system

Abstract

We provide the system. [Solution] Means for collecting information about deceased persons or pets provided by users, Means for preprocessing, correcting, and extracting the information, A means for training a generative model using the preprocessed information to imitate the personality and speaking style of a deceased person or pet, A means for generating speech using a model that imitates the way of speaking, A means of creating a virtual reality environment that users can use, A means for performing interactive dialogue with a user within the virtual reality environment, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance 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] Many people deeply cherish the emotional connection with their deceased loved ones or pets, but are troubled by the sense of loss and loneliness they feel after their presence is lost. It is difficult to recover from such emotional pain and regain mental peace. The conventional methods can only look back on the memories of the deceased loved ones or pets, and there is a lack of means to interact with these existences again in an interactive way.

Means for Solving the Problems

[0005] This invention generates an AI model that mimics the personality and speaking style of a deceased person or pet, based on information provided by the user, using machine learning and speech generation technology. Furthermore, by providing a system that allows the user to have an interactive conversation with the deceased person or pet in a virtual reality environment using this AI model, it is possible to recreate an emotional connection and promote the user's emotional healing. In addition, by using natural language processing technology to extract important keywords and phrases from the information provided by the user, it provides a means to realize a more faithful and realistic conversational experience.

[0006] A "user" refers to an individual who wishes to use the system to have a virtual interaction with a deceased person or pet.

[0007] "Information" refers to digital data provided by the user, such as photos, videos, audio recordings, letters, and conversation logs related to the deceased or pet.

[0008] "Preprocessing" refers to the process of analyzing information provided by the user and performing appropriate corrections and data extraction.

[0009] A "generative model" refers to an AI model created using machine learning algorithms to mimic the personality and speech patterns of a deceased person or pet.

[0010] "Speech generation" refers to the process of generating speech that closely resembles a human voice from text data using a generative model.

[0011] A "virtual reality environment" refers to a computer-generated space that uses VR technology to allow users to experience visual and auditory interactions with deceased loved ones or pets.

[0012] "Interactive dialogue" refers to real-time, two-way communication between the user and the AI ​​model within the system.

[0013] "Natural language processing" refers to the technology of analyzing text data to understand and interpret human language.

[0014] "Environment customization" refers to the process of changing and configuring the contents of the virtual reality environment based on user specifications. [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]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the language 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] This invention provides a system that allows users to virtually interact with a deceased person or pet based on various information provided by the user. This system can be implemented as follows.

[0037] Users access the system and provide information related to deceased loved ones or pets through an interface, such as photos, videos, audio recordings, letters, and conversation logs. The server organizes the received information and performs necessary preprocessing, such as removing noise and improving image quality. This prepares the information for training an AI model.

[0038] Next, the server uses the pre-processed information to train an AI generative model that mimics the personality and conversation patterns of the deceased or their pet. This generative model uses machine learning techniques to reproduce the deceased's catchphrases, phrases, and tone of voice. Additionally, a speech generation module is used to synthesize natural-sounding speech from the text information, outputting it in a form that closely resembles the voice of the deceased or their pet.

[0039] On the device side, a virtual reality environment is built to enrich the user experience. Using VR technology, users can recreate cherished places where they spent time with deceased loved ones or pets in the same space. This virtual space can be customized according to the user's preferences.

[0040] When a user enters the VR environment, they begin an interactive conversation with a virtual deceased person or pet. The device is designed to recognize the user's voice and actions and respond using an AI model to simulate a real conversation. For example, if the user asks, "How was your day?", the deceased person or pet can naturally reply, "It was a good day."

[0041] With the above configuration, the present invention can alleviate the feelings of loss and loneliness that many people experience and provide emotional healing by recreating emotional connections. Such a system offers users a new experience for reflecting on important memories.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users upload photos, videos, audio recordings, letters, and conversation logs related to deceased loved ones or pets to the system. This allows the system to collect data that forms the basis of the interaction.

[0045] Step 2:

[0046] The server analyzes the received data and performs preprocessing such as improving image quality and removing noise. This prepares the information for training the AI ​​model.

[0047] Step 3:

[0048] The server uses pre-processed data to train a generative model that learns the behavioral patterns of deceased individuals and pets. It utilizes machine learning techniques to build an AI model that mimics personality and speech patterns.

[0049] Step 4:

[0050] The server will have a module for generating speech from text based on a generative model. This will allow the text entered by the user to be played back in the voice of a deceased person or pet.

[0051] Step 5:

[0052] The device uses VR technology to create a virtual reality environment tailored to the user's settings. This includes places of personal significance and visually familiar settings.

[0053] Step 6:

[0054] Users put on VR devices and enter a virtual space to begin interactive conversations with deceased loved ones or pets.

[0055] Step 7:

[0056] The device recognizes user speech in real time and generates appropriate responses using an AI model on the server, thereby enabling natural conversation.

[0057] Step 8:

[0058] The server continuously analyzes user input and adjusts the AI ​​model to ensure a smooth flow of conversation, while continuing to provide a conversational experience.

[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 society, many people experience feelings of loss and loneliness when it comes to deceased loved ones or pets. Conventional technology has not provided a sufficiently satisfactory solution to this emotional challenge. There is a need for new systems that can more realistically recreate memories of deceased loved ones or pets and support emotional connections.

[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 collecting data about a deceased person or pet provided by the user, means for preprocessing the data, converting it into a unified format, and improving its quality, and means for training a generative model using machine learning techniques with the preprocessed data to mimic the characteristics of the deceased person or pet. This enables the data about the deceased person or pet to be processed effectively, allowing the user to have more natural and immersive conversations within the virtual environment.

[0064] "Data about the deceased or pet provided by the user" refers to multiple media containing memories and information related to the deceased or pet provided by the user (e.g., photographs, videos, audio recordings, letters, conversation logs, etc.).

[0065] "Preprocessing" refers to a series of operations that process collected data to improve its quality and standardize its format, and includes noise reduction, image quality enhancement, and audio filtering.

[0066] A "generative model using machine learning technology" refers to an artificial intelligence model that learns from a large amount of data and is used to imitate the characteristics and speech patterns of deceased people or pets.

[0067] A "virtual environment" refers to a virtual space where users can have an immersive experience through computer simulation, and is primarily constructed using virtual reality technology.

[0068] "Environment configuration means" refers to functions and technologies for adjusting and building a virtual environment according to user requests and preferences.

[0069] "Speech recognition technology" refers to the technology that converts speech into text in real time and is used to understand and respond to user speech.

[0070] "Converting data to a unified format" refers to the process of shaping data from different formats and standards into a consistent format, enabling efficient use of the data.

[0071] This invention provides a system that allows virtual interaction with a deceased person or pet, and is primarily realized through the cooperation of three parties: a server, a terminal, and a user.

[0072] The server first collects data provided by the user. This data includes photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server uses data processing software to preprocess this data and improve its quality. Specifically, it uses image processing libraries (e.g., OpenCV) to remove noise and audio processing libraries (e.g., Librosa) to remove background noise from audio.

[0073] Using pre-processed data, the server trains a generative AI model using a machine learning framework (e.g., TENSORFLOW®). This model is designed to mimic the personality and speaking style of deceased individuals or pets, allowing users to experience realistic conversations within a virtual environment. Through learning, the generative model mimics the deceased's mannerisms and speech patterns, and generates natural-sounding speech using speech synthesis software.

[0074] The device constructs a virtual space that allows users to experience an immersive environment using virtual reality technology. The user interface is customized using a virtual space construction platform (e.g., Unity), allowing users to recreate specific places of personal significance. The device provides an environment that users can intuitively interact with through a VR headset and controllers.

[0075] This system allows users to initiate conversations with deceased loved ones or pets in a virtual environment. For example, a user might ask, "How was your day?" and the virtual deceased or pet might respond, "It was a good day." Because the generative AI model generates natural-sounding responses based on the prompt, users can experience an emotional connection.

[0076] Thus, this invention aims to provide users with an opportunity to reflect on memories of deceased loved ones or pets in a new way and to gain emotional healing.

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

[0078] Step 1:

[0079] Users access the system through an interface and upload data related to deceased persons or pets. Inputs include photos, videos, audio recordings, letters, and conversation logs. This data may be provided in various file formats. As output, the server converts this data into a unified format and stores it in a database.

[0080] Step 2:

[0081] The server begins preprocessing the stored data. The input includes data in a unified format. The server uses image processing libraries (e.g., OpenCV) to remove noise from photos and videos, and leverages audio processing libraries (e.g., Librosa) to reduce background noise in audio data. The output is processed, high-quality media data.

[0082] Step 3:

[0083] The server begins training a generative AI model using preprocessed data. Inputs include photos, videos, and audio data. The server uses a machine learning framework (e.g., TensorFlow) to build a model that mimics the personality and speaking style of the deceased or their pet. Based on the data, the AI ​​learns the deceased's characteristic speech patterns and vocal tones. The output is a trained generative AI model.

[0084] Step 4:

[0085] The device utilizes a pre-trained AI model to construct a virtual environment. Inputs include the trained model and user customization requests. The device uses a virtual space construction platform (e.g., Unity) to faithfully recreate specific locations or scenes desired by the user. The output is an immersive virtual environment that the user can experience.

[0086] Step 5:

[0087] The user wears a VR headset connected to the device and participates in the virtual environment. Input includes the user's voice commands and actions. The device uses a speech recognition tool to convert the user's speech into text in real time, and an AI model generates a response based on this information. As output, a virtual voice response from a deceased person or pet is provided, enabling interaction with the user.

[0088] Through this series of processes, users can engage in natural and emotionally rich conversations with deceased loved ones or pets within a virtual environment.

[0089] (Application Example 1)

[0090] 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."

[0091] While technologies that virtually recreate conversations with deceased loved ones or pets have the potential to alleviate feelings of loss and loneliness, conventional technologies often fail to provide users with a truly realistic experience. Furthermore, opportunities to provide experiences based on memories in real-world settings are limited, creating a need for more interactive and personalized experiences that can be offered in physical stores.

[0092] 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.

[0093] In this invention, the server includes means for collecting information provided by the user, means for preprocessing, modifying, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate features and speech patterns. This makes it possible for users to virtually interact with deceased loved ones or pets in a physical store.

[0094] A "user" is an entity that provides information about deceased loved ones or pets to the system and experiences a virtual interaction with them.

[0095] "Information" refers to data such as photos, videos, and audio recordings related to the deceased or pet, and serves as material for the AI ​​model to learn from.

[0096] "Means of collection" refers to the process of acquiring information provided by users and incorporating it into the system.

[0097] "Preprocessing" refers to the process of removing noise from information and improving data quality.

[0098] A "generative model" is an algorithm that uses machine learning techniques to recreate the personality and speaking style of a deceased person or pet.

[0099] A "speech-imitating model" is an AI model that learns the conversation patterns and vocal characteristics of a deceased person or pet and has the ability to imitate them.

[0100] "Means of generating speech" refers to technology that synthesizes natural-sounding speech based on text data, and is used to approximate the voices of deceased people or pets.

[0101] A "virtual space" is a computer-generated environment that users can experience through virtual reality technology.

[0102] "Interactive dialogue" refers to two-way communication between the user and the system, providing a realistic experience that mimics actual conversations.

[0103] A "physical store" is a physical facility that exists in the real world and where users can visit to receive services or experiences.

[0104] "Device" refers to hardware installed in physical stores that allows users to have virtual experiences, and includes VR head-mounted displays, etc.

[0105] This invention is a system that provides virtual interaction with a deceased person or pet, offering a VR experience within a physical store. First, the user provides information related to the deceased or pet via a terminal. This information includes data such as photos, videos, and audio recordings, which are sent to a server. The server preprocesses the received information, removing noise and improving image quality to optimize it for training an AI model. This processing ensures the quality of the data.

[0106] Next, the server uses the pre-processed information to train a generative AI model that mimics the personality and conversational patterns of the deceased or pet. This AI model reproduces the deceased's catchphrases and speaking style. It also uses a speech generation module to synthesize natural-sounding voices that closely resemble the voice of the deceased or pet. This model utilizes machine learning frameworks such as TensorFlow.

[0107] Users visit a physical store and enter a virtual space using a specific device, such as a VR head-mounted display. This device allows users to experience interactive conversations with deceased loved ones or pets in a virtually recreated space. The virtual reality environment, built using Unity, can recreate memorable scenes based on user specifications.

[0108] As a concrete example, a user can choose a park they visited with their family in the past and recreate that scene in a virtual space. Within this space, they can interact with deceased loved ones or pets, and natural conversations can be initiated by prompts such as, "How was your day?" In this way, users can reminisce about irreplaceable memories and find emotional healing.

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

[0110] Step 1:

[0111] Users upload information about deceased persons or pets to the system using their devices. Inputs include data such as photos, videos, and audio recordings. This data is sent to a cloud server and converted into a format the system can handle. The server receives a collection of data from the user as output.

[0112] Step 2:

[0113] The server preprocesses the received data. The input is the set of data obtained in step 1. It cleans up the data by performing noise reduction and image quality enhancement. This results in a high-quality dataset suitable for training an AI model. Specific operations include image filtering and audio noise cancellation.

[0114] Step 3:

[0115] The server begins training the generative AI model using the preprocessed data. The input is the high-quality data obtained in step 2. This process uses machine learning algorithms to learn the deceased's personality and conversation patterns and build a model. The output is an AI model with mimicked conversation patterns and voice characteristics. Specific actions include tuning the model parameters and iterative training.

[0116] Step 4:

[0117] The terminal constructs a virtual space that the user can access. The input is information about the location and time specified by the user. Based on this, a virtual reality environment is generated using software such as Unity. The output is a virtual space that can be viewed on the user's VR device. Specific operations include 3D modeling and scene rendering.

[0118] Step 5:

[0119] In a virtual space, users engage in interactive conversations with deceased loved ones or pets. Input consists of words and actions spoken by the user. The server's AI model generates and outputs appropriate dialogue responses based on this input. Specific actions include speech recognition and natural language processing of the user's responses. A conversation can be initiated in the virtual space by uttering a prompt such as, "How was your day?"

