprets the received response and presents it to the user in text or audio. This allows the user to experience a conversation as if they were talking to a deceased person. The input is a pre-generated, secure response, and the output is the dialogue content presented to the end user.

[0668] (Application Example 1)

[0669] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0670] In modern society, there are many ways to remember the deceased, but methods that realistically recreate the personality and memories of the deceased, allowing users to find solace through natural dialogue with them, are limited. Furthermore, conventional interaction methods in virtual spaces have the problem of making it difficult for users to enjoy friendly communication with AI representations of the deceased. As a result, users are missing out on opportunities to experience new forms of interaction with their loved ones.

[0671] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0672] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for fine-tuning the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This enables the user to have a natural conversation with the deceased AI in a virtual space and experience a friendly interaction with the deceased.

[0673] "Information for recreating the deceased's personality" refers to digital data such as text messages, audio recordings, and images related to the deceased, which form the basis for recreating the deceased's unique communication style.

[0674] A "generative model" is an AI model that analyzes received digital data to reflect the personality and behavioral characteristics of the deceased, enabling realistic interaction with the user.

[0675] "Fine-tuning" is the process of adjusting a generative model based on the deceased person's digital data to reproduce their speech patterns and behavioral patterns.

[0676] "Means for analyzing emotions and generating appropriate responses" refers to technology that analyzes the user's emotional state based on input messages from the user, generates the optimal response, and provides it to the user.

[0677] "A means of providing a virtual space to facilitate interaction between users and the deceased AI" refers to a system that allows users to interact with the deceased AI in a virtual environment via a smart device, enabling friendly and approachable communication.

[0678] "Information based on permission given during the deceased's lifetime" refers to information for which the deceased consented to the use of digital data during their lifetime, and which will be used in a manner that respects privacy and consent.

[0679] "Information concealment technology" is a technique applied to ensure the security of generated responses, with the aim of protecting the response content from tampering and unauthorized access.

[0680] The system for realizing this invention includes a terminal for inputting the deceased's digital data, a server for processing the data, and an environment for enabling interaction with the user. First, the user uses the terminal to input information about the deceased, such as text messages, voice recordings, and images. This information is sent to the server as basic data for recreating the deceased's personality.

[0681] The server uses the received information to fine-tune the generated AI model. This process is necessary to reflect the deceased person's unique speech patterns and behavioral patterns in the model. The server also uses Google Cloud's Dialogflow or similar natural language processing technologies to analyze user messages and perform sentiment analysis to generate appropriate responses.

[0682] The generated responses are delivered to the user through a virtual space. In this process, smart devices play a role in facilitating the interaction between the user and the deceased AI. Users can interact with the deceased AI in a virtual environment via their smartphones or smart glasses, enjoying a new form of communication.

[0683] For example, if a user types "Tell me about your recent trip" into the device, the server analyzes their emotions and interests and generates a natural response from the AI, such as "What moments from that trip were particularly memorable?"

[0684] An example of a prompt in a generative AI model is an instruction such as, "When a user asks about the features of a product, how would the AI ​​explain it?" This helps ensure that the generated response is user-friendly and meaningful.

[0685] Through this invention, users can initiate friendly conversations with deceased AI figures in a virtual space and find emotional healing.

[0686] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0687] Step 1:

[0688] The user inputs digital data about the deceased into the terminal. The input data consists of text messages, voice recordings, images, etc., and the terminal sends this information to the server. The input here is the basic data for recreating the personality of the deceased, and the output is the transmission of data to the server.

[0689] Step 2:

[0690] The server analyzes the received digital data and fine-tunes the generative AI model. Specifically, the server learns the deceased person's speech patterns and behavioral patterns based on the digital data and optimizes the model. The input is the received digital data, and the output is the fine-tuned generative model.

[0691] Step 3:

[0692] The user initiates a conversation with the deceased AI via a terminal. The terminal sends input messages from the user to the server. The input is a text message from the user, which is then output to the server.

