System

Abstract

A system is provided.SOLUTION: A system comprising: means for recording player behavior; means for collecting facial expressions and audio of the player; means for analyzing the collected information to infer a state of mind of the player; means for generating a AI response based on the inferred state of mind; and means for presenting the generated AI response to the player.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] Conventional algorithm-based AI has difficulty reproducing the complex psychological tactics between players in board games such as Werewolf and Poker, where psychological warfare is an important element. This has resulted in a monotonous and predictable gaming experience when playing against the CPU, making it difficult to sustain the player's interest. The present invention aims to solve this problem by realizing an AI that analyzes the player's behavior and psychological state in real time and responds in a more human-like manner. [Means for solving the problem]

[0005] The present invention provides a system including a means for recording the player's actions, a means for collecting the player's facial expression and voice data, a means for analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state, and a means for presenting the generated AI response to the player. Furthermore, the system includes a means for setting the AI's personality and conducting psychological warfare based on the set personality, and a means for learning the AI's behavioral patterns to determine the next game strategy, thereby providing the player with a more realistic and exciting gaming experience.

[0006] "Player actions" include all actions taken by a player during a game, including, for example, selecting or exchanging cards, betting, and making statements.

[0007] "Player's facial expression" refers to the movements and expressions of the player's face, which indicate emotional states such as smiling, surprise, or nervousness.

[0008] "Audio Data" refers to recorded information of words or voices uttered by players during the game, intended to convey emotions or intentions.

[0009] "Analysis" refers to the process of inferring a player's behavioral patterns and psychological state based on collected data.

[0010] "Mental state" refers to the player's internal emotional and thought state, including feelings such as joy, fear, and tension.

[0011] "AI response" refers to the actions and statements that the AI ​​makes toward the player based on the analysis results.

[0012] "AI personality" refers to the characteristics of the personality and behavioral patterns set in an AI, such as attributes such as "a calm analyst" or "an impulsive gambler."

[0013] A "behavioral pattern" refers to a tendency for a player to repeatedly exhibit certain behaviors, including consistent behavior in specific situations.

[0014] A "game strategy" refers to a series of actions or plans chosen by a player or AI to gain an advantage in the game. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

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

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] System Overview

[0037] This invention provides a game system that analyzes the player's behavior and psychological state and uses AI to show more human-like responses. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the AI ​​responds appropriately based on that information, providing the player with a realistic and exciting match.

[0038] Program processing

[0039] Step 1: Initial Setup

[0040] server:

[0041] 1. Create a game room and manage player information.

[0042] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0043] Example: The server creates a Werewolf game room, and when a player joins, the AI ​​player is given the personality of a "calm analyst."

[0044] Step 2: Collect player data

[0045] Device:

[0046] 1. All player actions (card selection, exchanges, bets, conversations, etc.) are recorded as a log in real time.

[0047] 2. Using a camera and microphone, the player's facial expression and voice data are collected and sent to the server.

[0048] Example: A terminal logs the actions of players exchanging cards during a poker game, and at the same time, a camera captures the players' expressions of laughter or surprise, and sends the video data to a server.

[0049] Step 3: Data analysis

[0050] server:

[0051] 1. Analyze the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's hand habits and behavioral patterns, while the facial expression data and voice data are used as basic data to infer the player's emotional state.

[0052] 2. Analyze using machine learning algorithms to predict the player's psychological state in real time.

[0053] Example: The server analyzes the behavior of a player playing poker and discovers a behavioral pattern of "smiling when making high bets." Based on this, the server infers that the player has a strong poker hand.

[0054] Step 4: AI response generation

[0055] server:

[0056] 1. Based on the analysis results, the AI ​​player's next actions and statements are determined. The AI's responses are customized based on the inferred psychological state and behavioral patterns.

[0057] 2. The determined response is sent to the terminal in real time.

[0058] Example: The server carefully chooses the next hand and has the AI ​​player say, "You look like you have a strong hand."