[0120] 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.

[0121] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The system aims to understand the user's emotions in real time and improve the interactive experience based on that understanding. The specific configuration and operation are described below.

[0122] First, the user provides the system with photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server receives this data and performs the necessary preprocessing. This process includes correcting the data, denoising, and extracting important information.

[0123] Next, the server uses machine learning techniques to train a generative model that mimics the personality and speaking style of the deceased person or pet from the pre-processed data. This generative model is then used to generate voices, which are provided to the user as the voice of the deceased person or pet. These voices are adjusted in real time according to the content of the conversation with the user.

[0124] Furthermore, the device is equipped with an emotion engine. This engine can recognize the user's emotional state from their voice and facial expressions. When the user interacts in the virtual reality environment, this emotion engine detects not only the content of the user's speech but also their emotional responses and sends feedback to the server.

[0125] The server receives feedback from the emotion engine and dynamically adjusts the content and tone of the dialogue to match the user's emotional state. For example, if the user expresses sadness, the system provides more comforting content and generates responses to soothe the user. In this way, emotionally resonant communication can be achieved through dialogue within the virtual reality environment.

[0126] Finally, the visual and auditory elements within the virtual reality environment are adjusted in real time in response to the user's emotional changes. This feature allows users to have a more immersive experience and feel a deeper connection with their deceased loved ones or pets.

[0127] Based on the above, the present invention provides users with a rich, emotionally resonant dialogue experience, and serves as an effective means to alleviate feelings of loss and promote emotional healing.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] Users upload photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet to the system. This allows the system to collect information that forms the basis of the conversation.

[0131] Step 2:

[0132] The server analyzes the received data and performs preprocessing to improve image and sound quality and remove noise. This prepares the data for training the AI ​​model.

[0133] Step 3:

[0134] The server uses pre-processed information to train a generative model that mimics the behavioral patterns of the deceased or their pet. Machine learning algorithms are applied to create an AI model that reproduces their personality and speaking style.

[0135] Step 4:

[0136] The server uses a speech generation module to generate speech in the voice of a deceased person or pet, playing back the text entered by the user. In this process, it faithfully imitates the tone and characteristics of the voice.

[0137] Step 5:

[0138] The device uses an emotion engine to analyze the user's voice and facial expressions, recognizing emotions in real time. This data is sent to a server and used to facilitate the conversation.

[0139] Step 6:

[0140] The user puts on a VR device and enters a virtual reality environment. This environment serves as the foundation for interacting with deceased loved ones or pets, and is customizable.

[0141] Step 7:

[0142] The device sends information from the emotion engine to the server, which dynamically adjusts the dialogue and responses based on the user's emotional state. For example, if the user is sad, comforting content will be provided.

[0143] Step 8:

[0144] The visual and auditory elements within the virtual reality environment are also adjusted in real time to match the user's emotional changes. This adjustment is made to enhance the user's immersion.

[0145] Step 9:

[0146] The server analyzes data even after the user interaction has ended, implementing model improvement and feedback functions to help enhance the user experience.

[0147] Through these steps, the system can provide users with an emotionally resonant and interactive dialogue experience, supporting the mitigation of feelings of loss and promoting emotional healing.

[0148] (Example 2)

[0149] 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".

[0150] In modern times, a challenge for many people is the limited means they have to reflect on memories and emotions when they lose loved ones or pets. Traditional methods only allow them to reminisce through simple photos and videos, and because they do not offer interactive experiences, they do not adequately heal or alleviate the sense of loss.

[0151] 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.

[0152] In this invention, the server includes means for collecting information about a deceased person or pet provided by the user, means for preprocessing, correcting, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate the personality and manner of speaking of the deceased person or pet. This makes it possible to interactively reminisce about past memories and provide emotional support and comfort to the user.

[0153] "Information about a deceased person or pet provided by the user" refers to digital data such as photos, videos, audio, letters, and conversation logs that the user uploads to the system in relation to a deceased person or pet.

[0154] "Means for preprocessing, correction, and data extraction" refers to technical means that are responsible for processes such as removing noise from collected information and extracting important elements.

[0155] "Means of training generative models to mimic the personality and speech patterns of a deceased person or pet" refers to the process of using machine learning techniques to learn the characteristics of a deceased person or pet from pre-processed data and create an AI model with the aim of reproducing them.

[0156] "Means for generating and adjusting speech in real time" refers to technology that creates artificial speech using a generated model and instantly changes and adjusts this speech according to the context of the conversation.

[0157] "Means for recognizing a user's emotional state from voice and facial expressions" refers to technology that reads and analyzes emotions from the tone and speed of a user's speech, as well as their physical expressions.

[0158] "Means for dynamically adjusting the content and tone of dialogue" refers to technologies that change the content and tone of voice of the conversation generated by the system according to the user's emotional state.

[0159] "Means for constructing a virtual reality environment and adjusting its visual and auditory elements" refers to technologies that create a digital space and modify the images and sounds within it to match the user experience, in order to provide users with an immersive experience.

[0160] "Means of conducting interactive dialogue" refers to the technologies and processes that enable users to communicate with a system in a two-way manner.

[0161] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The following describes specific embodiments of this invention.

[0162] First, users provide the system with information related to the deceased or their pet. This includes photos, videos, audio recordings, letters, and conversation logs. The server collects this information and stores it in a database.

[0163] The server performs preprocessing on the received information, including data correction and noise reduction. Specifically, it filters out background noise from audio and uses facial recognition algorithms to extract important features from image data. At this stage, the server utilizes machine learning frameworks such as TensorFlow and PyTorch, which are implemented in Python.

[0164] Next, the server trains a generative model based on the pre-processed data. This builds an AI model that mimics the personality and speaking style of the deceased or their pet. This generative AI model generates speech that is adjusted in real time to match the content of the conversation with the user.

[0165] Next, the device is equipped with an emotion engine that recognizes the user's emotional state through their voice and facial expressions. This engine captures and analyzes the user's speech and facial expressions using sensors.

[0166] The server receives emotional state data transmitted from the terminal and dynamically adjusts the content and tone of the conversation. In this way, it can prepare comforting voices when the user expresses sadness and use a cheerful tone when discussing pleasant topics.

[0167] Finally, the virtual reality environment used by the user has the ability to adjust visual and auditory elements in real time based on the user's emotional state. This feature allows users to feel a strong bond with their deceased loved ones or pets while enjoying an immersive conversation.

[0168] For example, by entering prompts such as, "I would like you to recreate the voice of my grandfather when he talks about his favorite summer memories. Also, when I feel sad, I would like you to comfort me with warm words," users can communicate to the system the situations they want to experience.

[0169] This invention allows users to reconnect with deceased loved ones or pets in their hearts, providing healing from grief and offering emotional support.

[0170] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0171] Step 1:

[0172] Users provide the system with information such as photos, videos, audio, letters, and conversation logs related to deceased loved ones or pets. These media files are sent to the server as input. Specifically, users upload data through a dedicated application or web interface. The output is the storage of all data collected by the server.

[0173] Step 2:

[0174] The server preprocesses the data received from the user. The input is the raw data collected in the previous step. The server performs data correction, noise reduction, and extraction of important information. Specifically, this includes filtering audio data to remove background noise and performing facial recognition on image data to extract important features. The preprocessed results become the output and are passed to the next step as a new dataset.

[0175] Step 3:

[0176] The server trains a generative AI model using preprocessed data. The input is a preprocessed dataset. The server uses machine learning frameworks such as TensorFlow and PyTorch to optimize a model for mimicking the personality and speech patterns of deceased individuals or pets. Specifically, it analyzes past conversation logs to learn unique expressions and phrases. The output of this step is the trained generative model.

[0177] Step 4:

[0178] The server generates speech using the generated model and performs real-time adjustments during user interaction. The user's current utterances and emotional data are used as input. The output is real-time adjusted speech. Specific operations include adjusting the speech data generated by the AI ​​model in response to user reactions.

[0179] Step 5:

[0180] The device recognizes the user's voice and facial expressions to detect their emotional state. Input consists of voice and facial expression data captured by sensors built into the device. Output is sent to a server as data indicating the user's emotions. Specific operations include analyzing voice tone and speed, as well as tracking changes in facial expressions.

[0181] Step 6:

[0182] The server dynamically adjusts the content and tone of the dialogue based on emotional data from the terminal. The input is the user's emotional state data. The output is the adjusted communication content provided to the user. Specific actions include generating appropriate responses based on emotions, such as selecting a comforting message if the user expresses sadness.

[0183] Step 7:

[0184] The system adjusts the visual and auditory elements of the virtual reality environment based on the user's emotional state. Inputs are the user's emotional data and environment settings data. Output is the customized virtual reality environment experienced by the user. Specifically, if the user is emotionally calm, the system adjusts the visual and auditory elements, such as brightening the environment and softening the music.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0187] In modern society, people seek virtual experiences that allow them to feel a deep connection with deceased loved ones or pets through dialogue. However, conventional virtual experiences struggle to accurately recognize users' emotions and dynamically adjust responses according to the situation, failing to achieve emotionally resonant interactive dialogue. Therefore, there is a need to provide personalized dialogue and experiences that respond to users' emotions and promote emotional healing.

[0188] 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.

[0189] In this invention, the server includes means for recognizing the user's emotional state in real time, means for dynamically adjusting the dialogue content based on the emotion, and means for adjusting visual and auditory elements based on the emotion. This enables dialogue that is in line with the user's emotions, making an immersive experience that deepens emotional healing possible.

[0190] A "user" is an individual who utilizes the system, provides information about a deceased person or pet, and engages in dialogue within the virtual reality environment.

[0191] "Information gathering means" refers to methods and equipment used to obtain information about deceased persons or pets provided by users.

[0192] "Preprocessing means" refers to means of performing a process to correct collected information, remove data noise, and extract important data.

[0193] "Generative model training method" refers to the process of building a machine learning model to mimic the personality and speech patterns of a deceased person or pet, based on pre-processed information.

[0194] "Speech generation means" refers to technologies and devices that generate speech using generative models that mimic speaking styles.

[0195] "Methods for constructing a virtual reality environment" refers to the technologies and methods used to create a virtual space that users can experience.

[0196] An "interactive dialogue system" refers to a mechanism for interacting with users in real time and providing responses based on the user's reactions.

[0197] "Emotional state recognition means" refers to a technology or method for detecting and analyzing emotions from a user's voice or facial expressions.

[0198] "Dialogue content adjustment means" refers to a mechanism for adjusting the content and tone of a dialogue based on the recognized emotions of the user.

[0199] "Visual and auditory element adjustment means" refers to a technology that modifies the visual and auditory components within a virtual environment in accordance with the user's emotions.

[0200] To implement the present invention, the virtual dialogue system functions as follows between a server, a terminal, and a user: The server receives user-provided information about a deceased person or pet and runs a computer program to perform preprocessing. Preprocessing includes data correction, noise reduction, and extraction of important information. A generative model is trained using specific software, such as a machine learning library in Python, to create a model that mimics the personality and speaking style of the deceased person or pet. The generated model is used to produce synthesized speech. This speech data is used within a virtual reality environment accessible to the user.

[0201] The device is equipped with an emotion engine that has emotion recognition capabilities; for example, a smartphone or head-mounted display fulfills this role. The emotion engine identifies the user's emotional state in real time from their voice and facial expressions and sends it to a server. The server uses this feedback to dynamically adjust the content of the interaction. For example, if the user expresses sadness, the server improves the user experience by changing the response to something comforting. Furthermore, by adjusting the visual and auditory elements in virtual reality based on emotions, the user can have a more immersive experience.

[0202] As a concrete example, consider a scenario where a user is searching for a gift for a friend in a virtual store. In this case, the virtual customer service assistant suggests relevant products and services based on the user's interests and feelings. For example, if the user shows interest in a product, the assistant might suggest in a friendly tone, "How about a gift box that your friend will love?"

[0203] An example of a prompt message is: "If the user is looking for a gift, what should we suggest?" Based on this, the AI ​​system generates information that is sensitive to the user's emotions.

[0204] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0205] Step 1:

[0206] The server receives information from users about deceased persons or pets. This information includes photographs, videos, audio recordings, letters, and conversation logs. The input is user-provided information, and the output is collected raw data. At this stage, the server stores the raw data in a database for storage.

[0207] Step 2:

[0208] The server preprocesses the received information. The input is the raw data obtained in step 1, and the output is the noise-removed and corrected data. Specifically, image processing and audio filtering techniques are used to improve the quality of the data and prepare it for use in machine learning.

[0209] Step 3:

[0210] The server trains a generative AI model using preprocessed information. The input is the preprocessed data obtained in step 2, and the output is a trained model that mimics the personality and speech patterns of a deceased person or pet. Specifically, it analyzes the data using deep learning algorithms and constructs a generative model.

[0211] Step 4:

[0212] The server generates speech using a trained model. The input is the model obtained in step 3, which is text information for interaction with the user. The output is the generated synthesized speech. Specifically, the generated model creates speech data from the text and prepares it for the user to hear.

[0213] Step 5:

[0214] The device captures the user's voice and facial expressions in real time and performs emotion recognition. The input is the user's voice and video data, and the output is information about the user's emotional state. Specifically, it collects data using a camera and microphone and analyzes the user's emotions using an emotion recognition algorithm.

[0215] Step 6:

[0216] The server dynamically adjusts the dialogue content based on the emotional state obtained from the terminal. The input is the emotional data obtained in step 5, and the output is the dialogue content corresponding to that emotion. Specifically, it generates prompt sentences that switch the dialogue tone and content to match the user's emotion, thereby providing an interactive experience.

