system

Abstract

We provide the system. [Solution] Means for uploading digital information, A means for analyzing the aforementioned uploaded digital information and learning the communication style of a specific person, A means for generating a response based on the learned communication style, An information processing system that includes means for providing the generated response to the user.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, means for maintaining a connection with the deceased have been limited, and it has been difficult to alleviate the sense of loss. In this situation, although the reproduction of memories and conversations regarding the deceased has been demanded, conventional means have not been able to effectively achieve this. Therefore, there is a need for a technology that utilizes the digital information of the deceased to satisfy the emotional needs of users through natural conversations and the reproduction of memories.

Means for Solving the Problems

[0005] This invention provides an information processing system comprising means for uploading digital information, means for analyzing the uploaded digital information and learning the communication style of a specific person, means for generating responses based on the learned communication style, and means for providing the generated responses to the user. This system enables conversations and the recreation of memories based on the digital footprint of the deceased, thereby reducing feelings of loss and providing an environment where emotional connection can be felt. Furthermore, it can generate videos and slideshows to recreate memories, allowing users to visually enjoy the memory of the deceased.

[0006] "Digital information" refers to information that is stored or transmitted electronically in the form of images, audio, text data, etc.

[0007] "Uploading" refers to the operation in which a user transfers data from their own device to an external system such as a server.

[0008] "Analysis" refers to the process of examining digital information in detail using computer processing to extract meaning and patterns.

[0009] "Communication style" refers to the characteristics of language and expression used by a particular person when conveying information and engaging in dialogue.

[0010] "Learning" refers to the process by which a system accumulates and analyzes data to improve its own functions and enhance its ability to perform operations more accurately.

[0011] "Response" refers to the reply or reaction that a system generates in response to user input or questions.

[0012] "Providing" refers to the act of presenting or communicating the generated response to the user.

[0013] "Recreating memories" refers to the process of using digital data to allow users to relive past events and experiences visually and aurally.

[0014] "Videos and slideshows" refer to media presentations that display multiple images or videos in sequence. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered 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.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] The information processing system of the present invention utilizes digital information about a deceased person to enable dialogue with a specific person and the retrieval of memories. The following describes the configuration for implementing this system.

[0037] Users first upload various digital information about the deceased, such as photos, videos, and social media posts, to the system using their own devices. The device then formats this digital information appropriately and securely sends it to the server. On the server side, the received digital information is categorized and securely stored in a database.

[0038] The server analyzes the uploaded digital information. It utilizes natural language processing (NLP) and image recognition technologies to extract the characteristics and visual elements of the deceased person's conversations. This information is used as input data for machine learning algorithms, learning the communication style of specific individuals. Through this learning process, the server acquires the ability to generate natural-sounding responses.

[0039] When a user wishes to communicate with a deceased loved one again, they initiate a conversation session with the Memory Bot through their device. The user's statements are sent from the device to the server, which then creates a response and sends it back to the user. For example, if the user talks to the deceased about everyday events, the server generates a response tailored to the deceased's characteristics and provides it to the user through the device.

[0040] Furthermore, the server also has the ability to recreate specific memories specified by the user. Upon user request, it can combine relevant photos and videos to generate slideshows or videos that visually recreate specific events. The server then delivers these to the user's device, allowing them to visually enjoy memories of the deceased, accompanied by music and voice narration.

[0041] In this way, the present invention can provide emotional support to users based on a wealth of digital information about the deceased.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user operates the device to select digital information such as photos, videos, and social media posts of the deceased, and provides it to the system through the upload panel. The device converts this data into the specified format and transfers it to the server using a secure channel.

[0045] Step 2:

[0046] The server receives the transmitted digital information and stores it in a database. During this process, it records the data type, metadata, upload date and time, and classifies each piece of data.

[0047] Step 3:

[0048] The server analyzes the classified digital information. It uses natural language processing to extract themes and emotions from text data and image recognition technology to identify features from photos and videos. This information is fed into a learning model, which serves as foundational data for acquiring the deceased person's communication style.

[0049] Step 4:

[0050] The user initiates interaction with MemoryBot through an interface on their device. User speech and text input are sent from the device to the server.

[0051] Step 5:

[0052] The server receives user input and generates the most appropriate response based on pre-trained data. The generated response is then processed by a natural language processor to make it sound natural to the user.

[0053] Step 6:

[0054] The generated response is returned to the terminal and, if voice output is requested, is converted into speech using speech synthesis technology. The terminal then displays or plays this response to the user.

[0055] Step 7:

[0056] When a user wants to recreate a specific past memory, they send a request to the server through their device. The server searches for relevant digital information and generates a slideshow or video combining photos and videos.

[0057] Step 8:

[0058] The generated slideshows and videos are sent to the device, allowing the user to relive the memories through sight and sound. The device displays and allows the user to experience them.

[0059] (Example 1)

[0060] 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."

[0061] In modern times, there is a growing need for systems that utilize digital information to recreate personalized conversations and memories in order to maintain an emotional connection with the deceased. However, conventional technologies struggle to generate natural responses that accurately reflect the deceased's communication style or to recreate visually rich memories. As a result, users face the challenge of not receiving adequate emotional support.

[0062] 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.

[0063] In this invention, the server includes means for transmitting digital information via a device that accepts user input, means for processing the transmitted digital information and learning the dialogue characteristics of a specific subject, and means for creating a response based on the learned dialogue characteristics. This enables the generation of natural responses that reflect the deceased person's communication style and the visual reconstruction of memories by combining relevant information.

[0064] A "user" refers to an individual who uses the system to upload digital information and engage in dialogue or relive memories.

[0065] "Digital information" refers to information in electronically stored and manipulateable formats, such as visual data, audio data, and descriptive data.

[0066] "Device" refers to equipment used for transmitting, receiving, and playing back digital information. Examples include computers and smartphones.

[0067] A "server" refers to a central control system that processes received digital information, generates responses, and retrieves stored data.

[0068] "Dialogue characteristics" refer to characteristics related to the communication style and language patterns of a particular subject.

[0069] "Answer" refers to the dialogue content generated based on the user's input.

[0070] "Video data" refers to data in the form of videos or slideshows used to convey visual information.

[0071] "Reconstruction" refers to the process of visually or audibly reconstructing past events or conversations based on digital information.

[0072] The information processing system based on this invention is designed to provide users with an emotional connection through digital information about the deceased. This system uses terminals such as computers and smartphones as hardware, and a central server. The software includes programs that implement natural language processing and image recognition technologies.

[0073] Users upload digital information such as photos, videos, and text data related to the deceased from their devices to the system. The device formats the digital information into an appropriate format and sends it to the server using a secure protocol. HTTPS is used as an example.

[0074] The server analyzes the received digital information. Specifically, it uses natural language processing models to analyze text data and extract the deceased's conversational characteristics. It also uses image recognition technology to identify visual elements from photos and videos. This data is used as training data for a generative AI model, which learns the deceased's unique communication style and generates natural-sounding responses based on the results.

[0075] When a user wishes to communicate with a deceased person, the conversation begins by sending a prompt message to the server via the device. For example, by sending the prompt message "How was your day today?", a response reflecting the deceased person's communication style is generated and provided to the user via the device.

[0076] Furthermore, if a user wants to recreate a specific memory, the server generates a slideshow or video based on the digital information and delivers it to the device. For example, by sending a prompt such as "Collect photos of cherry blossom viewing in spring and create a slideshow," video data combining related photos and audio will be generated.

[0077] In this way, this system can provide users with an emotional connection to the deceased and visually recreate rich memories.

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

[0079] Step 1:

[0080] Users upload photos, videos, and text data of the deceased to the system from their devices. The format of the input digital information is standardized across all devices. This process includes image format conversion and text data structuring. After conversion, the digital information is sent to the server using secure means such as HTTPS.

[0081] Step 2:

[0082] The server classifies the received digital information and securely stores it in a database. The input information is categorized as visual data, audio data, and text data. Database registration includes metadata generation and encryption. This enables the server to efficiently search and retrieve data.

[0083] Step 3:

[0084] The server uses natural language processing (NLP) techniques to analyze text data and extract the deceased person's conversational characteristics. Noun phrases are extracted and sentiment analysis is performed on the input text data. This reveals characteristics related to communication style, which are then used to train generative AI models.

[0085] Step 4:

[0086] The server analyzes visual data using image recognition technology and extracts important visual elements. The input visual data is processed through object detection and face recognition algorithms. This structures the visual elements, which are then used to aid in memory recall and response generation.

[0087] Step 5:

[0088] The generative AI model generates natural responses to user statements based on the deceased person's conversational characteristics. When a user sends a prompt using their device, it becomes the model's input. For example, if the prompt "How was your day?" is entered, the server generates a response that reflects the deceased person's style and sends the result to the device.

[0089] Step 6:

[0090] The server generates slideshows and videos that recreate specific memories by combining digital information in response to user requests. Input requests include specifying keywords and photos related to the particular memory. The server retrieves relevant data from a database and generates video data to visually recreate the memory. This output is provided to the user via their device and becomes viewable.

[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 is a growing need to preserve memories and personalities of deceased individuals through digital information, but there is a lack of methods to utilize this information to provide direct and emotional experiences. Furthermore, there are challenges in conducting virtual reality-based conversations with deceased loved ones or recreating memories in real-world spaces. In this context, there is a need to provide users with more immersive and emotionally engaging experiences.

[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 functions for providing digital data, analyzing the provided digital data and learning the communication style of a specific subject, generating responses based on the learned communication style, presenting the generated responses to the user, and visually recreating a specific memory using a device for the user to experience virtual reality in a real space. This enables the user to have a virtual conversation with the deceased and experience a realistic recreation of memories.

[0096] "Digital data" refers to all information stored in electronic format, including visual, auditory, and textual information.

[0097] "Analysis" is the process of processing information stored in electronic format and extracting meaning and patterns.

[0098] "Communication style" refers to the unique linguistic and behavioral patterns that a particular individual exhibits in dialogue.

[0099] The "function to generate responses" refers to the ability to create appropriate responses based on analyzed data and provide them to the user.

[0100] "Devices for experiencing virtual reality in real space" refer to equipment used by users to experience virtual visual and auditory elements in a real-world environment.

[0101] "Visual reproduction" refers to the process of visually representing past events or memories using photographs and videos.

[0102] This system is an information processing platform that utilizes digital data about the deceased to provide users with an emotional experience. First, users provide the system with digital data such as images, audio, and text information about the deceased using a digital device. The provided digital data is securely transferred to the server via the terminal.

[0103] The server features high-performance processors and ample storage as hardware, and utilizes natural language processing libraries (e.g., spaCy and BERT) and machine learning platforms (e.g., TENSORFLOW®, PyTorch) as software. This server analyzes the provided digital data and extracts and learns specific communication patterns. In this process, it identifies the meaning and usage patterns of the data, which are then used to generate the necessary content.

[0104] The generated information is presented as a response on the user's digital device. Furthermore, by wearing devices that enable virtual reality experiences in the real world (e.g., smart glasses or VR headsets), users can visually recreate specific memories. This recreation process generates the visual and acoustic elements of the space the user experiences, allowing them to relive past memories or conversations with deceased loved ones in a virtual environment.

[0105] For example, if a user says, "Today I went to a park that the deceased loved," the system will generate a response such as, "Would you like to see a photo album to help us remember that day?" based on past photos and the user's memory data.

[0106] Examples of prompts to input into a generative AI model:

[0107] "I'd like to talk about the deceased person's favorite foods."

[0108] "Please create a video that evokes memories of old family trips."

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

[0110] Step 1:

[0111] The user uses a terminal to input images, audio, and text information related to the deceased. The terminal converts this digital data into the appropriate format and sends it to the server. At this point, the input is the user's digital data, and the output is formatted data.

[0112] Step 2:

[0113] The server analyzes the received digital data. Using image processing algorithms and natural language processing techniques, it detects specific patterns and features within the data. This analysis extracts information for learning the deceased person's communication style. The input is the digital data received from the terminal, and the output is the extracted feature data.