[0059] Step 5: Player feedback

[0060] Device:

[0061] 1. Displaying the AI's responses received from the server to the player, including audio output and on-screen text display.

[0062] 2. Provide an interface that prompts the player to take the next action.

[0063] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0064] Example

[0065] When this system is applied to the Werewolf game, the AI ​​analyzes players' comments and facial expressions to identify suspicious individuals. When applied to poker, the AI ​​infers a player's psychological state from their betting behavior and facial expressions, and adjusts their strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[0066] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0067] The processing flow will be explained below.

[0068] Step 1: Initial Setup

[0069] server:

[0070] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0071] 2. When a player joins the game, they set a personality for each AI player, which will be the basis for the AI's behavior patterns and reactions.

[0072] Specific behavior:

[0073] The server creates and initializes a new game room.

[0074] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "calm analyst" or "intuitive decision maker."

[0075] Step 2: Collect player data

[0076] Device:

[0077] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0078] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0079] Specific behavior:

[0080] The device instantly captures each of the player's actions and saves them as an event log.

[0081] The device's camera captures the player's facial expressions frame by frame, and the microphone records audio data in real time, which is then sent to a server.

[0082] Step 3: Data analysis

[0083] server:

[0084] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0085] 2. Using machine learning algorithms, we analyze data and predict players' psychological state in real time.

[0086] Specific behavior:

[0087] The behavioral analysis module analyzes the player's action history and learns specific behavioral patterns (for example, reactions when a specific card is dealt).

[0088] The emotion analysis module analyzes facial expression and voice data to estimate the player's emotional state (tension, anxiety, joy, etc.).

[0089] Step 4: AI response generation

[0090] server:

[0091] 1. Based on the analysis results, the AI ​​player's next action or statement is determined. The optimal reaction is generated based on the inferred psychological state and behavioral patterns.

[0092] 2. The determined response is sent to the terminal in real time.

[0093] Specific behavior:

[0094] The server runs the AI's action decision algorithm and generates the optimal next action or statement based on the player's behavior and psychological state.

[0095] The generated response is sent to the terminal for the next process.

[0096] Step 5: Player Feedback

[0097] Device:

[0098] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0099] 2. Provide an interface to prompt the player for their next action.

[0100] Specific behavior:

[0101] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[0102] Displays buttons and options that allow the player to choose their next action.

[0103] Step 6: Iterate on game progression

[0104] User:

[0105] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[0106] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[0107] Specific behavior:

[0108] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[0109] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[0110] Example 1

[0111] 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."

[0112] Conventional game systems lacked sufficient analysis of player behavior and psychological state, limiting real-time responses. As a result, players easily became bored with monotonous gameplay and were unable to obtain truly exciting experiences. In particular, the lack of AI responses that accurately reflected the player's emotions and behavior patterns led to a lack of tension and realism in competitive games.

[0113] 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.

[0114] In this invention, the server includes means for recording player actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data and using a machine learning algorithm to infer the player's psychological state, means for generating an AI response based on the inferred psychological state and behavioral pattern, and means for outputting voice and displaying on a screen to present the generated AI response to the player. This allows the player to receive AI responses based on their own actions and psychological state in real time, enabling a more exciting and realistic gaming experience.

[0115] A "means for recording player actions" is a device or method for saving a series of actions and choices made by a player in a game in log form.

[0116] "Means for collecting player's facial expression and voice data" refers to a device or method that uses a camera or microphone to collect a player's facial expression and voice in real time and record that data.

[0117] "Means of using machine learning algorithms to analyze collected data and infer a player's psychological state" refers to a device or method that uses machine learning technology to analyze and infer a player's emotions and psychological characteristics based on acquired behavioral, facial, and voice data.

[0118] "Means for generating AI responses based on inferred psychological states and behavioral patterns" refers to a device or method that allows an AI to design and generate appropriate responses and actions based on the analyzed psychological states and behavioral patterns of a player.

[0119] "Means for audio output and on-screen display to present the generated AI's response to the player" refers to a device or method that outputs audio via a speaker or headset and displays text and visuals on the screen to communicate the generated AI's response to the player.