[0217] Step 7:

[0218] The terminal adjusts the visual and auditory elements based on information transmitted from the server. The input is the adjustment instructions based on the dialogue content and emotions obtained in step 6, and the output is the modified virtual environment. Specifically, the visual and auditory elements of the virtual environment are provided to the user through the display and speakers to enhance immersion.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention provides a system that allows users to virtually interact with a deceased person or pet based on various information provided by the user. This system can be implemented as follows.

[0236] Users access the system and provide information related to deceased loved ones or pets through an interface, such as photos, videos, audio recordings, letters, and conversation logs. The server organizes the received information and performs necessary preprocessing, such as removing noise and improving image quality. This prepares the information for training an AI model.

[0237] Next, the server uses the pre-processed information to train an AI generative model that mimics the personality and conversation patterns of the deceased or their pet. This generative model uses machine learning techniques to reproduce the deceased's catchphrases, phrases, and tone of voice. Additionally, a speech generation module is used to synthesize natural-sounding speech from the text information, outputting it in a form that closely resembles the voice of the deceased or their pet.

[0238] On the device side, a virtual reality environment is built to enrich the user experience. Using VR technology, users can recreate cherished places where they spent time with deceased loved ones or pets in the same space. This virtual space can be customized according to the user's preferences.

[0239] When a user enters the VR environment, they begin an interactive conversation with a virtual deceased person or pet. The device is designed to recognize the user's voice and actions and respond using an AI model to simulate a real conversation. For example, if the user asks, "How was your day?", the deceased person or pet can naturally reply, "It was a good day."

[0240] With the above configuration, the present invention can alleviate the feelings of loss and loneliness that many people experience and provide emotional healing by recreating emotional connections. Such a system offers users a new experience for reflecting on important memories.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] Users upload photos, videos, audio recordings, letters, and conversation logs related to deceased loved ones or pets to the system. This allows the system to collect data that forms the basis of the interaction.

[0244] Step 2:

[0245] The server analyzes the received data and performs preprocessing such as improving image quality and removing noise. This prepares the information for training the AI ​​model.

[0246] Step 3:

[0247] The server uses pre-processed data to train a generative model that learns the behavioral patterns of deceased individuals and pets. It utilizes machine learning techniques to build an AI model that mimics personality and speech patterns.

[0248] Step 4:

[0249] The server will have a module for generating speech from text based on a generative model. This will allow the text entered by the user to be played back in the voice of a deceased person or pet.

[0250] Step 5:

[0251] The device uses VR technology to create a virtual reality environment tailored to the user's settings. This includes places of personal significance and visually familiar settings.

[0252] Step 6:

[0253] Users put on VR devices and enter a virtual space to begin interactive conversations with deceased loved ones or pets.

[0254] Step 7:

[0255] The device recognizes user speech in real time and generates appropriate responses using an AI model on the server, thereby enabling natural conversation.

[0256] Step 8:

[0257] The server continuously analyzes user input and adjusts the AI ​​model to ensure a smooth flow of conversation, while continuing to provide a conversational experience.

[0258] (Example 1)

[0259] 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."

[0260] In modern society, many people experience feelings of loss and loneliness when it comes to deceased loved ones or pets. Conventional technology has not provided a sufficiently satisfactory solution to this emotional challenge. There is a need for new systems that can more realistically recreate memories of deceased loved ones or pets and support emotional connections.

[0261] 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.

[0262] In this invention, the server includes means for collecting data about a deceased person or pet provided by the user, means for preprocessing the data, converting it into a unified format, and improving its quality, and means for training a generative model using machine learning techniques with the preprocessed data to mimic the characteristics of the deceased person or pet. This enables the data about the deceased person or pet to be processed effectively, allowing the user to have more natural and immersive conversations within the virtual environment.

[0263] "Data about the deceased or pet provided by the user" refers to multiple media containing memories and information related to the deceased or pet provided by the user (e.g., photographs, videos, audio recordings, letters, conversation logs, etc.).

[0264] "Preprocessing" refers to a series of operations that process collected data to improve its quality and standardize its format, and includes noise reduction, image quality enhancement, and audio filtering.

[0265] A "generative model using machine learning technology" refers to an artificial intelligence model that learns from a large amount of data and is used to imitate the characteristics and speech patterns of deceased people or pets.

[0266] A "virtual environment" refers to a virtual space where users can have an immersive experience through computer simulation, and is primarily constructed using virtual reality technology.

[0267] "Environment configuration means" refers to functions and technologies for adjusting and building a virtual environment according to user requests and preferences.

[0268] "Speech recognition technology" refers to the technology that converts speech into text in real time and is used to understand and respond to user speech.

[0269] "Converting data to a unified format" refers to the process of shaping data from different formats and standards into a consistent format, enabling efficient use of the data.

[0270] This invention provides a system that allows virtual interaction with a deceased person or pet, and is primarily realized through the cooperation of three parties: a server, a terminal, and a user.

[0271] The server first collects data provided by the user. This data includes photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server uses data processing software to preprocess this data and improve its quality. Specifically, it uses image processing libraries (e.g., OpenCV) to remove noise and audio processing libraries (e.g., Librosa) to remove background noise from audio.

[0272] Using pre-processed data, the server trains a generative AI model using a machine learning framework (e.g., TensorFlow). This model is designed to mimic the personality and speaking style of deceased individuals or pets, allowing users to experience realistic conversations within a virtual environment. Through learning, the generative model mimics the deceased's mannerisms and speech patterns, and generates natural-sounding speech using speech synthesis software.

[0273] The device constructs a virtual space that allows users to experience an immersive environment using virtual reality technology. The user interface is customized using a virtual space construction platform (e.g., Unity), allowing users to recreate specific places of personal significance. The device provides an environment that users can intuitively interact with through a VR headset and controllers.

[0274] This system allows users to initiate conversations with deceased loved ones or pets in a virtual environment. For example, a user might ask, "How was your day?" and the virtual deceased or pet might respond, "It was a good day." Because the generative AI model generates natural-sounding responses based on the prompt, users can experience an emotional connection.

[0275] Thus, this invention aims to provide users with an opportunity to reflect on memories of deceased loved ones or pets in a new way and to gain emotional healing.

[0276] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0277] Step 1:

[0278] Users access the system through an interface and upload data related to deceased persons or pets. Inputs include photos, videos, audio recordings, letters, and conversation logs. This data may be provided in various file formats. As output, the server converts this data into a unified format and stores it in a database.

[0279] Step 2:

[0280] The server starts preprocessing the saved data. The input includes data in a unified format. The server uses an image processing library (e.g., OpenCV) to remove noise from photos and videos, and utilizes an audio processing library (e.g., Librosa) to reduce background noise in audio data. As output, processed high-quality media data is obtained.

[0281] Step 3:

[0282] The server starts training a generative AI model using the preprocessed data. The input includes photo, video, and audio data. The server uses a machine learning framework (e.g., TensorFlow) to build a model that mimics the personality and speaking style of a deceased person or pet. Based on the data, the AI learns the characteristic speech and tone of the deceased person. As output, a trained generative AI model is obtained.

[0283] Step 4:

[0284] The terminal constructs a virtual environment using the trained AI model. The input includes the trained model and the user's customization requirements. The terminal uses a virtual space construction platform (e.g., Unity) to faithfully reproduce the specific locations and scenes desired by the user. As output, an immersive virtual environment that the user can experience is generated.

[0285] Step 5:

[0286] The user wears a VR headset connected to the terminal and participates in the virtual environment. The input includes the user's voice instructions and actions. The terminal uses a speech recognition tool to convert the user's speech into text in real time, and the AI model generates a response based on this information. As output, a virtual voice response from the deceased person or pet is provided, enabling interaction with the user.

[0287] Through this series of processes, users can engage in natural and emotionally rich conversations with deceased loved ones or pets within a virtual environment.

[0288] (Application Example 1)

[0289] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0290] While technologies that virtually recreate conversations with deceased loved ones or pets have the potential to alleviate feelings of loss and loneliness, conventional technologies often fail to provide users with a truly realistic experience. Furthermore, opportunities to provide experiences based on memories in real-world settings are limited, creating a need for more interactive and personalized experiences that can be offered in physical stores.

[0291] 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.

[0292] In this invention, the server includes means for collecting information provided by the user, means for preprocessing, modifying, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate features and speech patterns. This makes it possible for users to virtually interact with deceased loved ones or pets in a physical store.

[0293] A "user" is an entity that provides information about deceased loved ones or pets to the system and experiences a virtual interaction with them.

[0294] "Information" refers to data such as photos, videos, and audio recordings related to the deceased or pet, and serves as material for the AI ​​model to learn from.

[0295] "Means of collection" refers to the process of acquiring information provided by users and incorporating it into the system.

[0296] "Preprocessing" refers to the process of removing noise from information and improving data quality.

[0297] A "generative model" is an algorithm that uses machine learning techniques to recreate the personality and speaking style of a deceased person or pet.

[0298] A "speech-imitating model" is an AI model that learns the conversation patterns and vocal characteristics of a deceased person or pet and has the ability to imitate them.

[0299] "Means of generating speech" refers to technology that synthesizes natural-sounding speech based on text data, and is used to approximate the voices of deceased people or pets.

[0300] A "virtual space" is a computer-generated environment that users can experience through virtual reality technology.

[0301] "Interactive dialogue" refers to two-way communication between the user and the system, providing a realistic experience that mimics actual conversations.

[0302] A "physical store" is a physical facility that exists in the real world and where users can visit to receive services or experiences.

[0303] "Device" refers to hardware installed in physical stores that allows users to have virtual experiences, and includes VR head-mounted displays, etc.

[0304] This invention is a system that provides virtual interaction with a deceased person or pet, offering a VR experience within a physical store. First, the user provides information related to the deceased or pet via a terminal. This information includes data such as photos, videos, and audio recordings, which are sent to a server. The server preprocesses the received information, removing noise and improving image quality to optimize it for training an AI model. This processing ensures the quality of the data.

[0305] Next, the server uses the preprocessed information to train a generative AI model that mimics the personality and conversation patterns of the deceased person or pet. This AI model reproduces the deceased person's speech habits and way of speaking. Also, a voice generation module is used to synthesize a natural voice similar to that of the deceased person or pet. This model utilizes a machine learning framework such as TensorFlow.

[0306] The user visits a physical store and enters a virtual space using a specific device, such as a VR head-mounted display. With this device, the user can experience an interactive conversation with the deceased person or pet in a virtually reproduced space. The virtual reality environment built using Unity can reproduce a memory scene based on the user's specification.

[0307] As a specific example, for instance, the user can select a park that the family visited in the past and reproduce that scene in the virtual space. Within this space, it is possible to communicate with the deceased person or pet and elicit a natural conversation by uttering a prompt sentence such as "How was today?". In this way, the user can look back on precious memories and obtain mental healing.

[0308] The flow of the specific processing in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user uses a terminal to upload information about the deceased person or pet to the system. The input includes data such as photos, videos, and audio recordings. These data are sent to the cloud server and converted into a format that the system can handle. As output, the server obtains a set of data received from the user.

[0311] Step 2:

[0312] The server preprocesses the received data. The input is the set of data obtained in step 1. It cleans up the data by performing noise reduction and image quality enhancement. This results in a high-quality dataset suitable for training an AI model. Specific operations include image filtering and audio noise cancellation.

[0313] Step 3:

[0314] The server begins training the generative AI model using the preprocessed data. The input is the high-quality data obtained in step 2. This process uses machine learning algorithms to learn the deceased's personality and conversation patterns and build a model. The output is an AI model with mimicked conversation patterns and voice characteristics. Specific actions include tuning the model parameters and iterative training.

[0315] Step 4:

[0316] The terminal constructs a virtual space that the user can access. The input is information about the location and time specified by the user. Based on this, a virtual reality environment is generated using software such as Unity. The output is a virtual space that can be viewed on the user's VR device. Specific operations include 3D modeling and scene rendering.

[0317] Step 5:

[0318] In a virtual space, users engage in interactive conversations with deceased loved ones or pets. Input consists of words and actions spoken by the user. The server's AI model generates and outputs appropriate dialogue responses based on this input. Specific actions include speech recognition and natural language processing of the user's responses. A conversation can be initiated in the virtual space by uttering a prompt such as, "How was your day?"

[0319] 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.

[0320] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The system aims to understand the user's emotions in real time and improve the interactive experience based on that understanding. The specific configuration and operation are described below.

[0321] First, the user provides the system with photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server receives this data and performs the necessary preprocessing. This process includes correcting the data, denoising, and extracting important information.

[0322] Next, the server uses machine learning techniques to train a generative model that mimics the personality and speaking style of the deceased person or pet from the pre-processed data. This generative model is then used to generate voices, which are provided to the user as the voice of the deceased person or pet. These voices are adjusted in real time according to the content of the conversation with the user.

[0323] Furthermore, the device is equipped with an emotion engine. This engine can recognize the user's emotional state from their voice and facial expressions. When the user interacts in the virtual reality environment, this emotion engine detects not only the content of the user's speech but also their emotional responses and sends feedback to the server.

[0324] The server receives feedback from the emotion engine and dynamically adjusts the content and tone of the dialogue to match the user's emotional state. For example, if the user expresses sadness, the system provides more comforting content and generates responses to soothe the user. In this way, emotionally resonant communication can be achieved through dialogue within the virtual reality environment.

[0325] Finally, the visual and auditory elements within the virtual reality environment are adjusted in real time in response to the user's emotional changes. This feature allows users to have a more immersive experience and feel a deeper connection with their deceased loved ones or pets.

[0326] Based on the above, the present invention provides users with a rich, emotionally resonant dialogue experience, and serves as an effective means to alleviate feelings of loss and promote emotional healing.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] Users upload photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet to the system. This allows the system to collect information that forms the basis of the conversation.

[0330] Step 2:

[0331] The server analyzes the received data and performs preprocessing to improve image and sound quality and remove noise. This prepares the data for training the AI ​​model.

[0332] Step 3:

[0333] The server uses pre-processed information to train a generative model that mimics the behavioral patterns of the deceased or their pet. Machine learning algorithms are applied to create an AI model that reproduces their personality and speaking style.