[0114] Step 3:

[0115] The server learns based on the feature data obtained from the analysis. Using a machine learning model, it generates a model to mimic the deceased person's communication style. This process establishes the foundation for generating natural responses. The input is feature data, and the output is the learned communication model.

[0116] Step 4:

[0117] The user inputs the content they wish to communicate with the deceased via a terminal. The server generates an appropriate response to the user's input based on a trained model. The input is the content the user wishes to communicate, and the output is the generated response.

[0118] Step 5:

[0119] The generated response is presented to the user via the terminal. Furthermore, if the user so desires, a reproduction system is activated to provide a virtual reality experience in the real world. The input is the generated response, and the output is the presentation of the response to the user and the provision of the VR experience.

[0120] Step 6:

[0121] When a user begins a virtual reality experience, the server sends data to the VR device to visually recreate a specific memory. This allows the user to enjoy a unique and immersive experience. The input is the VR experience request from the user, and the output is the visual recreation experience on the VR device.

[0122] 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.

[0123] This invention relates to an information processing system that recognizes a user's emotional state and enables the provision of appropriate responses and content. This system is characterized by incorporating an emotion engine that determines emotions based on the user's voice and text data and adjusts the response accordingly.

[0124] Users upload digital information about the deceased through their device. The device converts the digital information into a predetermined format, encrypts it, and then sends it to the server. The server stores the received information, classifies it, and stores it in a database.

[0125] The server analyzes this digital information and learns the deceased's communication style through machine learning. This process involves natural language processing and image recognition technologies to extract the deceased's characteristics and language patterns.

[0126] Furthermore, the server incorporates an emotion engine that identifies emotions from the user's voice and text input. For example, if a user speaks in a sad tone, the server recognizes that emotion as "sadness" and adjusts its responses and content to suit that emotional state. Specifically, if a user says, "Today was a tough day," the server can generate a gentle response and present content that includes comfort and encouragement.

[0127] When a user wishes to recreate memories of a deceased loved one, they send a request to the server via their device. The server retrieves relevant images and videos, adds appropriate music and narration, and generates visual content. This generated content is streamed to the user, helping them relive memories and evoke emotions.

[0128] According to embodiments of the present invention, users can go beyond simply viewing digital data and receive personalized responses that respond to their emotions, thereby gaining a richer experience.

[0129] The following describes the processing flow.

[0130] Step 1:

[0131] The user selects digital information such as photos, videos, and text data of the deceased using a device and sends it through the system's upload interface. The device organizes this selected data according to a specified format and uploads it to the server using a secure protocol.

[0132] Step 2:

[0133] The server stores the received digital information for analysis and categorizes it by type. The stored data is then placed in a database, and identifiable metadata is added for use in subsequent analysis processes.

[0134] Step 3:

[0135] The server analyzes uploaded digital information using natural language processing and image recognition algorithms. In this analysis process, the deceased's communication style and tone of voice are extracted from text data, and visual features are identified from images and videos.

[0136] Step 4:

[0137] The server runs an emotion engine that identifies emotions in real time from user input. What the user says to the terminal and the text they type are sent to the server, where they are analyzed to detect emotions from the voice and text.

[0138] Step 5:

[0139] Based on the user's emotional state, the server generates an appropriate response, taking into account the deceased person's communication style. For example, if the server determines that the user is sad, it will generate a comforting response and return it to the terminal.

[0140] Step 6:

[0141] The generated response is sent to the terminal and either displayed to the user or played back as audio. The terminal presents the response in the format best suited to the user's device, providing the user with a natural and engaging conversation.

[0142] Step 7:

[0143] When a user wants to recreate a specific memory, they request this from the server via their device. The server collects the relevant digital data and generates a slideshow or video, including music and narration. This generated content may also be adjusted according to the user's current emotions.

[0144] Step 8:

[0145] The generated memory content is streamed to the device and delivered to the user. Through this, the user can visually and aurally relive memories of the deceased. The device supports content playback, allowing the user to relive memories in a comfortable way.

[0146] (Example 2)

[0147] 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".

[0148] In today's information society, much digital information is linked to individuals' memories and emotions, but simply treating it as data does not provide a rich experience. In particular, there is a need to utilize digital information about deceased individuals to provide users with an emotionally resonant experience.

[0149] 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.

[0150] In this invention, the server includes means for receiving digital information as input, means for processing the received digital information and analyzing the conversational style of a specific individual, means for constructing a response based on the analysis results, means for identifying the emotional state of the user, means for generating content adjusted based on the emotional state, and means for delivering the generated content to the user. This makes it possible to provide a rich experience that is attentive to the user's emotions while being based on individual memories and the characteristics of the deceased.

[0151] "Digital information" refers to electronically stored information, including visual data, audio data, and text data.

[0152] A "device that accepts input" is a device that receives digital information from users and prepares it for processing.

[0153] A "processing device" is a device used to analyze input digital information and to analyze the conversational style of a specific individual.

[0154] A "device that constructs responses based on analysis results" is a device that has the function of generating appropriate responses according to the analyzed individual's dialogue style.

[0155] A "device for identifying emotional states" is a device that has the function of determining emotions from the user's voice or text data and identifying that state.

[0156] A "device that generates adjusted content" is a device that has the function of customizing and generating content to be provided according to the identified emotional state.

[0157] A "distribution device" is a device that provides generated content to users, enabling an emotionally engaging experience.

[0158] The information processing system of the present invention aims to provide responses and content based on the user's emotional state. Specific embodiments of this system are described below.

[0159] Users input digital information related to the deceased via their device and upload it. During this process, the device converts the digital information into a specified format and securely transmits it to the server using encryption technology (e.g., SSL / TLS). Common electronic devices such as computers and smartphones can be used as devices.

[0160] The server stores the received digital information in a database and classifies and organizes the data. This database management may utilize relational database management systems (RDBMS) such as MySQL® or PostgreSQL. The server analyzes the digital information using libraries such as Python's TensorFlow to learn specific individual language patterns and communication styles.

[0161] Furthermore, the server incorporates an emotion engine that analyzes user voice and text input to identify emotions. This process utilizes natural language processing libraries such as NLTK and huggingface. Based on the user's emotions, the server uses generative AI models such as OpenAI's GPT to generate appropriate responses and content.

[0162] When generating content, media editing software such as Adobe Premiere can be used to combine related images and videos, and to add music and narration. The generated content is then streamed by the device and delivered to the user.

[0163] For example, if a user enters the text "I'm sad today because I'm remembering someone who passed away," the server will recognize that emotion and deliver a gentle response along with calming music accompanied by photos or videos related to the deceased. An example of the prompt in this case would be, "I'd like to see a video of happy summer memories with the deceased."

[0164] In this way, the information processing system of the present invention enables the provision of user experiences that are emotionally resonant.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] Users input and upload photos and text data related to the deceased person into their device. Because this input data may have different formats and sizes, the device converts the digital information into a unified format (e.g., JPEG image, text file format). Then, it prepares the data for secure transmission to the server using encryption technologies such as SSL / TLS.

[0168] Step 2:

[0169] The server decrypts the encrypted data received from the terminal and stores it in a database. The input digital information is categorized based on metadata (e.g., date, location, related person's name). This organizes the data to enable quick searching and access. SQL queries can be used for this process.

[0170] Step 3:

[0171] The server analyzes information stored in the database and learns the communication style of a specific individual. This process utilizes natural language processing and image recognition technologies, such as Python's TensorFlow. Text and image data of the deceased are provided as input, and a model representing the deceased's language patterns and behavioral characteristics is generated as output.

[0172] Step 4:

[0173] The user inputs emotion-related text or audio into the terminal. The server activates an emotion engine to identify the user's emotion. This involves using libraries such as NLTK or huggingface to analyze the input data. The output will be an identified emotional state, such as sadness or joy.

[0174] Step 5:

[0175] The server generates responses based on the identified user's emotional state. Here, a generative AI model is used to generate appropriate responses and content based on the prompt. For example, in response to the prompt "I'm sad today because I'm remembering someone who has passed away," it generates a gentle, comforting response and incorporates relevant content. The generated data is output as HTML or audio files.

[0176] Step 6:

[0177] Upon user request, the server retrieves relevant images and videos from the database and creates visual content using software such as Adobe Premiere. Music and narration are added to visualize memories of the deceased. This generated content is then streamed to the user via their device.

[0178] (Application Example 2)

[0179] 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".

[0180] In modern society, the uniformity of content provided by information processing systems makes it difficult to respond appropriately to users' emotional states and provide relevant content. Furthermore, there is a lack of support for users to easily select content that matches their current emotional state. Therefore, there is a need to realize highly personalized content delivery methods that respond to users' emotions.

[0181] 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.

[0182] In this invention, the server includes a function for uploading digital information, a function for analyzing the uploaded digital information and learning the communication style of a specific person, and a function for determining emotional states and adjusting responses based on those emotions. This makes it possible to provide personalized content that matches the diverse emotions of users.

[0183] "Digital information" refers to all information expressed in electronic format, including audio, text, and visual elements.

[0184] "Analysis" refers to the process of verifying the content of digital information and extracting specific patterns or features.

[0185] "Communication style" refers to the unique patterns and tendencies in language and expression used by a particular person.

[0186] "Emotional state" refers to the type and intensity of emotions judged from the user's voice and text.

[0187] "Response" refers to the reply or reaction that the system gives in response to input from the user.

[0188] "Content" refers to visual or auditory elements provided to users, such as images, music, and text.

[0189] "Function" refers to the ability or mechanism that a system possesses in order to perform a specific task or operation.

[0190] The system for realizing this invention consists of a platform including terminals, servers, and an emotion engine. Details are described below.

[0191] The terminal is responsible for collecting digital information from the user. This information includes voice instructions and text. The terminal converts this data into a predetermined format, encrypts it, and then sends it to the server. Devices such as smartphones and tablets are used in this process.

[0192] The server first analyzes the received digital information. This analysis uses the Python programming language and machine learning libraries such as TensorFlow. The server analyzes speech and text data and learns specific communication styles. The server also uses the Google® Cloud Speech-to-Text API to transcribe speech into text in real time and uses an emotion engine to determine the user's emotional state.

[0193] The emotion engine classifies emotions based on the user's speech content and tone. For example, if a user says, "I'm so stressed today," the system recognizes that emotion as "stress" and recommends content appropriate to that state, such as relaxing music.

[0194] Ultimately, the server uses a recommendation model built with Scikit-learn to select the most relevant content based on the user's emotional state. The selected content is stored on AWS® S3 and delivered to the user via streaming. Through this process, users receive personalized content that matches their emotional state.

[0195] For example, if a user expresses fatigue, the system analyzes that emotion and uses prompts to a generative AI model, such as "Please provide content that will help the user relax," to recommend appropriate streaming content.

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The terminal collects voice and text data from the user as input. The terminal converts this data into a predetermined format and securely transmits it to the server using AES encryption. The input is raw voice and text data, and the output is encrypted data received by the server.

[0199] Step 2:

[0200] The server decrypts the received encrypted digital data and analyzes it using a Python®-based program. Specifically, it extracts communication styles from text data using a natural language processing library. The input is encrypted data, and the output is the analyzed communication style.

[0201] Step 3:

[0202] The server uses the Google Cloud Speech-to-Text API to convert speech data into text in real time. This converts speech instructions into text, making it easier for the emotion engine to determine the emotional state. The input is speech data, and the output is text data.

[0203] Step 4:

[0204] The server's emotion engine classifies the user's emotional state based on text data. It uses a generative AI model to determine the emotion and outputs the result. The input is text data, and the output is the determined emotional state.

[0205] Step 5:

[0206] The server uses a recommendation model built with Scikit-learn to select appropriate content based on the determined emotional state. For example, if the user's emotional state is determined to be "relaxed," it will recommend music suitable for relaxation. The input is the emotional state, and the output is a list of selected content.