[0693] Step 4:

[0694] The server receives messages from users and performs sentiment analysis. Specifically, it uses sentiment recognition algorithms to determine the user's emotional state. The input is the user's text message, and the output is the sentiment analysis result.

[0695] Step 5:

[0696] The server generates an appropriate response using a generative model based on the sentiment analysis results. The model utilizes prompt text to recreate the deceased person's communication style. Inputs are the sentiment analysis results and text prompts, while output is the generated response.

[0697] Step 6:

[0698] The server applies information concealment techniques to the generated response and sends it to the terminal. Specifically, the response message is processed to protect it from unauthorized access and tampering. The input is the generated response, and the output is the secure response message.

[0699] Step 7:

[0700] The terminal provides the user with responses generated in a virtual space. Specifically, the interaction with the deceased AI is visually and audibly reproduced through the device the user uses. The input is a safe response message, and the output is visual and audible feedback to the user.

[0701] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0702] This invention is a system that combines an emotional engine that recreates the personality of a deceased person with an emotional engine that understands the user's emotions. Through this system, the user can process their emotions and find emotional healing through dialogue with the deceased. Specific embodiments are described below.

[0703] Data collection and input

[0704] The user prepares digital data (text, audio, images, etc.) about the deceased on their device. This data forms the basis for recreating the deceased's personality. The user selects this data through their device and sends it to the server. This step requires the use of only data for which permission was obtained from the deceased during their lifetime.

[0705] Fine-tuning of the generative model

[0706] The server analyzes data sent by the user and fine-tunes a generative model to recreate the deceased person's personality and behavioral characteristics. This model has the ability to learn the deceased person's distinctive communication style and generate personalized responses.

[0707] Analysis using an emotion engine

[0708] The server has an emotion engine built in, which analyzes the input messages in real time once the user starts a conversation. The emotion engine recognizes the user's emotional state from their text and voice, and the generative model adjusts the response accordingly.

[0709] Response generation and provision

[0710] The server generates an appropriate response that reflects the deceased's characteristics using a generative model. This response is tailored to the user's current emotions by an emotion engine, and its security is ensured by watermarking technology. The generated response is sent to the user's terminal, and the user confirms the response through the terminal.

[0711] Specific example

[0712] For example, if a user sends a text message saying, "Life has been tough lately," the server uses its emotion engine to recognize the user's emotion as "sadness." Based on this, the generative model generates a response in an encouraging tone, providing a message such as, "That must have been difficult. But I'm always rooting for you." Through this response, the user can feel as if they are actually being encouraged by the deceased, and it provides emotional support.

[0713] Thus, the present invention is a system that recreates communication with a deceased person in a new form and provides emotional support to the user.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] The user gathers text, audio, and image data related to the deceased on their device and prepares to input it into the system. The device has an interface for sending this data to a server, and the user uploads the data they have selected.

[0717] Step 2:

[0718] The server receives data sent from the user. The server verifies the format and integrity of the data and performs data analysis to extract the information necessary to recreate the deceased person's personality.

[0719] Step 3:

[0720] The server fine-tunes the generative model based on the extracted information. This model is adjusted to reproduce the deceased person's unique speech patterns and behavioral characteristics. The model is optimized according to the user's individual needs.

[0721] Step 4:

[0722] The user initiates interaction via a terminal and sends a message to the system. The server receives this message and prepares to process it.

[0723] Step 5:

[0724] The server uses an emotion engine to analyze user messages and recognize their emotional state. The emotion engine uses natural language processing and emotion classification techniques to evaluate the user's emotions in real time.

[0725] Step 6:

[0726] Based on the results of the emotion engine, the server generates a response using a generative model. This response corresponds to the user's current emotional state and is tailored to reflect the deceased person's communication style.

[0727] Step 7:

[0728] The server applies watermarking technology to the generated response to ensure its security. The response is then sent to the user's terminal, allowing the conversation to continue.