[0334] Step 4:

[0335] The server uses a speech generation module to generate speech in the voice of a deceased person or pet, playing back the text entered by the user. In this process, it faithfully imitates the tone and characteristics of the voice.

[0336] Step 5:

[0337] The device uses an emotion engine to analyze the user's voice and facial expressions, recognizing emotions in real time. This data is sent to a server and used to facilitate the conversation.

[0338] Step 6:

[0339] The user puts on a VR device and enters a virtual reality environment. This environment serves as the foundation for interacting with deceased loved ones or pets, and is customizable.

[0340] Step 7:

[0341] The device sends information from the emotion engine to the server, which dynamically adjusts the dialogue and responses based on the user's emotional state. For example, if the user is sad, comforting content will be provided.

[0342] Step 8:

[0343] The visual and auditory elements within the virtual reality environment are also adjusted in real time to match the user's emotional changes. This adjustment is made to enhance the user's immersion.

[0344] Step 9:

[0345] The server analyzes data even after the user interaction has ended, implementing model improvement and feedback functions to help enhance the user experience.

[0346] Through these steps, the system can provide users with an emotionally resonant and interactive dialogue experience, supporting the mitigation of feelings of loss and promoting emotional healing.

[0347] (Example 2)

[0348] 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".

[0349] In modern times, a challenge for many people is the limited means they have to reflect on memories and emotions when they lose loved ones or pets. Traditional methods only allow them to reminisce through simple photos and videos, and because they do not offer interactive experiences, they do not adequately heal or alleviate the sense of loss.

[0350] 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.

[0351] In this invention, the server includes means for collecting information about a deceased person or pet provided by the user, means for preprocessing, correcting, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate the personality and manner of speaking of the deceased person or pet. This makes it possible to interactively reminisce about past memories and provide emotional support and comfort to the user.

[0352] "Information about a deceased person or pet provided by the user" refers to digital data such as photos, videos, audio, letters, and conversation logs that the user uploads to the system in relation to a deceased person or pet.

[0353] "Means for preprocessing, correction, and data extraction" refers to technical means that are responsible for processes such as removing noise from collected information and extracting important elements.

[0354] "Means of training generative models to mimic the personality and speech patterns of a deceased person or pet" refers to the process of using machine learning techniques to learn the characteristics of a deceased person or pet from pre-processed data and create an AI model with the aim of reproducing them.

[0355] "Means for generating and adjusting speech in real time" refers to technology that creates artificial speech using a generated model and instantly changes and adjusts this speech according to the context of the conversation.

[0356] "Means for recognizing a user's emotional state from voice and facial expressions" refers to technology that reads and analyzes emotions from the tone and speed of a user's speech, as well as their physical expressions.

[0357] "Means for dynamically adjusting the content and tone of dialogue" refers to technologies that change the content and tone of voice of the conversation generated by the system according to the user's emotional state.

[0358] "Means for constructing a virtual reality environment and adjusting its visual and auditory elements" refers to technologies that create a digital space and modify the images and sounds within it to match the user experience, in order to provide users with an immersive experience.

[0359] "Means of conducting interactive dialogue" refers to the technologies and processes that enable users to communicate with a system in a two-way manner.

[0360] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The following describes specific embodiments of this invention.

[0361] First, users provide the system with information related to the deceased or their pet. This includes photos, videos, audio recordings, letters, and conversation logs. The server collects this information and stores it in a database.

[0362] The server performs preprocessing on the received information, including data correction and noise reduction. Specifically, it filters out background noise from audio and uses facial recognition algorithms to extract important features from image data. At this stage, the server utilizes machine learning frameworks such as TensorFlow and PyTorch, which are implemented in Python.

[0363] Next, the server trains a generative model based on the pre-processed data. This builds an AI model that mimics the personality and speaking style of the deceased or their pet. This generative AI model generates speech that is adjusted in real time to match the content of the conversation with the user.

[0364] Next, the device is equipped with an emotion engine that recognizes the user's emotional state through their voice and facial expressions. This engine captures and analyzes the user's speech and facial expressions using sensors.

[0365] The server receives emotional state data transmitted from the terminal and dynamically adjusts the content and tone of the conversation. In this way, it can prepare comforting voices when the user expresses sadness and use a cheerful tone when discussing pleasant topics.

[0366] Finally, the virtual reality environment used by the user has the ability to adjust visual and auditory elements in real time based on the user's emotional state. This feature allows users to feel a strong bond with their deceased loved ones or pets while enjoying an immersive conversation.

[0367] For example, by entering prompts such as, "I would like you to recreate the voice of my grandfather when he talks about his favorite summer memories. Also, when I feel sad, I would like you to comfort me with warm words," users can communicate to the system the situations they want to experience.

[0368] This invention allows users to reconnect with deceased loved ones or pets in their hearts, providing healing from grief and offering emotional support.

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] Users provide the system with information such as photos, videos, audio, letters, and conversation logs related to deceased loved ones or pets. These media files are sent to the server as input. Specifically, users upload data through a dedicated application or web interface. The output is the storage of all data collected by the server.

[0372] Step 2:

[0373] The server preprocesses the data received from the user. The input is the raw data collected in the previous step. The server performs data correction, noise reduction, and extraction of important information. Specifically, this includes filtering audio data to remove background noise and performing facial recognition on image data to extract important features. The preprocessed results become the output and are passed to the next step as a new dataset.

[0374] Step 3:

[0375] The server trains a generative AI model using preprocessed data. The input is a preprocessed dataset. The server uses machine learning frameworks such as TensorFlow and PyTorch to optimize a model for mimicking the personality and speech patterns of deceased individuals or pets. Specifically, it analyzes past conversation logs to learn unique expressions and phrases. The output of this step is the trained generative model.

[0376] Step 4:

[0377] The server generates speech using the generated model and performs real-time adjustments during user interaction. The user's current utterances and emotional data are used as input. The output is real-time adjusted speech. Specific operations include adjusting the speech data generated by the AI ​​model in response to user reactions.

[0378] Step 5:

[0379] The device recognizes the user's voice and facial expressions to detect their emotional state. Input consists of voice and facial expression data captured by sensors built into the device. Output is sent to a server as data indicating the user's emotions. Specific operations include analyzing voice tone and speed, as well as tracking changes in facial expressions.

[0380] Step 6:

[0381] The server dynamically adjusts the content and tone of the dialogue based on emotional data from the terminal. The input is the user's emotional state data. The output is the adjusted communication content provided to the user. Specific actions include generating appropriate responses based on emotions, such as selecting a comforting message if the user expresses sadness.

[0382] Step 7:

[0383] The system adjusts the visual and auditory elements of the virtual reality environment based on the user's emotional state. Inputs are the user's emotional data and environment settings data. Output is the customized virtual reality environment experienced by the user. Specifically, if the user is emotionally calm, the system adjusts the visual and auditory elements, such as brightening the environment and softening the music.

[0384] (Application Example 2)

[0385] 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 as the "terminal".

[0386] In modern society, people seek virtual experiences that allow them to feel a deep connection with deceased loved ones or pets through dialogue. However, conventional virtual experiences struggle to accurately recognize users' emotions and dynamically adjust responses according to the situation, failing to achieve emotionally resonant interactive dialogue. Therefore, there is a need to provide personalized dialogue and experiences that respond to users' emotions and promote emotional healing.

[0387] 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.

[0388] In this invention, the server includes means for recognizing the user's emotional state in real time, means for dynamically adjusting the dialogue content based on the emotion, and means for adjusting visual and auditory elements based on the emotion. This enables dialogue that is in line with the user's emotions, making an immersive experience that deepens emotional healing possible.

[0389] A "user" is an individual who utilizes the system, provides information about a deceased person or pet, and engages in dialogue within the virtual reality environment.

[0390] "Information gathering means" refers to methods and equipment used to obtain information about deceased persons or pets provided by users.

[0391] "Preprocessing means" refers to means of performing a process to correct collected information, remove data noise, and extract important data.

[0392] "Generative model training method" refers to the process of building a machine learning model to mimic the personality and speech patterns of a deceased person or pet, based on pre-processed information.

[0393] "Speech generation means" refers to technologies and devices that generate speech using generative models that mimic speaking styles.

[0394] "Methods for constructing a virtual reality environment" refers to the technologies and methods used to create a virtual space that users can experience.

[0395] An "interactive dialogue system" refers to a mechanism for interacting with users in real time and providing responses based on the user's reactions.

[0396] "Emotional state recognition means" refers to a technology or method for detecting and analyzing emotions from a user's voice or facial expressions.

[0397] "Dialogue content adjustment means" refers to a mechanism for adjusting the content and tone of a dialogue based on the recognized emotions of the user.

[0398] "Visual and auditory element adjustment means" refers to a technology that modifies the visual and auditory components within a virtual environment in accordance with the user's emotions.

[0399] To implement the present invention, the virtual dialogue system functions as follows between a server, a terminal, and a user: The server receives user-provided information about a deceased person or pet and runs a computer program to perform preprocessing. Preprocessing includes data correction, noise reduction, and extraction of important information. A generative model is trained using specific software, such as a machine learning library in Python, to create a model that mimics the personality and speaking style of the deceased person or pet. The generated model is used to produce synthesized speech. This speech data is used within a virtual reality environment accessible to the user.

[0400] The device is equipped with an emotion engine that has emotion recognition capabilities; for example, a smartphone or head-mounted display fulfills this role. The emotion engine identifies the user's emotional state in real time from their voice and facial expressions and sends it to a server. The server uses this feedback to dynamically adjust the content of the interaction. For example, if the user expresses sadness, the server improves the user experience by changing the response to something comforting. Furthermore, by adjusting the visual and auditory elements in virtual reality based on emotions, the user can have a more immersive experience.

[0401] As a concrete example, consider a scenario where a user is searching for a gift for a friend in a virtual store. In this case, the virtual customer service assistant suggests relevant products and services based on the user's interests and feelings. For example, if the user shows interest in a product, the assistant might suggest in a friendly tone, "How about a gift box that your friend will love?"

[0402] An example of a prompt message is: "If the user is looking for a gift, what should we suggest?" Based on this, the AI ​​system generates information that is sensitive to the user's emotions.

[0403] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0404] Step 1:

[0405] The server receives information from users about deceased persons or pets. This information includes photographs, videos, audio recordings, letters, and conversation logs. The input is user-provided information, and the output is collected raw data. At this stage, the server stores the raw data in a database for storage.

[0406] Step 2:

[0407] The server preprocesses the received information. The input is the raw data obtained in step 1, and the output is the noise-removed and corrected data. Specifically, image processing and audio filtering techniques are used to improve the quality of the data and prepare it for use in machine learning.

[0408] Step 3:

[0409] The server trains a generative AI model using preprocessed information. The input is the preprocessed data obtained in step 2, and the output is a trained model that mimics the personality and speech patterns of a deceased person or pet. Specifically, it analyzes the data using deep learning algorithms and constructs a generative model.

[0410] Step 4:

[0411] The server generates speech using a trained model. The input is the model obtained in step 3, which is text information for interaction with the user. The output is the generated synthesized speech. Specifically, the generated model creates speech data from the text and prepares it for the user to hear.

[0412] Step 5:

[0413] The device captures the user's voice and facial expressions in real time and performs emotion recognition. The input is the user's voice and video data, and the output is information about the user's emotional state. Specifically, it collects data using a camera and microphone and analyzes the user's emotions using an emotion recognition algorithm.

[0414] Step 6:

[0415] The server dynamically adjusts the dialogue content based on the emotional state obtained from the terminal. The input is the emotional data obtained in step 5, and the output is the dialogue content corresponding to that emotion. Specifically, it generates prompt sentences that switch the dialogue tone and content to match the user's emotion, thereby providing an interactive experience.

[0416] Step 7:

[0417] The terminal adjusts the visual and auditory elements based on information transmitted from the server. The input is the adjustment instructions based on the dialogue content and emotions obtained in step 6, and the output is the modified virtual environment. Specifically, the visual and auditory elements of the virtual environment are provided to the user through the display and speakers to enhance immersion.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] [Third Embodiment]

[0422] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0423] 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.

[0424] 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).

[0425] 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.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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".

[0434] This invention provides a system that allows users to virtually interact with a deceased person or pet based on various information provided by the user. This system can be implemented as follows.

[0435] Users access the system and provide information related to deceased loved ones or pets through an interface, such as photos, videos, audio recordings, letters, and conversation logs. The server organizes the received information and performs necessary preprocessing, such as removing noise and improving image quality. This prepares the information for training an AI model.

[0436] Next, the server uses the pre-processed information to train an AI generative model that mimics the personality and conversation patterns of the deceased or their pet. This generative model uses machine learning techniques to reproduce the deceased's catchphrases, phrases, and tone of voice. Additionally, a speech generation module is used to synthesize natural-sounding speech from the text information, outputting it in a form that closely resembles the voice of the deceased or their pet.

[0437] On the device side, a virtual reality environment is built to enrich the user experience. Using VR technology, users can recreate cherished places where they spent time with deceased loved ones or pets in the same space. This virtual space can be customized according to the user's preferences.

[0438] When a user enters the VR environment, they begin an interactive conversation with a virtual deceased person or pet. The device is designed to recognize the user's voice and actions and respond using an AI model to simulate a real conversation. For example, if the user asks, "How was your day?", the deceased person or pet can naturally reply, "It was a good day."

[0439] With the above configuration, the present invention can alleviate the feelings of loss and loneliness that many people experience and provide emotional healing by recreating emotional connections. Such a system offers users a new experience for reflecting on important memories.

[0440] The following describes the processing flow.

[0441] Step 1:

[0442] Users upload photos, videos, audio recordings, letters, and conversation logs related to deceased loved ones or pets to the system. This allows the system to collect data that forms the basis of the interaction.

[0443] Step 2:

[0444] The server analyzes the received data and performs preprocessing such as improving image quality and removing noise. This prepares the information for training the AI ​​model.

