System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving voice data or text data from a user; means for analyzing an emotion of the received voice data or text data using natural language processing or voice analysis; means for storing and managing an analysis result; means for updating and growing an attribute of a character based on the analysis result; and means for adding a point to an account of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to provide a means for users to promote positive emotions in order to solve the increasing problem of lonely deaths. Specifically, as loneliness and social isolation become more serious, the aim is to alleviate loneliness and solve part of the social problem by allowing users to express their emotions and have positive emotions. Current systems lack the ability to analyze users' emotions in real time and provide appropriate feedback and rewards based on the results, so a more effective solution is needed. [Means for solving the problem]

[0005] The present invention solves the above problems by the following means.

[0006] The system includes a means for receiving voice data or text data from a user, a means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis, and a means for saving and managing the analysis results. It also includes a means for updating and developing a character's attributes based on the analysis results and a means for adding points to the user's account. It also includes a means for generating a character using a generative AI model based on character customization options selected by the user, and a means for anonymously communicating with other users based on the user's emotional state. This allows users to express their emotions and receive feedback, promoting positive emotions and reducing feelings of loneliness.

[0007] "User" refers to an individual entity that uses this system.

[0008] "Voice data" refers to data input by a user via voice.

[0009] "Text data" refers to data entered by a user through characters.

[0010] "Natural language processing" refers to technology for analyzing text data and understanding its content and emotions.

[0011] "Voice analysis" refers to the technology of converting voice data into text and analyzing its content and emotions.

[0012] "Sentiment analysis" refers to the process of identifying a user's emotions using natural language processing and / or speech analysis.

[0013] "Storage and management" refers to the operation of storing analysis results and other data in a database or the like, so that they can be accessed and updated as needed.

[0014] "Character" refers to a virtual entity that is generated on the system and provides interaction and feedback to the user.

[0015] "Attributes" refer to the specific characteristics or skills that a character possesses.

[0016] "Growing" refers to the process of evolving a character's attributes and changing them based on the user's activities and emotions.

[0017] "Points" refer to numerical rewards awarded based on a user's actions and emotions.

[0018] "Generative AI Model" refers to the artificial intelligence algorithms used to generate a virtual character based on selected options.

[0019] "Anonymous communication" refers to a system that allows users to interact with other users without revealing their personal information.

[0020] "Feedback" refers to information that encourages behavioral improvements and emotional changes by providing users with analysis results and system responses. [Brief explanation of the drawings]

[0021] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0022] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0023] First, the terms used in the following description will be explained.

[0024] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0025] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0026] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0027] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0028] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0032] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0033] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0034] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0035] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0036] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0039] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0040] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0041] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0042] The present invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards based on the results. A detailed explanation of how to implement this system is provided below.

[0043] System Overview

[0044] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[0045] Receiving voice and text data

[0046] Emotion analysis

[0047] Character Generation and Growth

[0048] Point reward system

[0049] Anonymous communication feature

[0050] Receiving voice and text data

[0051] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0052] Examples:

[0053] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0054] Emotion analysis

[0055] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0056] Examples:

[0057] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0058] Character Generation and Growth

[0059] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0060] Examples:

[0061] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0062] Point reward system

[0063] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0064] Examples:

[0065] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0066] Anonymous communication feature

[0067] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0068] Examples:

[0069] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[0070] The system described herein analyzes users' emotions and promotes positive emotions to address the increasing problem of lonely deaths, allowing users to manage their emotions and reduce feelings of social isolation through positive activities.

[0071] The processing flow will be explained below.

[0072] Step 1:

[0073] The user uses the device to open an application and selects voice input mode or text input mode.

[0074] Step 2:

[0075] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[0076] Step 3:

[0077] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[0078] Step 4:

[0079] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[0080] Step 5:

[0081] The server uses a natural language processing (NLP) engine to analyze the text data. In the case of voice data, it is first converted into text by a voice analysis engine, and then analyzed by the NLP engine. As a result of the analysis, an emotion tag (e.g., happy, sad) is generated.

[0082] Step 6:

[0083] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[0084] Step 7:

[0085] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[0086] Step 8:

[0087] The server updates the character's attributes based on growth points, determines new skills and changes, and generates updated character data.

[0088] Step 9:

[0089] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[0090] Step 10:

[0091] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[0092] Step 11:

[0093] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[0094] Step 12:

[0095] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[0096] Step 13:

[0097] When a user enters an emotional state that allows anonymous communication through the terminal, the server identifies other users in the same emotional state and creates an anonymous chat room. The terminal displays chat room information to the user.

[0098] Step 14:

[0099] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[0100] Example 1

[0101] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0102] Currently, many people feel lonely and socially isolated, which has led to an increase in the problem of lonely deaths. Existing solutions have not been effective enough to address this issue. Therefore, there is a need for a system that can promote positive emotions and social interaction among users.

[0103] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0104] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or speech analysis, and means for updating and developing the character's attributes based on the analysis results, thereby enabling accurate analysis of the user's emotional state in real time, promoting positive emotions, and even social interaction with other users through anonymous communication.

[0105] "Voice data" means digitized voice information provided by a user through voice input.

[0106] "Text data" refers to character information provided by a user through character input.

[0107] "Natural language processing" is a technology that allows machines to understand and analyze human language.

[0108] "Voice analysis" is a technology that analyzes voice data and identifies its characteristics and content.

[0109] "Analyzing emotions" refers to the process of analyzing received audio or text data to identify the user's emotional state therein.

[0110] "Updating and developing the character's attributes" means changing the appearance, skills, and characteristics of the virtual character based on the results of the user's emotional analysis.

[0111] "Adding points" means that the system adds a certain number of points to the user's account.

[0112] "Anonymous communication" is a feature that allows users to interact with other users without revealing their true identity.

[0113] "Generative AI model" refers to an artificial intelligence model used to generate characters and other elements.

[0114] A "cloud server" is a server infrastructure provided over the Internet.

[0115] MODE FOR CARRYING OUT THE INVENTION

[0116] This invention relates to an "emotion analysis application system" that analyzes a user's emotions. This system determines the user's emotional state and, based on the results, changes the attributes of a virtual character, awards points, and promotes anonymous communication. This system is primarily composed of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud.

[0117] Hardware and Software Configuration

[0118] The system includes the following hardware and software:

[0119] User devices: smartphones, tablets, computers

[0120] Server: Cloud server (e.g. AWS, Google Cloud)

[0121] Natural Language Processing Engine: Transformer-based NLP models (e.g., BERT, GPT-3)

[0122] Generative AI models: GANs (generative artificial network), Transformer models

[0123] Speech analysis engine: Google Cloud Speech-to-Text API, Amazon Transcribe

[0124] System Operation Overview

[0125] 1. A user uses a device to open an application that provides a voice or text input interface.

[0126] 2. The user enters voice or text data, for example, entering the text message "Today was a fun day."

[0127] 3. The device temporarily stores the data entered by the user and then sends the data to a server in the cloud.

[0128] 4. The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, and generates an emotion tag as a result of the analysis.

[0129] 5. The server updates the attributes of the virtual character based on the analysis results, allowing the character to grow. Every time the user expresses positive emotions, the character acquires new skills and changes its appearance.

[0130] 6. The server will calculate points based on the sentiment analysis results and add them to the user's account, which can be used for character customization and special rewards.

[0131] 7. The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0132] Specific examples

[0133] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0134] The server receives text data such as "Today was a fun day" and analyzes it using a natural language processing (NLP) engine to generate a positive emotion tag for "fun."

[0135] By continuously acquiring positive emotion tags, the virtual character will learn new dance skills and change its appearance to become brighter.

[0136] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0137] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[0138] Prompt Sentence Examples

[0139] Example prompt 1: "The user types, 'Today was a good day.' Classify this as a positive sentiment tag."

[0140] Example prompt 2: "The user types, 'I had a terrible day today.' Classify this as a negative sentiment tag."

[0141] Example prompt 3: "The user repeatedly expressed the emotion 'fun'. As a result, we'll add a new dance skill to the virtual character and brighten up its appearance."

[0142] In this way, the entire system works together to analyze the user's emotional state and provide feedback and rewards, ultimately helping users to reduce their sense of social isolation through positive activities.

[0143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0144] Step 1:

[0145] A user opens an application using a terminal, which provides an interface for receiving input voice or text data.

[0146] Input: User speech and text input.

[0147] Output: Temporarily saved audio or text data.

[0148] What happens: The user types in the text "Today was a fun day."

[0149] Step 2:

[0150] The device sends the voice data or text data entered by the user to a server on the cloud.

[0151] Input: Temporarily saved audio or text data.

[0152] Output: The data sent to the server.

[0153] Specific operation: The device sends text data saying "Today was a fun day."

[0154] Step 3:

[0155] The server analyzes the received voice data or text data using a natural language processing engine and a voice analysis engine.

[0156] Input: The audio or text data received by the server.

[0157] Output: Sentiment tags as the analysis results.

[0158] Specific operation: The server analyzes the text data "Today was a fun day" using an NLP engine and generates a positive emotion tag for "fun."

[0159] Step 4:

[0160] The server stores and manages the analysis results, and also uses them to update the character's attributes.

[0161] Input: Sentiment tags as analysis results.

[0162] Output: Updated character attributes.

[0163] Specific behavior: When a positive emotion tag is generated, the character will learn new skills and change their appearance.

[0164] Step 5:

[0165] The server calculates points based on the emotion analysis results and adds them to the user's account.

[0166] Input: Emotion tags as analysis results and user account information.

[0167] Output: The added points.

[0168] Specific Action: Add 10 points based on positive emotions.

[0169] Step 6:

[0170] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[0171] Input: Sentiment tags as analysis results.

[0172] Output:Anonymous chat room created.

[0173] Specific operation: For users who feel lonely, create an anonymous chat room with other users who share the same feelings.

[0174] Through these processing steps, the system analyzes the user's emotions and provides feedback and rewards, thereby promoting positive social interactions.

[0175] (Application example 1)

[0176] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0177] The present invention aims to provide a system that reduces the sense of social isolation and promotes positive emotions in elderly people living alone and users who feel lonely. In particular, the system has a function to monitor the user's emotional state and notify family members or security service providers as necessary, thereby reducing the risk of lonely death.

[0178] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0179] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis, means for saving and managing the analysis results, means for updating and developing character attributes based on the analysis results, means for adding points to the user's account, and means for generating an alert and notifying a specific recipient if the analysis results are negative. This makes it possible to grasp the user's emotional state, promote positive emotions, and provide appropriate support as needed.

[0180] "Voice data" is a digital recording of a user's voice uttered to an application.

[0181] "Text data" refers to character information that a user inputs to an application.

[0182] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0183] "Speech analysis" is a technology that uses digital signal processing technology to analyze voice data and understand its content and characteristics.

[0184] An "emotion tag" is a label that indicates an emotional state analyzed from audio data or text data.

[0185] A "character" is a virtual being that is generated and grows according to the user's emotional state.

[0186] A "generative AI model" is a model that has been trained using artificial intelligence techniques to perform a specific task.

[0187] "Attributes" are the characteristics and traits that a character possesses.

[0188] "Points" are virtual rewards that users can earn by expressing positive emotions.

[0189] An "alert" is a warning that notifies a specific recipient when a user's emotional state is negative.

[0190] "Recipients" are family members or security service providers who are notified depending on the user's emotional state.

[0191] MODE FOR CARRYING OUT THE INVENTION

[0192] The present invention relates to a user emotion monitoring security system for reducing the risk of lonely death. This system has the function of analyzing the user's emotional state and notifying the user, their family, or a security service provider as necessary.

[0193] System configuration

[0194] The system of the present invention consists of the following main components:

[0195] 1. User terminal: A device for inputting user voice data or text data. Specifically, a mobile device such as a smartphone or tablet is used.

[0196] 2. Cloud server: Analyzes and stores data, and provides APIs.

[0197] 3. Natural Language Processing (NLP) Engine: An NLP engine is used to analyze the received text data and identify the user's sentiment. An example is Google Cloud Natural Language API.

[0198] 4. Speech analysis engine: Used to analyze voice data. An example is IBM Watson Speech to Text.

[0199] 5. Generative AI model: Responsible for character generation and development. For example, OpenAI's GPT series is used for this part.

[0200] 6. Database: A system for storing the results of sentiment analysis and user data.

[0201] System Operation

[0202] 1. Receiving voice and text data

[0203] The user uses the device to input voice or text data, which is then sent to the cloud server. For example, if a user voice-types "I'm feeling a little down today" into their smartphone, this data is immediately sent to the cloud server.

[0204] 2. Emotion analysis

[0205] The server uses an NLP engine and a speech analysis engine to analyze the received data, which generates an emotion tag. For example, if the user says "I'm feeling a little down today," a negative emotion tag is generated.

[0206] 3. Character Creation and Development

[0207] The generative AI model generates a character based on the user's customization options. Furthermore, the character's attributes are updated and developed based on the results of emotion analysis. If a positive emotion tag is generated, the character will acquire new skills and other changes.

[0208] 4. Point reward system

[0209] Based on the user's positive sentiment analysis, points are calculated and added to the user's account, which can be used to customize characters and earn special rewards.

[0210] 5. Security Alert System

[0211] If the analysis result is negative, the server generates an alert and notifies specific recipients (family members or security service providers). For example, if a user shows negative emotions for three consecutive days, the server notifies family members that "the user may have been depressed recently."

[0212] Specific examples

[0213] When a user types "I've been feeling a bit tired lately" into their smartphone, this information is sent to a cloud server and analyzed by an NLP engine. A negative emotion tag is attached, and the generative AI model provides the user with feedback such as "Try to get some rest today." If a negative emotion tag is generated for three consecutive days, an alert is sent to family members.

[0214] Prompt Sentence Examples

[0215] Input: The user is feeling depressed

[0216] Output: Generate positive feedback and check if a security alert is triggered

[0217] This allows the system to manage the user's emotions and provide appropriate support to family and related parties when necessary.

[0218] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0219] Step 1:

[0220] The user inputs voice or text data into the device. For example, when the user opens a smartphone application and inputs "I'm a little tired today" by voice or text, this data is generated.

[0221] Input: User speaks or enters text

[0222] Output: Audio data or text data

[0223] Step 2:

[0224] The device sends the input voice data or text data to the cloud server, which then transfers the data to the cloud server using a secure communication protocol.

[0225] Input: Audio or text data

[0226] Output: Data sent to the cloud server

[0227] Step 3:

[0228] The server analyzes the received voice data with a voice analysis engine and the text data with a natural language processing (NLP) engine. The analysis generates a specific emotion tag (e.g., "negative").

[0229] Input: Audio or text data sent to the server

[0230] Output: Emotion tag

[0231] Step 4:

[0232] The server stores and manages the emotion tags obtained as a result of emotion analysis. The original data is also recorded in the database along with the emotion tags.

[0233] Input: emotion tag

[0234] Output: Emotion tags and raw data stored in the database

[0235] Step 5:

[0236] Based on the emotion analysis results, the server uses a generative AI model to generate and update the character and develop its attributes. The generative AI model applies new skills, changes to appearance, etc. to the character based on prompts.

[0237] Input: emotion tag

[0238] Output: Updated character

[0239] Step 6:

[0240] The server calculates points based on positive sentiment analysis results and adds them to the user's account. For example, if a user types "I had fun today," 10 points will be added.

[0241] Input: Positive sentiment tag

[0242] Output: Updated user points

[0243] Step 7:

[0244] If the sentiment analysis result is negative, the server generates an alert and notifies specific recipients (e.g., family members or security service providers) so that necessary assistance can be provided quickly.