[0729] Step 8:

[0730] The device displays a response to the user and, if necessary, plays it back as audio. The user receives this response and can continue the conversation.

[0731] (Example 2)

[0732] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0733] There is a need to maintain an emotional connection through records of the deceased, but conventional technologies are insufficient in recreating the personality of the deceased, recognizing the user's emotions, and providing appropriate responses. To solve this problem, it is necessary to more accurately recreate the characteristics of the deceased and generate appropriate responses that correspond to the user's emotions.

[0734] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0735] In this invention, the server includes means for inputting information related to the deceased, means for adjusting the characteristics of the deceased using a generative artificial intelligence model, and means for analyzing user input, recognizing emotions, and adjusting responses. This enables natural and emotional dialogue with the deceased and provides emotional support to the user.

[0736] "Information related to the deceased" refers to digital data such as text, audio, and images necessary to recreate the deceased's personality and behavioral characteristics.

[0737] A "generative artificial intelligence model" is a machine learning model that has the ability to learn the characteristics of a person based on input data and generate personalized responses.

[0738] "User input" refers to text and voice data that users provide to the server through interaction.

[0739] An "emotion engine" is a technology that analyzes user input in real time and recognizes the emotions behind it.

[0740] "Digital watermarking technology" is a technique used to ensure the security of digital data, and it involves embedding an invisible mark into the data.

[0741] "Adjusting the response" refers to optimizing the tone and content of the generated response based on the perceived emotions.

[0742] The embodiments for carrying out the present invention are described below.

[0743] In the system for implementing the invention, the user, terminal, and server play key roles. First, the user inputs information into the terminal to recreate the deceased person's personality. This information includes text, audio, and images related to the deceased, and only data permitted during their lifetime must be used. The terminal has the function of transmitting this data to the server.

[0744] The server analyzes the received data and uses a generative artificial intelligence model to fine-tune the model in order to recreate the deceased person's personality and behavioral characteristics. The generative artificial intelligence model used here is based on a large-scale machine learning framework and makes extensive use of natural language processing (NLP) techniques.

[0745] Next, the server is equipped with an emotion engine that analyzes the user's input through dialogue in real time. The emotion engine recognizes emotions from the user's input and can adjust the response output by the generating AI model to correspond to those emotions. The response is protected by watermarking technology to ensure security and is sent to the user's device.

[0746] For example, if a user sends a message from their device saying, "Life has been tough lately," the server uses an emotion engine to recognize the emotion as "sadness" and provides a response based on that, such as, "That must have been difficult. But I'm always rooting for you." This allows the user to feel as if the deceased person is actually encouraging them.

[0747] An example of a prompt might be: "The user is feeling sad about something that happened recently. Understand this emotion and generate a gentle, encouraging response."

[0748] In this way, a system is created that provides emotional support to users through dialogue with the deceased.

[0749] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0750] Step 1:

[0751] The user prepares information related to the deceased. Specifically, they select digital data such as text, audio, and images using their device. This data must be authorized by the deceased during their lifetime. The prepared data becomes the input data sent from the device to the server.

[0752] Step 2:

[0753] The server analyzes the received data. Specifically, it classifies the data according to its format (text, audio, and image) and extracts key phrases from the text data using natural language processing. It also analyzes characteristic speech patterns from the audio data and uses this extracted information to fine-tune the parameters of the generative artificial intelligence model. This generates output that reproduces the personality and behavioral characteristics of the deceased.

[0754] Step 3:

[0755] The server analyzes user input in real time. It receives messages sent by the user through dialogue and recognizes the emotions using its emotion engine. For example, if the input message is "Life has been difficult lately," the server classifies this emotion as "sadness" and outputs parameters to adjust the response.

[0756] Step 4:

[0757] Based on emotional data obtained by the emotion engine, the server uses a generative AI model to generate an appropriate response. The generated response is adjusted to match the user's emotional state, and may include encouraging words such as, "That must have been tough, but I'm always rooting for you." This response is watermarked to ensure security.