[0445] Step 3:

[0446] The server uses pre-processed data to train a generative model that learns the behavioral patterns of deceased individuals and pets. It utilizes machine learning techniques to build an AI model that mimics personality and speech patterns.

[0447] Step 4:

[0448] The server will have a module for generating speech from text based on a generative model. This will allow the text entered by the user to be played back in the voice of a deceased person or pet.

[0449] Step 5:

[0450] The device uses VR technology to create a virtual reality environment tailored to the user's settings. This includes places of personal significance and visually familiar settings.

[0451] Step 6:

[0452] Users put on VR devices and enter a virtual space to begin interactive conversations with deceased loved ones or pets.

[0453] Step 7:

[0454] The device recognizes user speech in real time and generates appropriate responses using an AI model on the server, thereby enabling natural conversation.

[0455] Step 8:

[0456] The server continuously analyzes user input and adjusts the AI ​​model to ensure a smooth flow of conversation, while continuing to provide a conversational experience.

[0457] (Example 1)

[0458] 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."

[0459] In modern society, many people experience feelings of loss and loneliness when it comes to deceased loved ones or pets. Conventional technology has not provided a sufficiently satisfactory solution to this emotional challenge. There is a need for new systems that can more realistically recreate memories of deceased loved ones or pets and support emotional connections.

[0460] 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.

[0461] In this invention, the server includes means for collecting data about a deceased person or pet provided by the user, means for preprocessing the data, converting it into a unified format, and improving its quality, and means for training a generative model using machine learning techniques with the preprocessed data to mimic the characteristics of the deceased person or pet. This enables the data about the deceased person or pet to be processed effectively, allowing the user to have more natural and immersive conversations within the virtual environment.

[0462] "Data about the deceased or pet provided by the user" refers to multiple media containing memories and information related to the deceased or pet provided by the user (e.g., photographs, videos, audio recordings, letters, conversation logs, etc.).

[0463] "Preprocessing" refers to a series of operations that process collected data to improve its quality and standardize its format, and includes noise reduction, image quality enhancement, and audio filtering.

[0464] A "generative model using machine learning technology" refers to an artificial intelligence model that learns from a large amount of data and is used to imitate the characteristics and speech patterns of deceased people or pets.

[0465] A "virtual environment" refers to a virtual space where users can have an immersive experience through computer simulation, and is primarily constructed using virtual reality technology.

[0466] "Environment configuration means" refers to functions and technologies for adjusting and building a virtual environment according to user requests and preferences.

[0467] "Speech recognition technology" refers to the technology that converts speech into text in real time and is used to understand and respond to user speech.

[0468] "Converting data to a unified format" refers to the process of shaping data from different formats and standards into a consistent format, enabling efficient use of the data.

[0469] This invention provides a system that allows virtual interaction with a deceased person or pet, and is primarily realized through the cooperation of three parties: a server, a terminal, and a user.

[0470] The server first collects data provided by the user. This data includes photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server uses data processing software to preprocess this data and improve its quality. Specifically, it uses image processing libraries (e.g., OpenCV) to remove noise and audio processing libraries (e.g., Librosa) to remove background noise from audio.

[0471] Using pre-processed data, the server trains a generative AI model using a machine learning framework (e.g., TensorFlow). This model is designed to mimic the personality and speaking style of deceased individuals or pets, allowing users to experience realistic conversations within a virtual environment. Through learning, the generative model mimics the deceased's mannerisms and speech patterns, and generates natural-sounding speech using speech synthesis software.

[0472] The device constructs a virtual space that allows users to experience an immersive environment using virtual reality technology. The user interface is customized using a virtual space construction platform (e.g., Unity), allowing users to recreate specific places of personal significance. The device provides an environment that users can intuitively interact with through a VR headset and controllers.

[0473] This system allows users to initiate conversations with deceased loved ones or pets in a virtual environment. For example, a user might ask, "How was your day?" and the virtual deceased or pet might respond, "It was a good day." Because the generative AI model generates natural-sounding responses based on the prompt, users can experience an emotional connection.

[0474] Thus, this invention aims to provide users with an opportunity to reflect on memories of deceased loved ones or pets in a new way and to gain emotional healing.

[0475] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0476] Step 1:

[0477] Users access the system through an interface and upload data related to deceased persons or pets. Inputs include photos, videos, audio recordings, letters, and conversation logs. This data may be provided in various file formats. As output, the server converts this data into a unified format and stores it in a database.

[0478] Step 2:

[0479] The server begins preprocessing the stored data. The input includes data in a unified format. The server uses image processing libraries (e.g., OpenCV) to remove noise from photos and videos, and leverages audio processing libraries (e.g., Librosa) to reduce background noise in audio data. The output is processed, high-quality media data.

[0480] Step 3:

[0481] The server begins training a generative AI model using preprocessed data. Inputs include photos, videos, and audio data. The server uses a machine learning framework (e.g., TensorFlow) to build a model that mimics the personality and speaking style of the deceased or their pet. Based on the data, the AI ​​learns the deceased's characteristic speech patterns and vocal tones. The output is a trained generative AI model.

[0482] Step 4:

[0483] The device utilizes a pre-trained AI model to construct a virtual environment. Inputs include the trained model and user customization requests. The device uses a virtual space construction platform (e.g., Unity) to faithfully recreate specific locations or scenes desired by the user. The output is an immersive virtual environment that the user can experience.

[0484] Step 5:

[0485] The user wears a VR headset connected to the device and participates in the virtual environment. Input includes the user's voice commands and actions. The device uses a speech recognition tool to convert the user's speech into text in real time, and an AI model generates a response based on this information. As output, a virtual voice response from a deceased person or pet is provided, enabling interaction with the user.

[0486] Through this series of processes, users can engage in natural and emotionally rich conversations with deceased loved ones or pets within a virtual environment.

[0487] (Application Example 1)

[0488] 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."

[0489] While technologies that virtually recreate conversations with deceased loved ones or pets have the potential to alleviate feelings of loss and loneliness, conventional technologies often fail to provide users with a truly realistic experience. Furthermore, opportunities to provide experiences based on memories in real-world settings are limited, creating a need for more interactive and personalized experiences that can be offered in physical stores.

[0490] 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.

[0491] In this invention, the server includes means for collecting information provided by the user, means for preprocessing, modifying, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate features and speech patterns. This makes it possible for users to virtually interact with deceased loved ones or pets in a physical store.

[0492] A "user" is an entity that provides information about deceased loved ones or pets to the system and experiences a virtual interaction with them.

[0493] "Information" refers to data such as photos, videos, and audio recordings related to the deceased or pet, and serves as material for the AI ​​model to learn from.

[0494] "Means of collection" refers to the process of acquiring information provided by users and incorporating it into the system.

[0495] "Preprocessing" refers to the process of removing noise from information and improving data quality.

[0496] A "generative model" is an algorithm that uses machine learning techniques to recreate the personality and speaking style of a deceased person or pet.

[0497] A "speech-imitating model" is an AI model that learns the conversation patterns and vocal characteristics of a deceased person or pet and has the ability to imitate them.

[0498] "Means of generating speech" refers to technology that synthesizes natural-sounding speech based on text data, and is used to approximate the voices of deceased people or pets.

[0499] A "virtual space" is a computer-generated environment that users can experience through virtual reality technology.

[0500] "Interactive dialogue" refers to two-way communication between the user and the system, providing a realistic experience that mimics actual conversations.

[0501] A "physical store" is a physical facility that exists in the real world and where users can visit to receive services or experiences.

[0502] "Device" refers to hardware installed in physical stores that allows users to have virtual experiences, and includes VR head-mounted displays, etc.

[0503] This invention is a system that provides virtual interaction with a deceased person or pet, offering a VR experience within a physical store. First, the user provides information related to the deceased or pet via a terminal. This information includes data such as photos, videos, and audio recordings, which are sent to a server. The server preprocesses the received information, removing noise and improving image quality to optimize it for training an AI model. This processing ensures the quality of the data.

[0504] Next, the server uses the pre-processed information to train a generative AI model that mimics the personality and conversational patterns of the deceased or pet. This AI model reproduces the deceased's catchphrases and speaking style. It also uses a speech generation module to synthesize natural-sounding voices that closely resemble the voice of the deceased or pet. This model utilizes machine learning frameworks such as TensorFlow.

[0505] Users visit a physical store and enter a virtual space using a specific device, such as a VR head-mounted display. This device allows users to experience interactive conversations with deceased loved ones or pets in a virtually recreated space. The virtual reality environment, built using Unity, can recreate memorable scenes based on user specifications.

[0506] As a concrete example, a user can choose a park they visited with their family in the past and recreate that scene in a virtual space. Within this space, they can interact with deceased loved ones or pets, and natural conversations can be initiated by prompts such as, "How was your day?" In this way, users can reminisce about irreplaceable memories and find emotional healing.

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

[0508] Step 1:

[0509] Users upload information about deceased persons or pets to the system using their devices. Inputs include data such as photos, videos, and audio recordings. This data is sent to a cloud server and converted into a format the system can handle. The server receives a collection of data from the user as output.

[0510] Step 2:

[0511] The server preprocesses the received data. The input is the set of data obtained in step 1. It cleans up the data by performing noise reduction and image quality enhancement. This results in a high-quality dataset suitable for training an AI model. Specific operations include image filtering and audio noise cancellation.

[0512] Step 3:

[0513] The server begins training the generative AI model using the preprocessed data. The input is the high-quality data obtained in step 2. This process uses machine learning algorithms to learn the deceased's personality and conversation patterns and build a model. The output is an AI model with mimicked conversation patterns and voice characteristics. Specific actions include tuning the model parameters and iterative training.

[0514] Step 4:

[0515] The terminal constructs a virtual space that the user can access. The input is information about the location and time specified by the user. Based on this, a virtual reality environment is generated using software such as Unity. The output is a virtual space that can be viewed on the user's VR device. Specific operations include 3D modeling and scene rendering.

[0516] Step 5:

[0517] In a virtual space, users engage in interactive conversations with deceased loved ones or pets. Input consists of words and actions spoken by the user. The server's AI model generates and outputs appropriate dialogue responses based on this input. Specific actions include speech recognition and natural language processing of the user's responses. A conversation can be initiated in the virtual space by uttering a prompt such as, "How was your day?"

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

[0519] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The system aims to understand the user's emotions in real time and improve the interactive experience based on that understanding. The specific configuration and operation are described below.

[0520] First, the user provides the system with photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server receives this data and performs the necessary preprocessing. This process includes correcting the data, denoising, and extracting important information.

[0521] Next, the server uses machine learning techniques to train a generative model that mimics the personality and speaking style of the deceased person or pet from the pre-processed data. This generative model is then used to generate voices, which are provided to the user as the voice of the deceased person or pet. These voices are adjusted in real time according to the content of the conversation with the user.

[0522] Furthermore, the device is equipped with an emotion engine. This engine can recognize the user's emotional state from their voice and facial expressions. When the user interacts in the virtual reality environment, this emotion engine detects not only the content of the user's speech but also their emotional responses and sends feedback to the server.

[0523] The server receives feedback from the emotion engine and dynamically adjusts the content and tone of the dialogue to match the user's emotional state. For example, if the user expresses sadness, the system provides more comforting content and generates responses to soothe the user. In this way, emotionally resonant communication can be achieved through dialogue within the virtual reality environment.

[0524] Finally, the visual and auditory elements within the virtual reality environment are adjusted in real time in response to the user's emotional changes. This feature allows users to have a more immersive experience and feel a deeper connection with their deceased loved ones or pets.

[0525] Based on the above, the present invention provides users with a rich, emotionally resonant dialogue experience, and serves as an effective means to alleviate feelings of loss and promote emotional healing.

[0526] The following describes the processing flow.

[0527] Step 1:

[0528] Users upload photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet to the system. This allows the system to collect information that forms the basis of the conversation.

[0529] Step 2:

[0530] The server analyzes the received data and performs preprocessing to improve image and sound quality and remove noise. This prepares the data for training the AI ​​model.

[0531] Step 3:

[0532] The server uses pre-processed information to train a generative model that mimics the behavioral patterns of the deceased or their pet. Machine learning algorithms are applied to create an AI model that reproduces their personality and speaking style.

[0533] Step 4:

[0534] The server uses a speech generation module to generate speech in the voice of a deceased person or pet, playing back the text entered by the user. In this process, it faithfully imitates the tone and characteristics of the voice.

[0535] Step 5:

[0536] The device uses an emotion engine to analyze the user's voice and facial expressions, recognizing emotions in real time. This data is sent to a server and used to facilitate the conversation.

[0537] Step 6:

[0538] The user puts on a VR device and enters a virtual reality environment. This environment serves as the foundation for interacting with deceased loved ones or pets, and is customizable.

[0539] Step 7:

[0540] The device sends information from the emotion engine to the server, which dynamically adjusts the dialogue and responses based on the user's emotional state. For example, if the user is sad, comforting content will be provided.

[0541] Step 8:

[0542] The visual and auditory elements within the virtual reality environment are also adjusted in real time to match the user's emotional changes. This adjustment is made to enhance the user's immersion.

[0543] Step 9:

[0544] The server analyzes data even after the user interaction has ended, implementing model improvement and feedback functions to help enhance the user experience.

[0545] Through these steps, the system can provide users with an emotionally resonant and interactive dialogue experience, supporting the mitigation of feelings of loss and promoting emotional healing.

[0546] (Example 2)

[0547] 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."

[0548] In modern times, a challenge for many people is the limited means they have to reflect on memories and emotions when they lose loved ones or pets. Traditional methods only allow them to reminisce through simple photos and videos, and because they do not offer interactive experiences, they do not adequately heal or alleviate the sense of loss.

[0549] 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.

[0550] In this invention, the server includes means for collecting information about a deceased person or pet provided by the user, means for preprocessing, correcting, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate the personality and manner of speaking of the deceased person or pet. This makes it possible to interactively reminisce about past memories and provide emotional support and comfort to the user.