[0245] Input: Negative sentiment tag

[0246] Output: Alert notification sent

[0247] This will create a system that analyzes the user's emotional state throughout all steps and provides appropriate feedback and necessary assistance.

[0248] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0249] The present invention provides an "emotion analysis application system" that can encourage positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards. In particular, by combining it with an emotion engine, it achieves real-time, highly accurate emotion analysis. A detailed explanation of how to implement this system is provided below.

[0250] System Overview

[0251] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[0252] Receiving voice and text data

[0253] Emotion analysis

[0254] Character Generation and Growth

[0255] Point reward system

[0256] Anonymous communication feature

[0257] Emotion Engine

[0258] Receiving voice and text data

[0259] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0260] Examples:

[0261] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0262] Emotion analysis

[0263] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0264] Examples:

[0265] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0266] Real-time analysis of emotion engine

[0267] The server uses an emotion engine to analyze the user's voice and text data in real time, and the identified emotion data is immediately reflected in the user profile and stored in a database.

[0268] Examples:

[0269] When a user inputs the text "I'm very sad," the server's emotion engine analyzes the emotion "sad" in real time and stores the results in a database.

[0270] Character Generation and Growth

[0271] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0272] Examples:

[0273] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0274] Point reward system

[0275] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0276] Examples:

[0277] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0278] Anonymous communication feature

[0279] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0280] Examples:

[0281] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[0282] Providing Feedback

[0283] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0284] Examples:

[0285] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[0286] The system described in this specification analyzes users' emotions and promotes positive emotions to address the growing problem of lonely deaths. This system allows users to manage their emotions and reduce feelings of social isolation through positive activities. Furthermore, the added emotion engine enables real-time, highly accurate emotion analysis, enabling more personalized feedback and support.

[0287] The processing flow will be explained below.

[0288] Step 1:

[0289] The user uses the device to open an application and selects voice input mode or text input mode.

[0290] Step 2:

[0291] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[0292] Step 3:

[0293] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[0294] Step 4:

[0295] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[0296] Step 5:

[0297] The server analyzes the voice and text data in real time using an emotion engine, which uses natural language processing (NLP) and speech analysis techniques to identify the user's emotions from the data.

[0298] Step 6:

[0299] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[0300] Step 7:

[0301] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[0302] Step 8:

[0303] The server updates the character's attributes based on growth points, determines new skills and appearance changes, and generates updated character data.

[0304] Step 9:

[0305] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[0306] Step 10:

[0307] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[0308] Step 11:

[0309] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[0310] Step 12:

[0311] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[0312] Step 13:

[0313] When a user uses the anonymous communication function based on their emotional state, the server identifies other users with the same emotional state and creates an anonymous chat room, and the terminal displays the chat room information to the user.

[0314] Step 14:

[0315] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0316] Step 15:

[0317] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[0318] Example 2

[0319] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0320] This invention relates to a system that analyzes users' emotions and promotes positive emotions in order to solve the problem of lonely deaths and improve users' mental health. However, conventional systems often have low accuracy in emotion analysis or difficulty in responding in real time. As a result, feedback and support to users are delayed, and effective mental support is not provided. Furthermore, features such as character development and anonymous communication between users are lacking, resulting in a lack of improvement in the user experience. This has led to the issue of difficulty in continuously eliciting positive emotions in users and the inability to alleviate feelings of social isolation.

[0321] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0322] In this invention, the server includes: means for receiving voice data or text data from a user; means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis; means for reflecting, saving, and managing the analysis results in real time; means for updating and developing a character's attributes based on the analysis results; means for calculating points based on the user's positive emotion analysis results and adding them to the user's account; means for generating and providing feedback to the user; means for generating a character based on character customization options selected by the user using a generative AI model; and means for providing opportunities for anonymous communication with other users based on the user's emotional state. This allows for highly accurate, real-time analysis of a user's emotions and providing personalized feedback and rewards, thereby promoting positive emotions and reducing feelings of social isolation.

[0323] "Voice data" is data input by a user using voice, and is used for emotion analysis.

[0324] "Text data" is data that is input by a user using characters and is used for emotion analysis.

[0325] "Natural language processing" refers to the technology of analyzing and understanding human language using a computer program, and is used to extract emotions from user text data.

[0326] "Voice analysis" refers to the technology of analyzing voice data and extracting features, and is used to determine emotions from a user's voice data.

[0327] "Sentiment analysis" refers to the process of analyzing received audio or text data to identify a user's emotions.

[0328] "Database" refers to a system for systematically storing and managing information such as analyzed emotional data and user profiles.

[0329] A "character" is a virtual entity that a user selects or customizes, and whose attributes are updated and developed based on the results of emotion analysis.

[0330] A "generative AI model" refers to a technology that uses artificial intelligence to generate appropriate output data for specific input data, in this case for character generation and customization.

[0331] A "point reward system" refers to a system that calculates points based on the results of analyzing a user's positive emotions and rewards the user.

[0332] "Feedback" refers to responses to the user, such as suggestions, encouragement, advice, etc., generated based on sentiment analysis.

[0333] "Anonymous communication" refers to a feature that provides users with the opportunity to interact with other users without revealing their identity.

[0334] The present invention relates to an "emotion analysis system" that analyzes a user's emotions and promotes positive emotions. Detailed embodiments of the present invention will be described below.

[0335] System Configuration

[0336] This system consists of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud. The main functions of this system are as follows:

[0337] 1. Receiving voice and text data

[0338] 2. Emotion analysis

[0339] 3. Character Creation and Development

[0340] 4. Point reward system

[0341] 5. Anonymous communication feature

[0342] 6. Providing Feedback

[0343] Receiving voice and text data

[0344] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0345] Examples:

[0346] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0347] Emotion analysis

[0348] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0349] Examples:

[0350] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0351] Character Generation and Growth

[0352] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0353] Examples:

[0354] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0355] Point reward system

[0356] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0357] Examples:

[0358] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0359] Anonymous communication feature

[0360] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0361] Examples:

[0362] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[0363] Providing Feedback

[0364] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0365] Examples:

[0366] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[0367] Example prompts for generative AI models

[0368] Possible prompts to input to a generative AI model include:

[0369] "When a user inputs positive emotions, generate new skills or changes to the appearance of the virtual character based on that emotion."

[0370] As described above, with the above-mentioned configuration and specific examples, the present invention provides a system that can analyze a user's emotions with high accuracy and promote positive emotions, thereby reducing feelings of social isolation.

[0371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0372] Step 1:

[0373] The user inputs voice or text data.

[0374] A user uses a terminal to input a voice or text message. For example, a user opens an application and inputs the text "Today was a fun day." This input data (voice data or text data) is sent to the next processing step.

[0375] Step 2:

[0376] The terminal sends the input data to the server.

[0377] The device sends the voice or text data entered by the user to the server, where it can be analyzed in the next processing step. The input here is the user's voice or text data, and the output is the data sent to the server.

[0378] Step 3:

[0379] The server analyzes the voice or text data using a natural language processing (NLP) engine and a voice analysis engine.

[0380] The server analyzes the received data using an NLP engine or speech analysis engine to identify the user's emotional state. For example, it generates a positive emotion tag "fun" for the text data "Today was a fun day." The input is the data sent to the server, and the output is the generated emotion tag.

[0381] Step 4:

[0382] The server stores the analysis results in a database.

[0383] The emotion tags generated by the server are saved in a database in real time by the emotion engine. This saving process reflects the analysis results in the user profile. The input is the generated emotion tags, and the output is the user's emotion data saved in the database.

[0384] Step 5:

[0385] The server generates and updates characters using generative AI models.

[0386] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes in real time based on the results of emotional analysis. Each time the user expresses positive emotion, the character acquires a new skill or changes appearance. The input is the emotional analysis results and customization options, and the output is the generated or updated character.

[0387] Step 6:

[0388] The server calculates points based on positive sentiment analysis results and adds them to the user's account.

[0389] The server calculates points based on the user's positive sentiment analysis result and adds them to the user's account. For example, if the user enters "Today is a great day," the server adds 10 points based on this sentiment. The input is the positive sentiment analysis result, and the output is the added points.

[0390] Step 7:

[0391] The terminal notifies the user of the point information.

[0392] The terminal notifies the user of the point information received from the server. For example, a message saying "10 points have been added to your account" is displayed. The input is the added point information, and the output is the message notified to the user.

[0393] Step 8:

[0394] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[0395] The server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results. This function allows users to anonymously interact with other users and promote positive emotions. The input is the user's emotion analysis results, and the output is anonymous chat room information.

[0396] Step 9:

[0397] The terminal displays the anonymous chat room information to the user.

[0398] The terminal displays the anonymous chat room information received from the server to the user. For example, a message saying "An anonymous chat room has been created" is displayed, and the user can now access the chat room. The input is the anonymous chat room information, and the output is the message displayed to the user.

[0399] Step 10:

[0400] The server provides appropriate feedback to the user.

[0401] The server generates and provides feedback such as encouragement or advice to the user based on the analysis results from the emotion engine. For example, if the user inputs "sad," the server generates the feedback "Why don't you try doing something fun today?" The input is the analysis result, and the output is the generated feedback message.

[0402] Step 11:

[0403] The device displays the feedback to the user.

[0404] The terminal displays to the user the feedback message it receives from the server, for example, "Why not try something fun today?" The input is the feedback message, and the output is the message displayed to the user.

[0405] In this way, the entire system works together to analyze the user's emotions and carry out a series of processes to promote positive emotions.

[0406] (Application example 2)

[0407] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0408] In modern society, the number of people experiencing loneliness and isolation is increasing, and this has become a serious problem. In particular, there is a need to prevent lonely deaths, but emotional care is often inadequate. In addition, there is a lack of approaches to improving emotional situations, so there is a need for methods to promote positive emotions in daily life.

[0409] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0410] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions in the received voice data or text data using natural language processing or voice analysis, means for suggesting optimal meals to the user based on the analysis results, and means for providing discount coupons based on the positive emotion analysis results. This makes it possible to analyze the user's emotional state, promote positive emotions through meals, and alleviate feelings of loneliness and isolation.

[0411] "Voice data" refers to data that is a digital recording of a user's voice.

[0412] "Text data" refers to digital data containing text information entered by a user.

[0413] "Natural language processing" is the field of computer science that aims to understand and analyze human language.

[0414] "Voice analysis" is a technology that analyzes voice data and extracts meaning and emotions from it.

[0415] "Emotion analysis" is a technology that identifies emotions from voice data and text data.

[0416] A "character" is a virtual being or avatar that can be customized by a user.

[0417] "Attributes" are specific characteristics or traits that a character possesses.

[0418] "Growth" refers to the process by which a character evolves based on the user's actions and emotions, gaining new skills and appearances.

[0419] "Points" are rewards awarded based on a user's positive behavior and the results of emotional analysis.

[0420] A "meal" is any food or drink consumed by a user.

[0421] A "discount coupon" is a digital or physical coupon that entitles a user to a service or product at a discounted price.

[0422] This invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system grasps the user's emotional state through analysis of voice and text data and provides appropriate feedback. It also makes meal suggestions and offers discount coupons based on the analysis results.

[0423] System configuration

[0424] This system mainly consists of a user device and a server. User devices include smartphones, tablets, and computers. The server is located on the cloud and is responsible for analyzing voice and text data, managing data, and providing feedback.

[0425] Receiving voice and text data

[0426] Using an application on the device, users input their emotions and state of mind through voice or text, and the device immediately transmits this data to the server.

[0427] Specific examples

[0428] A user opens the application on their smartphone and types in the text, "Today was a fun day." The device immediately sends this data to the server.

[0429] Emotion analysis

[0430] The server receives the transmitted voice or text data and uses a natural language processing (NLP) engine or a voice analysis engine to analyze the user's emotions and generate emotion tags such as positive, negative, or neutral.

[0431] Specific examples

[0432] The text data "Today was a fun day" is analyzed using an NLP engine to generate a positive emotion tag for "fun."

[0433] Optimal meal suggestions

[0434] Based on the analysis results, the server uses a generative AI model to suggest the best meal to improve the user's emotional state, presenting specific meal menus according to the user's emotions.

[0435] Specific examples

[0436] If you type "I'm feeling a little lonely today," it will suggest a warm soup or a nutritious salad.

[0437] Offering discount coupons

[0438] If a positive emotion tag is obtained, the server will offer the user a discount coupon that can be used on their next meal order.

[0439] Specific examples

[0440] If a user types "Today is a great day," the server will offer them a 10% off coupon.

[0441] Hardware and software used

[0442] Hardware: smartphones, tablets, computers

[0443] Software: Natural language processing engine (NLP engine), speech analysis engine, generative AI model

[0444] Example prompts for generative AI models

[0445] A user enters, "I'm feeling a bit tired and lonely today." Based on this emotion, please suggest dishes that will improve the user's mood. For example, you could recommend meals such as "warm soup," "nutritious salad," or "protein bar that's perfect for replenishing energy." Please include a reason for your recommendation.

[0446] As described above, the emotion analysis application system can analyze the user's emotional state in real time and provide appropriate feedback, meal suggestions, and discount coupons based on that analysis, thereby promoting positive emotions and helping to reduce feelings of loneliness and isolation.

[0447] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0448] Step 1:

[0449] A user starts the application using a device such as a smartphone or tablet. The user inputs their emotional state by voice or text. The input data (voice data or text data) is temporarily stored on the device.

[0450] Input: Text or voice when the user inputs their emotional state.

[0451] Output: Audio or text data stored on the device.

[0452] Action: The user enters the text "Today was a fun day."

[0453] Step 2:

[0454] The device sends the input voice or text data to the server, where the data is encrypted and transmitted securely.

[0455] Input: Voice or text data stored on the device.

[0456] Output: The audio or text data sent to the server.

[0457] Operation: The device sends text data such as "Today was a fun day" to the server.

[0458] Step 3:

[0459] The server analyzes the received voice or text data using a natural language processing (NLP) engine or speech analysis engine for sentiment analysis, which generates sentiment tags such as positive, negative, and neutral.

[0460] Input: The audio or text data sent to the server.

[0461] Output: A sentiment tag (e.g., "fun").

[0462] How it works: The server analyzes the text data "Today was a fun day" and generates a positive emotion tag for "fun."

[0463] Step 4:

[0464] The server uses a generative AI model to create prompts to suggest optimal meals for the user based on the analyzed emotion tags, and then uses the generative AI model to generate specific meal menus.

[0465] Input: Sentiment tag (positive, negative, neutral, etc.).

[0466] Output: Specific meal menu suggestions.

[0467] How it works: If the emotion tag is "fun," the generative AI model will suggest meals such as "hot soup" or "nutritious salad."

[0468] Step 5:

[0469] If the server obtains a positive emotion tag, it generates and sends the user a discount coupon that can be used on their next meal order.

[0470] Input: Positive sentiment tags.

[0471] Output: Discount coupon.

[0472] What it does: If the server receives the input "Today is a great day," it generates a 10% off coupon and sends it to the user.

[0473] Step 6:

[0474] The server sends the meal menu prompt and discount coupon information to the user terminal, which displays the information for the user to check.

[0475] Input: Specific meal suggestions and discount coupons.

[0476] Output: Meal menu and coupons displayed on the user's device.

[0477] What it does: The device displays "Recommended Meal: Hot Soup" and "10% Off Coupon."

[0478] Through the above processing flow, the system analyzes users' emotions and provides optimal feedback, meal suggestions, and discount coupons.

[0479] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0480] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0481] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0482] [Second embodiment]

[0483] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0484] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0485] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0486] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0487] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0488] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0489] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0490] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0491] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0492] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0493] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0494] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0495] The present invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards based on the results. A detailed explanation of how to implement this system is provided below.