[0207] Step 6:

[0208] To stream content selected by the user, the server utilizes content data stored in AWS S3. This allows users to instantly enjoy content that matches their mood. The input is a list of content, and the output is the streamed content.

[0209] 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.

[0210] 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.

[0211] 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.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] 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.

[0215] 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).

[0216] 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.

[0217] 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.

[0218] 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).

[0219] 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.

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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".

[0225] The information processing system of the present invention utilizes digital information about a deceased person to enable dialogue with a specific person and the retrieval of memories. The following describes the configuration for implementing this system.

[0226] Users first upload various digital information about the deceased, such as photos, videos, and social media posts, to the system using their own devices. The device then formats this digital information appropriately and securely sends it to the server. On the server side, the received digital information is categorized and securely stored in a database.

[0227] The server analyzes the uploaded digital information. It utilizes natural language processing (NLP) and image recognition technologies to extract the characteristics and visual elements of the deceased person's conversations. This information is used as input data for machine learning algorithms, learning the communication style of specific individuals. Through this learning process, the server acquires the ability to generate natural-sounding responses.

[0228] When a user wishes to communicate with a deceased loved one again, they initiate a conversation session with the Memory Bot through their device. The user's statements are sent from the device to the server, which then creates a response and sends it back to the user. For example, if the user talks to the deceased about everyday events, the server generates a response tailored to the deceased's characteristics and provides it to the user through the device.

[0229] Furthermore, the server also has the ability to recreate specific memories specified by the user. Upon user request, it can combine relevant photos and videos to generate slideshows or videos that visually recreate specific events. The server then delivers these to the user's device, allowing them to visually enjoy memories of the deceased, accompanied by music and voice narration.

[0230] In this way, the present invention can provide emotional support to users based on a wealth of digital information about the deceased.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user operates the device to select digital information such as photos, videos, and social media posts of the deceased, and provides it to the system through the upload panel. The device converts this data into the specified format and transfers it to the server using a secure channel.

[0234] Step 2:

[0235] The server receives the transmitted digital information and stores it in a database. During this process, it records the data type, metadata, upload date and time, and classifies each piece of data.

[0236] Step 3:

[0237] The server analyzes the classified digital information. It uses natural language processing to extract themes and emotions from text data and image recognition technology to identify features from photos and videos. This information is fed into a learning model, which serves as foundational data for acquiring the deceased person's communication style.

[0238] Step 4:

[0239] The user initiates interaction with MemoryBot through an interface on their device. User speech and text input are sent from the device to the server.

[0240] Step 5:

[0241] The server receives user input and generates the most appropriate response based on pre-trained data. The generated response is then processed by a natural language processor to make it sound natural to the user.

[0242] Step 6:

[0243] The generated response is returned to the terminal and, if voice output is requested, is converted into speech using speech synthesis technology. The terminal then displays or plays this response to the user.

[0244] Step 7:

[0245] When a user wants to recreate a specific past memory, they send a request to the server through their device. The server searches for relevant digital information and generates a slideshow or video combining photos and videos.

[0246] Step 8:

[0247] The generated slideshows and videos are sent to the device, allowing the user to relive the memories through sight and sound. The device displays and allows the user to experience them.

[0248] (Example 1)

[0249] 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."

[0250] In modern times, there is a growing need for systems that utilize digital information to recreate personalized conversations and memories in order to maintain an emotional connection with the deceased. However, conventional technologies struggle to generate natural responses that accurately reflect the deceased's communication style or to recreate visually rich memories. As a result, users face the challenge of not receiving adequate emotional support.

[0251] 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.

[0252] In this invention, the server includes means for transmitting digital information via a device that accepts user input, means for processing the transmitted digital information and learning the dialogue characteristics of a specific subject, and means for creating a response based on the learned dialogue characteristics. This enables the generation of natural responses that reflect the deceased person's communication style and the visual reconstruction of memories by combining relevant information.

[0253] A "user" refers to an individual who uses the system to upload digital information and engage in dialogue or relive memories.

[0254] "Digital information" refers to information in electronically stored and manipulateable formats, such as visual data, audio data, and descriptive data.

[0255] "Device" refers to equipment used for transmitting, receiving, and playing back digital information. Examples include computers and smartphones.

[0256] A "server" refers to a central control system that processes received digital information, generates responses, and retrieves stored data.

[0257] "Dialogue characteristics" refer to characteristics related to the communication style and language patterns of a particular subject.

[0258] "Answer" refers to the dialogue content generated based on the user's input.

[0259] "Video data" refers to data in the form of videos or slideshows used to convey visual information.

[0260] "Reconstruction" refers to the process of visually or audibly reconstructing past events or conversations based on digital information.

[0261] The information processing system based on this invention is designed to provide users with an emotional connection through digital information about the deceased. This system uses terminals such as computers and smartphones as hardware, and a central server. The software includes programs that implement natural language processing and image recognition technologies.

[0262] Users upload digital information such as photos, videos, and text data related to the deceased from their devices to the system. The device formats the digital information into an appropriate format and sends it to the server using a secure protocol. HTTPS is used as an example.

[0263] The server analyzes the received digital information. Specifically, it uses natural language processing models to analyze text data and extract the deceased's conversational characteristics. It also uses image recognition technology to identify visual elements from photos and videos. This data is used as training data for a generative AI model, which learns the deceased's unique communication style and generates natural-sounding responses based on the results.

[0264] When a user wishes to communicate with a deceased person, the conversation begins by sending a prompt message to the server via the device. For example, by sending the prompt message "How was your day today?", a response reflecting the deceased person's communication style is generated and provided to the user via the device.

[0265] Furthermore, if a user wants to recreate a specific memory, the server generates a slideshow or video based on the digital information and delivers it to the device. For example, by sending a prompt such as "Collect photos of cherry blossom viewing in spring and create a slideshow," video data combining related photos and audio will be generated.

[0266] In this way, this system can provide users with an emotional connection to the deceased and visually recreate rich memories.

[0267] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0268] Step 1:

[0269] Users upload photos, videos, and text data of the deceased to the system from their devices. The format of the input digital information is standardized across all devices. This process includes image format conversion and text data structuring. After conversion, the digital information is sent to the server using secure means such as HTTPS.

[0270] Step 2:

[0271] The server classifies the received digital information and securely stores it in a database. The input information is categorized as visual data, audio data, and text data. Database registration includes metadata generation and encryption. This enables the server to efficiently search and retrieve data.

[0272] Step 3:

[0273] The server uses natural language processing (NLP) techniques to analyze text data and extract the deceased person's conversational characteristics. Noun phrases are extracted and sentiment analysis is performed on the input text data. This reveals characteristics related to communication style, which are then used to train generative AI models.

[0274] Step 4:

[0275] The server analyzes visual data using image recognition technology and extracts important visual elements. The input visual data is processed through object detection and face recognition algorithms. This structures the visual elements, which are then used to aid in memory recall and response generation.

[0276] Step 5:

[0277] The generative AI model generates natural responses to user statements based on the deceased person's conversational characteristics. When a user sends a prompt using their device, it becomes the model's input. For example, if the prompt "How was your day?" is entered, the server generates a response that reflects the deceased person's style and sends the result to the device.

[0278] Step 6:

[0279] The server generates a slideshow or video that combines digital information to reproduce a specific memory in response to a user's request. The input request includes keywords or photo specifications related to a specific memory. The server retrieves relevant data from the database and generates video data for visual reproduction. The output is provided to the user through the terminal and can be viewed.

[0280] (Application Example 1)

[0281] 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".

[0282] In modern society, the need to store the memories and personalities of the deceased through digital information is increasing, but there is a lack of methods to utilize this information to provide direct and emotional experiences. Additionally, there is an issue that it is difficult to conduct interactions with the deceased or reproduce memories using virtual reality in the real space. In such a situation, it is required to provide users with a more immersive emotional experience.

[0283] 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.

[0284] In this invention, the server includes a function for providing digital data, a function for analyzing the provided digital data and acquiring the communication style of a specific target, a function for generating a reaction based on the acquired communication style, a function for presenting the generated reaction to the user, and a function for visually reproducing a specific memory using a device for the user to perform a virtual reality experience in the real space. Thereby, the user can have a virtual interaction with the deceased and experience the real reproduction of memories.

[0285] "Digital data" refers to all information stored in an electronic form including visual information, acoustic information, and character information.

[0286] "Analysis" refers to the procedure of processing information stored in electronic form and extracting meaning and patterns.

[0287] "Communication style" refers to the specific linguistic and behavioral patterns shown by a particular individual in conversation.

[0288] "Function to generate a response" refers to the ability to create an appropriate response based on the analyzed data and provide it to the user.

[0289] "Device for conducting virtual reality experiences in the real world" refers to the equipment used by users to have virtual visual and auditory experiences in the real environment.

[0290] "Visually reproduce" refers to the procedure of visually expressing past events or memories using photos or videos.

[0291] This system is an information processing platform that utilizes digital data related to the deceased and provides emotional experiences to users. First, the user uses a digital device to provide digital data such as images, voices, and text information of the deceased to the system. The provided digital data is securely transferred to the server through the terminal.

[0292] The server has a high-performance processor and sufficient storage as hardware, and uses natural language processing libraries (e.g., spaCy and BERT) and machine learning platforms (e.g., TensorFlow, PyTorch) as software. This server analyzes the provided digital data, extracts and learns specific communication styles. In this process, the meaning and usage patterns of the data are identified and utilized for generating the necessary content.

[0293] The generated information is presented as a response on the user's digital device. Furthermore, by wearing devices that enable virtual reality experiences in the real world (e.g., smart glasses or VR headsets), users can visually recreate specific memories. This recreation process generates the visual and acoustic elements of the space the user experiences, allowing them to relive past memories or conversations with deceased loved ones in a virtual environment.

[0294] For example, if a user says, "Today I went to a park that the deceased loved," the system will generate a response such as, "Would you like to see a photo album to help us remember that day?" based on past photos and the user's memory data.

[0295] Examples of prompts to input into a generative AI model:

[0296] "I'd like to talk about the deceased person's favorite foods."

[0297] "Please create a video that evokes memories of old family trips."

[0298] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0299] Step 1:

[0300] The user uses a terminal to input images, audio, and text information related to the deceased. The terminal converts this digital data into the appropriate format and sends it to the server. At this point, the input is the user's digital data, and the output is formatted data.

[0301] Step 2:

[0302] The server analyzes the received digital data. Using image processing algorithms and natural language processing techniques, it detects specific patterns and features from the data. Through this analysis, information for learning the communication style of the deceased is extracted. The input is the digital data received from the terminal, and the output is the extracted feature data.

[0303] Step 3:

[0304] The server conducts learning based on the feature data obtained from the analysis. Using a machine learning model, it generates a model for imitating the communication style of the deceased. Through this process, a foundation for generating natural responses is constructed. The input is the feature data, and the output is the learned communication model.

[0305] Step 4:

[0306] The user inputs the content they want to interact with the deceased via the terminal. The server generates an appropriate response to the user's input based on the learned model. The input is the content the user wants to interact with, and the output is the generated response.

[0307] Step 5:

[0308] The generated response is presented to the user through the terminal. Furthermore, if the user desires, a reproduction system operates to provide a virtual reality experience in the real world. The input is the generated response, and the output is the presentation of the response to the user and the provision of the VR experience.

[0309] Step 6:

[0310] When the user starts the virtual reality experience, the server transmits data for visually reproducing specific memories for the VR device. Thereby, the user can enjoy a unique immersive experience. The input is the VR experience request from the user, and the output is the visual reproduction experience on the VR device.

[0311] 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.

[0312] This invention relates to an information processing system that recognizes a user's emotional state and enables the provision of appropriate responses and content. This system is characterized by incorporating an emotion engine that determines emotions based on the user's voice and text data and adjusts the response accordingly.

[0313] Users upload digital information about the deceased through their device. The device converts the digital information into a predetermined format, encrypts it, and then sends it to the server. The server stores the received information, classifies it, and stores it in a database.