[0551] "Information about a deceased person or pet provided by the user" refers to digital data such as photos, videos, audio, letters, and conversation logs that the user uploads to the system in relation to a deceased person or pet.

[0552] "Means for preprocessing, correction, and data extraction" refers to technical means that are responsible for processes such as removing noise from collected information and extracting important elements.

[0553] "Means of training generative models to mimic the personality and speech patterns of a deceased person or pet" refers to the process of using machine learning techniques to learn the characteristics of a deceased person or pet from pre-processed data and create an AI model with the aim of reproducing them.

[0554] "Means for generating and adjusting speech in real time" refers to technology that creates artificial speech using a generated model and instantly changes and adjusts this speech according to the context of the conversation.

[0555] "Means for recognizing a user's emotional state from voice and facial expressions" refers to technology that reads and analyzes emotions from the tone and speed of a user's speech, as well as their physical expressions.

[0556] "Means for dynamically adjusting the content and tone of dialogue" refers to technologies that change the content and tone of voice of the conversation generated by the system according to the user's emotional state.

[0557] "Means for constructing a virtual reality environment and adjusting its visual and auditory elements" refers to technologies that create a digital space and modify the images and sounds within it to match the user experience, in order to provide users with an immersive experience.

[0558] "Means of conducting interactive dialogue" refers to the technologies and processes that enable users to communicate with a system in a two-way manner.

[0559] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The following describes specific embodiments of this invention.

[0560] First, users provide the system with information related to the deceased or their pet. This includes photos, videos, audio recordings, letters, and conversation logs. The server collects this information and stores it in a database.

[0561] The server performs preprocessing on the received information, including data correction and noise reduction. Specifically, it filters out background noise from audio and uses facial recognition algorithms to extract important features from image data. At this stage, the server utilizes machine learning frameworks such as TensorFlow and PyTorch, which are implemented in Python.

[0562] Next, the server trains a generative model based on the pre-processed data. This builds an AI model that mimics the personality and speaking style of the deceased or their pet. This generative AI model generates speech that is adjusted in real time to match the content of the conversation with the user.

[0563] Next, the device is equipped with an emotion engine that recognizes the user's emotional state through their voice and facial expressions. This engine captures and analyzes the user's speech and facial expressions using sensors.

[0564] The server receives emotional state data transmitted from the terminal and dynamically adjusts the content and tone of the conversation. In this way, it can prepare comforting voices when the user expresses sadness and use a cheerful tone when discussing pleasant topics.

[0565] Finally, the virtual reality environment used by the user has the ability to adjust visual and auditory elements in real time based on the user's emotional state. This feature allows users to feel a strong bond with their deceased loved ones or pets while enjoying an immersive conversation.

[0566] For example, by entering prompts such as, "I would like you to recreate the voice of my grandfather when he talks about his favorite summer memories. Also, when I feel sad, I would like you to comfort me with warm words," users can communicate to the system the situations they want to experience.

[0567] This invention allows users to reconnect with deceased loved ones or pets in their hearts, providing healing from grief and offering emotional support.

[0568] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0569] Step 1:

[0570] Users provide the system with information such as photos, videos, audio, letters, and conversation logs related to deceased loved ones or pets. These media files are sent to the server as input. Specifically, users upload data through a dedicated application or web interface. The output is the storage of all data collected by the server.

[0571] Step 2:

[0572] The server preprocesses the data received from the user. The input is the raw data collected in the previous step. The server performs data correction, noise reduction, and extraction of important information. Specifically, this includes filtering audio data to remove background noise and performing facial recognition on image data to extract important features. The preprocessed results become the output and are passed to the next step as a new dataset.

[0573] Step 3:

[0574] The server trains a generative AI model using preprocessed data. The input is a preprocessed dataset. The server uses machine learning frameworks such as TensorFlow and PyTorch to optimize a model for mimicking the personality and speech patterns of deceased individuals or pets. Specifically, it analyzes past conversation logs to learn unique expressions and phrases. The output of this step is the trained generative model.

[0575] Step 4:

[0576] The server generates speech using the generated model and performs real-time adjustments during user interaction. The user's current utterances and emotional data are used as input. The output is real-time adjusted speech. Specific operations include adjusting the speech data generated by the AI ​​model in response to user reactions.

[0577] Step 5:

[0578] The device recognizes the user's voice and facial expressions to detect their emotional state. Input consists of voice and facial expression data captured by sensors built into the device. Output is sent to a server as data indicating the user's emotions. Specific operations include analyzing voice tone and speed, as well as tracking changes in facial expressions.

[0579] Step 6:

[0580] The server dynamically adjusts the content and tone of the dialogue based on emotional data from the terminal. The input is the user's emotional state data. The output is the adjusted communication content provided to the user. Specific actions include generating appropriate responses based on emotions, such as selecting a comforting message if the user expresses sadness.

[0581] Step 7:

[0582] The system adjusts the visual and auditory elements of the virtual reality environment based on the user's emotional state. Inputs are the user's emotional data and environment settings data. Output is the customized virtual reality environment experienced by the user. Specifically, if the user is emotionally calm, the system adjusts the visual and auditory elements, such as brightening the environment and softening the music.

[0583] (Application Example 2)

[0584] 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."

[0585] In modern society, people seek virtual experiences that allow them to feel a deep connection with deceased loved ones or pets through dialogue. However, conventional virtual experiences struggle to accurately recognize users' emotions and dynamically adjust responses according to the situation, failing to achieve emotionally resonant interactive dialogue. Therefore, there is a need to provide personalized dialogue and experiences that respond to users' emotions and promote emotional healing.

[0586] 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.

[0587] In this invention, the server includes means for recognizing the user's emotional state in real time, means for dynamically adjusting the dialogue content based on the emotion, and means for adjusting visual and auditory elements based on the emotion. This enables dialogue that is in line with the user's emotions, making an immersive experience that deepens emotional healing possible.

[0588] A "user" is an individual who utilizes the system, provides information about a deceased person or pet, and engages in dialogue within the virtual reality environment.

[0589] "Information gathering means" refers to methods and equipment used to obtain information about deceased persons or pets provided by users.

[0590] "Preprocessing means" refers to means of performing a process to correct collected information, remove data noise, and extract important data.

[0591] "Generative model training method" refers to the process of building a machine learning model to mimic the personality and speech patterns of a deceased person or pet, based on pre-processed information.

[0592] "Speech generation means" refers to technologies and devices that generate speech using generative models that mimic speaking styles.

[0593] "Methods for constructing a virtual reality environment" refers to the technologies and methods used to create a virtual space that users can experience.

[0594] An "interactive dialogue system" refers to a mechanism for interacting with users in real time and providing responses based on the user's reactions.

[0595] "Emotional state recognition means" refers to a technology or method for detecting and analyzing emotions from a user's voice or facial expressions.

[0596] "Dialogue content adjustment means" refers to a mechanism for adjusting the content and tone of a dialogue based on the recognized emotions of the user.

[0597] "Visual and auditory element adjustment means" refers to a technology that modifies the visual and auditory components within a virtual environment in accordance with the user's emotions.

[0598] To implement the present invention, the virtual dialogue system functions as follows between a server, a terminal, and a user: The server receives user-provided information about a deceased person or pet and runs a computer program to perform preprocessing. Preprocessing includes data correction, noise reduction, and extraction of important information. A generative model is trained using specific software, such as a machine learning library in Python, to create a model that mimics the personality and speaking style of the deceased person or pet. The generated model is used to produce synthesized speech. This speech data is used within a virtual reality environment accessible to the user.

[0599] The device is equipped with an emotion engine that has emotion recognition capabilities; for example, a smartphone or head-mounted display fulfills this role. The emotion engine identifies the user's emotional state in real time from their voice and facial expressions and sends it to a server. The server uses this feedback to dynamically adjust the content of the interaction. For example, if the user expresses sadness, the server improves the user experience by changing the response to something comforting. Furthermore, by adjusting the visual and auditory elements in virtual reality based on emotions, the user can have a more immersive experience.

[0600] As a concrete example, consider a scenario where a user is searching for a gift for a friend in a virtual store. In this case, the virtual customer service assistant suggests relevant products and services based on the user's interests and feelings. For example, if the user shows interest in a product, the assistant might suggest in a friendly tone, "How about a gift box that your friend will love?"

[0601] An example of a prompt message is: "If the user is looking for a gift, what should we suggest?" Based on this, the AI ​​system generates information that is sensitive to the user's emotions.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] The server receives information from users about deceased persons or pets. This information includes photographs, videos, audio recordings, letters, and conversation logs. The input is user-provided information, and the output is collected raw data. At this stage, the server stores the raw data in a database for storage.

[0605] Step 2:

[0606] The server preprocesses the received information. The input is the raw data obtained in step 1, and the output is the noise-removed and corrected data. Specifically, image processing and audio filtering techniques are used to improve the quality of the data and prepare it for use in machine learning.

[0607] Step 3:

[0608] The server trains a generative AI model using preprocessed information. The input is the preprocessed data obtained in step 2, and the output is a trained model that mimics the personality and speech patterns of a deceased person or pet. Specifically, it analyzes the data using deep learning algorithms and constructs a generative model.

[0609] Step 4:

[0610] The server generates speech using a trained model. The input is the model obtained in step 3, which is text information for interaction with the user. The output is the generated synthesized speech. Specifically, the generated model creates speech data from the text and prepares it for the user to hear.

[0611] Step 5:

[0612] The device captures the user's voice and facial expressions in real time and performs emotion recognition. The input is the user's voice and video data, and the output is information about the user's emotional state. Specifically, it collects data using a camera and microphone and analyzes the user's emotions using an emotion recognition algorithm.

[0613] Step 6:

[0614] The server dynamically adjusts the dialogue content based on the emotional state obtained from the terminal. The input is the emotional data obtained in step 5, and the output is the dialogue content corresponding to that emotion. Specifically, it generates prompt sentences that switch the dialogue tone and content to match the user's emotion, thereby providing an interactive experience.

[0615] Step 7:

[0616] The terminal adjusts the visual and auditory elements based on information transmitted from the server. The input is the adjustment instructions based on the dialogue content and emotions obtained in step 6, and the output is the modified virtual environment. Specifically, the visual and auditory elements of the virtual environment are provided to the user through the display and speakers to enhance immersion.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] [Fourth Embodiment]

[0621] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0622] 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.

[0623] 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).

[0624] 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.

[0625] 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.

[0626] 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).

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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".

[0634] This invention provides a system that allows users to virtually interact with a deceased person or pet based on various information provided by the user. This system can be implemented as follows.

[0635] Users access the system and provide information related to deceased loved ones or pets through an interface, such as photos, videos, audio recordings, letters, and conversation logs. The server organizes the received information and performs necessary preprocessing, such as removing noise and improving image quality. This prepares the information for training an AI model.

[0636] Next, the server uses the pre-processed information to train an AI generative model that mimics the personality and conversation patterns of the deceased or their pet. This generative model uses machine learning techniques to reproduce the deceased's catchphrases, phrases, and tone of voice. Additionally, a speech generation module is used to synthesize natural-sounding speech from the text information, outputting it in a form that closely resembles the voice of the deceased or their pet.

[0637] On the device side, a virtual reality environment is built to enrich the user experience. Using VR technology, users can recreate cherished places where they spent time with deceased loved ones or pets in the same space. This virtual space can be customized according to the user's preferences.

[0638] When a user enters the VR environment, they begin an interactive conversation with a virtual deceased person or pet. The device is designed to recognize the user's voice and actions and respond using an AI model to simulate a real conversation. For example, if the user asks, "How was your day?", the deceased person or pet can naturally reply, "It was a good day."

[0639] With the above configuration, the present invention can alleviate the feelings of loss and loneliness that many people experience and provide emotional healing by recreating emotional connections. Such a system offers users a new experience for reflecting on important memories.

[0640] The following describes the processing flow.

[0641] Step 1:

[0642] Users upload photos, videos, audio recordings, letters, and conversation logs related to deceased loved ones or pets to the system. This allows the system to collect data that forms the basis of the interaction.

[0643] Step 2:

[0644] The server analyzes the received data and performs preprocessing such as improving image quality and removing noise. This prepares the information for training the AI ​​model.

[0645] Step 3:

[0646] The server uses pre-processed data to train a generative model that learns the behavioral patterns of deceased individuals and pets. It utilizes machine learning techniques to build an AI model that mimics personality and speech patterns.

[0647] Step 4:

[0648] The server will have a module for generating speech from text based on a generative model. This will allow the text entered by the user to be played back in the voice of a deceased person or pet.

[0649] Step 5:

[0650] The device uses VR technology to create a virtual reality environment tailored to the user's settings. This includes places of personal significance and visually familiar settings.

[0651] Step 6:

[0652] Users put on VR devices and enter a virtual space to begin interactive conversations with deceased loved ones or pets.

[0653] Step 7:

[0654] The device recognizes user speech in real time and generates appropriate responses using an AI model on the server, thereby enabling natural conversation.

[0655] Step 8:

[0656] The server continuously analyzes user input and adjusts the AI ​​model to ensure a smooth flow of conversation, while continuing to provide a conversational experience.

[0657] (Example 1)

[0658] 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".

[0659] In modern society, many people experience feelings of loss and loneliness when it comes to deceased loved ones or pets. Conventional technology has not provided a sufficiently satisfactory solution to this emotional challenge. There is a need for new systems that can more realistically recreate memories of deceased loved ones or pets and support emotional connections.

[0660] 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.

[0661] In this invention, the server includes means for collecting data about a deceased person or pet provided by the user, means for preprocessing the data, converting it into a unified format, and improving its quality, and means for training a generative model using machine learning techniques with the preprocessed data to mimic the characteristics of the deceased person or pet. This enables the data about the deceased person or pet to be processed effectively, allowing the user to have more natural and immersive conversations within the virtual environment.