[0496] System Overview

[0497] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[0498] Receiving voice and text data

[0499] Emotion analysis

[0500] Character Generation and Growth

[0501] Point reward system

[0502] Anonymous communication feature

[0503] Receiving voice and text data

[0504] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0505] Examples:

[0506] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0507] Emotion analysis

[0508] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0509] Examples:

[0510] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0511] Character Generation and Growth

[0512] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0513] Examples:

[0514] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0515] Point reward system

[0516] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0517] Examples:

[0518] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0519] Anonymous communication feature

[0520] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0521] Examples:

[0522] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[0523] The system described herein analyzes users' emotions and promotes positive emotions to address the increasing problem of lonely deaths, allowing users to manage their emotions and reduce feelings of social isolation through positive activities.

[0524] The processing flow will be explained below.

[0525] Step 1:

[0526] The user uses the device to open an application and selects voice input mode or text input mode.

[0527] Step 2:

[0528] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[0529] Step 3:

[0530] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[0531] Step 4:

[0532] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[0533] Step 5:

[0534] The server uses a natural language processing (NLP) engine to analyze the text data. In the case of voice data, it is first converted into text by a voice analysis engine, and then analyzed by the NLP engine. As a result of the analysis, an emotion tag (e.g., happy, sad) is generated.

[0535] Step 6:

[0536] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[0537] Step 7:

[0538] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[0539] Step 8:

[0540] The server updates the character's attributes based on growth points, determines new skills and changes, and generates updated character data.

[0541] Step 9:

[0542] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[0543] Step 10:

[0544] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[0545] Step 11:

[0546] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[0547] Step 12:

[0548] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[0549] Step 13:

[0550] When a user enters an emotional state that allows anonymous communication through the terminal, the server identifies other users in the same emotional state and creates an anonymous chat room. The terminal displays chat room information to the user.

[0551] Step 14:

[0552] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[0553] Example 1

[0554] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0555] Currently, many people feel lonely and socially isolated, which has led to an increase in the problem of lonely deaths. Existing solutions have not been effective enough to address this issue. Therefore, there is a need for a system that can promote positive emotions and social interaction among users.

[0556] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0557] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or speech analysis, and means for updating and developing the character's attributes based on the analysis results, thereby enabling accurate analysis of the user's emotional state in real time, promoting positive emotions, and even social interaction with other users through anonymous communication.

[0558] "Voice data" means digitized voice information provided by a user through voice input.

[0559] "Text data" refers to character information provided by a user through character input.

[0560] "Natural language processing" is a technology that allows machines to understand and analyze human language.

[0561] "Voice analysis" is a technology that analyzes voice data and identifies its characteristics and content.

[0562] "Analyzing emotions" refers to the process of analyzing received audio or text data to identify the user's emotional state therein.

[0563] "Updating and developing the character's attributes" means changing the appearance, skills, and characteristics of the virtual character based on the results of the user's emotional analysis.

[0564] "Adding points" means that the system adds a certain number of points to the user's account.

[0565] "Anonymous communication" is a feature that allows users to interact with other users without revealing their true identity.

[0566] "Generative AI model" refers to an artificial intelligence model used to generate characters and other elements.

[0567] A "cloud server" is a server infrastructure provided over the Internet.

[0568] MODE FOR CARRYING OUT THE INVENTION

[0569] This invention relates to an "emotion analysis application system" that analyzes a user's emotions. This system determines the user's emotional state and, based on the results, changes the attributes of a virtual character, awards points, and promotes anonymous communication. This system is primarily composed of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud.

[0570] Hardware and Software Configuration

[0571] The system includes the following hardware and software:

[0572] User devices: smartphones, tablets, computers

[0573] Server: Cloud server (e.g. AWS, Google Cloud)

[0574] Natural Language Processing Engine: Transformer-based NLP models (e.g., BERT, GPT-3)

[0575] Generative AI models: GANs (generative artificial network), Transformer models

[0576] Speech analysis engine: Google Cloud Speech-to-Text API, Amazon Transcribe

[0577] System Operation Overview

[0578] 1. A user uses a device to open an application that provides a voice or text input interface.

[0579] 2. The user enters voice or text data, for example, entering the text message "Today was a fun day."

[0580] 3. The device temporarily stores the data entered by the user and then sends the data to a server in the cloud.

[0581] 4. The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, and generates an emotion tag as a result of the analysis.

[0582] 5. The server updates the attributes of the virtual character based on the analysis results, allowing the character to grow. Every time the user expresses positive emotions, the character acquires new skills and changes its appearance.

[0583] 6. The server will calculate points based on the sentiment analysis results and add them to the user's account, which can be used for character customization and special rewards.

[0584] 7. The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0585] Specific examples

[0586] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0587] The server receives text data such as "Today was a fun day" and analyzes it using a natural language processing (NLP) engine to generate a positive emotion tag for "fun."

[0588] By continuously acquiring positive emotion tags, the virtual character will learn new dance skills and change its appearance to become brighter.

[0589] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0590] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[0591] Prompt Sentence Examples

[0592] Example prompt 1: "The user types, 'Today was a good day.' Classify this as a positive sentiment tag."

[0593] Example prompt 2: "The user types, 'I had a terrible day today.' Classify this as a negative sentiment tag."

[0594] Example prompt 3: "The user repeatedly expressed the emotion 'fun'. As a result, we'll add a new dance skill to the virtual character and brighten up its appearance."

[0595] In this way, the entire system works together to analyze the user's emotional state and provide feedback and rewards, ultimately helping users to reduce their sense of social isolation through positive activities.

[0596] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0597] Step 1:

[0598] A user opens an application using a terminal, which provides an interface for receiving input voice or text data.

[0599] Input: User speech and text input.

[0600] Output: Temporarily saved audio or text data.

[0601] What happens: The user types in the text "Today was a fun day."

[0602] Step 2:

[0603] The device sends the voice data or text data entered by the user to a server on the cloud.

[0604] Input: Temporarily saved audio or text data.

[0605] Output: The data sent to the server.

[0606] Specific operation: The device sends text data saying "Today was a fun day."

[0607] Step 3:

[0608] The server analyzes the received voice data or text data using a natural language processing engine and a voice analysis engine.

[0609] Input: The audio or text data received by the server.

[0610] Output: Sentiment tags as the analysis results.

[0611] Specific operation: The server analyzes the text data "Today was a fun day" using an NLP engine and generates a positive emotion tag for "fun."

[0612] Step 4:

[0613] The server stores and manages the analysis results, and also uses them to update the character's attributes.

[0614] Input: Sentiment tags as analysis results.

[0615] Output: Updated character attributes.

[0616] Specific behavior: When a positive emotion tag is generated, the character will learn new skills and change their appearance.

[0617] Step 5:

[0618] The server calculates points based on the emotion analysis results and adds them to the user's account.

[0619] Input: Emotion tags as analysis results and user account information.

[0620] Output: The added points.

[0621] Specific Action: Add 10 points based on positive emotions.

[0622] Step 6:

[0623] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[0624] Input: Sentiment tags as analysis results.

[0625] Output:Anonymous chat room created.

[0626] Specific operation: For users who feel lonely, create an anonymous chat room with other users who share the same feelings.

[0627] Through these processing steps, the system analyzes the user's emotions and provides feedback and rewards, thereby promoting positive social interactions.

[0628] (Application example 1)

[0629] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0630] The present invention aims to provide a system that reduces the sense of social isolation and promotes positive emotions in elderly people living alone and users who feel lonely. In particular, the system has a function to monitor the user's emotional state and notify family members or security service providers as necessary, thereby reducing the risk of lonely death.

[0631] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0632] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis, means for saving and managing the analysis results, means for updating and developing character attributes based on the analysis results, means for adding points to the user's account, and means for generating an alert and notifying a specific recipient if the analysis results are negative. This makes it possible to grasp the user's emotional state, promote positive emotions, and provide appropriate support as needed.

[0633] "Voice data" is a digital recording of a user's voice uttered to an application.

[0634] "Text data" refers to character information that a user inputs to an application.

[0635] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[0636] "Speech analysis" is a technology that uses digital signal processing technology to analyze voice data and understand its content and characteristics.

[0637] An "emotion tag" is a label that indicates an emotional state analyzed from audio data or text data.

[0638] A "character" is a virtual being that is generated and grows according to the user's emotional state.

[0639] A "generative AI model" is a model that has been trained using artificial intelligence techniques to perform a specific task.

[0640] "Attributes" are the characteristics and traits that a character possesses.

[0641] "Points" are virtual rewards that users can earn by expressing positive emotions.

[0642] An "alert" is a warning that notifies a specific recipient when a user's emotional state is negative.

[0643] "Recipients" are family members or security service providers who are notified depending on the user's emotional state.

[0644] MODE FOR CARRYING OUT THE INVENTION

[0645] The present invention relates to a user emotion monitoring security system for reducing the risk of lonely death. This system has the function of analyzing the user's emotional state and notifying the user, their family, or a security service provider as necessary.

[0646] System configuration

[0647] The system of the present invention consists of the following main components:

[0648] 1. User terminal: A device for inputting user voice data or text data. Specifically, a mobile device such as a smartphone or tablet is used.

[0649] 2. Cloud server: Analyzes and stores data, and provides APIs.

[0650] 3. Natural Language Processing (NLP) Engine: An NLP engine is used to analyze the received text data and identify the user's sentiment. An example is Google Cloud Natural Language API.

[0651] 4. Speech analysis engine: Used to analyze voice data. An example is IBM Watson Speech to Text.

[0652] 5. Generative AI model: Responsible for character generation and development. For example, OpenAI's GPT series is used for this part.

[0653] 6. Database: A system for storing the results of sentiment analysis and user data.

[0654] System Operation

[0655] 1. Receiving voice and text data

[0656] The user uses the device to input voice or text data, which is then sent to the cloud server. For example, if a user voice-types "I'm feeling a little down today" into their smartphone, this data is immediately sent to the cloud server.

[0657] 2. Emotion analysis

[0658] The server uses an NLP engine and a speech analysis engine to analyze the received data, which generates an emotion tag. For example, if the user says "I'm feeling a little down today," a negative emotion tag is generated.

[0659] 3. Character Creation and Development

[0660] The generative AI model generates a character based on the user's customization options. Furthermore, the character's attributes are updated and developed based on the results of emotion analysis. If a positive emotion tag is generated, the character will acquire new skills and other changes.

[0661] 4. Point reward system

[0662] Based on the user's positive sentiment analysis, points are calculated and added to the user's account, which can be used to customize characters and earn special rewards.

[0663] 5. Security Alert System

[0664] If the analysis result is negative, the server generates an alert and notifies specific recipients (family members or security service providers). For example, if a user shows negative emotions for three consecutive days, the server notifies family members that "the user may have been depressed recently."

[0665] Specific examples

[0666] When a user types "I've been feeling a bit tired lately" into their smartphone, this information is sent to a cloud server and analyzed by an NLP engine. A negative emotion tag is attached, and the generative AI model provides the user with feedback such as "Try to get some rest today." If a negative emotion tag is generated for three consecutive days, an alert is sent to family members.

[0667] Prompt Sentence Examples

[0668] Input: The user is feeling depressed

[0669] Output: Generate positive feedback and check if a security alert is triggered

[0670] This allows the system to manage the user's emotions and provide appropriate support to family and related parties when necessary.

[0671] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0672] Step 1:

[0673] The user inputs voice or text data into the device. For example, when the user opens a smartphone application and inputs "I'm a little tired today" by voice or text, this data is generated.

[0674] Input: User speaks or enters text

[0675] Output: Audio data or text data

[0676] Step 2:

[0677] The device sends the input voice data or text data to the cloud server, which then transfers the data to the cloud server using a secure communication protocol.

[0678] Input: Audio or text data

[0679] Output: Data sent to the cloud server

[0680] Step 3:

[0681] The server analyzes the received voice data with a voice analysis engine and the text data with a natural language processing (NLP) engine. The analysis generates a specific emotion tag (e.g., "negative").

[0682] Input: Audio or text data sent to the server

[0683] Output: Emotion tag

[0684] Step 4:

[0685] The server stores and manages the emotion tags obtained as a result of emotion analysis. The original data is also recorded in the database along with the emotion tags.

[0686] Input: emotion tag

[0687] Output: Emotion tags and raw data stored in the database

[0688] Step 5:

[0689] Based on the emotion analysis results, the server uses a generative AI model to generate and update the character and develop its attributes. The generative AI model applies new skills, changes to appearance, etc. to the character based on prompts.

[0690] Input: emotion tag

[0691] Output: Updated character

[0692] Step 6:

[0693] The server calculates points based on positive sentiment analysis results and adds them to the user's account. For example, if a user types "I had fun today," 10 points will be added.

[0694] Input: Positive sentiment tag

[0695] Output: Updated user points

[0696] Step 7:

[0697] If the sentiment analysis result is negative, the server generates an alert and notifies specific recipients (e.g., family members or security service providers) so that necessary assistance can be provided quickly.

[0698] Input: Negative sentiment tag

[0699] Output: Alert notification sent

[0700] This will create a system that analyzes the user's emotional state throughout all steps and provides appropriate feedback and necessary assistance.

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

[0702] The present invention provides an "emotion analysis application system" that can encourage positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards. In particular, by combining it with an emotion engine, it achieves real-time, highly accurate emotion analysis. A detailed explanation of how to implement this system is provided below.

[0703] System Overview

[0704] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[0705] Receiving voice and text data

[0706] Emotion analysis

[0707] Character Generation and Growth

[0708] Point reward system

[0709] Anonymous communication feature

[0710] Emotion Engine

[0711] Receiving voice and text data

[0712] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0713] Examples:

[0714] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0715] Emotion analysis

[0716] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0717] Examples:

[0718] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0719] Real-time analysis of emotion engine

[0720] The server uses an emotion engine to analyze the user's voice and text data in real time, and the identified emotion data is immediately reflected in the user profile and stored in a database.

[0721] Examples:

[0722] When a user inputs the text "I'm very sad," the server's emotion engine analyzes the emotion "sad" in real time and stores the results in a database.

[0723] Character Generation and Growth

[0724] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0725] Examples:

[0726] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0727] Point reward system

[0728] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0729] Examples:

[0730] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0731] Anonymous communication feature

[0732] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0733] Examples:

[0734] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[0735] Providing Feedback

[0736] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0737] Examples:

[0738] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[0739] The system described in this specification analyzes users' emotions and promotes positive emotions to address the growing problem of lonely deaths. This system allows users to manage their emotions and reduce feelings of social isolation through positive activities. Furthermore, the added emotion engine enables real-time, highly accurate emotion analysis, enabling more personalized feedback and support.

[0740] The processing flow will be explained below.

[0741] Step 1:

[0742] The user uses the device to open an application and selects voice input mode or text input mode.

[0743] Step 2:

[0744] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[0745] Step 3:

[0746] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[0747] Step 4:

[0748] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[0749] Step 5:

[0750] The server analyzes the voice and text data in real time using an emotion engine, which uses natural language processing (NLP) and speech analysis techniques to identify the user's emotions from the data.

[0751] Step 6:

[0752] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[0753] Step 7:

[0754] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[0755] Step 8:

[0756] The server updates the character's attributes based on growth points, determines new skills and appearance changes, and generates updated character data.

[0757] Step 9:

[0758] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[0759] Step 10:

[0760] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[0761] Step 11:

[0762] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[0763] Step 12:

[0764] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[0765] Step 13:

[0766] When a user uses the anonymous communication function based on their emotional state, the server identifies other users with the same emotional state and creates an anonymous chat room, and the terminal displays the chat room information to the user.