[0314] The server analyzes this digital information and learns the deceased's communication style through machine learning. This process involves natural language processing and image recognition technologies to extract the deceased's characteristics and language patterns.

[0315] Furthermore, the server incorporates an emotion engine that identifies emotions from the user's voice and text input. For example, if a user speaks in a sad tone, the server recognizes that emotion as "sadness" and adjusts its responses and content to suit that emotional state. Specifically, if a user says, "Today was a tough day," the server can generate a gentle response and present content that includes comfort and encouragement.

[0316] When a user wishes to recreate memories of a deceased loved one, they send a request to the server via their device. The server retrieves relevant images and videos, adds appropriate music and narration, and generates visual content. This generated content is streamed to the user, helping them relive memories and evoke emotions.

[0317] According to embodiments of the present invention, users can go beyond simply viewing digital data and receive personalized responses that respond to their emotions, thereby gaining a richer experience.

[0318] The following describes the processing flow.

[0319] Step 1:

[0320] The user selects digital information such as photos, videos, and text data of the deceased using a device and sends it through the system's upload interface. The device organizes this selected data according to a specified format and uploads it to the server using a secure protocol.

[0321] Step 2:

[0322] The server stores the received digital information for analysis and categorizes it by type. The stored data is then placed in a database, and identifiable metadata is added for use in subsequent analysis processes.

[0323] Step 3:

[0324] The server analyzes uploaded digital information using natural language processing and image recognition algorithms. In this analysis process, the deceased's communication style and tone of voice are extracted from text data, and visual features are identified from images and videos.

[0325] Step 4:

[0326] The server runs an emotion engine that identifies emotions in real time from user input. What the user says to the terminal and the text they type are sent to the server, where they are analyzed to detect emotions from the voice and text.

[0327] Step 5:

[0328] Based on the user's emotional state, the server generates an appropriate response, taking into account the deceased person's communication style. For example, if the server determines that the user is sad, it will generate a comforting response and return it to the terminal.

[0329] Step 6:

[0330] The generated response is sent to the terminal and either displayed to the user or played back as audio. The terminal presents the response in the format best suited to the user's device, providing the user with a natural and engaging conversation.

[0331] Step 7:

[0332] When a user wants to recreate a specific memory, they request this from the server via their device. The server collects the relevant digital data and generates a slideshow or video, including music and narration. This generated content may also be adjusted according to the user's current emotions.

[0333] Step 8:

[0334] The generated memory content is streamed to the device and delivered to the user. Through this, the user can visually and aurally relive memories of the deceased. The device supports content playback, allowing the user to relive memories in a comfortable way.

[0335] (Example 2)

[0336] 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".

[0337] In today's information society, much digital information is linked to individuals' memories and emotions, but simply treating it as data does not provide a rich experience. In particular, there is a need to utilize digital information about deceased individuals to provide users with an emotionally resonant experience.

[0338] 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.

[0339] In this invention, the server includes means for receiving digital information as input, means for processing the received digital information and analyzing the conversational style of a specific individual, means for constructing a response based on the analysis results, means for identifying the emotional state of the user, means for generating content adjusted based on the emotional state, and means for delivering the generated content to the user. This makes it possible to provide a rich experience that is attentive to the user's emotions while being based on individual memories and the characteristics of the deceased.

[0340] "Digital information" refers to electronically stored information, including visual data, audio data, and text data.

[0341] A "device that accepts input" is a device that receives digital information from users and prepares it for processing.

[0342] A "processing device" is a device used to analyze input digital information and to analyze the conversational style of a specific individual.

[0343] A "device that constructs responses based on analysis results" is a device that has the function of generating appropriate responses according to the analyzed individual's dialogue style.

[0344] A "device for identifying emotional states" is a device that has the function of determining emotions from the user's voice or text data and identifying that state.

[0345] A "device that generates adjusted content" is a device that has the function of customizing and generating content to be provided according to the identified emotional state.

[0346] A "distribution device" is a device that provides generated content to users, enabling an emotionally engaging experience.

[0347] The information processing system of the present invention aims to provide responses and content based on the user's emotional state. Specific embodiments of this system are described below.

[0348] Users input digital information related to the deceased via their device and upload it. During this process, the device converts the digital information into a specified format and securely transmits it to the server using encryption technology (e.g., SSL / TLS). Common electronic devices such as computers and smartphones can be used as devices.

[0349] The server stores the received digital information in a database and classifies and organizes the data. Relational database management systems (RDBMS) such as MySQL or PostgreSQL may be used for this database management. The server analyzes the digital information using libraries such as Python's TensorFlow to learn the language patterns and communication styles of specific individuals.

[0350] Furthermore, the server incorporates an emotion engine that analyzes user voice and text input to identify emotions. This process utilizes natural language processing libraries such as NLTK and huggingface. Based on the user's emotions, the server uses generative AI models such as OpenAI's GPT to generate appropriate responses and content.

[0351] When generating content, media editing software such as Adobe Premiere can be used to combine related images and videos, and to add music and narration. The generated content is then streamed by the device and delivered to the user.

[0352] For example, if a user enters the text "I'm sad today because I'm remembering someone who passed away," the server will recognize that emotion and deliver a gentle response along with calming music accompanied by photos or videos related to the deceased. An example of the prompt in this case would be, "I'd like to see a video of happy summer memories with the deceased."

[0353] In this way, the information processing system of the present invention enables the provision of user experiences that are emotionally resonant.

[0354] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0355] Step 1:

[0356] Users input and upload photos and text data related to the deceased person into their device. Because this input data may have different formats and sizes, the device converts the digital information into a unified format (e.g., JPEG image, text file format). Then, it prepares the data for secure transmission to the server using encryption technologies such as SSL / TLS.

[0357] Step 2:

[0358] The server decrypts the encrypted data received from the terminal and stores it in a database. The input digital information is categorized based on metadata (e.g., date, location, related person's name). This organizes the data to enable quick searching and access. SQL queries can be used for this process.

[0359] Step 3:

[0360] The server analyzes information stored in the database and learns the communication style of a specific individual. This process utilizes natural language processing and image recognition technologies, such as Python's TensorFlow. Text and image data of the deceased are provided as input, and a model representing the deceased's language patterns and behavioral characteristics is generated as output.

[0361] Step 4:

[0362] The user inputs emotion-related text or audio into the terminal. The server activates an emotion engine to identify the user's emotion. This involves using libraries such as NLTK or huggingface to analyze the input data. The output will be an identified emotional state, such as sadness or joy.

[0363] Step 5:

[0364] The server generates responses based on the identified user's emotional state. Here, a generative AI model is used to generate appropriate responses and content based on the prompt. For example, in response to the prompt "I'm sad today because I'm remembering someone who has passed away," it generates a gentle, comforting response and incorporates relevant content. The generated data is output as HTML or audio files.

[0365] Step 6:

[0366] Upon user request, the server retrieves relevant images and videos from the database and creates visual content using software such as Adobe Premiere. Music and narration are added to visualize memories of the deceased. This generated content is then streamed to the user via their device.

[0367] (Application Example 2)

[0368] 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."

[0369] In modern society, the uniformity of content provided by information processing systems makes it difficult to respond appropriately to users' emotional states and provide relevant content. Furthermore, there is a lack of support for users to easily select content that matches their current emotional state. Therefore, there is a need to realize highly personalized content delivery methods that respond to users' emotions.

[0370] 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.

[0371] In this invention, the server includes a function for uploading digital information, a function for analyzing the uploaded digital information and learning the communication style of a specific person, and a function for determining emotional states and adjusting responses based on those emotions. This makes it possible to provide personalized content that matches the diverse emotions of users.

[0372] "Digital information" refers to all information expressed in electronic format, including audio, text, and visual elements.

[0373] "Analysis" refers to the process of verifying the content of digital information and extracting specific patterns or features.

[0374] "Communication style" refers to the unique patterns and tendencies in language and expression used by a particular person.

[0375] "Emotional state" refers to the type and intensity of emotions judged from the user's voice and text.

[0376] "Response" refers to the reply or reaction that the system gives in response to input from the user.

[0377] "Content" refers to visual or auditory elements provided to users, such as images, music, and text.

[0378] "Function" refers to the ability or mechanism that a system possesses in order to perform a specific task or operation.

[0379] The system for realizing this invention consists of a platform including terminals, servers, and an emotion engine. Details are described below.

[0380] The terminal is responsible for collecting digital information from the user. This information includes voice instructions and text. The terminal converts this data into a predetermined format, encrypts it, and then sends it to the server. Devices such as smartphones and tablets are used in this process.

[0381] The server first analyzes the received digital information. This analysis uses the Python programming language and machine learning libraries such as TensorFlow. The server analyzes speech and text data and learns specific communication styles. The server also uses the Google Cloud Speech-to-Text API to transcribe speech into text in real time and uses an emotion engine to determine the user's emotional state.

[0382] The emotion engine classifies emotions based on the user's speech content and tone. For example, if a user says, "I'm so stressed today," the system recognizes that emotion as "stress" and recommends content appropriate to that state, such as relaxing music.

[0383] Ultimately, the server uses a recommendation model built with Scikit-learn to select the most relevant content based on the user's emotional state. The selected content is stored on AWS S3 and delivered to the user via streaming. Through this entire process, users receive personalized content that matches their emotional state.

[0384] For example, if a user expresses fatigue, the system analyzes that emotion and uses prompts to a generative AI model, such as "Please provide content that will help the user relax," to recommend appropriate streaming content.

[0385] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0386] Step 1:

[0387] The terminal collects voice and text data from the user as input. The terminal converts this data into a predetermined format and securely transmits it to the server using AES encryption. The input is raw voice and text data, and the output is encrypted data received by the server.

[0388] Step 2:

[0389] The server decrypts the received encrypted digital data and analyzes it using a Python-based program. Specifically, it extracts communication styles from text data using a natural language processing library. The input is encrypted data, and the output is the analyzed communication style.

[0390] Step 3:

[0391] The server uses the Google Cloud Speech-to-Text API to convert speech data into text in real time. This converts speech instructions into text, making it easier for the emotion engine to determine the emotional state. The input is speech data, and the output is text data.

[0392] Step 4:

[0393] The server's emotion engine classifies the user's emotional state based on text data. It uses a generative AI model to determine the emotion and outputs the result. The input is text data, and the output is the determined emotional state.

[0394] Step 5:

[0395] The server uses a recommendation model built with Scikit-learn to select appropriate content based on the determined emotional state. For example, if the user's emotional state is determined to be "relaxed," it will recommend music suitable for relaxation. The input is the emotional state, and the output is a list of selected content.

[0396] Step 6:

[0397] To stream content selected by the user, the server utilizes content data stored in AWS S3. This allows users to instantly enjoy content that matches their mood. The input is a list of content, and the output is the streamed content.

[0398] 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.

[0399] 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.

[0400] 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.

[0401] [Third Embodiment]

[0402] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0403] 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.

[0404] 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).

[0405] 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.

[0406] 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.

[0407] 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).

[0408] 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.

[0409] 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.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] 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".

[0414] The information processing system of the present invention utilizes digital information about a deceased person to enable dialogue with a specific person and the retrieval of memories. The following describes the configuration for implementing this system.

[0415] Users first upload various digital information about the deceased, such as photos, videos, and social media posts, to the system using their own devices. The device then formats this digital information appropriately and securely sends it to the server. On the server side, the received digital information is categorized and securely stored in a database.

[0416] The server analyzes the uploaded digital information. It utilizes natural language processing (NLP) and image recognition technologies to extract the characteristics and visual elements of the deceased person's conversations. This information is used as input data for machine learning algorithms, learning the communication style of specific individuals. Through this learning process, the server acquires the ability to generate natural-sounding responses.

[0417] When a user wishes to communicate with a deceased loved one again, they initiate a conversation session with the Memory Bot through their device. The user's statements are sent from the device to the server, which then creates a response and sends it back to the user. For example, if the user talks to the deceased about everyday events, the server generates a response tailored to the deceased's characteristics and provides it to the user through the device.