[0662] "Data about the deceased or pet provided by the user" refers to multiple media containing memories and information related to the deceased or pet provided by the user (e.g., photographs, videos, audio recordings, letters, conversation logs, etc.).

[0663] "Preprocessing" refers to a series of operations that process collected data to improve its quality and standardize its format, and includes noise reduction, image quality enhancement, and audio filtering.

[0664] A "generative model using machine learning technology" refers to an artificial intelligence model that learns from a large amount of data and is used to imitate the characteristics and speech patterns of deceased people or pets.

[0665] A "virtual environment" refers to a virtual space where users can have an immersive experience through computer simulation, and is primarily constructed using virtual reality technology.

[0666] "Environment configuration means" refers to functions and technologies for adjusting and building a virtual environment according to user requests and preferences.

[0667] "Speech recognition technology" refers to the technology that converts speech into text in real time and is used to understand and respond to user speech.

[0668] "Converting data to a unified format" refers to the process of shaping data from different formats and standards into a consistent format, enabling efficient use of the data.

[0669] This invention provides a system that allows virtual interaction with a deceased person or pet, and is primarily realized through the cooperation of three parties: a server, a terminal, and a user.

[0670] The server first collects data provided by the user. This data includes photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server uses data processing software to preprocess this data and improve its quality. Specifically, it uses image processing libraries (e.g., OpenCV) to remove noise and audio processing libraries (e.g., Librosa) to remove background noise from audio.

[0671] Using pre-processed data, the server trains a generative AI model using a machine learning framework (e.g., TensorFlow). This model is designed to mimic the personality and speaking style of deceased individuals or pets, allowing users to experience realistic conversations within a virtual environment. Through learning, the generative model mimics the deceased's mannerisms and speech patterns, and generates natural-sounding speech using speech synthesis software.

[0672] The device constructs a virtual space that allows users to experience an immersive environment using virtual reality technology. The user interface is customized using a virtual space construction platform (e.g., Unity), allowing users to recreate specific places of personal significance. The device provides an environment that users can intuitively interact with through a VR headset and controllers.

[0673] This system allows users to initiate conversations with deceased loved ones or pets in a virtual environment. For example, a user might ask, "How was your day?" and the virtual deceased or pet might respond, "It was a good day." Because the generative AI model generates natural-sounding responses based on the prompt, users can experience an emotional connection.

[0674] Thus, this invention aims to provide users with an opportunity to reflect on memories of deceased loved ones or pets in a new way and to gain emotional healing.

[0675] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0676] Step 1:

[0677] Users access the system through an interface and upload data related to deceased persons or pets. Inputs include photos, videos, audio recordings, letters, and conversation logs. This data may be provided in various file formats. As output, the server converts this data into a unified format and stores it in a database.

[0678] Step 2:

[0679] The server begins preprocessing the stored data. The input includes data in a unified format. The server uses image processing libraries (e.g., OpenCV) to remove noise from photos and videos, and leverages audio processing libraries (e.g., Librosa) to reduce background noise in audio data. The output is processed, high-quality media data.

[0680] Step 3:

[0681] The server begins training a generative AI model using preprocessed data. Inputs include photos, videos, and audio data. The server uses a machine learning framework (e.g., TensorFlow) to build a model that mimics the personality and speaking style of the deceased or their pet. Based on the data, the AI ​​learns the deceased's characteristic speech patterns and vocal tones. The output is a trained generative AI model.

[0682] Step 4:

[0683] The device utilizes a pre-trained AI model to construct a virtual environment. Inputs include the trained model and user customization requests. The device uses a virtual space construction platform (e.g., Unity) to faithfully recreate specific locations or scenes desired by the user. The output is an immersive virtual environment that the user can experience.

[0684] Step 5:

[0685] The user wears a VR headset connected to the device and participates in the virtual environment. Input includes the user's voice commands and actions. The device uses a speech recognition tool to convert the user's speech into text in real time, and an AI model generates a response based on this information. As output, a virtual voice response from a deceased person or pet is provided, enabling interaction with the user.

[0686] Through this series of processes, users can engage in natural and emotionally rich conversations with deceased loved ones or pets within a virtual environment.

[0687] (Application Example 1)

[0688] 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".

[0689] While technologies that virtually recreate conversations with deceased loved ones or pets have the potential to alleviate feelings of loss and loneliness, conventional technologies often fail to provide users with a truly realistic experience. Furthermore, opportunities to provide experiences based on memories in real-world settings are limited, creating a need for more interactive and personalized experiences that can be offered in physical stores.

[0690] 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.

[0691] In this invention, the server includes means for collecting information provided by the user, means for preprocessing, modifying, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate features and speech patterns. This makes it possible for users to virtually interact with deceased loved ones or pets in a physical store.

[0692] A "user" is an entity that provides information about deceased loved ones or pets to the system and experiences a virtual interaction with them.

[0693] "Information" refers to data such as photos, videos, and audio recordings related to the deceased or pet, and serves as material for the AI ​​model to learn from.

[0694] "Means of collection" refers to the process of acquiring information provided by users and incorporating it into the system.

[0695] "Preprocessing" refers to the process of removing noise from information and improving data quality.

[0696] A "generative model" is an algorithm that uses machine learning techniques to recreate the personality and speaking style of a deceased person or pet.

[0697] A "speech-imitating model" is an AI model that learns the conversation patterns and vocal characteristics of a deceased person or pet and has the ability to imitate them.

[0698] "Means of generating speech" refers to technology that synthesizes natural-sounding speech based on text data, and is used to approximate the voices of deceased people or pets.

[0699] A "virtual space" is a computer-generated environment that users can experience through virtual reality technology.

[0700] "Interactive dialogue" refers to two-way communication between the user and the system, providing a realistic experience that mimics actual conversations.

[0701] A "physical store" is a physical facility that exists in the real world and where users can visit to receive services or experiences.

[0702] "Device" refers to hardware installed in physical stores that allows users to have virtual experiences, and includes VR head-mounted displays, etc.

[0703] This invention is a system that provides virtual interaction with a deceased person or pet, offering a VR experience within a physical store. First, the user provides information related to the deceased or pet via a terminal. This information includes data such as photos, videos, and audio recordings, which are sent to a server. The server preprocesses the received information, removing noise and improving image quality to optimize it for training an AI model. This processing ensures the quality of the data.

[0704] Next, the server uses the pre-processed information to train a generative AI model that mimics the personality and conversational patterns of the deceased or pet. This AI model reproduces the deceased's catchphrases and speaking style. It also uses a speech generation module to synthesize natural-sounding voices that closely resemble the voice of the deceased or pet. This model utilizes machine learning frameworks such as TensorFlow.

[0705] Users visit a physical store and enter a virtual space using a specific device, such as a VR head-mounted display. This device allows users to experience interactive conversations with deceased loved ones or pets in a virtually recreated space. The virtual reality environment, built using Unity, can recreate memorable scenes based on user specifications.

[0706] As a concrete example, a user can choose a park they visited with their family in the past and recreate that scene in a virtual space. Within this space, they can interact with deceased loved ones or pets, and natural conversations can be initiated by prompts such as, "How was your day?" In this way, users can reminisce about irreplaceable memories and find emotional healing.

[0707] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0708] Step 1:

[0709] Users upload information about deceased persons or pets to the system using their devices. Inputs include data such as photos, videos, and audio recordings. This data is sent to a cloud server and converted into a format the system can handle. The server receives a collection of data from the user as output.

[0710] Step 2:

[0711] The server preprocesses the received data. The input is the set of data obtained in step 1. It cleans up the data by performing noise reduction and image quality enhancement. This results in a high-quality dataset suitable for training an AI model. Specific operations include image filtering and audio noise cancellation.

[0712] Step 3:

[0713] The server begins training the generative AI model using the preprocessed data. The input is the high-quality data obtained in step 2. This process uses machine learning algorithms to learn the deceased's personality and conversation patterns and build a model. The output is an AI model with mimicked conversation patterns and voice characteristics. Specific actions include tuning the model parameters and iterative training.

[0714] Step 4:

[0715] The terminal constructs a virtual space that the user can access. The input is information about the location and time specified by the user. Based on this, a virtual reality environment is generated using software such as Unity. The output is a virtual space that can be viewed on the user's VR device. Specific operations include 3D modeling and scene rendering.

[0716] Step 5:

[0717] In a virtual space, users engage in interactive conversations with deceased loved ones or pets. Input consists of words and actions spoken by the user. The server's AI model generates and outputs appropriate dialogue responses based on this input. Specific actions include speech recognition and natural language processing of the user's responses. A conversation can be initiated in the virtual space by uttering a prompt such as, "How was your day?"

[0718] 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.

[0719] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The system aims to understand the user's emotions in real time and improve the interactive experience based on that understanding. The specific configuration and operation are described below.

[0720] First, the user provides the system with photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet. The server receives this data and performs the necessary preprocessing. This process includes correcting the data, denoising, and extracting important information.

[0721] Next, the server uses machine learning techniques to train a generative model that mimics the personality and speaking style of the deceased person or pet from the pre-processed data. This generative model is then used to generate voices, which are provided to the user as the voice of the deceased person or pet. These voices are adjusted in real time according to the content of the conversation with the user.

[0722] Furthermore, the device is equipped with an emotion engine. This engine can recognize the user's emotional state from their voice and facial expressions. When the user interacts in the virtual reality environment, this emotion engine detects not only the content of the user's speech but also their emotional responses and sends feedback to the server.

[0723] The server receives feedback from the emotion engine and dynamically adjusts the content and tone of the dialogue to match the user's emotional state. For example, if the user expresses sadness, the system provides more comforting content and generates responses to soothe the user. In this way, emotionally resonant communication can be achieved through dialogue within the virtual reality environment.

[0724] Finally, the visual and auditory elements within the virtual reality environment are adjusted in real time in response to the user's emotional changes. This feature allows users to have a more immersive experience and feel a deeper connection with their deceased loved ones or pets.

[0725] Based on the above, the present invention provides users with a rich, emotionally resonant dialogue experience, and serves as an effective means to alleviate feelings of loss and promote emotional healing.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] Users upload photos, videos, audio recordings, letters, and conversation logs related to the deceased or their pet to the system. This allows the system to collect information that forms the basis of the conversation.

[0729] Step 2:

[0730] The server analyzes the received data and performs preprocessing to improve image and sound quality and remove noise. This prepares the data for training the AI ​​model.

[0731] Step 3:

[0732] The server uses pre-processed information to train a generative model that mimics the behavioral patterns of the deceased or their pet. Machine learning algorithms are applied to create an AI model that reproduces their personality and speaking style.

[0733] Step 4:

[0734] The server uses a speech generation module to generate speech in the voice of a deceased person or pet, playing back the text entered by the user. In this process, it faithfully imitates the tone and characteristics of the voice.

[0735] Step 5:

[0736] The device uses an emotion engine to analyze the user's voice and facial expressions, recognizing emotions in real time. This data is sent to a server and used to facilitate the conversation.

[0737] Step 6:

[0738] The user puts on a VR device and enters a virtual reality environment. This environment serves as the foundation for interacting with deceased loved ones or pets, and is customizable.

[0739] Step 7:

[0740] The device sends information from the emotion engine to the server, which dynamically adjusts the dialogue and responses based on the user's emotional state. For example, if the user is sad, comforting content will be provided.

[0741] Step 8:

[0742] The visual and auditory elements within the virtual reality environment are also adjusted in real time to match the user's emotional changes. This adjustment is made to enhance the user's immersion.

[0743] Step 9:

[0744] The server analyzes data even after the user interaction has ended, implementing model improvement and feedback functions to help enhance the user experience.

[0745] Through these steps, the system can provide users with an emotionally resonant and interactive dialogue experience, supporting the mitigation of feelings of loss and promoting emotional healing.

[0746] (Example 2)

[0747] 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".

[0748] In modern times, a challenge for many people is the limited means they have to reflect on memories and emotions when they lose loved ones or pets. Traditional methods only allow them to reminisce through simple photos and videos, and because they do not offer interactive experiences, they do not adequately heal or alleviate the sense of loss.

[0749] 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.

[0750] In this invention, the server includes means for collecting information about a deceased person or pet provided by the user, means for preprocessing, correcting, and extracting data from the information, and means for training a generative model using the preprocessed information to imitate the personality and manner of speaking of the deceased person or pet. This makes it possible to interactively reminisce about past memories and provide emotional support and comfort to the user.

[0751] "Information about a deceased person or pet provided by the user" refers to digital data such as photos, videos, audio, letters, and conversation logs that the user uploads to the system in relation to a deceased person or pet.

[0752] "Means for preprocessing, correction, and data extraction" refers to technical means that are responsible for processes such as removing noise from collected information and extracting important elements.

[0753] "Means of training generative models to mimic the personality and speech patterns of a deceased person or pet" refers to the process of using machine learning techniques to learn the characteristics of a deceased person or pet from pre-processed data and create an AI model with the aim of reproducing them.

[0754] "Means for generating and adjusting speech in real time" refers to technology that creates artificial speech using a generated model and instantly changes and adjusts this speech according to the context of the conversation.

[0755] "Means for recognizing a user's emotional state from voice and facial expressions" refers to technology that reads and analyzes emotions from the tone and speed of a user's speech, as well as their physical expressions.

[0756] "Means for dynamically adjusting the content and tone of dialogue" refers to technologies that change the content and tone of voice of the conversation generated by the system according to the user's emotional state.

[0757] "Means for constructing a virtual reality environment and adjusting its visual and auditory elements" refers to technologies that create a digital space and modify the images and sounds within it to match the user experience, in order to provide users with an immersive experience.

[0758] "Means of conducting interactive dialogue" refers to the technologies and processes that enable users to communicate with a system in a two-way manner.

[0759] This invention provides a virtual dialogue system that incorporates emotion recognition technology based on information about a deceased person or pet. The following describes specific embodiments of this invention.