[0767] Step 14:

[0768] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0769] Step 15:

[0770] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[0771] Example 2

[0772] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0773] This invention relates to a system that analyzes users' emotions and promotes positive emotions in order to solve the problem of lonely deaths and improve users' mental health. However, conventional systems often have low accuracy in emotion analysis or difficulty in responding in real time. As a result, feedback and support to users are delayed, and effective mental support is not provided. Furthermore, features such as character development and anonymous communication between users are lacking, resulting in a lack of improvement in the user experience. This has led to the issue of difficulty in continuously eliciting positive emotions in users and the inability to alleviate feelings of social isolation.

[0774] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0775] In this invention, the server includes: means for receiving voice data or text data from a user; means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis; means for reflecting, saving, and managing the analysis results in real time; means for updating and developing a character's attributes based on the analysis results; means for calculating points based on the user's positive emotion analysis results and adding them to the user's account; means for generating and providing feedback to the user; means for generating a character based on character customization options selected by the user using a generative AI model; and means for providing opportunities for anonymous communication with other users based on the user's emotional state. This allows for highly accurate, real-time analysis of a user's emotions and providing personalized feedback and rewards, thereby promoting positive emotions and reducing feelings of social isolation.

[0776] "Voice data" is data input by a user using voice, and is used for emotion analysis.

[0777] "Text data" is data that is input by a user using characters and is used for emotion analysis.

[0778] "Natural language processing" refers to the technology of analyzing and understanding human language using a computer program, and is used to extract emotions from user text data.

[0779] "Voice analysis" refers to the technology of analyzing voice data and extracting features, and is used to determine emotions from a user's voice data.

[0780] "Sentiment analysis" refers to the process of analyzing received audio or text data to identify a user's emotions.

[0781] "Database" refers to a system for systematically storing and managing information such as analyzed emotional data and user profiles.

[0782] A "character" is a virtual entity that a user selects or customizes, and whose attributes are updated and developed based on the results of emotion analysis.

[0783] A "generative AI model" refers to a technology that uses artificial intelligence to generate appropriate output data for specific input data, in this case for character generation and customization.

[0784] A "point reward system" refers to a system that calculates points based on the results of analyzing a user's positive emotions and rewards the user.

[0785] "Feedback" refers to responses to the user, such as suggestions, encouragement, advice, etc., generated based on sentiment analysis.

[0786] "Anonymous communication" refers to a feature that provides users with the opportunity to interact with other users without revealing their identity.

[0787] The present invention relates to an "emotion analysis system" that analyzes a user's emotions and promotes positive emotions. Detailed embodiments of the present invention will be described below.

[0788] System Configuration

[0789] This system consists of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud. The main functions of this system are as follows:

[0790] 1. Receiving voice and text data

[0791] 2. Emotion analysis

[0792] 3. Character Creation and Development

[0793] 4. Point reward system

[0794] 5. Anonymous communication feature

[0795] 6. Providing Feedback

[0796] Receiving voice and text data

[0797] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0798] Examples:

[0799] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0800] Emotion analysis

[0801] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0802] Examples:

[0803] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0804] Character Generation and Growth

[0805] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0806] Examples:

[0807] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0808] Point reward system

[0809] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0810] Examples:

[0811] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0812] Anonymous communication feature

[0813] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0814] Examples:

[0815] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[0816] Providing Feedback

[0817] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[0818] Examples:

[0819] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[0820] Example prompts for generative AI models

[0821] Possible prompts to input to a generative AI model include:

[0822] "When a user inputs positive emotions, generate new skills or changes to the appearance of the virtual character based on that emotion."

[0823] As described above, with the above-mentioned configuration and specific examples, the present invention provides a system that can analyze a user's emotions with high accuracy and promote positive emotions, thereby reducing feelings of social isolation.

[0824] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0825] Step 1:

[0826] The user inputs voice or text data.

[0827] A user uses a terminal to input a voice or text message. For example, a user opens an application and inputs the text "Today was a fun day." This input data (voice data or text data) is sent to the next processing step.

[0828] Step 2:

[0829] The terminal sends the input data to the server.

[0830] The device sends the voice or text data entered by the user to the server, where it can be analyzed in the next processing step. The input here is the user's voice or text data, and the output is the data sent to the server.

[0831] Step 3:

[0832] The server analyzes the voice or text data using a natural language processing (NLP) engine and a voice analysis engine.

[0833] The server analyzes the received data using an NLP engine or speech analysis engine to identify the user's emotional state. For example, it generates a positive emotion tag "fun" for the text data "Today was a fun day." The input is the data sent to the server, and the output is the generated emotion tag.

[0834] Step 4:

[0835] The server stores the analysis results in a database.

[0836] The emotion tags generated by the server are saved in a database in real time by the emotion engine. This saving process reflects the analysis results in the user profile. The input is the generated emotion tags, and the output is the user's emotion data saved in the database.

[0837] Step 5:

[0838] The server generates and updates characters using generative AI models.

[0839] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes in real time based on the results of emotional analysis. Each time the user expresses positive emotion, the character acquires a new skill or changes appearance. The input is the emotional analysis results and customization options, and the output is the generated or updated character.

[0840] Step 6:

[0841] The server calculates points based on positive sentiment analysis results and adds them to the user's account.

[0842] The server calculates points based on the user's positive sentiment analysis result and adds them to the user's account. For example, if the user enters "Today is a great day," the server adds 10 points based on this sentiment. The input is the positive sentiment analysis result, and the output is the added points.

[0843] Step 7:

[0844] The terminal notifies the user of the point information.

[0845] The terminal notifies the user of the point information received from the server. For example, a message saying "10 points have been added to your account" is displayed. The input is the added point information, and the output is the message notified to the user.

[0846] Step 8:

[0847] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[0848] The server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results. This function allows users to anonymously interact with other users and promote positive emotions. The input is the user's emotion analysis results, and the output is anonymous chat room information.

[0849] Step 9:

[0850] The terminal displays the anonymous chat room information to the user.

[0851] The terminal displays the anonymous chat room information received from the server to the user. For example, a message saying "An anonymous chat room has been created" is displayed, and the user can now access the chat room. The input is the anonymous chat room information, and the output is the message displayed to the user.

[0852] Step 10:

[0853] The server provides appropriate feedback to the user.

[0854] The server generates and provides feedback such as encouragement or advice to the user based on the analysis results from the emotion engine. For example, if the user inputs "sad," the server generates the feedback "Why don't you try doing something fun today?" The input is the analysis result, and the output is the generated feedback message.

[0855] Step 11:

[0856] The device displays the feedback to the user.

[0857] The terminal displays to the user the feedback message it receives from the server, for example, "Why not try something fun today?" The input is the feedback message, and the output is the message displayed to the user.

[0858] In this way, the entire system works together to analyze the user's emotions and carry out a series of processes to promote positive emotions.

[0859] (Application example 2)

[0860] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0861] In modern society, the number of people experiencing loneliness and isolation is increasing, and this has become a serious problem. In particular, there is a need to prevent lonely deaths, but emotional care is often inadequate. In addition, there is a lack of approaches to improving emotional situations, so there is a need for methods to promote positive emotions in daily life.

[0862] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0863] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions in the received voice data or text data using natural language processing or voice analysis, means for suggesting optimal meals to the user based on the analysis results, and means for providing discount coupons based on the positive emotion analysis results. This makes it possible to analyze the user's emotional state, promote positive emotions through meals, and alleviate feelings of loneliness and isolation.

[0864] "Voice data" refers to data that is a digital recording of a user's voice.

[0865] "Text data" refers to digital data containing text information entered by a user.

[0866] "Natural language processing" is the field of computer science that aims to understand and analyze human language.

[0867] "Voice analysis" is a technology that analyzes voice data and extracts meaning and emotions from it.

[0868] "Emotion analysis" is a technology that identifies emotions from voice data and text data.

[0869] A "character" is a virtual being or avatar that can be customized by a user.

[0870] "Attributes" are specific characteristics or traits that a character possesses.

[0871] "Growth" refers to the process by which a character evolves based on the user's actions and emotions, gaining new skills and appearances.

[0872] "Points" are rewards awarded based on a user's positive behavior and the results of emotional analysis.

[0873] A "meal" is any food or drink consumed by a user.

[0874] A "discount coupon" is a digital or physical coupon that entitles a user to a service or product at a discounted price.

[0875] This invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system grasps the user's emotional state through analysis of voice and text data and provides appropriate feedback. It also makes meal suggestions and offers discount coupons based on the analysis results.

[0876] System configuration

[0877] This system mainly consists of a user device and a server. User devices include smartphones, tablets, and computers. The server is located on the cloud and is responsible for analyzing voice and text data, managing data, and providing feedback.

[0878] Receiving voice and text data

[0879] Using an application on the device, users input their emotions and state of mind through voice or text, and the device immediately transmits this data to the server.

[0880] Specific examples

[0881] A user opens the application on their smartphone and types in the text, "Today was a fun day." The device immediately sends this data to the server.

[0882] Emotion analysis

[0883] The server receives the transmitted voice or text data and uses a natural language processing (NLP) engine or a voice analysis engine to analyze the user's emotions and generate emotion tags such as positive, negative, or neutral.

[0884] Specific examples

[0885] The text data "Today was a fun day" is analyzed using an NLP engine to generate a positive emotion tag for "fun."

[0886] Optimal meal suggestions

[0887] Based on the analysis results, the server uses a generative AI model to suggest the best meal to improve the user's emotional state, presenting specific meal menus according to the user's emotions.

[0888] Specific examples

[0889] If you type "I'm feeling a little lonely today," it will suggest a warm soup or a nutritious salad.

[0890] Offering discount coupons

[0891] If a positive emotion tag is obtained, the server will offer the user a discount coupon that can be used on their next meal order.

[0892] Specific examples

[0893] If a user types "Today is a great day," the server will offer them a 10% off coupon.

[0894] Hardware and software used

[0895] Hardware: smartphones, tablets, computers

[0896] Software: Natural language processing engine (NLP engine), speech analysis engine, generative AI model

[0897] Example prompts for generative AI models

[0898] A user enters, "I'm feeling a bit tired and lonely today." Based on this emotion, please suggest dishes that will improve the user's mood. For example, you could recommend meals such as "warm soup," "nutritious salad," or "protein bar that's perfect for replenishing energy." Please include a reason for your recommendation.

[0899] As described above, the emotion analysis application system can analyze the user's emotional state in real time and provide appropriate feedback, meal suggestions, and discount coupons based on that analysis, thereby promoting positive emotions and helping to reduce feelings of loneliness and isolation.

[0900] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0901] Step 1:

[0902] A user starts the application using a device such as a smartphone or tablet. The user inputs their emotional state by voice or text. The input data (voice data or text data) is temporarily stored on the device.

[0903] Input: Text or voice when the user inputs their emotional state.

[0904] Output: Audio or text data stored on the device.

[0905] Action: The user enters the text "Today was a fun day."

[0906] Step 2:

[0907] The device sends the input voice or text data to the server, where the data is encrypted and transmitted securely.

[0908] Input: Voice or text data stored on the device.

[0909] Output: The audio or text data sent to the server.

[0910] Operation: The device sends text data such as "Today was a fun day" to the server.

[0911] Step 3:

[0912] The server analyzes the received voice or text data using a natural language processing (NLP) engine or speech analysis engine for sentiment analysis, which generates sentiment tags such as positive, negative, and neutral.

[0913] Input: The audio or text data sent to the server.

[0914] Output: A sentiment tag (e.g., "fun").

[0915] How it works: The server analyzes the text data "Today was a fun day" and generates a positive emotion tag for "fun."

[0916] Step 4:

[0917] The server uses a generative AI model to create prompts to suggest optimal meals for the user based on the analyzed emotion tags, and then uses the generative AI model to generate specific meal menus.

[0918] Input: Sentiment tag (positive, negative, neutral, etc.).

[0919] Output: Specific meal menu suggestions.

[0920] How it works: If the emotion tag is "fun," the generative AI model will suggest meals such as "hot soup" or "nutritious salad."

[0921] Step 5:

[0922] If the server obtains a positive emotion tag, it generates and sends the user a discount coupon that can be used on their next meal order.

[0923] Input: Positive sentiment tags.

[0924] Output: Discount coupon.

[0925] What it does: If the server receives the input "Today is a great day," it generates a 10% off coupon and sends it to the user.

[0926] Step 6:

[0927] The server sends the meal menu prompt and discount coupon information to the user terminal, which displays the information for the user to check.

[0928] Input: Specific meal suggestions and discount coupons.

[0929] Output: Meal menu and coupons displayed on the user's device.

[0930] What it does: The device displays "Recommended Meal: Hot Soup" and "10% Off Coupon."

[0931] Through the above processing flow, the system analyzes users' emotions and provides optimal feedback, meal suggestions, and discount coupons.

[0932] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0933] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0934] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0935] [Third embodiment]

[0936] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0937] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0938] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0939] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0940] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0941] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0942] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0943] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0944] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0945] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0946] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0947] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0948] The present invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards based on the results. A detailed explanation of how to implement this system is provided below.

[0949] System Overview

[0950] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[0951] Receiving voice and text data

[0952] Emotion analysis

[0953] Character Generation and Growth

[0954] Point reward system

[0955] Anonymous communication feature

[0956] Receiving voice and text data

[0957] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[0958] Examples:

[0959] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[0960] Emotion analysis

[0961] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[0962] Examples:

[0963] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[0964] Character Generation and Growth

[0965] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[0966] Examples:

[0967] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[0968] Point reward system

[0969] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[0970] Examples:

[0971] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[0972] Anonymous communication feature

[0973] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[0974] Examples:

[0975] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[0976] The system described herein analyzes users' emotions and promotes positive emotions to address the increasing problem of lonely deaths, allowing users to manage their emotions and reduce feelings of social isolation through positive activities.

[0977] The processing flow will be explained below.

[0978] Step 1:

[0979] The user uses the device to open an application and selects voice input mode or text input mode.

[0980] Step 2:

[0981] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[0982] Step 3:

[0983] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[0984] Step 4:

[0985] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[0986] Step 5:

[0987] The server uses a natural language processing (NLP) engine to analyze the text data. In the case of voice data, it is first converted into text by a voice analysis engine, and then analyzed by the NLP engine. As a result of the analysis, an emotion tag (e.g., happy, sad) is generated.

[0988] Step 6:

[0989] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[0990] Step 7:

[0991] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[0992] Step 8:

[0993] The server updates the character's attributes based on growth points, determines new skills and changes, and generates updated character data.

[0994] Step 9:

[0995] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[0996] Step 10:

[0997] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[0998] Step 11:

[0999] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[1000] Step 12:

[1001] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[1002] Step 13:

[1003] When a user enters an emotional state that allows anonymous communication through the terminal, the server identifies other users in the same emotional state and creates an anonymous chat room. The terminal displays chat room information to the user.

[1004] Step 14:

[1005] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[1006] Example 1

[1007] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1008] Currently, many people feel lonely and socially isolated, which has led to an increase in the problem of lonely deaths. Existing solutions have not been effective enough to address this issue. Therefore, there is a need for a system that can promote positive emotions and social interaction among users.

[1009] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1010] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or speech analysis, and means for updating and developing the character's attributes based on the analysis results, thereby enabling accurate analysis of the user's emotional state in real time, promoting positive emotions, and even social interaction with other users through anonymous communication.

[1011] "Voice data" means digitized voice information provided by a user through voice input.

[1012] "Text data" refers to character information provided by a user through character input.

[1013] "Natural language processing" is a technology that allows machines to understand and analyze human language.