[0120] "Means for setting an AI's personality and engaging in psychological warfare based on the set personality" refers to a device or method for initially setting a specific personality or characteristics in an AI and engaging in psychological warfare with the player within the game based on that.

[0121] "Means for learning behavioral patterns and determining the next game strategy" refers to a device or method that analyzes a player's past behavioral data and uses the results to plan and determine future strategies and actions in the game.

[0122] MODE FOR CARRYING OUT THE INVENTION

[0123] The system of the present invention analyzes the player's behavior and psychological state and uses AI to provide more human-like responses, thereby providing a realistic and exciting competitive game. The components of the system and their specific implementation methods are described in detail below.

[0124] System Components

[0125] 1. A way to record player actions

[0126] Terminal: All actions that players take in the game (e.g., card selection and exchange, bets, conversations, etc.) are logged in real time using a local database such as SQLite.

[0127] 2. A means of collecting facial and audio data from players

[0128] Device: Using a camera and microphone, the player's facial expression and voice data are collected in real time. Facial expression data is analyzed using the OpenCV library, and voice data is converted to text using the Google Cloud Speech-to-Text API.

[0129] 3. Using machine learning algorithms to analyze data and infer player psychology

[0130] Server: The collected behavioral logs, facial expression data, and audio data are preprocessed using Python's pandas library, and the facial expression data is analyzed using a TensorFlow model.Furthermore, psychological states are inferred in real time using scikit-learn's random forest and neural network.

[0131] 4. A means of generating AI responses based on inferred psychological states and behavioral patterns

[0132] Server: Based on the analysis results, the server designs the next actions and statements of the AI ​​player. It customizes responses based on preset rules, conditional statements, and probability models, and transmits them to the device in real time via the WebSocket protocol.

[0133] 5. A means of outputting audio and displaying the generated AI's responses to the player

[0134] Terminal: Displays the AI's responses received from the server to the player, using Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen, and provides an interface to wait for the next action.

[0135] Specific examples

[0136] Poker game example:

[0137] During a poker game, the device logs the player's actions when exchanging cards. At the same time, the camera captures the player's expressions of laughter or surprise, and sends the video data to the server in real time. The server analyzes this and discovers a behavioral pattern: "Smiling when placing a high bet." Based on this, the AI ​​says, "Judging from your expression, that's a strong hand," and presents it to the player in real time.

[0138] Prompt Sentence Examples

[0139] Example prompts for generative AI models:

[0140] "We provide a dataset containing player behavior patterns and psychological states. Please analyze this information and infer the psychological state of a player when they smile during high bets in poker. Then, based on that inference, suggest what action the AI ​​player should take next."

[0141] In this way, the present invention analyzes the player's behavior and psychological state in real time and provides AI responses based on that analysis, thereby achieving a more realistic gaming experience.

[0142] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0143] Step 1:

[0144] server:

[0145] The server creates a game room and manages player information. When each player joins the game, it sets the AI ​​personality. For example, when player A joins, the AI ​​personality "Calm Analyst" is set, and that information is saved in a MySQL database.

[0146] Input: Player participation information

[0147] Output: Game room setting information, AI personality setting information

[0148] Specific operation: Record player information and AI personality in a MySQL database.

[0149] Step 2:

[0150] Device:

[0151] The device records the player's actions (such as card selection and exchange, betting, and conversation) in real time as a log. It also collects facial expression data using a camera and voice data using a microphone, and sends the data to the server.

[0152] Input: Player behavior data, facial expression data, voice data

[0153] Output: Data sent to the server (behavior log, facial expression data, voice data)

[0154] Specific operations: Record behavior logs in SQLite, capture facial expressions using OpenCV, convert speech to text using the Google Cloud Speech-to-Text API, and send these to the server.

[0155] Step 3:

[0156] server:

[0157] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it preprocesses the data using Python's pandas library, analyzes the facial expression data using a TensorFlow model, and then uses scikit-learn's machine learning algorithm to infer psychological states.