[0418] Furthermore, the server also has the ability to recreate specific memories specified by the user. Upon user request, it can combine relevant photos and videos to generate slideshows or videos that visually recreate specific events. The server then delivers these to the user's device, allowing them to visually enjoy memories of the deceased, accompanied by music and voice narration.

[0419] In this way, the present invention can provide emotional support to users based on a wealth of digital information about the deceased.

[0420] The following describes the processing flow.

[0421] Step 1:

[0422] The user operates the device to select digital information such as photos, videos, and social media posts of the deceased, and provides it to the system through the upload panel. The device converts this data into the specified format and transfers it to the server using a secure channel.

[0423] Step 2:

[0424] The server receives the transmitted digital information and stores it in a database. During this process, it records the data type, metadata, upload date and time, and classifies each piece of data.

[0425] Step 3:

[0426] The server analyzes the classified digital information. It uses natural language processing to extract themes and emotions from text data and image recognition technology to identify features from photos and videos. This information is fed into a learning model, which serves as foundational data for acquiring the deceased person's communication style.

[0427] Step 4:

[0428] The user initiates interaction with MemoryBot through an interface on their device. User speech and text input are sent from the device to the server.

[0429] Step 5:

[0430] The server receives user input and generates the most appropriate response based on pre-trained data. The generated response is then processed by a natural language processor to make it sound natural to the user.

[0431] Step 6:

[0432] The generated response is returned to the terminal and, if voice output is requested, is converted into speech using speech synthesis technology. The terminal then displays or plays this response to the user.

[0433] Step 7:

[0434] When a user wants to recreate a specific past memory, they send a request to the server through their device. The server searches for relevant digital information and generates a slideshow or video combining photos and videos.

[0435] Step 8:

[0436] The generated slideshows and videos are sent to the device, allowing the user to relive the memories through sight and sound. The device displays and allows the user to experience them.

[0437] (Example 1)

[0438] 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."

[0439] In modern times, there is a growing need for systems that utilize digital information to recreate personalized conversations and memories in order to maintain an emotional connection with the deceased. However, conventional technologies struggle to generate natural responses that accurately reflect the deceased's communication style or to recreate visually rich memories. As a result, users face the challenge of not receiving adequate emotional support.

[0440] 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.

[0441] In this invention, the server includes means for transmitting digital information via a device that accepts user input, means for processing the transmitted digital information and learning the dialogue characteristics of a specific subject, and means for creating a response based on the learned dialogue characteristics. This enables the generation of natural responses that reflect the deceased person's communication style and the visual reconstruction of memories by combining relevant information.

[0442] A "user" refers to an individual who uses the system to upload digital information and engage in dialogue or relive memories.

[0443] "Digital information" refers to information in electronically stored and manipulateable formats, such as visual data, audio data, and descriptive data.

[0444] "Device" refers to equipment used for transmitting, receiving, and playing back digital information. Examples include computers and smartphones.

[0445] A "server" refers to a central control system that processes received digital information, generates responses, and retrieves stored data.

[0446] "Dialogue characteristics" refer to characteristics related to the communication style and language patterns of a particular subject.

[0447] "Answer" refers to the dialogue content generated based on the user's input.

[0448] "Video data" refers to data in the form of videos or slideshows used to convey visual information.

[0449] "Reconstruction" refers to the process of visually or audibly reconstructing past events or conversations based on digital information.

[0450] The information processing system based on this invention is designed to provide users with an emotional connection through digital information about the deceased. This system uses terminals such as computers and smartphones as hardware, and a central server. The software includes programs that implement natural language processing and image recognition technologies.

[0451] Users upload digital information such as photos, videos, and text data related to the deceased from their devices to the system. The device formats the digital information into an appropriate format and sends it to the server using a secure protocol. HTTPS is used as an example.

[0452] The server analyzes the received digital information. Specifically, it uses natural language processing models to analyze text data and extract the deceased's conversational characteristics. It also uses image recognition technology to identify visual elements from photos and videos. This data is used as training data for a generative AI model, which learns the deceased's unique communication style and generates natural-sounding responses based on the results.

[0453] When a user wishes to communicate with a deceased person, the conversation begins by sending a prompt message to the server via the device. For example, by sending the prompt message "How was your day today?", a response reflecting the deceased person's communication style is generated and provided to the user via the device.

[0454] Furthermore, if a user wants to recreate a specific memory, the server generates a slideshow or video based on the digital information and delivers it to the device. For example, by sending a prompt such as "Collect photos of cherry blossom viewing in spring and create a slideshow," video data combining related photos and audio will be generated.

[0455] In this way, this system can provide users with an emotional connection to the deceased and visually recreate rich memories.

[0456] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0457] Step 1:

[0458] Users upload photos, videos, and text data of the deceased to the system from their devices. The format of the input digital information is standardized across all devices. This process includes image format conversion and text data structuring. After conversion, the digital information is sent to the server using secure means such as HTTPS.

[0459] Step 2:

[0460] The server classifies the received digital information and securely stores it in a database. The input information is categorized as visual data, audio data, and text data. Database registration includes metadata generation and encryption. This enables the server to efficiently search and retrieve data.

[0461] Step 3:

[0462] The server uses natural language processing (NLP) techniques to analyze text data and extract the deceased person's conversational characteristics. Noun phrases are extracted and sentiment analysis is performed on the input text data. This reveals characteristics related to communication style, which are then used to train generative AI models.

[0463] Step 4:

[0464] The server analyzes visual data using image recognition technology and extracts important visual elements. The input visual data is processed through object detection and face recognition algorithms. This structures the visual elements, which are then used to aid in memory recall and response generation.

[0465] Step 5:

[0466] The generative AI model generates natural responses to user statements based on the deceased person's conversational characteristics. When a user sends a prompt using their device, it becomes the model's input. For example, if the prompt "How was your day?" is entered, the server generates a response that reflects the deceased person's style and sends the result to the device.

[0467] Step 6:

[0468] The server generates slideshows and videos that recreate specific memories by combining digital information in response to user requests. Input requests include specifying keywords and photos related to the particular memory. The server retrieves relevant data from a database and generates video data to visually recreate the memory. This output is provided to the user via their device and becomes viewable.

[0469] (Application Example 1)

[0470] 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."

[0471] In modern society, there is a growing need to preserve memories and personalities of deceased individuals through digital information, but there is a lack of methods to utilize this information to provide direct and emotional experiences. Furthermore, there are challenges in conducting virtual reality-based conversations with deceased loved ones or recreating memories in real-world spaces. In this context, there is a need to provide users with more immersive and emotionally engaging experiences.

[0472] 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.

[0473] In this invention, the server includes functions for providing digital data, analyzing the provided digital data and learning the communication style of a specific subject, generating responses based on the learned communication style, presenting the generated responses to the user, and visually recreating a specific memory using a device for the user to experience virtual reality in a real space. This enables the user to have a virtual conversation with the deceased and experience a realistic recreation of memories.

[0474] "Digital data" refers to all information stored in electronic format, including visual, auditory, and textual information.

[0475] "Analysis" is the process of processing information stored in electronic format and extracting meaning and patterns.

[0476] "Communication style" refers to the unique linguistic and behavioral patterns that a particular individual exhibits in dialogue.

[0477] The "function to generate responses" refers to the ability to create appropriate responses based on analyzed data and provide them to the user.

[0478] "Devices for experiencing virtual reality in real space" refer to equipment used by users to experience virtual visual and auditory elements in a real-world environment.

[0479] "Visual reproduction" refers to the process of visually representing past events or memories using photographs and videos.

[0480] This system is an information processing platform that utilizes digital data about the deceased to provide users with an emotional experience. First, users provide the system with digital data such as images, audio, and text information about the deceased using a digital device. The provided digital data is securely transferred to the server via the terminal.

[0481] The server features high-performance processors and ample storage as hardware, and utilizes natural language processing libraries (e.g., spaCy and BERT) and machine learning platforms (e.g., TensorFlow, PyTorch) as software. This server analyzes the provided digital data and extracts and learns specific communication patterns. In this process, it identifies the meaning and usage patterns of the data, which are then used to generate the necessary content.

[0482] The generated information is presented as a response on the user's digital device. Furthermore, by wearing devices that enable virtual reality experiences in the real world (e.g., smart glasses or VR headsets), users can visually recreate specific memories. This recreation process generates the visual and acoustic elements of the space the user experiences, allowing them to relive past memories or conversations with deceased loved ones in a virtual environment.

[0483] For example, if a user says, "Today I went to a park that the deceased loved," the system will generate a response such as, "Would you like to see a photo album to help us remember that day?" based on past photos and the user's memory data.

[0484] Examples of prompts to input into a generative AI model:

[0485] "I'd like to talk about the deceased person's favorite foods."

[0486] "Please create a video that evokes memories of old family trips."

[0487] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0488] Step 1:

[0489] The user uses a terminal to input images, audio, and text information related to the deceased. The terminal converts this digital data into the appropriate format and sends it to the server. At this point, the input is the user's digital data, and the output is formatted data.

[0490] Step 2:

[0491] The server analyzes the received digital data. Using image processing algorithms and natural language processing techniques, it detects specific patterns and features within the data. This analysis extracts information for learning the deceased person's communication style. The input is the digital data received from the terminal, and the output is the extracted feature data.

[0492] Step 3:

[0493] The server learns based on the feature data obtained from the analysis. Using a machine learning model, it generates a model to mimic the deceased person's communication style. This process establishes the foundation for generating natural responses. The input is feature data, and the output is the learned communication model.

[0494] Step 4:

[0495] The user inputs the content they wish to communicate with the deceased via a terminal. The server generates an appropriate response to the user's input based on a trained model. The input is the content the user wishes to communicate, and the output is the generated response.

[0496] Step 5:

[0497] The generated response is presented to the user via the terminal. Furthermore, if the user so desires, a reproduction system is activated to provide a virtual reality experience in the real world. The input is the generated response, and the output is the presentation of the response to the user and the provision of the VR experience.

[0498] Step 6:

[0499] When a user begins a virtual reality experience, the server sends data to the VR device to visually recreate a specific memory. This allows the user to enjoy a unique and immersive experience. The input is the VR experience request from the user, and the output is the visual recreation experience on the VR device.

[0500] 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.

[0501] This invention relates to an information processing system that recognizes a user's emotional state and enables the provision of appropriate responses and content. This system is characterized by incorporating an emotion engine that determines emotions based on the user's voice and text data and adjusts the response accordingly.

[0502] Users upload digital information about the deceased through their device. The device converts the digital information into a predetermined format, encrypts it, and then sends it to the server. The server stores the received information, classifies it, and stores it in a database.

[0503] The server analyzes this digital information and learns the deceased's communication style through machine learning. This process involves natural language processing and image recognition technologies to extract the deceased's characteristics and language patterns.

[0504] Furthermore, the server incorporates an emotion engine that identifies emotions from the user's voice and text input. For example, if a user speaks in a sad tone, the server recognizes that emotion as "sadness" and adjusts its responses and content to suit that emotional state. Specifically, if a user says, "Today was a tough day," the server can generate a gentle response and present content that includes comfort and encouragement.

[0505] When a user wishes to recreate memories of a deceased loved one, they send a request to the server via their device. The server retrieves relevant images and videos, adds appropriate music and narration, and generates visual content. This generated content is streamed to the user, helping them relive memories and evoke emotions.

[0506] According to embodiments of the present invention, users can go beyond simply viewing digital data and receive personalized responses that respond to their emotions, thereby gaining a richer experience.

[0507] The following describes the processing flow.

[0508] Step 1:

[0509] The user selects digital information such as photos, videos, and text data of the deceased using a device and sends it through the system's upload interface. The device organizes this selected data according to a specified format and uploads it to the server using a secure protocol.

[0510] Step 2:

[0511] The server stores the received digital information for analysis and categorizes it by type. The stored data is then placed in a database, and identifiable metadata is added for use in subsequent analysis processes.

[0512] Step 3:

[0513] The server analyzes uploaded digital information using natural language processing and image recognition algorithms. In this analysis process, the deceased's communication style and tone of voice are extracted from text data, and visual features are identified from images and videos.