[1014] "Voice analysis" is a technology that analyzes voice data and identifies its characteristics and content.

[1015] "Analyzing emotions" refers to the process of analyzing received audio or text data to identify the user's emotional state therein.

[1016] "Updating and developing the character's attributes" means changing the appearance, skills, and characteristics of the virtual character based on the results of the user's emotional analysis.

[1017] "Adding points" means that the system adds a certain number of points to the user's account.

[1018] "Anonymous communication" is a feature that allows users to interact with other users without revealing their true identity.

[1019] "Generative AI model" refers to an artificial intelligence model used to generate characters and other elements.

[1020] A "cloud server" is a server infrastructure provided over the Internet.

[1021] MODE FOR CARRYING OUT THE INVENTION

[1022] This invention relates to an "emotion analysis application system" that analyzes a user's emotions. This system determines the user's emotional state and, based on the results, changes the attributes of a virtual character, awards points, and promotes anonymous communication. This system is primarily composed of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud.

[1023] Hardware and Software Configuration

[1024] The system includes the following hardware and software:

[1025] User devices: smartphones, tablets, computers

[1026] Server: Cloud server (e.g. AWS, Google Cloud)

[1027] Natural Language Processing Engine: Transformer-based NLP models (e.g., BERT, GPT-3)

[1028] Generative AI models: GANs (generative artificial network), Transformer models

[1029] Speech analysis engine: Google Cloud Speech-to-Text API, Amazon Transcribe

[1030] System Operation Overview

[1031] 1. A user uses a device to open an application that provides a voice or text input interface.

[1032] 2. The user enters voice or text data, for example, entering the text message "Today was a fun day."

[1033] 3. The device temporarily stores the data entered by the user and then sends the data to a server in the cloud.

[1034] 4. The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, and generates an emotion tag as a result of the analysis.

[1035] 5. The server updates the attributes of the virtual character based on the analysis results, allowing the character to grow. Every time the user expresses positive emotions, the character acquires new skills and changes its appearance.

[1036] 6. The server will calculate points based on the sentiment analysis results and add them to the user's account, which can be used for character customization and special rewards.

[1037] 7. The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1038] Specific examples

[1039] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1040] The server receives text data such as "Today was a fun day" and analyzes it using a natural language processing (NLP) engine to generate a positive emotion tag for "fun."

[1041] By continuously acquiring positive emotion tags, the virtual character will learn new dance skills and change its appearance to become brighter.

[1042] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1043] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[1044] Prompt Sentence Examples

[1045] Example prompt 1: "The user types, 'Today was a good day.' Classify this as a positive sentiment tag."

[1046] Example prompt 2: "The user types, 'I had a terrible day today.' Classify this as a negative sentiment tag."

[1047] Example prompt 3: "The user repeatedly expressed the emotion 'fun'. As a result, we'll add a new dance skill to the virtual character and brighten up its appearance."

[1048] In this way, the entire system works together to analyze the user's emotional state and provide feedback and rewards, ultimately helping users to reduce their sense of social isolation through positive activities.

[1049] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1050] Step 1:

[1051] A user opens an application using a terminal, which provides an interface for receiving input voice or text data.

[1052] Input: User speech and text input.

[1053] Output: Temporarily saved audio or text data.

[1054] What happens: The user types in the text "Today was a fun day."

[1055] Step 2:

[1056] The device sends the voice data or text data entered by the user to a server on the cloud.

[1057] Input: Temporarily saved audio or text data.

[1058] Output: The data sent to the server.

[1059] Specific operation: The device sends text data saying "Today was a fun day."

[1060] Step 3:

[1061] The server analyzes the received voice data or text data using a natural language processing engine and a voice analysis engine.

[1062] Input: The audio or text data received by the server.

[1063] Output: Sentiment tags as the analysis results.

[1064] Specific operation: The server analyzes the text data "Today was a fun day" using an NLP engine and generates a positive emotion tag for "fun."

[1065] Step 4:

[1066] The server stores and manages the analysis results, and also uses them to update the character's attributes.

[1067] Input: Sentiment tags as analysis results.

[1068] Output: Updated character attributes.

[1069] Specific behavior: When a positive emotion tag is generated, the character will learn new skills and change their appearance.

[1070] Step 5:

[1071] The server calculates points based on the emotion analysis results and adds them to the user's account.

[1072] Input: Emotion tags as analysis results and user account information.

[1073] Output: The added points.

[1074] Specific Action: Add 10 points based on positive emotions.

[1075] Step 6:

[1076] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[1077] Input: Sentiment tags as analysis results.

[1078] Output:Anonymous chat room created.

[1079] Specific operation: For users who feel lonely, create an anonymous chat room with other users who share the same feelings.

[1080] Through these processing steps, the system analyzes the user's emotions and provides feedback and rewards, thereby promoting positive social interactions.

[1081] (Application example 1)

[1082] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1083] The present invention aims to provide a system that reduces the sense of social isolation and promotes positive emotions in elderly people living alone and users who feel lonely. In particular, the system has a function to monitor the user's emotional state and notify family members or security service providers as necessary, thereby reducing the risk of lonely death.

[1084] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1085] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis, means for saving and managing the analysis results, means for updating and developing character attributes based on the analysis results, means for adding points to the user's account, and means for generating an alert and notifying a specific recipient if the analysis results are negative. This makes it possible to grasp the user's emotional state, promote positive emotions, and provide appropriate support as needed.

[1086] "Voice data" is a digital recording of a user's voice uttered to an application.

[1087] "Text data" refers to character information that a user inputs to an application.

[1088] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[1089] "Speech analysis" is a technology that uses digital signal processing technology to analyze voice data and understand its content and characteristics.

[1090] An "emotion tag" is a label that indicates an emotional state analyzed from audio data or text data.

[1091] A "character" is a virtual being that is generated and grows according to the user's emotional state.

[1092] A "generative AI model" is a model that has been trained using artificial intelligence techniques to perform a specific task.

[1093] "Attributes" are the characteristics and traits that a character possesses.

[1094] "Points" are virtual rewards that users can earn by expressing positive emotions.

[1095] An "alert" is a warning that notifies a specific recipient when a user's emotional state is negative.

[1096] "Recipients" are family members or security service providers who are notified depending on the user's emotional state.

[1097] MODE FOR CARRYING OUT THE INVENTION

[1098] The present invention relates to a user emotion monitoring security system for reducing the risk of lonely death. This system has the function of analyzing the user's emotional state and notifying the user, their family, or a security service provider as necessary.

[1099] System configuration

[1100] The system of the present invention consists of the following main components:

[1101] 1. User terminal: A device for inputting user voice data or text data. Specifically, a mobile device such as a smartphone or tablet is used.

[1102] 2. Cloud server: Analyzes and stores data, and provides APIs.

[1103] 3. Natural Language Processing (NLP) Engine: An NLP engine is used to analyze the received text data and identify the user's sentiment. An example is Google Cloud Natural Language API.

[1104] 4. Speech analysis engine: Used to analyze voice data. An example is IBM Watson Speech to Text.

[1105] 5. Generative AI model: Responsible for character generation and development. For example, OpenAI's GPT series is used for this part.

[1106] 6. Database: A system for storing the results of sentiment analysis and user data.

[1107] System Operation

[1108] 1. Receiving voice and text data

[1109] The user uses the device to input voice or text data, which is then sent to the cloud server. For example, if a user voice-types "I'm feeling a little down today" into their smartphone, this data is immediately sent to the cloud server.

[1110] 2. Emotion analysis

[1111] The server uses an NLP engine and a speech analysis engine to analyze the received data, which generates an emotion tag. For example, if the user says "I'm feeling a little down today," a negative emotion tag is generated.

[1112] 3. Character Creation and Development

[1113] The generative AI model generates a character based on the user's customization options. Furthermore, the character's attributes are updated and developed based on the results of emotion analysis. If a positive emotion tag is generated, the character will acquire new skills and other changes.

[1114] 4. Point reward system

[1115] Based on the user's positive sentiment analysis, points are calculated and added to the user's account, which can be used to customize characters and earn special rewards.

[1116] 5. Security Alert System

[1117] If the analysis result is negative, the server generates an alert and notifies specific recipients (family members or security service providers). For example, if a user shows negative emotions for three consecutive days, the server notifies family members that "the user may have been depressed recently."

[1118] Specific examples

[1119] When a user types "I've been feeling a bit tired lately" into their smartphone, this information is sent to a cloud server and analyzed by an NLP engine. A negative emotion tag is attached, and the generative AI model provides the user with feedback such as "Try to get some rest today." If a negative emotion tag is generated for three consecutive days, an alert is sent to family members.

[1120] Prompt Sentence Examples

[1121] Input: The user is feeling depressed

[1122] Output: Generate positive feedback and check if a security alert is triggered

[1123] This allows the system to manage the user's emotions and provide appropriate support to family and related parties when necessary.

[1124] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1125] Step 1:

[1126] The user inputs voice or text data into the device. For example, when the user opens a smartphone application and inputs "I'm a little tired today" by voice or text, this data is generated.

[1127] Input: User speaks or enters text

[1128] Output: Audio data or text data

[1129] Step 2:

[1130] The device sends the input voice data or text data to the cloud server, which then transfers the data to the cloud server using a secure communication protocol.

[1131] Input: Audio or text data

[1132] Output: Data sent to the cloud server

[1133] Step 3:

[1134] The server analyzes the received voice data with a voice analysis engine and the text data with a natural language processing (NLP) engine. The analysis generates a specific emotion tag (e.g., "negative").

[1135] Input: Audio or text data sent to the server

[1136] Output: Emotion tag

[1137] Step 4:

[1138] The server stores and manages the emotion tags obtained as a result of emotion analysis. The original data is also recorded in the database along with the emotion tags.

[1139] Input: emotion tag

[1140] Output: Emotion tags and raw data stored in the database

[1141] Step 5:

[1142] Based on the emotion analysis results, the server uses a generative AI model to generate and update the character and develop its attributes. The generative AI model applies new skills, changes to appearance, etc. to the character based on prompts.

[1143] Input: emotion tag

[1144] Output: Updated character

[1145] Step 6:

[1146] The server calculates points based on positive sentiment analysis results and adds them to the user's account. For example, if a user types "I had fun today," 10 points will be added.

[1147] Input: Positive sentiment tag

[1148] Output: Updated user points

[1149] Step 7:

[1150] If the sentiment analysis result is negative, the server generates an alert and notifies specific recipients (e.g., family members or security service providers) so that necessary assistance can be provided quickly.

[1151] Input: Negative sentiment tag

[1152] Output: Alert notification sent

[1153] This will create a system that analyzes the user's emotional state throughout all steps and provides appropriate feedback and necessary assistance.

[1154] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1155] The present invention provides an "emotion analysis application system" that can encourage positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards. In particular, by combining it with an emotion engine, it achieves real-time, highly accurate emotion analysis. A detailed explanation of how to implement this system is provided below.

[1156] System Overview

[1157] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[1158] Receiving voice and text data

[1159] Emotion analysis

[1160] Character Generation and Growth

[1161] Point reward system

[1162] Anonymous communication feature

[1163] Emotion Engine

[1164] Receiving voice and text data

[1165] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[1166] Examples:

[1167] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1168] Emotion analysis

[1169] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[1170] Examples:

[1171] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[1172] Real-time analysis of emotion engine

[1173] The server uses an emotion engine to analyze the user's voice and text data in real time, and the identified emotion data is immediately reflected in the user profile and stored in a database.

[1174] Examples:

[1175] When a user inputs the text "I'm very sad," the server's emotion engine analyzes the emotion "sad" in real time and stores the results in a database.

[1176] Character Generation and Growth

[1177] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[1178] Examples:

[1179] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[1180] Point reward system

[1181] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[1182] Examples:

[1183] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1184] Anonymous communication feature

[1185] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1186] Examples:

[1187] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[1188] Providing Feedback

[1189] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1190] Examples:

[1191] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[1192] The system described in this specification analyzes users' emotions and promotes positive emotions to address the growing problem of lonely deaths. This system allows users to manage their emotions and reduce feelings of social isolation through positive activities. Furthermore, the added emotion engine enables real-time, highly accurate emotion analysis, enabling more personalized feedback and support.

[1193] The processing flow will be explained below.

[1194] Step 1:

[1195] The user uses the device to open an application and selects voice input mode or text input mode.

[1196] Step 2:

[1197] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[1198] Step 3:

[1199] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[1200] Step 4:

[1201] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[1202] Step 5:

[1203] The server analyzes the voice and text data in real time using an emotion engine, which uses natural language processing (NLP) and speech analysis techniques to identify the user's emotions from the data.

[1204] Step 6:

[1205] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[1206] Step 7:

[1207] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[1208] Step 8:

[1209] The server updates the character's attributes based on growth points, determines new skills and appearance changes, and generates updated character data.

[1210] Step 9:

[1211] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[1212] Step 10:

[1213] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[1214] Step 11:

[1215] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[1216] Step 12:

[1217] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[1218] Step 13:

[1219] When a user uses the anonymous communication function based on their emotional state, the server identifies other users with the same emotional state and creates an anonymous chat room, and the terminal displays the chat room information to the user.

[1220] Step 14:

[1221] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1222] Step 15:

[1223] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[1224] Example 2

[1225] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1226] This invention relates to a system that analyzes users' emotions and promotes positive emotions in order to solve the problem of lonely deaths and improve users' mental health. However, conventional systems often have low accuracy in emotion analysis or difficulty in responding in real time. As a result, feedback and support to users are delayed, and effective mental support is not provided. Furthermore, features such as character development and anonymous communication between users are lacking, resulting in a lack of improvement in the user experience. This has led to the issue of difficulty in continuously eliciting positive emotions in users and the inability to alleviate feelings of social isolation.

[1227] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1228] In this invention, the server includes: means for receiving voice data or text data from a user; means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis; means for reflecting, saving, and managing the analysis results in real time; means for updating and developing a character's attributes based on the analysis results; means for calculating points based on the user's positive emotion analysis results and adding them to the user's account; means for generating and providing feedback to the user; means for generating a character based on character customization options selected by the user using a generative AI model; and means for providing opportunities for anonymous communication with other users based on the user's emotional state. This allows for highly accurate, real-time analysis of a user's emotions and providing personalized feedback and rewards, thereby promoting positive emotions and reducing feelings of social isolation.

[1229] "Voice data" is data input by a user using voice, and is used for emotion analysis.

[1230] "Text data" is data that is input by a user using characters and is used for emotion analysis.

[1231] "Natural language processing" refers to the technology of analyzing and understanding human language using a computer program, and is used to extract emotions from user text data.

[1232] "Voice analysis" refers to the technology of analyzing voice data and extracting features, and is used to determine emotions from a user's voice data.

[1233] "Sentiment analysis" refers to the process of analyzing received audio or text data to identify a user's emotions.

[1234] "Database" refers to a system for systematically storing and managing information such as analyzed emotional data and user profiles.

[1235] A "character" is a virtual entity that a user selects or customizes, and whose attributes are updated and developed based on the results of emotion analysis.

[1236] A "generative AI model" refers to a technology that uses artificial intelligence to generate appropriate output data for specific input data, in this case for character generation and customization.

[1237] A "point reward system" refers to a system that calculates points based on the results of analyzing a user's positive emotions and rewards the user.

[1238] "Feedback" refers to responses to the user, such as suggestions, encouragement, advice, etc., generated based on sentiment analysis.

[1239] "Anonymous communication" refers to a feature that provides users with the opportunity to interact with other users without revealing their identity.

[1240] The present invention relates to an "emotion analysis system" that analyzes a user's emotions and promotes positive emotions. Detailed embodiments of the present invention will be described below.