[0758] Step 5:

[0759] The generated response is sent from the server to the user's terminal. The user receives the response on the terminal and can view it on the screen. Through this process, the system is designed to help the user reconstruct their emotional connection with the deceased.

[0760] (Application Example 2)

[0761] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0762] For users seeking emotional healing through dialogue with the deceased, there is a need for a system that faithfully reproduces the personality of the deceased while providing appropriate responses in real time that respond to the user's emotions. Furthermore, ensuring the safety and integrity of the generated responses and providing the dialogue experience to users through readily accessible mobile devices and display devices is a challenge.

[0763] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0764] In this invention, the server includes means for inputting information to recreate the personality of the deceased, means for optimizing the personality and behavioral characteristics of the deceased using a generative model, and means for analyzing emotions based on user input and generating appropriate responses. This allows users to safely receive personalized responses from the deceased, thereby achieving emotional healing.

[0765] "Information for recreating the deceased's personality" refers to digital data (such as voice, text, and images) from the deceased's lifetime, which is used to recreate the deceased's personality and communication style.

[0766] A "generative model" is a collection of algorithms designed to analyze data using machine learning and, through learning, reproduce the characteristics of the target.

[0767] "Optimization methods" refer to the process of adjusting the parameters of a generative model based on input information to precisely reproduce the desired characteristics.

[0768] "Means for analyzing emotions and generating appropriate responses" refers to technology that emotionally analyzes user input (text or voice) in real time and generates responses tailored to that state.

[0769] "Technologies for ensuring data integrity" refer to technologies that guarantee that generated responses and data have not been tampered with, and include technologies such as digital watermarking.

[0770] "Through mobile devices and display devices" indicates that the system can be used through devices such as smartphones and smart glasses.

[0771] This invention is a system that recreates the personality of a deceased person and provides emotional healing to the user through dialogue. The system includes the processes of data input, optimization of the generative model, emotion analysis, and response generation. First, the user's terminal sends information about the deceased (voice, text, images, etc.) to the server. This information is used as basic data to recreate the personality of the deceased.

[0772] The server analyzes the transmitted information using a generative model (e.g., OpenAI GPT-4) and optimizes the model to reproduce the deceased person's personality and behavioral characteristics. Next, the user's speech is transmitted to the server in real time through the input device, such as the terminal's microphone. The server has emotion recognition software (e.g., Microsoft Azure Emotion API) built in to analyze the user's emotional state. Based on this analysis, the generative model generates the optimal response.

[0773] The server applies digital watermarking technology to the generated response to ensure data integrity. This response is then sent to the user's device, allowing the user to experience what it's like to converse with a deceased person. The device could be a smartphone or smart glasses.

[0774] For example, if a user says, "Today I want to celebrate a special day with someone important to me," the sentiment analysis software understands that wish, and the generative model generates a response such as, "Those memories will always be precious to you, enjoy them to the fullest."

[0775] An example of a prompt message is, "When the user feels emotionally lonely, generate kind words of encouragement from the deceased." This allows the system to provide a personalized conversational experience that responds to the user's emotions.

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] The terminal inputs audio, text, and image data related to the deceased and sends it to the server. The input data includes information to reconstruct the deceased's personality and communication style. The server receives this data and stores it in a database.

[0779] Step 2:

[0780] The server optimizes the generative AI model using the stored data. Specifically, it analyzes the data using machine learning algorithms to learn the characteristics of the deceased. This process results in a dialogue model that reflects the personality of the deceased. The input is the data of the deceased received by the server, and the output is the optimized generative model.

[0781] Step 3:

[0782] The user initiates a conversation through a terminal. User input (text or voice) is converted into a digital signal by the terminal and transmitted to the server in real time. The server uses the input signal to analyze the user's emotional state. This includes data processing using emotion recognition software. The input is the user's speech data, and the output is the analyzed emotion data.