[0514] Step 4:

[0515] The server runs an emotion engine that identifies emotions in real time from user input. What the user says to the terminal and the text they type are sent to the server, where they are analyzed to detect emotions from the voice and text.

[0516] Step 5:

[0517] Based on the user's emotional state, the server generates an appropriate response, taking into account the deceased person's communication style. For example, if the server determines that the user is sad, it will generate a comforting response and return it to the terminal.

[0518] Step 6:

[0519] The generated response is sent to the terminal and either displayed to the user or played back as audio. The terminal presents the response in the format best suited to the user's device, providing the user with a natural and engaging conversation.

[0520] Step 7:

[0521] When a user wants to recreate a specific memory, they request this from the server via their device. The server collects the relevant digital data and generates a slideshow or video, including music and narration. This generated content may also be adjusted according to the user's current emotions.

[0522] Step 8:

[0523] The generated memory content is streamed to the device and delivered to the user. Through this, the user can visually and aurally relive memories of the deceased. The device supports content playback, allowing the user to relive memories in a comfortable way.

[0524] (Example 2)

[0525] 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."

[0526] In today's information society, much digital information is linked to individuals' memories and emotions, but simply treating it as data does not provide a rich experience. In particular, there is a need to utilize digital information about deceased individuals to provide users with an emotionally resonant experience.

[0527] 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.

[0528] In this invention, the server includes means for receiving digital information as input, means for processing the received digital information and analyzing the conversational style of a specific individual, means for constructing a response based on the analysis results, means for identifying the emotional state of the user, means for generating content adjusted based on the emotional state, and means for delivering the generated content to the user. This makes it possible to provide a rich experience that is attentive to the user's emotions while being based on individual memories and the characteristics of the deceased.

[0529] "Digital information" refers to electronically stored information, including visual data, audio data, and text data.

[0530] A "device that accepts input" is a device that receives digital information from users and prepares it for processing.

[0531] A "processing device" is a device used to analyze input digital information and to analyze the conversational style of a specific individual.

[0532] A "device that constructs responses based on analysis results" is a device that has the function of generating appropriate responses according to the analyzed individual's dialogue style.

[0533] A "device for identifying emotional states" is a device that has the function of determining emotions from the user's voice or text data and identifying that state.

[0534] A "device that generates adjusted content" is a device that has the function of customizing and generating content to be provided according to the identified emotional state.

[0535] A "distribution device" is a device that provides generated content to users, enabling an emotionally engaging experience.

[0536] The information processing system of the present invention aims to provide responses and content based on the user's emotional state. Specific embodiments of this system are described below.

[0537] Users input digital information related to the deceased via their device and upload it. During this process, the device converts the digital information into a specified format and securely transmits it to the server using encryption technology (e.g., SSL / TLS). Common electronic devices such as computers and smartphones can be used as devices.

[0538] The server stores the received digital information in a database and classifies and organizes the data. Relational database management systems (RDBMS) such as MySQL or PostgreSQL may be used for this database management. The server analyzes the digital information using libraries such as Python's TensorFlow to learn the language patterns and communication styles of specific individuals.

[0539] Furthermore, the server incorporates an emotion engine that analyzes user voice and text input to identify emotions. This process utilizes natural language processing libraries such as NLTK and huggingface. Based on the user's emotions, the server uses generative AI models such as OpenAI's GPT to generate appropriate responses and content.

[0540] When generating content, media editing software such as Adobe Premiere can be used to combine related images and videos, and to add music and narration. The generated content is then streamed by the device and delivered to the user.

[0541] For example, if a user enters the text "I'm sad today because I'm remembering someone who passed away," the server will recognize that emotion and deliver a gentle response along with calming music accompanied by photos or videos related to the deceased. An example of the prompt in this case would be, "I'd like to see a video of happy summer memories with the deceased."

[0542] In this way, the information processing system of the present invention enables the provision of user experiences that are emotionally resonant.

[0543] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0544] Step 1:

[0545] Users input and upload photos and text data related to the deceased person into their device. Because this input data may have different formats and sizes, the device converts the digital information into a unified format (e.g., JPEG image, text file format). Then, it prepares the data for secure transmission to the server using encryption technologies such as SSL / TLS.

[0546] Step 2:

[0547] The server decrypts the encrypted data received from the terminal and stores it in a database. The input digital information is categorized based on metadata (e.g., date, location, related person's name). This organizes the data to enable quick searching and access. SQL queries can be used for this process.

[0548] Step 3:

[0549] The server analyzes information stored in the database and learns the communication style of a specific individual. This process utilizes natural language processing and image recognition technologies, such as Python's TensorFlow. Text and image data of the deceased are provided as input, and a model representing the deceased's language patterns and behavioral characteristics is generated as output.

[0550] Step 4:

[0551] The user inputs emotion-related text or audio into the terminal. The server activates an emotion engine to identify the user's emotion. This involves using libraries such as NLTK or huggingface to analyze the input data. The output will be an identified emotional state, such as sadness or joy.

[0552] Step 5:

[0553] The server generates responses based on the identified user's emotional state. Here, a generative AI model is used to generate appropriate responses and content based on the prompt. For example, in response to the prompt "I'm sad today because I'm remembering someone who has passed away," it generates a gentle, comforting response and incorporates relevant content. The generated data is output as HTML or audio files.

[0554] Step 6:

[0555] Upon user request, the server retrieves relevant images and videos from the database and creates visual content using software such as Adobe Premiere. Music and narration are added to visualize memories of the deceased. This generated content is then streamed to the user via their device.

[0556] (Application Example 2)

[0557] 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."

[0558] In modern society, the uniformity of content provided by information processing systems makes it difficult to respond appropriately to users' emotional states and provide relevant content. Furthermore, there is a lack of support for users to easily select content that matches their current emotional state. Therefore, there is a need to realize highly personalized content delivery methods that respond to users' emotions.

[0559] 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.

[0560] In this invention, the server includes a function for uploading digital information, a function for analyzing the uploaded digital information and learning the communication style of a specific person, and a function for determining emotional states and adjusting responses based on those emotions. This makes it possible to provide personalized content that matches the diverse emotions of users.

[0561] "Digital information" refers to all information expressed in electronic format, including audio, text, and visual elements.

[0562] "Analysis" refers to the process of verifying the content of digital information and extracting specific patterns or features.

[0563] "Communication style" refers to the unique patterns and tendencies in language and expression used by a particular person.

[0564] "Emotional state" refers to the type and intensity of emotions judged from the user's voice and text.

[0565] "Response" refers to the reply or reaction that the system gives in response to input from the user.

[0566] "Content" refers to visual or auditory elements provided to users, such as images, music, and text.

[0567] "Function" refers to the ability or mechanism that a system possesses in order to perform a specific task or operation.

[0568] The system for realizing this invention consists of a platform including terminals, servers, and an emotion engine. Details are described below.

[0569] The terminal is responsible for collecting digital information from the user. This information includes voice instructions and text. The terminal converts this data into a predetermined format, encrypts it, and then sends it to the server. Devices such as smartphones and tablets are used in this process.

[0570] The server first analyzes the received digital information. This analysis uses the Python programming language and machine learning libraries such as TensorFlow. The server analyzes speech and text data and learns specific communication styles. The server also uses the Google Cloud Speech-to-Text API to transcribe speech into text in real time and uses an emotion engine to determine the user's emotional state.

[0571] The emotion engine classifies emotions based on the user's speech content and tone. For example, if a user says, "I'm so stressed today," the system recognizes that emotion as "stress" and recommends content appropriate to that state, such as relaxing music.

[0572] Ultimately, the server uses a recommendation model built with Scikit-learn to select the most relevant content based on the user's emotional state. The selected content is stored on AWS S3 and delivered to the user via streaming. Through this entire process, users receive personalized content that matches their emotional state.

[0573] For example, if a user expresses fatigue, the system analyzes that emotion and uses prompts to a generative AI model, such as "Please provide content that will help the user relax," to recommend appropriate streaming content.

[0574] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0575] Step 1:

[0576] The terminal collects voice and text data from the user as input. The terminal converts this data into a predetermined format and securely transmits it to the server using AES encryption. The input is raw voice and text data, and the output is encrypted data received by the server.

[0577] Step 2:

[0578] The server decrypts the received encrypted digital data and analyzes it using a Python-based program. Specifically, it extracts communication styles from text data using a natural language processing library. The input is encrypted data, and the output is the analyzed communication style.

[0579] Step 3:

[0580] The server uses the Google Cloud Speech-to-Text API to convert speech data into text in real time. This converts speech instructions into text, making it easier for the emotion engine to determine the emotional state. The input is speech data, and the output is text data.

[0581] Step 4:

[0582] The server's emotion engine classifies the user's emotional state based on text data. It uses a generative AI model to determine the emotion and outputs the result. The input is text data, and the output is the determined emotional state.

[0583] Step 5:

[0584] The server uses a recommendation model built with Scikit-learn to select appropriate content based on the determined emotional state. For example, if the user's emotional state is determined to be "relaxed," it will recommend music suitable for relaxation. The input is the emotional state, and the output is a list of selected content.

[0585] Step 6:

[0586] To stream content selected by the user, the server utilizes content data stored in AWS S3. This allows users to instantly enjoy content that matches their mood. The input is a list of content, and the output is the streamed content.

[0587] 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.

[0588] 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.

[0589] 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.

[0590] [Fourth Embodiment]

[0591] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0592] 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.

[0593] 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).

[0594] 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.

[0595] 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.

[0596] 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).

[0597] 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.

[0598] 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.

[0599] 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.

[0600] 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.

[0601] 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.

[0602] 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.

[0603] 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".

[0604] The information processing system of the present invention utilizes digital information about a deceased person to enable dialogue with a specific person and the retrieval of memories. The following describes the configuration for implementing this system.

[0605] Users first upload various digital information about the deceased, such as photos, videos, and social media posts, to the system using their own devices. The device then formats this digital information appropriately and securely sends it to the server. On the server side, the received digital information is categorized and securely stored in a database.

[0606] The server analyzes the uploaded digital information. It utilizes natural language processing (NLP) and image recognition technologies to extract the characteristics and visual elements of the deceased person's conversations. This information is used as input data for machine learning algorithms, learning the communication style of specific individuals. Through this learning process, the server acquires the ability to generate natural-sounding responses.

[0607] When a user wishes to communicate with a deceased loved one again, they initiate a conversation session with the Memory Bot through their device. The user's statements are sent from the device to the server, which then creates a response and sends it back to the user. For example, if the user talks to the deceased about everyday events, the server generates a response tailored to the deceased's characteristics and provides it to the user through the device.

[0608] Furthermore, the server also has the ability to recreate specific memories specified by the user. Upon user request, it can combine relevant photos and videos to generate slideshows or videos that visually recreate specific events. The server then delivers these to the user's device, allowing them to visually enjoy memories of the deceased, accompanied by music and voice narration.

[0609] In this way, the present invention can provide emotional support to users based on a wealth of digital information about the deceased.

[0610] The following describes the processing flow.

[0611] Step 1:

[0612] The user operates the device to select digital information such as photos, videos, and social media posts of the deceased, and provides it to the system through the upload panel. The device converts this data into the specified format and transfers it to the server using a secure channel.

[0613] Step 2:

[0614] The server receives the transmitted digital information and stores it in a database. During this process, it records the data type, metadata, upload date and time, and classifies each piece of data.

[0615] Step 3:

[0616] The server analyzes the classified digital information. It uses natural language processing to extract themes and emotions from text data and image recognition technology to identify features from photos and videos. This information is fed into a learning model, which serves as foundational data for acquiring the deceased person's communication style.

[0617] Step 4:

[0618] The user initiates interaction with MemoryBot through an interface on their device. User speech and text input are sent from the device to the server.

[0619] Step 5:

[0620] The server receives user input and generates the most appropriate response based on pre-trained data. The generated response is then processed by a natural language processor to make it sound natural to the user.