[1241] System Configuration

[1242] This system consists of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud. The main functions of this system are as follows:

[1243] 1. Receiving voice and text data

[1244] 2. Emotion analysis

[1245] 3. Character Creation and Development

[1246] 4. Point reward system

[1247] 5. Anonymous communication feature

[1248] 6. Providing Feedback

[1249] Receiving voice and text data

[1250] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[1251] Examples:

[1252] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1253] Emotion analysis

[1254] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[1255] Examples:

[1256] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[1257] Character Generation and Growth

[1258] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[1259] Examples:

[1260] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[1261] Point reward system

[1262] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[1263] Examples:

[1264] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1265] Anonymous communication feature

[1266] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1267] Examples:

[1268] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[1269] Providing Feedback

[1270] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1271] Examples:

[1272] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[1273] Example prompts for generative AI models

[1274] Possible prompts to input to a generative AI model include:

[1275] "When a user inputs positive emotions, generate new skills or changes to the appearance of the virtual character based on that emotion."

[1276] As described above, with the above-mentioned configuration and specific examples, the present invention provides a system that can analyze a user's emotions with high accuracy and promote positive emotions, thereby reducing feelings of social isolation.

[1277] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1278] Step 1:

[1279] The user inputs voice or text data.

[1280] A user uses a terminal to input a voice or text message. For example, a user opens an application and inputs the text "Today was a fun day." This input data (voice data or text data) is sent to the next processing step.

[1281] Step 2:

[1282] The terminal sends the input data to the server.

[1283] The device sends the voice or text data entered by the user to the server, where it can be analyzed in the next processing step. The input here is the user's voice or text data, and the output is the data sent to the server.

[1284] Step 3:

[1285] The server analyzes the voice or text data using a natural language processing (NLP) engine and a voice analysis engine.

[1286] The server analyzes the received data using an NLP engine or speech analysis engine to identify the user's emotional state. For example, it generates a positive emotion tag "fun" for the text data "Today was a fun day." The input is the data sent to the server, and the output is the generated emotion tag.

[1287] Step 4:

[1288] The server stores the analysis results in a database.

[1289] The emotion tags generated by the server are saved in a database in real time by the emotion engine. This saving process reflects the analysis results in the user profile. The input is the generated emotion tags, and the output is the user's emotion data saved in the database.

[1290] Step 5:

[1291] The server generates and updates characters using generative AI models.

[1292] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes in real time based on the results of emotional analysis. Each time the user expresses positive emotion, the character acquires a new skill or changes appearance. The input is the emotional analysis results and customization options, and the output is the generated or updated character.

[1293] Step 6:

[1294] The server calculates points based on positive sentiment analysis results and adds them to the user's account.

[1295] The server calculates points based on the user's positive sentiment analysis result and adds them to the user's account. For example, if the user enters "Today is a great day," the server adds 10 points based on this sentiment. The input is the positive sentiment analysis result, and the output is the added points.

[1296] Step 7:

[1297] The terminal notifies the user of the point information.

[1298] The terminal notifies the user of the point information received from the server. For example, a message saying "10 points have been added to your account" is displayed. The input is the added point information, and the output is the message notified to the user.

[1299] Step 8:

[1300] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[1301] The server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results. This function allows users to anonymously interact with other users and promote positive emotions. The input is the user's emotion analysis results, and the output is anonymous chat room information.

[1302] Step 9:

[1303] The terminal displays the anonymous chat room information to the user.

[1304] The terminal displays the anonymous chat room information received from the server to the user. For example, a message saying "An anonymous chat room has been created" is displayed, and the user can now access the chat room. The input is the anonymous chat room information, and the output is the message displayed to the user.

[1305] Step 10:

[1306] The server provides appropriate feedback to the user.

[1307] The server generates and provides feedback such as encouragement or advice to the user based on the analysis results from the emotion engine. For example, if the user inputs "sad," the server generates the feedback "Why don't you try doing something fun today?" The input is the analysis result, and the output is the generated feedback message.

[1308] Step 11:

[1309] The device displays the feedback to the user.

[1310] The terminal displays to the user the feedback message it receives from the server, for example, "Why not try something fun today?" The input is the feedback message, and the output is the message displayed to the user.

[1311] In this way, the entire system works together to analyze the user's emotions and carry out a series of processes to promote positive emotions.

[1312] (Application example 2)

[1313] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1314] In modern society, the number of people experiencing loneliness and isolation is increasing, and this has become a serious problem. In particular, there is a need to prevent lonely deaths, but emotional care is often inadequate. In addition, there is a lack of approaches to improving emotional situations, so there is a need for methods to promote positive emotions in daily life.

[1315] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1316] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions in the received voice data or text data using natural language processing or voice analysis, means for suggesting optimal meals to the user based on the analysis results, and means for providing discount coupons based on the positive emotion analysis results. This makes it possible to analyze the user's emotional state, promote positive emotions through meals, and alleviate feelings of loneliness and isolation.

[1317] "Voice data" refers to data that is a digital recording of a user's voice.

[1318] "Text data" refers to digital data containing text information entered by a user.

[1319] "Natural language processing" is the field of computer science that aims to understand and analyze human language.

[1320] "Voice analysis" is a technology that analyzes voice data and extracts meaning and emotions from it.

[1321] "Emotion analysis" is a technology that identifies emotions from voice data and text data.

[1322] A "character" is a virtual being or avatar that can be customized by a user.

[1323] "Attributes" are specific characteristics or traits that a character possesses.

[1324] "Growth" refers to the process by which a character evolves based on the user's actions and emotions, gaining new skills and appearances.

[1325] "Points" are rewards awarded based on a user's positive behavior and the results of emotional analysis.

[1326] A "meal" is any food or drink consumed by a user.

[1327] A "discount coupon" is a digital or physical coupon that entitles a user to a service or product at a discounted price.

[1328] This invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system grasps the user's emotional state through analysis of voice and text data and provides appropriate feedback. It also makes meal suggestions and offers discount coupons based on the analysis results.

[1329] System configuration

[1330] This system mainly consists of a user device and a server. User devices include smartphones, tablets, and computers. The server is located on the cloud and is responsible for analyzing voice and text data, managing data, and providing feedback.

[1331] Receiving voice and text data

[1332] Using an application on the device, users input their emotions and state of mind through voice or text, and the device immediately transmits this data to the server.

[1333] Specific examples

[1334] A user opens the application on their smartphone and types in the text, "Today was a fun day." The device immediately sends this data to the server.

[1335] Emotion analysis

[1336] The server receives the transmitted voice or text data and uses a natural language processing (NLP) engine or a voice analysis engine to analyze the user's emotions and generate emotion tags such as positive, negative, or neutral.

[1337] Specific examples

[1338] The text data "Today was a fun day" is analyzed using an NLP engine to generate a positive emotion tag for "fun."

[1339] Optimal meal suggestions

[1340] Based on the analysis results, the server uses a generative AI model to suggest the best meal to improve the user's emotional state, presenting specific meal menus according to the user's emotions.

[1341] Specific examples

[1342] If you type "I'm feeling a little lonely today," it will suggest a warm soup or a nutritious salad.

[1343] Offering discount coupons

[1344] If a positive emotion tag is obtained, the server will offer the user a discount coupon that can be used on their next meal order.

[1345] Specific examples

[1346] If a user types "Today is a great day," the server will offer them a 10% off coupon.

[1347] Hardware and software used

[1348] Hardware: smartphones, tablets, computers

[1349] Software: Natural language processing engine (NLP engine), speech analysis engine, generative AI model

[1350] Example prompts for generative AI models

[1351] A user enters, "I'm feeling a bit tired and lonely today." Based on this emotion, please suggest dishes that will improve the user's mood. For example, you could recommend meals such as "warm soup," "nutritious salad," or "protein bar that's perfect for replenishing energy." Please include a reason for your recommendation.

[1352] As described above, the emotion analysis application system can analyze the user's emotional state in real time and provide appropriate feedback, meal suggestions, and discount coupons based on that analysis, thereby promoting positive emotions and helping to reduce feelings of loneliness and isolation.

[1353] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1354] Step 1:

[1355] A user starts the application using a device such as a smartphone or tablet. The user inputs their emotional state by voice or text. The input data (voice data or text data) is temporarily stored on the device.

[1356] Input: Text or voice when the user inputs their emotional state.

[1357] Output: Audio or text data stored on the device.

[1358] Action: The user enters the text "Today was a fun day."

[1359] Step 2:

[1360] The device sends the input voice or text data to the server, where the data is encrypted and transmitted securely.

[1361] Input: Voice or text data stored on the device.

[1362] Output: The audio or text data sent to the server.

[1363] Operation: The device sends text data such as "Today was a fun day" to the server.

[1364] Step 3:

[1365] The server analyzes the received voice or text data using a natural language processing (NLP) engine or speech analysis engine for sentiment analysis, which generates sentiment tags such as positive, negative, and neutral.

[1366] Input: The audio or text data sent to the server.

[1367] Output: A sentiment tag (e.g., "fun").

[1368] How it works: The server analyzes the text data "Today was a fun day" and generates a positive emotion tag for "fun."

[1369] Step 4:

[1370] The server uses a generative AI model to create prompts to suggest optimal meals for the user based on the analyzed emotion tags, and then uses the generative AI model to generate specific meal menus.

[1371] Input: Sentiment tag (positive, negative, neutral, etc.).

[1372] Output: Specific meal menu suggestions.

[1373] How it works: If the emotion tag is "fun," the generative AI model will suggest meals such as "hot soup" or "nutritious salad."

[1374] Step 5:

[1375] If the server obtains a positive emotion tag, it generates and sends the user a discount coupon that can be used on their next meal order.

[1376] Input: Positive sentiment tags.

[1377] Output: Discount coupon.

[1378] What it does: If the server receives the input "Today is a great day," it generates a 10% off coupon and sends it to the user.

[1379] Step 6:

[1380] The server sends the meal menu prompt and discount coupon information to the user terminal, which displays the information for the user to check.

[1381] Input: Specific meal suggestions and discount coupons.

[1382] Output: Meal menu and coupons displayed on the user's device.

[1383] What it does: The device displays "Recommended Meal: Hot Soup" and "10% Off Coupon."

[1384] Through the above processing flow, the system analyzes users' emotions and provides optimal feedback, meal suggestions, and discount coupons.

[1385] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1386] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1387] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1388] [Fourth embodiment]

[1389] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1390] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1391] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1392] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1393] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1394] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1395] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1396] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1397] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1398] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1399] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1400] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1401] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1402] The present invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards based on the results. A detailed explanation of how to implement this system is provided below.

[1403] System Overview

[1404] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[1405] Receiving voice and text data

[1406] Emotion analysis

[1407] Character Generation and Growth

[1408] Point reward system

[1409] Anonymous communication feature

[1410] Receiving voice and text data

[1411] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[1412] Examples:

[1413] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1414] Emotion analysis

[1415] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[1416] Examples:

[1417] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[1418] Character Generation and Growth

[1419] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[1420] Examples:

[1421] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[1422] Point reward system

[1423] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[1424] Examples:

[1425] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1426] Anonymous communication feature

[1427] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1428] Examples:

[1429] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[1430] The system described herein analyzes users' emotions and promotes positive emotions to address the increasing problem of lonely deaths, allowing users to manage their emotions and reduce feelings of social isolation through positive activities.

[1431] The processing flow will be explained below.

[1432] Step 1:

[1433] The user uses the device to open an application and selects voice input mode or text input mode.

[1434] Step 2:

[1435] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[1436] Step 3:

[1437] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[1438] Step 4:

[1439] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[1440] Step 5:

[1441] The server uses a natural language processing (NLP) engine to analyze the text data. In the case of voice data, it is first converted into text by a voice analysis engine, and then analyzed by the NLP engine. As a result of the analysis, an emotion tag (e.g., happy, sad) is generated.

[1442] Step 6:

[1443] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[1444] Step 7:

[1445] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[1446] Step 8:

[1447] The server updates the character's attributes based on growth points, determines new skills and changes, and generates updated character data.

[1448] Step 9:

[1449] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[1450] Step 10:

[1451] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[1452] Step 11:

[1453] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[1454] Step 12:

[1455] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[1456] Step 13:

[1457] When a user enters an emotional state that allows anonymous communication through the terminal, the server identifies other users in the same emotional state and creates an anonymous chat room. The terminal displays chat room information to the user.

[1458] Step 14:

[1459] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[1460] Example 1

[1461] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1462] Currently, many people feel lonely and socially isolated, which has led to an increase in the problem of lonely deaths. Existing solutions have not been effective enough to address this issue. Therefore, there is a need for a system that can promote positive emotions and social interaction among users.

[1463] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1464] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or speech analysis, and means for updating and developing the character's attributes based on the analysis results, thereby enabling accurate analysis of the user's emotional state in real time, promoting positive emotions, and even social interaction with other users through anonymous communication.

[1465] "Voice data" means digitized voice information provided by a user through voice input.

[1466] "Text data" refers to character information provided by a user through character input.

[1467] "Natural language processing" is a technology that allows machines to understand and analyze human language.

[1468] "Voice analysis" is a technology that analyzes voice data and identifies its characteristics and content.

[1469] "Analyzing emotions" refers to the process of analyzing received audio or text data to identify the user's emotional state therein.

[1470] "Updating and developing the character's attributes" means changing the appearance, skills, and characteristics of the virtual character based on the results of the user's emotional analysis.

[1471] "Adding points" means that the system adds a certain number of points to the user's account.

[1472] "Anonymous communication" is a feature that allows users to interact with other users without revealing their true identity.

[1473] "Generative AI model" refers to an artificial intelligence model used to generate characters and other elements.

[1474] A "cloud server" is a server infrastructure provided over the Internet.

[1475] MODE FOR CARRYING OUT THE INVENTION

[1476] This invention relates to an "emotion analysis application system" that analyzes a user's emotions. This system determines the user's emotional state and, based on the results, changes the attributes of a virtual character, awards points, and promotes anonymous communication. This system is primarily composed of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud.

[1477] Hardware and Software Configuration

[1478] The system includes the following hardware and software:

[1479] User devices: smartphones, tablets, computers

[1480] Server: Cloud server (e.g. AWS, Google Cloud)

[1481] Natural Language Processing Engine: Transformer-based NLP models (e.g., BERT, GPT-3)

[1482] Generative AI models: GANs (generative artificial network), Transformer models

[1483] Speech analysis engine: Google Cloud Speech-to-Text API, Amazon Transcribe

[1484] System Operation Overview

[1485] 1. A user uses a device to open an application that provides a voice or text input interface.

[1486] 2. The user enters voice or text data, for example, entering the text message "Today was a fun day."

[1487] 3. The device temporarily stores the data entered by the user and then sends the data to a server in the cloud.

[1488] 4. The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, and generates an emotion tag as a result of the analysis.

[1489] 5. The server updates the attributes of the virtual character based on the analysis results, allowing the character to grow. Every time the user expresses positive emotions, the character acquires new skills and changes its appearance.

[1490] 6. The server will calculate points based on the sentiment analysis results and add them to the user's account, which can be used for character customization and special rewards.

[1491] 7. The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1492] Specific examples

[1493] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1494] The server receives text data such as "Today was a fun day" and analyzes it using a natural language processing (NLP) engine to generate a positive emotion tag for "fun."

[1495] By continuously acquiring positive emotion tags, the virtual character will learn new dance skills and change its appearance to become brighter.

[1496] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1497] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results.

[1498] Prompt Sentence Examples

[1499] Example prompt 1: "The user types, 'Today was a good day.' Classify this as a positive sentiment tag."