[0760] First, users provide the system with information related to the deceased or their pet. This includes photos, videos, audio recordings, letters, and conversation logs. The server collects this information and stores it in a database.

[0761] The server performs preprocessing on the received information, including data correction and noise reduction. Specifically, it filters out background noise from audio and uses facial recognition algorithms to extract important features from image data. At this stage, the server utilizes machine learning frameworks such as TensorFlow and PyTorch, which are implemented in Python.

[0762] Next, the server trains a generative model based on the pre-processed data. This builds an AI model that mimics the personality and speaking style of the deceased or their pet. This generative AI model generates speech that is adjusted in real time to match the content of the conversation with the user.

[0763] Next, the device is equipped with an emotion engine that recognizes the user's emotional state through their voice and facial expressions. This engine captures and analyzes the user's speech and facial expressions using sensors.

[0764] The server receives emotional state data transmitted from the terminal and dynamically adjusts the content and tone of the conversation. In this way, it can prepare comforting voices when the user expresses sadness and use a cheerful tone when discussing pleasant topics.

[0765] Finally, the virtual reality environment used by the user has the ability to adjust visual and auditory elements in real time based on the user's emotional state. This feature allows users to feel a strong bond with their deceased loved ones or pets while enjoying an immersive conversation.

[0766] For example, by entering prompts such as, "I would like you to recreate the voice of my grandfather when he talks about his favorite summer memories. Also, when I feel sad, I would like you to comfort me with warm words," users can communicate to the system the situations they want to experience.

[0767] This invention allows users to reconnect with deceased loved ones or pets in their hearts, providing healing from grief and offering emotional support.

[0768] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0769] Step 1:

[0770] Users provide the system with information such as photos, videos, audio, letters, and conversation logs related to deceased loved ones or pets. These media files are sent to the server as input. Specifically, users upload data through a dedicated application or web interface. The output is the storage of all data collected by the server.

[0771] Step 2:

[0772] The server preprocesses the data received from the user. The input is the raw data collected in the previous step. The server performs data correction, noise reduction, and extraction of important information. Specifically, this includes filtering audio data to remove background noise and performing facial recognition on image data to extract important features. The preprocessed results become the output and are passed to the next step as a new dataset.

[0773] Step 3:

[0774] The server trains a generative AI model using preprocessed data. The input is a preprocessed dataset. The server uses machine learning frameworks such as TensorFlow and PyTorch to optimize a model for mimicking the personality and speech patterns of deceased individuals or pets. Specifically, it analyzes past conversation logs to learn unique expressions and phrases. The output of this step is the trained generative model.

[0775] Step 4:

[0776] The server generates speech using the generated model and performs real-time adjustments during user interaction. The user's current utterances and emotional data are used as input. The output is real-time adjusted speech. Specific operations include adjusting the speech data generated by the AI ​​model in response to user reactions.

[0777] Step 5:

[0778] The device recognizes the user's voice and facial expressions to detect their emotional state. Input consists of voice and facial expression data captured by sensors built into the device. Output is sent to a server as data indicating the user's emotions. Specific operations include analyzing voice tone and speed, as well as tracking changes in facial expressions.

[0779] Step 6:

[0780] The server dynamically adjusts the content and tone of the dialogue based on emotional data from the terminal. The input is the user's emotional state data. The output is the adjusted communication content provided to the user. Specific actions include generating appropriate responses based on emotions, such as selecting a comforting message if the user expresses sadness.

[0781] Step 7:

[0782] The system adjusts the visual and auditory elements of the virtual reality environment based on the user's emotional state. Inputs are the user's emotional data and environment settings data. Output is the customized virtual reality environment experienced by the user. Specifically, if the user is emotionally calm, the system adjusts the visual and auditory elements, such as brightening the environment and softening the music.

[0783] (Application Example 2)

[0784] 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".

[0785] In modern society, people seek virtual experiences that allow them to feel a deep connection with deceased loved ones or pets through dialogue. However, conventional virtual experiences struggle to accurately recognize users' emotions and dynamically adjust responses according to the situation, failing to achieve emotionally resonant interactive dialogue. Therefore, there is a need to provide personalized dialogue and experiences that respond to users' emotions and promote emotional healing.

[0786] 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.

[0787] In this invention, the server includes means for recognizing the user's emotional state in real time, means for dynamically adjusting the dialogue content based on the emotion, and means for adjusting visual and auditory elements based on the emotion. This enables dialogue that is in line with the user's emotions, making an immersive experience that deepens emotional healing possible.

[0788] A "user" is an individual who utilizes the system, provides information about a deceased person or pet, and engages in dialogue within the virtual reality environment.

[0789] "Information gathering means" refers to methods and equipment used to obtain information about deceased persons or pets provided by users.

[0790] "Preprocessing means" refers to means of performing a process to correct collected information, remove data noise, and extract important data.

[0791] "Generative model training method" refers to the process of building a machine learning model to mimic the personality and speech patterns of a deceased person or pet, based on pre-processed information.

[0792] "Speech generation means" refers to technologies and devices that generate speech using generative models that mimic speaking styles.

[0793] "Methods for constructing a virtual reality environment" refers to the technologies and methods used to create a virtual space that users can experience.

[0794] An "interactive dialogue system" refers to a mechanism for interacting with users in real time and providing responses based on the user's reactions.

[0795] "Emotional state recognition means" refers to a technology or method for detecting and analyzing emotions from a user's voice or facial expressions.

[0796] "Dialogue content adjustment means" refers to a mechanism for adjusting the content and tone of a dialogue based on the recognized emotions of the user.

[0797] "Visual and auditory element adjustment means" refers to a technology that modifies the visual and auditory components within a virtual environment in accordance with the user's emotions.

[0798] To implement the present invention, the virtual dialogue system functions as follows between a server, a terminal, and a user: The server receives user-provided information about a deceased person or pet and runs a computer program to perform preprocessing. Preprocessing includes data correction, noise reduction, and extraction of important information. A generative model is trained using specific software, such as a machine learning library in Python, to create a model that mimics the personality and speaking style of the deceased person or pet. The generated model is used to produce synthesized speech. This speech data is used within a virtual reality environment accessible to the user.

[0799] The device is equipped with an emotion engine that has emotion recognition capabilities; for example, a smartphone or head-mounted display fulfills this role. The emotion engine identifies the user's emotional state in real time from their voice and facial expressions and sends it to a server. The server uses this feedback to dynamically adjust the content of the interaction. For example, if the user expresses sadness, the server improves the user experience by changing the response to something comforting. Furthermore, by adjusting the visual and auditory elements in virtual reality based on emotions, the user can have a more immersive experience.

[0800] As a concrete example, consider a scenario where a user is searching for a gift for a friend in a virtual store. In this case, the virtual customer service assistant suggests relevant products and services based on the user's interests and feelings. For example, if the user shows interest in a product, the assistant might suggest in a friendly tone, "How about a gift box that your friend will love?"

[0801] An example of a prompt message is: "If the user is looking for a gift, what should we suggest?" Based on this, the AI ​​system generates information that is sensitive to the user's emotions.

[0802] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0803] Step 1:

[0804] The server receives information from users about deceased persons or pets. This information includes photographs, videos, audio recordings, letters, and conversation logs. The input is user-provided information, and the output is collected raw data. At this stage, the server stores the raw data in a database for storage.

[0805] Step 2:

[0806] The server preprocesses the received information. The input is the raw data obtained in step 1, and the output is the noise-removed and corrected data. Specifically, image processing and audio filtering techniques are used to improve the quality of the data and prepare it for use in machine learning.

[0807] Step 3:

[0808] The server trains a generative AI model using preprocessed information. The input is the preprocessed data obtained in step 2, and the output is a trained model that mimics the personality and speech patterns of a deceased person or pet. Specifically, it analyzes the data using deep learning algorithms and constructs a generative model.

[0809] Step 4:

[0810] The server generates speech using a trained model. The input is the model obtained in step 3, which is text information for interaction with the user. The output is the generated synthesized speech. Specifically, the generated model creates speech data from the text and prepares it for the user to hear.

[0811] Step 5:

[0812] The device captures the user's voice and facial expressions in real time and performs emotion recognition. The input is the user's voice and video data, and the output is information about the user's emotional state. Specifically, it collects data using a camera and microphone and analyzes the user's emotions using an emotion recognition algorithm.

[0813] Step 6:

[0814] The server dynamically adjusts the dialogue content based on the emotional state obtained from the terminal. The input is the emotional data obtained in step 5, and the output is the dialogue content corresponding to that emotion. Specifically, it generates prompt sentences that switch the dialogue tone and content to match the user's emotion, thereby providing an interactive experience.

[0815] Step 7:

[0816] The terminal adjusts the visual and auditory elements based on information transmitted from the server. The input is the adjustment instructions based on the dialogue content and emotions obtained in step 6, and the output is the modified virtual environment. Specifically, the visual and auditory elements of the virtual environment are provided to the user through the display and speakers to enhance immersion.

[0817] 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.

[0818] 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.

[0819] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0820] 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.

[0821] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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."

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0838] The following is further disclosed regarding the embodiments described above.

[0839] (Claim 1)

[0840] Means for collecting information about deceased persons or pets provided by users,

[0841] Means for preprocessing, correcting, and extracting the information,

[0842] A means for training a generative model using the preprocessed information to imitate the personality and speaking style of a deceased person or pet,

[0843] A means for generating speech using a model that imitates the way of speaking,

[0844] A means of creating a virtual reality environment that users can use,

[0845] A means for performing interactive dialogue with a user within the virtual reality environment,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, further comprising means for extracting important keywords and phrases from collected information about deceased persons or pets using natural language processing.

[0849] (Claim 3)

[0850] The system according to claim 1, further comprising means for customizing the environment to reproduce memories of a specific place or time based on user specifications in the construction of a virtual reality environment.

[0851] "Example 1"

[0852] (Claim 1)

[0853] Means for collecting data about deceased persons or pets provided by users,

[0854] A means of preprocessing the data, converting the data to a unified format, and improving its quality,

[0855] A means of training a generative model using machine learning techniques with preprocessed data to mimic the characteristics of a deceased person or pet,

[0856] A means of generating speech using automatic speech generation technology by utilizing a generative model that mimics,

[0857] A means of creating a virtual environment available to users and customizing the interface,

[0858] A means for conducting a conversation with a user within the virtual environment and processing the conversation in real time using speech recognition technology,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, further comprising means for extracting important information from collected data relating to deceased persons or pets using automated language processing technology.

[0862] (Claim 3)

[0863] The system according to claim 1, further comprising environment setting means for reproducing a specific space based on user preferences in the construction of a virtual environment.

[0864] "Application Example 1"

[0865] (Claim 1)

[0866] Means of collecting information provided by users,

[0867] Means for preprocessing, correcting, and extracting the information,

[0868] A means for training a generative model using the preprocessed information and for imitating features and speech patterns,

[0869] A means for generating speech using a model that imitates the way of speaking,

[0870] A means of creating a virtual space that users can use,

[0871] A means for performing interactive dialogue with the user within the virtual space,

[0872] A means of providing a virtual experience through devices installed in a physical store,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, further comprising means for extracting important keywords and phrases from collected information using natural language processing.

[0876] (Claim 3)

[0877] The system according to claim 1, further comprising means for customizing the environment to reproduce memories of a specific place or time based on user specifications in the construction of a virtual space.

[0878] "Example 2 of combining an emotion engine"

[0879] (Claim 1)

[0880] Means for collecting information about deceased persons or pets provided by users,

[0881] Means for preprocessing, correcting, and extracting the information,

[0882] A means for training a generative model using the preprocessed information to imitate the personality and speaking style of a deceased person or pet,

[0883] A means for generating speech using a generative model that imitates the way of speaking and adjusting it in real time,

[0884] A means of recognizing the user's emotional state from voice and facial expressions,

[0885] Means for dynamically adjusting the content and tone of the dialogue based on the emotional state,

[0886] A means for constructing a virtual reality environment available to the user and adjusting its visual and auditory elements,

[0887] A means for performing interactive dialogue with a user within the virtual reality environment,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, further comprising means for extracting important keywords and phrases from collected information about deceased persons or pets using natural language processing.

[0891] (Claim 3)

[0892] The system according to claim 1, further comprising means for customizing the environment to reproduce memories of a specific place or time based on user specifications in the construction of a virtual reality environment.

[0893] "Application example 2 of combining emotional engines"

[0894] (Claim 1)

[0895] Means for collecting information about deceased persons or pets provided by users,

[0896] Means for preprocessing, correcting, and extracting the information,

[0897] A means for training a generative model using the preprocessed information to imitate the personality and speaking style of a deceased person or pet,

[0898] A means for generating speech using a model that imitates the way of speaking,

[0899] A means of creating a virtual reality environment that users can use,

[0900] A means for performing interactive dialogue with a user within the virtual reality environment,

[0901] A means for recognizing the user's emotional state in real time and dynamically adjusting the content of the conversation based on that emotion,

[0902] Means for adjusting visual and auditory elements based on user emotions,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, further comprising means for extracting important keywords and phrases from collected information about deceased persons or pets using natural language processing.

[0906] (Claim 3)

[0907] The system according to claim 1, further comprising means for customizing the environment to reproduce a specific environment based on user specifications in the construction of a virtual reality environment. [Explanation of Symbols]

[0908] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means for collecting information about deceased persons or pets provided by users, Means for preprocessing, correcting, and extracting the information, A means for training a generative model using the preprocessed information to imitate the personality and speaking style of a deceased person or pet, A means for generating speech using a model that imitates the way of speaking, A means of creating a virtual reality environment that users can use, A means for performing interactive dialogue with a user within the virtual reality environment, A system that includes this.

2. The system according to claim 1, further comprising means for extracting important keywords and phrases from collected information about deceased persons or pets using natural language processing.

3. The system according to claim 1, further comprising means for customizing the environment to reproduce memories of a specific place or time based on user specifications in the construction of a virtual reality environment.

Images