[0621] Step 6:

[0622] The generated response is returned to the terminal and, if voice output is requested, is converted into speech using speech synthesis technology. The terminal then displays or plays this response to the user.

[0623] Step 7:

[0624] When a user wants to recreate a specific past memory, they send a request to the server through their device. The server searches for relevant digital information and generates a slideshow or video combining photos and videos.

[0625] Step 8:

[0626] The generated slideshows and videos are sent to the device, allowing the user to relive the memories through sight and sound. The device displays and allows the user to experience them.

[0627] (Example 1)

[0628] 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".

[0629] In modern times, there is a growing need for systems that utilize digital information to recreate personalized conversations and memories in order to maintain an emotional connection with the deceased. However, conventional technologies struggle to generate natural responses that accurately reflect the deceased's communication style or to recreate visually rich memories. As a result, users face the challenge of not receiving adequate emotional support.

[0630] 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.

[0631] In this invention, the server includes means for transmitting digital information via a device that accepts user input, means for processing the transmitted digital information and learning the dialogue characteristics of a specific subject, and means for creating a response based on the learned dialogue characteristics. This enables the generation of natural responses that reflect the deceased person's communication style and the visual reconstruction of memories by combining relevant information.

[0632] A "user" refers to an individual who uses the system to upload digital information and engage in dialogue or relive memories.

[0633] "Digital information" refers to information in electronically stored and manipulateable formats, such as visual data, audio data, and descriptive data.

[0634] "Device" refers to equipment used for transmitting, receiving, and playing back digital information. Examples include computers and smartphones.

[0635] A "server" refers to a central control system that processes received digital information, generates responses, and retrieves stored data.

[0636] "Dialogue characteristics" refer to characteristics related to the communication style and language patterns of a particular subject.

[0637] "Answer" refers to the dialogue content generated based on the user's input.

[0638] "Video data" refers to data in the form of videos or slideshows used to convey visual information.

[0639] "Reconstruction" refers to the process of visually or audibly reconstructing past events or conversations based on digital information.

[0640] The information processing system based on this invention is designed to provide users with an emotional connection through digital information about the deceased. This system uses terminals such as computers and smartphones as hardware, and a central server. The software includes programs that implement natural language processing and image recognition technologies.

[0641] Users upload digital information such as photos, videos, and text data related to the deceased from their devices to the system. The device formats the digital information into an appropriate format and sends it to the server using a secure protocol. HTTPS is used as an example.

[0642] The server analyzes the received digital information. Specifically, it uses natural language processing models to analyze text data and extract the deceased's conversational characteristics. It also uses image recognition technology to identify visual elements from photos and videos. This data is used as training data for a generative AI model, which learns the deceased's unique communication style and generates natural-sounding responses based on the results.

[0643] When a user wishes to communicate with a deceased person, the conversation begins by sending a prompt message to the server via the device. For example, by sending the prompt message "How was your day today?", a response reflecting the deceased person's communication style is generated and provided to the user via the device.

[0644] Furthermore, if a user wants to recreate a specific memory, the server generates a slideshow or video based on the digital information and delivers it to the device. For example, by sending a prompt such as "Collect photos of cherry blossom viewing in spring and create a slideshow," video data combining related photos and audio will be generated.

[0645] In this way, this system can provide users with an emotional connection to the deceased and visually recreate rich memories.

[0646] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0647] Step 1:

[0648] Users upload photos, videos, and text data of the deceased to the system from their devices. The format of the input digital information is standardized across all devices. This process includes image format conversion and text data structuring. After conversion, the digital information is sent to the server using secure means such as HTTPS.

[0649] Step 2:

[0650] The server classifies the received digital information and securely stores it in a database. The input information is categorized as visual data, audio data, and text data. Database registration includes metadata generation and encryption. This enables the server to efficiently search and retrieve data.

[0651] Step 3:

[0652] The server uses natural language processing (NLP) techniques to analyze text data and extract the deceased person's conversational characteristics. Noun phrases are extracted and sentiment analysis is performed on the input text data. This reveals characteristics related to communication style, which are then used to train generative AI models.

[0653] Step 4:

[0654] The server analyzes visual data using image recognition technology and extracts important visual elements. The input visual data is processed through object detection and face recognition algorithms. This structures the visual elements, which are then used to aid in memory recall and response generation.

[0655] Step 5:

[0656] The generative AI model generates natural responses to user statements based on the deceased person's conversational characteristics. When a user sends a prompt using their device, it becomes the model's input. For example, if the prompt "How was your day?" is entered, the server generates a response that reflects the deceased person's style and sends the result to the device.

[0657] Step 6:

[0658] The server generates slideshows and videos that recreate specific memories by combining digital information in response to user requests. Input requests include specifying keywords and photos related to the particular memory. The server retrieves relevant data from a database and generates video data to visually recreate the memory. This output is provided to the user via their device and becomes viewable.

[0659] (Application Example 1)

[0660] 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".

[0661] In modern society, there is a growing need to preserve memories and personalities of deceased individuals through digital information, but there is a lack of methods to utilize this information to provide direct and emotional experiences. Furthermore, there are challenges in conducting virtual reality-based conversations with deceased loved ones or recreating memories in real-world spaces. In this context, there is a need to provide users with more immersive and emotionally engaging experiences.

[0662] 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.

[0663] In this invention, the server includes functions for providing digital data, analyzing the provided digital data and learning the communication style of a specific subject, generating responses based on the learned communication style, presenting the generated responses to the user, and visually recreating a specific memory using a device for the user to experience virtual reality in a real space. This enables the user to have a virtual conversation with the deceased and experience a realistic recreation of memories.

[0664] "Digital data" refers to all information stored in electronic format, including visual, auditory, and textual information.

[0665] "Analysis" is the process of processing information stored in electronic format and extracting meaning and patterns.

[0666] "Communication style" refers to the unique linguistic and behavioral patterns that a particular individual exhibits in dialogue.

[0667] The "function to generate responses" refers to the ability to create appropriate responses based on analyzed data and provide them to the user.

[0668] "Devices for experiencing virtual reality in real space" refer to equipment used by users to experience virtual visual and auditory elements in a real-world environment.

[0669] "Visual reproduction" refers to the process of visually representing past events or memories using photographs and videos.

[0670] This system is an information processing platform that utilizes digital data about the deceased to provide users with an emotional experience. First, users provide the system with digital data such as images, audio, and text information about the deceased using a digital device. The provided digital data is securely transferred to the server via the terminal.

[0671] The server features high-performance processors and ample storage as hardware, and utilizes natural language processing libraries (e.g., spaCy and BERT) and machine learning platforms (e.g., TensorFlow, PyTorch) as software. This server analyzes the provided digital data and extracts and learns specific communication patterns. In this process, it identifies the meaning and usage patterns of the data, which are then used to generate the necessary content.

[0672] The generated information is presented as a response on the user's digital device. Furthermore, by wearing devices that enable virtual reality experiences in the real world (e.g., smart glasses or VR headsets), users can visually recreate specific memories. This recreation process generates the visual and acoustic elements of the space the user experiences, allowing them to relive past memories or conversations with deceased loved ones in a virtual environment.

[0673] For example, if a user says, "Today I went to a park that the deceased loved," the system will generate a response such as, "Would you like to see a photo album to help us remember that day?" based on past photos and the user's memory data.

[0674] Examples of prompts to input into a generative AI model:

[0675] "I'd like to talk about the deceased person's favorite foods."

[0676] "Please create a video that evokes memories of old family trips."

[0677] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0678] Step 1:

[0679] The user uses a terminal to input images, audio, and text information related to the deceased. The terminal converts this digital data into the appropriate format and sends it to the server. At this point, the input is the user's digital data, and the output is formatted data.

[0680] Step 2:

[0681] The server analyzes the received digital data. Using image processing algorithms and natural language processing techniques, it detects specific patterns and features within the data. This analysis extracts information for learning the deceased person's communication style. The input is the digital data received from the terminal, and the output is the extracted feature data.

[0682] Step 3:

[0683] The server learns based on the feature data obtained from the analysis. Using a machine learning model, it generates a model to mimic the deceased person's communication style. This process establishes the foundation for generating natural responses. The input is feature data, and the output is the learned communication model.

[0684] Step 4:

[0685] The user inputs the content they wish to communicate with the deceased via a terminal. The server generates an appropriate response to the user's input based on a trained model. The input is the content the user wishes to communicate, and the output is the generated response.

[0686] Step 5:

[0687] The generated response is presented to the user via the terminal. Furthermore, if the user so desires, a reproduction system is activated to provide a virtual reality experience in the real world. The input is the generated response, and the output is the presentation of the response to the user and the provision of the VR experience.

[0688] Step 6:

[0689] When a user begins a virtual reality experience, the server sends data to the VR device to visually recreate a specific memory. This allows the user to enjoy a unique and immersive experience. The input is the VR experience request from the user, and the output is the visual recreation experience on the VR device.

[0690] 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.

[0691] This invention relates to an information processing system that recognizes a user's emotional state and enables the provision of appropriate responses and content. This system is characterized by incorporating an emotion engine that determines emotions based on the user's voice and text data and adjusts the response accordingly.

[0692] Users upload digital information about the deceased through their device. The device converts the digital information into a predetermined format, encrypts it, and then sends it to the server. The server stores the received information, classifies it, and stores it in a database.

[0693] The server analyzes this digital information and learns the deceased's communication style through machine learning. This process involves natural language processing and image recognition technologies to extract the deceased's characteristics and language patterns.

[0694] Furthermore, the server incorporates an emotion engine that identifies emotions from the user's voice and text input. For example, if a user speaks in a sad tone, the server recognizes that emotion as "sadness" and adjusts its responses and content to suit that emotional state. Specifically, if a user says, "Today was a tough day," the server can generate a gentle response and present content that includes comfort and encouragement.

[0695] When a user wishes to recreate memories of a deceased loved one, they send a request to the server via their device. The server retrieves relevant images and videos, adds appropriate music and narration, and generates visual content. This generated content is streamed to the user, helping them relive memories and evoke emotions.

[0696] According to embodiments of the present invention, users can go beyond simply viewing digital data and receive personalized responses that respond to their emotions, thereby gaining a richer experience.

[0697] The following describes the processing flow.

[0698] Step 1:

[0699] The user selects digital information such as photos, videos, and text data of the deceased using a device and sends it through the system's upload interface. The device organizes this selected data according to a specified format and uploads it to the server using a secure protocol.

[0700] Step 2:

[0701] The server stores the received digital information for analysis and categorizes it by type. The stored data is then placed in a database, and identifiable metadata is added for use in subsequent analysis processes.

[0702] Step 3:

[0703] The server analyzes uploaded digital information using natural language processing and image recognition algorithms. In this analysis process, the deceased's communication style and tone of voice are extracted from text data, and visual features are identified from images and videos.

[0704] Step 4:

[0705] The server runs an emotion engine that identifies emotions in real time from user input. What the user says to the terminal and the text they type are sent to the server, where they are analyzed to detect emotions from the voice and text.

[0706] Step 5:

[0707] Based on the user's emotional state, the server generates an appropriate response, taking into account the deceased person's communication style. For example, if the server determines that the user is sad, it will generate a comforting response and return it to the terminal.

[0708] Step 6:

[0709] The generated response is sent to the terminal and either displayed to the user or played back as audio. The terminal presents the response in the format best suited to the user's device, providing the user with a natural and engaging conversation.

[0710] Step 7:

[0711] When a user wants to recreate a specific memory, they request this from the server via their device. The server collects the relevant digital data and generates a slideshow or video, including music and narration. This generated content may also be adjusted according to the user's current emotions.

[0712] Step 8:

[0713] The generated memory content is streamed to the device and delivered to the user. Through this, the user can visually and aurally relive memories of the deceased. The device supports content playback, allowing the user to relive memories in a comfortable way.

[0714] (Example 2)

[0715] 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".