[1500] Example prompt 2: "The user types, 'I had a terrible day today.' Classify this as a negative sentiment tag."

[1501] Example prompt 3: "The user repeatedly expressed the emotion 'fun'. As a result, we'll add a new dance skill to the virtual character and brighten up its appearance."

[1502] In this way, the entire system works together to analyze the user's emotional state and provide feedback and rewards, ultimately helping users to reduce their sense of social isolation through positive activities.

[1503] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1504] Step 1:

[1505] A user opens an application using a terminal, which provides an interface for receiving input voice or text data.

[1506] Input: User speech and text input.

[1507] Output: Temporarily saved audio or text data.

[1508] What happens: The user types in the text "Today was a fun day."

[1509] Step 2:

[1510] The device sends the voice data or text data entered by the user to a server on the cloud.

[1511] Input: Temporarily saved audio or text data.

[1512] Output: The data sent to the server.

[1513] Specific operation: The device sends text data saying "Today was a fun day."

[1514] Step 3:

[1515] The server analyzes the received voice data or text data using a natural language processing engine and a voice analysis engine.

[1516] Input: The audio or text data received by the server.

[1517] Output: Sentiment tags as the analysis results.

[1518] Specific operation: The server analyzes the text data "Today was a fun day" using an NLP engine and generates a positive emotion tag for "fun."

[1519] Step 4:

[1520] The server stores and manages the analysis results, and also uses them to update the character's attributes.

[1521] Input: Sentiment tags as analysis results.

[1522] Output: Updated character attributes.

[1523] Specific behavior: When a positive emotion tag is generated, the character will learn new skills and change their appearance.

[1524] Step 5:

[1525] The server calculates points based on the emotion analysis results and adds them to the user's account.

[1526] Input: Emotion tags as analysis results and user account information.

[1527] Output: The added points.

[1528] Specific Action: Add 10 points based on positive emotions.

[1529] Step 6:

[1530] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[1531] Input: Sentiment tags as analysis results.

[1532] Output:Anonymous chat room created.

[1533] Specific operation: For users who feel lonely, create an anonymous chat room with other users who share the same feelings.

[1534] Through these processing steps, the system analyzes the user's emotions and provides feedback and rewards, thereby promoting positive social interactions.

[1535] (Application example 1)

[1536] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1537] The present invention aims to provide a system that reduces the sense of social isolation and promotes positive emotions in elderly people living alone and users who feel lonely. In particular, the system has a function to monitor the user's emotional state and notify family members or security service providers as necessary, thereby reducing the risk of lonely death.

[1538] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1539] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis, means for saving and managing the analysis results, means for updating and developing character attributes based on the analysis results, means for adding points to the user's account, and means for generating an alert and notifying a specific recipient if the analysis results are negative. This makes it possible to grasp the user's emotional state, promote positive emotions, and provide appropriate support as needed.

[1540] "Voice data" is a digital recording of a user's voice uttered to an application.

[1541] "Text data" refers to character information that a user inputs to an application.

[1542] "Natural language processing" is a technology that allows computers to understand and analyze human language.

[1543] "Speech analysis" is a technology that uses digital signal processing technology to analyze voice data and understand its content and characteristics.

[1544] An "emotion tag" is a label that indicates an emotional state analyzed from audio data or text data.

[1545] A "character" is a virtual being that is generated and grows according to the user's emotional state.

[1546] A "generative AI model" is a model that has been trained using artificial intelligence techniques to perform a specific task.

[1547] "Attributes" are the characteristics and traits that a character possesses.

[1548] "Points" are virtual rewards that users can earn by expressing positive emotions.

[1549] An "alert" is a warning that notifies a specific recipient when a user's emotional state is negative.

[1550] "Recipients" are family members or security service providers who are notified depending on the user's emotional state.

[1551] MODE FOR CARRYING OUT THE INVENTION

[1552] The present invention relates to a user emotion monitoring security system for reducing the risk of lonely death. This system has the function of analyzing the user's emotional state and notifying the user, their family, or a security service provider as necessary.

[1553] System configuration

[1554] The system of the present invention consists of the following main components:

[1555] 1. User terminal: A device for inputting user voice data or text data. Specifically, a mobile device such as a smartphone or tablet is used.

[1556] 2. Cloud server: Analyzes and stores data, and provides APIs.

[1557] 3. Natural Language Processing (NLP) Engine: An NLP engine is used to analyze the received text data and identify the user's sentiment. An example is Google Cloud Natural Language API.

[1558] 4. Speech analysis engine: Used to analyze voice data. An example is IBM Watson Speech to Text.

[1559] 5. Generative AI model: Responsible for character generation and development. For example, OpenAI's GPT series is used for this part.

[1560] 6. Database: A system for storing the results of sentiment analysis and user data.

[1561] System Operation

[1562] 1. Receiving voice and text data

[1563] The user uses the device to input voice or text data, which is then sent to the cloud server. For example, if a user voice-types "I'm feeling a little down today" into their smartphone, this data is immediately sent to the cloud server.

[1564] 2. Emotion analysis

[1565] The server uses an NLP engine and a speech analysis engine to analyze the received data, which generates an emotion tag. For example, if the user says "I'm feeling a little down today," a negative emotion tag is generated.

[1566] 3. Character Creation and Development

[1567] The generative AI model generates a character based on the user's customization options. Furthermore, the character's attributes are updated and developed based on the results of emotion analysis. If a positive emotion tag is generated, the character will acquire new skills and other changes.

[1568] 4. Point reward system

[1569] Based on the user's positive sentiment analysis, points are calculated and added to the user's account, which can be used to customize characters and earn special rewards.

[1570] 5. Security Alert System

[1571] If the analysis result is negative, the server generates an alert and notifies specific recipients (family members or security service providers). For example, if a user shows negative emotions for three consecutive days, the server notifies family members that "the user may have been depressed recently."

[1572] Specific examples

[1573] When a user types "I've been feeling a bit tired lately" into their smartphone, this information is sent to a cloud server and analyzed by an NLP engine. A negative emotion tag is attached, and the generative AI model provides the user with feedback such as "Try to get some rest today." If a negative emotion tag is generated for three consecutive days, an alert is sent to family members.

[1574] Prompt Sentence Examples

[1575] Input: The user is feeling depressed

[1576] Output: Generate positive feedback and check if a security alert is triggered

[1577] This allows the system to manage the user's emotions and provide appropriate support to family and related parties when necessary.

[1578] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1579] Step 1:

[1580] The user inputs voice or text data into the device. For example, when the user opens a smartphone application and inputs "I'm a little tired today" by voice or text, this data is generated.

[1581] Input: User speaks or enters text

[1582] Output: Audio data or text data

[1583] Step 2:

[1584] The device sends the input voice data or text data to the cloud server, which then transfers the data to the cloud server using a secure communication protocol.

[1585] Input: Audio or text data

[1586] Output: Data sent to the cloud server

[1587] Step 3:

[1588] The server analyzes the received voice data with a voice analysis engine and the text data with a natural language processing (NLP) engine. The analysis generates a specific emotion tag (e.g., "negative").

[1589] Input: Audio or text data sent to the server

[1590] Output: Emotion tag

[1591] Step 4:

[1592] The server stores and manages the emotion tags obtained as a result of emotion analysis. The original data is also recorded in the database along with the emotion tags.

[1593] Input: emotion tag

[1594] Output: Emotion tags and raw data stored in the database

[1595] Step 5:

[1596] Based on the emotion analysis results, the server uses a generative AI model to generate and update the character and develop its attributes. The generative AI model applies new skills, changes to appearance, etc. to the character based on prompts.

[1597] Input: emotion tag

[1598] Output: Updated character

[1599] Step 6:

[1600] The server calculates points based on positive sentiment analysis results and adds them to the user's account. For example, if a user types "I had fun today," 10 points will be added.

[1601] Input: Positive sentiment tag

[1602] Output: Updated user points

[1603] Step 7:

[1604] If the sentiment analysis result is negative, the server generates an alert and notifies specific recipients (e.g., family members or security service providers) so that necessary assistance can be provided quickly.

[1605] Input: Negative sentiment tag

[1606] Output: Alert notification sent

[1607] This will create a system that analyzes the user's emotional state throughout all steps and provides appropriate feedback and necessary assistance.

[1608] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1609] The present invention provides an "emotion analysis application system" that can encourage positive emotions in users in order to solve the increasing problem of lonely deaths. This system analyzes the user's emotional state and provides optimal feedback and rewards. In particular, by combining it with an emotion engine, it achieves real-time, highly accurate emotion analysis. A detailed explanation of how to implement this system is provided below.

[1610] System Overview

[1611] This system consists of a user device and a server. The user device can be a smartphone, tablet, or computer, and the server is located on the cloud. This system has the following main functions:

[1612] Receiving voice and text data

[1613] Emotion analysis

[1614] Character Generation and Growth

[1615] Point reward system

[1616] Anonymous communication feature

[1617] Emotion Engine

[1618] Receiving voice and text data

[1619] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[1620] Examples:

[1621] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1622] Emotion analysis

[1623] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[1624] Examples:

[1625] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[1626] Real-time analysis of emotion engine

[1627] The server uses an emotion engine to analyze the user's voice and text data in real time, and the identified emotion data is immediately reflected in the user profile and stored in a database.

[1628] Examples:

[1629] When a user inputs the text "I'm very sad," the server's emotion engine analyzes the emotion "sad" in real time and stores the results in a database.

[1630] Character Generation and Growth

[1631] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[1632] Examples:

[1633] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[1634] Point reward system

[1635] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[1636] Examples:

[1637] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1638] Anonymous communication feature

[1639] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1640] Examples:

[1641] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[1642] Providing Feedback

[1643] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1644] Examples:

[1645] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[1646] The system described in this specification analyzes users' emotions and promotes positive emotions to address the growing problem of lonely deaths. This system allows users to manage their emotions and reduce feelings of social isolation through positive activities. Furthermore, the added emotion engine enables real-time, highly accurate emotion analysis, enabling more personalized feedback and support.

[1647] The processing flow will be explained below.

[1648] Step 1:

[1649] The user uses the device to open an application and selects voice input mode or text input mode.

[1650] Step 2:

[1651] The user inputs voice or text data to express their feelings. For example, they input a message such as "Today was a fun day." The device temporarily stores this data.

[1652] Step 3:

[1653] The device sends the stored voice or text data to the server, and when sending, it checks that the data format is appropriate.

[1654] Step 4:

[1655] The server checks the received audio or text data and prepares for analysis. It checks the data consistency and, if there are no problems, proceeds to the next analysis step.

[1656] Step 5:

[1657] The server analyzes the voice and text data in real time using an emotion engine, which uses natural language processing (NLP) and speech analysis techniques to identify the user's emotions from the data.

[1658] Step 6:

[1659] The server associates the emotion tags generated as a result of the analysis with the user's profile and stores them in a database, thereby accumulating the user's emotion history.

[1660] Step 7:

[1661] The server calculates the character's growth points based on the user's emotion analysis. Positive emotions increase the growth points. These points are reflected in the evolution of the character's skills and appearance.

[1662] Step 8:

[1663] The server updates the character's attributes based on growth points, determines new skills and appearance changes, and generates updated character data.

[1664] Step 9:

[1665] The server sends the updated character data to the device, which displays the new character's skills and appearance changes to the user. For example, a character might acquire a new dance skill.

[1666] Step 10:

[1667] The server calculates points based on positive sentiment analysis and adds them to the user's account, which can be used to customize characters and earn special rewards.

[1668] Step 11:

[1669] The user uses points to select new customization options (e.g., clothing and accessories) for their character. The device sends the selected customization data to the server.

[1670] Step 12:

[1671] The server generates new character data using a generative AI model based on the selected customization options, and sends the generated data to the device to display to the user.

[1672] Step 13:

[1673] When a user uses the anonymous communication function based on their emotional state, the server identifies other users with the same emotional state and creates an anonymous chat room, and the terminal displays the chat room information to the user.

[1674] Step 14:

[1675] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1676] Step 15:

[1677] Users can check their character's evolution, point balance, and emotion history within the application for future use. This information will be available the next time they log in.

[1678] Example 2

[1679] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1680] This invention relates to a system that analyzes users' emotions and promotes positive emotions in order to solve the problem of lonely deaths and improve users' mental health. However, conventional systems often have low accuracy in emotion analysis or difficulty in responding in real time. As a result, feedback and support to users are delayed, and effective mental support is not provided. Furthermore, features such as character development and anonymous communication between users are lacking, resulting in a lack of improvement in the user experience. This has led to the issue of difficulty in continuously eliciting positive emotions in users and the inability to alleviate feelings of social isolation.

[1681] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1682] In this invention, the server includes: means for receiving voice data or text data from a user; means for analyzing emotions from the received voice data or text data using natural language processing or voice analysis; means for reflecting, saving, and managing the analysis results in real time; means for updating and developing a character's attributes based on the analysis results; means for calculating points based on the user's positive emotion analysis results and adding them to the user's account; means for generating and providing feedback to the user; means for generating a character based on character customization options selected by the user using a generative AI model; and means for providing opportunities for anonymous communication with other users based on the user's emotional state. This allows for highly accurate, real-time analysis of a user's emotions and providing personalized feedback and rewards, thereby promoting positive emotions and reducing feelings of social isolation.

[1683] "Voice data" is data input by a user using voice, and is used for emotion analysis.

[1684] "Text data" is data that is input by a user using characters and is used for emotion analysis.

[1685] "Natural language processing" refers to the technology of analyzing and understanding human language using a computer program, and is used to extract emotions from user text data.

[1686] "Voice analysis" refers to the technology of analyzing voice data and extracting features, and is used to determine emotions from a user's voice data.

[1687] "Sentiment analysis" refers to the process of analyzing received audio or text data to identify a user's emotions.

[1688] "Database" refers to a system for systematically storing and managing information such as analyzed emotional data and user profiles.

[1689] A "character" is a virtual entity that a user selects or customizes, and whose attributes are updated and developed based on the results of emotion analysis.

[1690] A "generative AI model" refers to a technology that uses artificial intelligence to generate appropriate output data for specific input data, in this case for character generation and customization.

[1691] A "point reward system" refers to a system that calculates points based on the results of analyzing a user's positive emotions and rewards the user.

[1692] "Feedback" refers to responses to the user, such as suggestions, encouragement, advice, etc., generated based on sentiment analysis.

[1693] "Anonymous communication" refers to a feature that provides users with the opportunity to interact with other users without revealing their identity.

[1694] The present invention relates to an "emotion analysis system" that analyzes a user's emotions and promotes positive emotions. Detailed embodiments of the present invention will be described below.

[1695] System Configuration

[1696] This system consists of a user terminal and a server. The user terminal is a device such as a smartphone, tablet, or computer, and the server is located on the cloud. The main functions of this system are as follows:

[1697] 1. Receiving voice and text data

[1698] 2. Emotion analysis

[1699] 3. Character Creation and Development

[1700] 4. Point reward system

[1701] 5. Anonymous communication feature

[1702] 6. Providing Feedback

[1703] Receiving voice and text data

[1704] A user uses a terminal to input voice or text data, which can be messages or dialogues expressing emotions, and the terminal transmits the input data to a server.

[1705] Examples:

[1706] A user opens an application on their device and types in the text "Today was a fun day." The device immediately sends this data to the server.

[1707] Emotion analysis

[1708] The server uses a natural language processing (NLP) engine and a speech analysis engine to analyze the received voice or text data, thereby identifying the user's emotional state, for example, generating an emotional tag such as positive, negative, or neutral.