[0783] Step 4:

[0784] The server uses the analyzed sentiment data to generate an appropriate response from an optimized generative model. A message tailored to the user's emotions is generated, and data integrity is ensured through watermarking technology. The input is sentiment data, and the output is a secure response message.

[0785] Step 5:

[0786] The generated response message is sent from the server to the terminal. The terminal displays this response to the user. Through this, the user can have an experience as if they were conversing with a deceased person. The input is the message sent from the server, and the output is the response information that the user confirms.

[0787] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0788] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0789] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0790] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0791] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0792] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0793] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0794] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0795] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0796] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0797] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0798] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0799] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0800] 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.

[0801] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0802] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0803] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0804] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0805] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0806] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0807] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0808] The following is further disclosed regarding the embodiments described above.

[0809] (Claim 1)

[0810] A means of inputting data to recreate the personality of the deceased,

[0811] A method for fine-tuning the personality and behavioral characteristics of a deceased person using a generative model,

[0812] A means of analyzing emotions based on user input and generating an appropriate response,

[0813] Means for providing the generated response to the user,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, which uses data based on the deceased's permission given during their lifetime.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein the generated response is subjected to digital watermarking technology to ensure security.

[0819] "Example 1"

[0820] (Claim 1)

[0821] A device for inputting information,

[0822] A device that adjusts personality and behavioral characteristics using a generated knowledge model,

[0823] A device that analyzes emotions based on user input and generates appropriate responses,

[0824] A device that provides the generated response,

[0825] A device that employs techniques to keep the generated response safe,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, which uses information based on past authorizations.

[0829] (Claim 3)

[0830] The system according to claim 1, which includes a function to improve the model based on evaluations obtained from users.

[0831] "Application Example 1"

[0832] (Claim 1)

[0833] A means of inputting information to recreate the personality of the deceased,

[0834] A method for fine-tuning the personality and behavioral characteristics of a deceased person using a generative model,

[0835] A means of analyzing emotions based on user input and generating an appropriate response,

[0836] A means to facilitate interaction between the user and the deceased AI by providing the generated response in a virtual space,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, which uses information based on the deceased's permission given during their lifetime.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein information concealment techniques are applied to the generated response to ensure security.

[0842] "Example 2 of combining an emotion engine"

[0843] (Claim 1)

[0844] A means of entering information related to the deceased,

[0845] A means of adjusting the characteristics of the deceased using a generative artificial intelligence model,

[0846] A means of analyzing user input, recognizing emotions, and adjusting responses,

[0847] Means for transmitting the generated response to a receiving device,

[0848] A method for performing real-time emotion analysis using an emotion engine,

[0849] A means of applying digital watermarking technology to the generated response,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, which uses information authorized by the deceased during their lifetime.

[0853] (Claim 3)

[0854] The system according to claim 1, wherein the response is adjusted based on the user's emotions using an emotion engine.

[0855] "Application example 2 when combining with an emotional engine"

[0856] (Claim 1)

[0857] A means of inputting information to recreate the personality of the deceased,

[0858] A means of optimizing the personality and behavioral characteristics of the deceased using a generative model,

[0859] A means of analyzing emotions based on user input and generating appropriate responses,

[0860] A means of applying techniques to the generated response to ensure data integrity,

[0861] A means of providing the generated response to the user,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, which uses information based on the deceased person's consent during their lifetime.

[0865] (Claim 3)

[0866] The system according to claim 1, which provides a dialogue that recreates the personality of a deceased person through a mobile device or display device. [Explanation of Symbols]

[0867] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting data to recreate the personality of the deceased, A method for fine-tuning the personality and behavioral characteristics of a deceased person using a generative model, A means of analyzing emotions based on user input and generating an appropriate response, Means for providing the generated response to the user, A system that includes this.

2. The system according to claim 1, which uses data based on the deceased's permission given during their lifetime.

3. The system according to claim 1, wherein the generated response is subjected to digital watermarking technology to ensure security.

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