[0716] In today's information society, much digital information is linked to individuals' memories and emotions, but simply treating it as data does not provide a rich experience. In particular, there is a need to utilize digital information about deceased individuals to provide users with an emotionally resonant experience.

[0717] 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.

[0718] In this invention, the server includes means for receiving digital information as input, means for processing the received digital information and analyzing the conversational style of a specific individual, means for constructing a response based on the analysis results, means for identifying the emotional state of the user, means for generating content adjusted based on the emotional state, and means for delivering the generated content to the user. This makes it possible to provide a rich experience that is attentive to the user's emotions while being based on individual memories and the characteristics of the deceased.

[0719] "Digital information" refers to electronically stored information, including visual data, audio data, and text data.

[0720] A "device that accepts input" is a device that receives digital information from users and prepares it for processing.

[0721] A "processing device" is a device used to analyze input digital information and to analyze the conversational style of a specific individual.

[0722] A "device that constructs responses based on analysis results" is a device that has the function of generating appropriate responses according to the analyzed individual's dialogue style.

[0723] A "device for identifying emotional states" is a device that has the function of determining emotions from the user's voice or text data and identifying that state.

[0724] A "device that generates adjusted content" is a device that has the function of customizing and generating content to be provided according to the identified emotional state.

[0725] A "distribution device" is a device that provides generated content to users, enabling an emotionally engaging experience.

[0726] The information processing system of the present invention aims to provide responses and content based on the user's emotional state. Specific embodiments of this system are described below.

[0727] Users input digital information related to the deceased via their device and upload it. During this process, the device converts the digital information into a specified format and securely transmits it to the server using encryption technology (e.g., SSL / TLS). Common electronic devices such as computers and smartphones can be used as devices.

[0728] The server stores the received digital information in a database and classifies and organizes the data. Relational database management systems (RDBMS) such as MySQL or PostgreSQL may be used for this database management. The server analyzes the digital information using libraries such as Python's TensorFlow to learn the language patterns and communication styles of specific individuals.

[0729] Furthermore, the server incorporates an emotion engine that analyzes user voice and text input to identify emotions. This process utilizes natural language processing libraries such as NLTK and huggingface. Based on the user's emotions, the server uses generative AI models such as OpenAI's GPT to generate appropriate responses and content.

[0730] When generating content, media editing software such as Adobe Premiere can be used to combine related images and videos, and to add music and narration. The generated content is then streamed by the device and delivered to the user.

[0731] For example, if a user enters the text "I'm sad today because I'm remembering someone who passed away," the server will recognize that emotion and deliver a gentle response along with calming music accompanied by photos or videos related to the deceased. An example of the prompt in this case would be, "I'd like to see a video of happy summer memories with the deceased."

[0732] In this way, the information processing system of the present invention enables the provision of user experiences that are emotionally resonant.

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] Users input and upload photos and text data related to the deceased person into their device. Because this input data may have different formats and sizes, the device converts the digital information into a unified format (e.g., JPEG image, text file format). Then, it prepares the data for secure transmission to the server using encryption technologies such as SSL / TLS.

[0736] Step 2:

[0737] The server decrypts the encrypted data received from the terminal and stores it in a database. The input digital information is categorized based on metadata (e.g., date, location, related person's name). This organizes the data to enable quick searching and access. SQL queries can be used for this process.

[0738] Step 3:

[0739] The server analyzes information stored in the database and learns the communication style of a specific individual. This process utilizes natural language processing and image recognition technologies, such as Python's TensorFlow. Text and image data of the deceased are provided as input, and a model representing the deceased's language patterns and behavioral characteristics is generated as output.

[0740] Step 4:

[0741] The user inputs emotion-related text or audio into the terminal. The server activates an emotion engine to identify the user's emotion. This involves using libraries such as NLTK or huggingface to analyze the input data. The output will be an identified emotional state, such as sadness or joy.

[0742] Step 5:

[0743] The server generates responses based on the identified user's emotional state. Here, a generative AI model is used to generate appropriate responses and content based on the prompt. For example, in response to the prompt "I'm sad today because I'm remembering someone who has passed away," it generates a gentle, comforting response and incorporates relevant content. The generated data is output as HTML or audio files.

[0744] Step 6:

[0745] Upon user request, the server retrieves relevant images and videos from the database and creates visual content using software such as Adobe Premiere. Music and narration are added to visualize memories of the deceased. This generated content is then streamed to the user via their device.

[0746] (Application Example 2)

[0747] 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".

[0748] In modern society, the uniformity of content provided by information processing systems makes it difficult to respond appropriately to users' emotional states and provide relevant content. Furthermore, there is a lack of support for users to easily select content that matches their current emotional state. Therefore, there is a need to realize highly personalized content delivery methods that respond to users' emotions.

[0749] 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.

[0750] In this invention, the server includes a function for uploading digital information, a function for analyzing the uploaded digital information and learning the communication style of a specific person, and a function for determining emotional states and adjusting responses based on those emotions. This makes it possible to provide personalized content that matches the diverse emotions of users.

[0751] "Digital information" refers to all information expressed in electronic format, including audio, text, and visual elements.

[0752] "Analysis" refers to the process of verifying the content of digital information and extracting specific patterns or features.

[0753] "Communication style" refers to the unique patterns and tendencies in language and expression used by a particular person.

[0754] "Emotional state" refers to the type and intensity of emotions judged from the user's voice and text.

[0755] "Response" refers to the reply or reaction that the system gives in response to input from the user.

[0756] "Content" refers to visual or auditory elements provided to users, such as images, music, and text.

[0757] "Function" refers to the ability or mechanism that a system possesses in order to perform a specific task or operation.

[0758] The system for realizing this invention consists of a platform including terminals, servers, and an emotion engine. Details are described below.

[0759] The terminal is responsible for collecting digital information from the user. This information includes voice instructions and text. The terminal converts this data into a predetermined format, encrypts it, and then sends it to the server. Devices such as smartphones and tablets are used in this process.

[0760] The server first analyzes the received digital information. This analysis uses the Python programming language and machine learning libraries such as TensorFlow. The server analyzes speech and text data and learns specific communication styles. The server also uses the Google Cloud Speech-to-Text API to transcribe speech into text in real time and uses an emotion engine to determine the user's emotional state.

[0761] The emotion engine classifies emotions based on the user's speech content and tone. For example, if a user says, "I'm so stressed today," the system recognizes that emotion as "stress" and recommends content appropriate to that state, such as relaxing music.

[0762] Ultimately, the server uses a recommendation model built with Scikit-learn to select the most relevant content based on the user's emotional state. The selected content is stored on AWS S3 and delivered to the user via streaming. Through this entire process, users receive personalized content that matches their emotional state.

[0763] For example, if a user expresses fatigue, the system analyzes that emotion and uses prompts to a generative AI model, such as "Please provide content that will help the user relax," to recommend appropriate streaming content.

[0764] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0765] Step 1:

[0766] The terminal collects voice and text data from the user as input. The terminal converts this data into a predetermined format and securely transmits it to the server using AES encryption. The input is raw voice and text data, and the output is encrypted data received by the server.

[0767] Step 2:

[0768] The server decrypts the received encrypted digital data and analyzes it using a Python-based program. Specifically, it extracts communication styles from text data using a natural language processing library. The input is encrypted data, and the output is the analyzed communication style.

[0769] Step 3:

[0770] The server uses the Google Cloud Speech-to-Text API to convert speech data into text in real time. This converts speech instructions into text, making it easier for the emotion engine to determine the emotional state. The input is speech data, and the output is text data.

[0771] Step 4:

[0772] The server's emotion engine classifies the user's emotional state based on text data. It uses a generative AI model to determine the emotion and outputs the result. The input is text data, and the output is the determined emotional state.

[0773] Step 5:

[0774] The server uses a recommendation model built with Scikit-learn to select appropriate content based on the determined emotional state. For example, if the user's emotional state is determined to be "relaxed," it will recommend music suitable for relaxation. The input is the emotional state, and the output is a list of selected content.

[0775] Step 6:

[0776] To stream content selected by the user, the server utilizes content data stored in AWS S3. This allows users to instantly enjoy content that matches their mood. The input is a list of content, and the output is the streamed content.

[0777] 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.

[0778] 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.

[0779] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0780] 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.

[0781] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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."

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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.

[0796] 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.

[0797] 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.

[0798] The following is further disclosed regarding the embodiments described above.

[0799] (Claim 1)

[0800] Means for uploading digital information,

[0801] A means for analyzing the aforementioned uploaded digital information and learning the communication style of a specific person,

[0802] A means for generating a response based on the learned communication style,

[0803] An information processing system that includes means for providing the generated response to the user.

[0804] (Claim 2)

[0805] The information processing system according to claim 1, wherein the digital information includes image, audio, and text data.

[0806] (Claim 3)

[0807] The information processing system according to claim 1, further comprising means for generating videos or slideshows to recreate specific memories in response to a user's request.

[0808] "Example 1"

[0809] (Claim 1)

[0810] A means for transmitting digital information via a device that accepts user input,

[0811] A means for processing transmitted digital information and learning the dialogue characteristics of a specific target,

[0812] A means for generating responses based on learned dialogue characteristics,

[0813] A means of presenting the generated response to the user through the device,

[0814] A system that includes means for creating video data to recreate a specific memory by combining relevant information in response to a user's request.

[0815] (Claim 2)

[0816] The system according to claim 1, wherein the digital information includes visual data, audio data, and descriptive data.

[0817] (Claim 3)

[0818] The system according to claim 1, in which a user receives a response through a dialogue session initiated after transmitting digital information.

[0819] "Application Example 1"

[0820] (Claim 1)

[0821] Functions for providing digital data,

[0822] The aforementioned digital data is analyzed and a function is acquired to learn the communication style of a specific subject.

[0823] A function that generates responses based on the acquired communication style,

[0824] A function that presents the generated response to the user,

[0825] A device that allows users to experience virtual reality in real space, with the ability to visually recreate specific memories,

[0826] A system that includes this.

[0827] (Claim 2)

[0828] The system according to claim 1, wherein the digital data includes visual data, acoustic data, and character data.

[0829] (Claim 3)

[0830] The system according to claim 1, further comprising a function to generate video content to embody a specific recollection in response to a user's request.

[0831] "Example 2 of combining an emotion engine"

[0832] (Claim 1)

[0833] A device that accepts digital information as input,

[0834] A device that processes the digital information received as input and analyzes the dialogue style of a specific individual,

[0835] A device for assembling a response based on the aforementioned analysis results,

[0836] A device for identifying the emotional state of the user,

[0837] A device that generates content adjusted based on the aforementioned emotional state,

[0838] A system including a device for distributing the generated content to users.

[0839] (Claim 2)

[0840] The system according to claim 1, wherein the digital information includes visual data, audio data, and text data.

[0841] (Claim 3)

[0842] The system according to claim 1, further comprising a device that generates audiovisual content for recreating a specific memory in response to a user's request.

[0843] "Application example 2 when combining with an emotional engine"

[0844] (Claim 1)

[0845] Features for uploading digital information,

[0846] The aforementioned function analyzes the uploaded digital information and learns the communication style of a specific person,

[0847] A function that generates a response based on the learned communication style,

[0848] The function of identifying emotional states and adjusting responses based on those emotions,

[0849] A function to provide the generated response to the user,

[0850] A system that includes a function to recommend content based on the user's emotional state.

[0851] (Claim 2)

[0852] The system according to claim 1, wherein the digital information includes visual data, audio data, and text data.

[0853] (Claim 3)

[0854] The system according to claim 1, further comprising a function to generate video or introductory content to recreate a specific memory in response to a user's request. [Explanation of Symbols]

[0855] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for uploading digital information, A means for analyzing the aforementioned uploaded digital information and learning the communication style of a specific person, A means for generating a response based on the learned communication style, An information processing system that includes means for providing the generated response to the user.

2. The information processing system according to claim 1, wherein the digital information includes image, audio, and text data.

3. The information processing system according to claim 1, further comprising means for generating videos or slideshows to recreate specific memories in response to a user's request.

Images