[1709] Examples:

[1710] The server receives text data such as "Today was a fun day" and analyzes it using an NLP engine to generate a positive emotion tag for "fun."

[1711] Character Generation and Growth

[1712] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes based on the results of emotion analysis. Each time the user expresses positive emotion, the character acquires new skills and changes appearance.

[1713] Examples:

[1714] By repeatedly expressing the emotion tag "fun," the character will acquire new dance skills and its appearance will become brighter.

[1715] Point reward system

[1716] The server calculates points based on the user's positive sentiment analysis and adds them to the user's account, which can be used for character customization and special rewards.

[1717] Examples:

[1718] The user types "Today is a great day," and the server adds 10 points based on this positive sentiment, which the user can use to buy new clothes for their character.

[1719] Anonymous communication feature

[1720] The server provides users with the opportunity for anonymous communication with other users based on their emotional state, allowing them to have positive interactions with other users through direct dialogue and messaging.

[1721] Examples:

[1722] When a user feels lonely, the server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results, and the terminal displays the chat room information to the user.

[1723] Providing Feedback

[1724] Based on the emotional data analyzed by the emotion engine, the server provides appropriate feedback to the user, such as encouragement or advice to improve the user's emotional state.

[1725] Examples:

[1726] If the user expresses the emotion "sad," the server provides feedback such as "Why don't you try doing something fun today?"

[1727] Example prompts for generative AI models

[1728] Possible prompts to input to a generative AI model include:

[1729] "When a user inputs positive emotions, generate new skills or changes to the appearance of the virtual character based on that emotion."

[1730] As described above, with the above-mentioned configuration and specific examples, the present invention provides a system that can analyze a user's emotions with high accuracy and promote positive emotions, thereby reducing feelings of social isolation.

[1731] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1732] Step 1:

[1733] The user inputs voice or text data.

[1734] A user uses a terminal to input a voice or text message. For example, a user opens an application and inputs the text "Today was a fun day." This input data (voice data or text data) is sent to the next processing step.

[1735] Step 2:

[1736] The terminal sends the input data to the server.

[1737] The device sends the voice or text data entered by the user to the server, where it can be analyzed in the next processing step. The input here is the user's voice or text data, and the output is the data sent to the server.

[1738] Step 3:

[1739] The server analyzes the voice or text data using a natural language processing (NLP) engine and a voice analysis engine.

[1740] The server analyzes the received data using an NLP engine or speech analysis engine to identify the user's emotional state. For example, it generates a positive emotion tag "fun" for the text data "Today was a fun day." The input is the data sent to the server, and the output is the generated emotion tag.

[1741] Step 4:

[1742] The server stores the analysis results in a database.

[1743] The emotion tags generated by the server are saved in a database in real time by the emotion engine. This saving process reflects the analysis results in the user profile. The input is the generated emotion tags, and the output is the user's emotion data saved in the database.

[1744] Step 5:

[1745] The server generates and updates characters using generative AI models.

[1746] The server uses a generative AI model to generate a virtual character based on the customization options selected by the user. It also updates and develops the character's attributes in real time based on the results of emotional analysis. Each time the user expresses positive emotion, the character acquires a new skill or changes appearance. The input is the emotional analysis results and customization options, and the output is the generated or updated character.

[1747] Step 6:

[1748] The server calculates points based on positive sentiment analysis results and adds them to the user's account.

[1749] The server calculates points based on the user's positive sentiment analysis result and adds them to the user's account. For example, if the user enters "Today is a great day," the server adds 10 points based on this sentiment. The input is the positive sentiment analysis result, and the output is the added points.

[1750] Step 7:

[1751] The terminal notifies the user of the point information.

[1752] The terminal notifies the user of the point information received from the server. For example, a message saying "10 points have been added to your account" is displayed. The input is the added point information, and the output is the message notified to the user.

[1753] Step 8:

[1754] The server provides opportunities for anonymous communication with other users based on the user's emotional state.

[1755] The server creates an anonymous chat room with other users who are in a similar emotional state based on the emotion analysis results. This function allows users to anonymously interact with other users and promote positive emotions. The input is the user's emotion analysis results, and the output is anonymous chat room information.

[1756] Step 9:

[1757] The terminal displays the anonymous chat room information to the user.

[1758] The terminal displays the anonymous chat room information received from the server to the user. For example, a message saying "An anonymous chat room has been created" is displayed, and the user can now access the chat room. The input is the anonymous chat room information, and the output is the message displayed to the user.

[1759] Step 10:

[1760] The server provides appropriate feedback to the user.

[1761] The server generates and provides feedback such as encouragement or advice to the user based on the analysis results from the emotion engine. For example, if the user inputs "sad," the server generates the feedback "Why don't you try doing something fun today?" The input is the analysis result, and the output is the generated feedback message.

[1762] Step 11:

[1763] The device displays the feedback to the user.

[1764] The terminal displays to the user the feedback message it receives from the server, for example, "Why not try something fun today?" The input is the feedback message, and the output is the message displayed to the user.

[1765] In this way, the entire system works together to analyze the user's emotions and carry out a series of processes to promote positive emotions.

[1766] (Application example 2)

[1767] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1768] In modern society, the number of people experiencing loneliness and isolation is increasing, and this has become a serious problem. In particular, there is a need to prevent lonely deaths, but emotional care is often inadequate. In addition, there is a lack of approaches to improving emotional situations, so there is a need for methods to promote positive emotions in daily life.

[1769] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1770] In this invention, the server includes means for receiving voice data or text data from a user, means for analyzing emotions in the received voice data or text data using natural language processing or voice analysis, means for suggesting optimal meals to the user based on the analysis results, and means for providing discount coupons based on the positive emotion analysis results. This makes it possible to analyze the user's emotional state, promote positive emotions through meals, and alleviate feelings of loneliness and isolation.

[1771] "Voice data" refers to data that is a digital recording of a user's voice.

[1772] "Text data" refers to digital data containing text information entered by a user.

[1773] "Natural language processing" is the field of computer science that aims to understand and analyze human language.

[1774] "Voice analysis" is a technology that analyzes voice data and extracts meaning and emotions from it.

[1775] "Emotion analysis" is a technology that identifies emotions from voice data and text data.

[1776] A "character" is a virtual being or avatar that can be customized by a user.

[1777] "Attributes" are specific characteristics or traits that a character possesses.

[1778] "Growth" refers to the process by which a character evolves based on the user's actions and emotions, gaining new skills and appearances.

[1779] "Points" are rewards awarded based on a user's positive behavior and the results of emotional analysis.

[1780] A "meal" is any food or drink consumed by a user.

[1781] A "discount coupon" is a digital or physical coupon that entitles a user to a service or product at a discounted price.

[1782] This invention provides an "emotion analysis application system" that can promote positive emotions in users in order to solve the increasing problem of lonely deaths. This system grasps the user's emotional state through analysis of voice and text data and provides appropriate feedback. It also makes meal suggestions and offers discount coupons based on the analysis results.

[1783] System configuration

[1784] This system mainly consists of a user device and a server. User devices include smartphones, tablets, and computers. The server is located on the cloud and is responsible for analyzing voice and text data, managing data, and providing feedback.

[1785] Receiving voice and text data

[1786] Using an application on the device, users input their emotions and state of mind through voice or text, and the device immediately transmits this data to the server.

[1787] Specific examples

[1788] A user opens the application on their smartphone and types in the text, "Today was a fun day." The device immediately sends this data to the server.

[1789] Emotion analysis

[1790] The server receives the transmitted voice or text data and uses a natural language processing (NLP) engine or a voice analysis engine to analyze the user's emotions and generate emotion tags such as positive, negative, or neutral.

[1791] Specific examples

[1792] The text data "Today was a fun day" is analyzed using an NLP engine to generate a positive emotion tag for "fun."

[1793] Optimal meal suggestions

[1794] Based on the analysis results, the server uses a generative AI model to suggest the best meal to improve the user's emotional state, presenting specific meal menus according to the user's emotions.

[1795] Specific examples

[1796] If you type "I'm feeling a little lonely today," it will suggest a warm soup or a nutritious salad.

[1797] Offering discount coupons

[1798] If a positive emotion tag is obtained, the server will offer the user a discount coupon that can be used on their next meal order.

[1799] Specific examples

[1800] If a user types "Today is a great day," the server will offer them a 10% off coupon.

[1801] Hardware and software used

[1802] Hardware: smartphones, tablets, computers

[1803] Software: Natural language processing engine (NLP engine), speech analysis engine, generative AI model

[1804] Example prompts for generative AI models

[1805] A user enters, "I'm feeling a bit tired and lonely today." Based on this emotion, please suggest dishes that will improve the user's mood. For example, you could recommend meals such as "warm soup," "nutritious salad," or "protein bar that's perfect for replenishing energy." Please include a reason for your recommendation.

[1806] As described above, the emotion analysis application system can analyze the user's emotional state in real time and provide appropriate feedback, meal suggestions, and discount coupons based on that analysis, thereby promoting positive emotions and helping to reduce feelings of loneliness and isolation.

[1807] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1808] Step 1:

[1809] A user starts the application using a device such as a smartphone or tablet. The user inputs their emotional state by voice or text. The input data (voice data or text data) is temporarily stored on the device.

[1810] Input: Text or voice when the user inputs their emotional state.

[1811] Output: Audio or text data stored on the device.

[1812] Action: The user enters the text "Today was a fun day."

[1813] Step 2:

[1814] The device sends the input voice or text data to the server, where the data is encrypted and transmitted securely.

[1815] Input: Voice or text data stored on the device.

[1816] Output: The audio or text data sent to the server.

[1817] Operation: The device sends text data such as "Today was a fun day" to the server.

[1818] Step 3:

[1819] The server analyzes the received voice or text data using a natural language processing (NLP) engine or speech analysis engine for sentiment analysis, which generates sentiment tags such as positive, negative, and neutral.

[1820] Input: The audio or text data sent to the server.

[1821] Output: A sentiment tag (e.g., "fun").

[1822] How it works: The server analyzes the text data "Today was a fun day" and generates a positive emotion tag for "fun."

[1823] Step 4:

[1824] The server uses a generative AI model to create prompts to suggest optimal meals for the user based on the analyzed emotion tags, and then uses the generative AI model to generate specific meal menus.

[1825] Input: Sentiment tag (positive, negative, neutral, etc.).

[1826] Output: Specific meal menu suggestions.

[1827] How it works: If the emotion tag is "fun," the generative AI model will suggest meals such as "hot soup" or "nutritious salad."

[1828] Step 5:

[1829] If the server obtains a positive emotion tag, it generates and sends the user a discount coupon that can be used on their next meal order.

[1830] Input: Positive sentiment tags.

[1831] Output: Discount coupon.

[1832] What it does: If the server receives the input "Today is a great day," it generates a 10% off coupon and sends it to the user.

[1833] Step 6:

[1834] The server sends the meal menu prompt and discount coupon information to the user terminal, which displays the information for the user to check.

[1835] Input: Specific meal suggestions and discount coupons.

[1836] Output: Meal menu and coupons displayed on the user's device.

[1837] What it does: The device displays "Recommended Meal: Hot Soup" and "10% Off Coupon."

[1838] Through the above processing flow, the system analyzes users' emotions and provides optimal feedback, meal suggestions, and discount coupons.

[1839] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1840] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1841] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1842] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1843] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1844] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1845] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1846] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1847] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1848] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1849] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1850] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1851] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1852] 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.

[1853] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1854] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1855] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1856] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1857] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1858] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1859] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1860] The following is further disclosed regarding the above embodiment.

[1861] (Claim 1)

[1862] means for receiving voice data or text data from a user;

[1863] means for analyzing emotion from the received voice or text data using natural language processing or speech analysis;

[1864] a means of storing and managing the analysis results;

[1865] A means to update and develop the character's attributes based on the analysis results,

[1866] a means for adding points to a user's account;

[1867] A system including:

[1868] (Claim 2)

[1869] 10. The system of claim 1, further comprising: means for generating a character using a generative AI model based on user-selected character customization options.

[1870] (Claim 3)

[1871] 10. The system of claim 1, further comprising means for providing anonymous communication opportunities for other users based on the user's emotional state.

[1872] "Example 1"

[1873] (Claim 1)

[1874] means for receiving voice data or text data from a user;

[1875] means for analyzing emotion from the received voice or text data using natural language processing or speech analysis;

[1876] a means of storing and managing the analysis results;

[1877] A means to update and develop the character's attributes based on the analysis results,

[1878] a means for adding points to a user's account;

[1879] means for providing opportunities for anonymous communication with other users based on the user's emotional state;

[1880] A system including:

[1881] (Claim 2)

[1882] 10. The system of claim 1, further comprising: means for generating a character using a generative AI model based on user-selected character customization options.

[1883] (Claim 3)

[1884] 10. The system of claim 1, utilizing a cloud server to perform processing and including a natural language processing engine and a generative AI model.

[1885] "Application Example 1"

[1886] (Claim 1)

[1887] means for receiving voice data or text data from a user;

[1888] means for analyzing emotion from the received voice or text data using natural language processing or speech analysis;

[1889] a means of storing and managing the analysis results;

[1890] A means to update and develop the character's attributes based on the analysis results,

[1891] a means for adding points to a user's account;

[1892] A means to generate an alert and notify designated recipients if the analysis results are negative;

[1893] A system including:

[1894] (Claim 2)

[1895] 10. The system of claim 1, further comprising: means for generating a character using a generative AI model based on user-selected character customization options.

[1896] (Claim 3)

[1897] 10. The system of claim 1, further comprising means for providing anonymous communication opportunities for other users based on the user's emotional state.

[1898] "Example 2: Combining Emotion Engines"

[1899] (Claim 1)

[1900] means for receiving voice data or text data from a user;

[1901] means for analyzing emotion from the received voice or text data using natural language processing or speech analysis;

[1902] A means to reflect, save and manage analysis results in real time,

[1903] A means to update and develop the character's attributes based on the analysis results,

[1904] a means for calculating points based on the user's positive sentiment analysis result and adding the points to the user's account;

[1905] means for generating and providing feedback to the user;

[1906] A system including:

[1907] (Claim 2)

[1908] 10. The system of claim 1, further comprising: means for generating a character based on user-selected character customization options using a generative AI model.

[1909] (Claim 3)

[1910] 10. The system of claim 1, further comprising means for providing opportunities for anonymous communication with other users based on the user's emotional state.

[1911] "Application example 2 when combining emotion engines"

[1912] (Claim 1)

[1913] means for receiving voice data or text data from a user;

[1914] means for analyzing emotion from the received voice or text data using natural language processing or speech analysis;

[1915] a means of storing and managing the analysis results;

[1916] A means to update and develop the character's attributes based on the analysis results,

[1917] a means for adding points to a user's account;

[1918] A means for suggesting optimal meals to users based on the analysis results;

[1919] A means for providing discount coupons based on positive sentiment analysis results;

[1920] A system including:

[1921] (Claim 2)

[1922] 10. The system of claim 1, further comprising: means for generating a character using a generative AI model based on user-selected character customization options.

[1923] (Claim 3)

[1924] 10. The system of claim 1, further comprising means for providing anonymous communication opportunities for other users based on the user's emotional state. [Explanation of symbols]

[1925] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving voice data or text data from a user; means for analyzing emotion from the received voice or text data using natural language processing or speech analysis; a means of storing and managing the analysis results; A means to update and develop the character's attributes based on the analysis results, a means for adding points to a user's account; A system including:

2. The system of claim 1 , further comprising: means for generating a character using a generative AI model based on user-selected character customization options.

3. The system of claim 1 further comprising means for providing anonymous communication opportunities for other users based on the user's emotional state.

Images