[0158] Input: Behavioral log, facial expression data, voice data

[0159] Output: Predicted psychological state, behavioral patterns

[0160] Specific operations: Preprocessing behavioral logs with pandas, facial expression analysis with TensorFlow, and psychological state estimation with scikit-learn.

[0161] Step 4:

[0162] server:

[0163] The server generates AI responses based on the inferred psychological state and behavioral patterns by using preset rules, conditional statements, and probability models to determine the AI's next actions and statements, and transmits them to the device in real time using the WebSocket protocol.

[0164] Input: Predicted psychological state, behavioral patterns

[0165] Output: AI response (actions and statements)

[0166] Specific operation: A response is generated based on the results of the machine learning algorithm and sent to the device via WebSocket.

[0167] Step 5:

[0168] Device:

[0169] The device displays the AI's responses received from the server to the player. Specifically, it uses Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen. It also provides an interface to prompt the player to take the next action.

[0170] Input: AI response from the server

[0171] Output: The response (audio and text) presented to the player

[0172] Specific operations: Outputs voice, displays text, and displays a GUI prompting the next action.

[0173] (Application example 1)

[0174] 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."

[0175] On conventional online shopping sites, the user's shopping experience is not personalized, and real-time responses and product recommendations based on the player's behavior and emotional state are not provided, limiting the improvement of user satisfaction. The present invention aims to revolutionize the traditional shopping experience and dramatically improve user satisfaction by collecting user behavior, facial expressions, and voice data in real time and using artificial intelligence to provide appropriate responses and product recommendations based on that data.

[0176] 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.

[0177] In this invention, the server includes means for recording user behavior, means for collecting user facial expression and voice data, means for analyzing the collected data to infer the user's psychological state, means for generating an AI response based on the inferred psychological state, means for presenting the generated AI response to the user, means for recording the user's browsing, selection, and purchase behavior, and means for recommending products based on the user's preferences and past purchase data, thereby enabling personalized recommendations and information provision that responds to the user's behavior and psychological state in real time.

[0178] "User" refers to an individual or corporation that uses the System to shop.

[0179] "Action" refers to the operations, actions, and intentional acts that users perform on the system.

[0180] "Facial expression data" refers to video information that records the user's facial movements and expressions.

[0181] "Voice Data" means acoustic information that records a user's speech or other sounds.

[0182] "Artificial intelligence" refers to a computer program that uses machine learning algorithms and data analysis techniques to understand a user's behavior and psychological state and generate appropriate responses.

[0183] "Reaction" refers to the responses and actions that AI generates based on the user's behavior and psychological state.

[0184] "Product recommendation" refers to artificial intelligence suggesting specific products to purchase based on user preferences and past purchase data.

[0185] "Data analysis" refers to the process of processing collected user behavioral data, facial expression data, and voice data to infer the user's psychological state and preferences.

[0186] "User information" refers comprehensively to data about users, such as personal information, behavioral history, and purchase history.

[0187] "Personalization" refers to providing services that are customized to suit the individual characteristics and preferences of each user.

[0188] "Recommendation content" refers to information about products or services suggested to users.

[0189] "System" refers to the hardware and software that analyzes user behavior and psychological state and enables artificial intelligence to generate appropriate responses and recommendations.

[0190] The system of the present invention analyzes a user's behavior and psychological state and provides personalized product recommendations based on the results. This system is mainly composed of a server, a smartphone terminal, and a machine learning algorithm. Specific embodiments are described below.

[0191] System Overview

[0192] Initial Setup

[0193] The server initiates a user's shopping session and manages user information. At the start of each session, the AI ​​sets up a recommendation algorithm based on past purchase data and browsing history.

[0194] Data collection

[0195] The smartphone device records the user's browsing, selection, purchase, and other actions in real time, and also collects facial expression and voice data using the device's built-in camera and microphone, which are then sent to a server.

[0196] Data analysis

[0197] The server analyzes the collected behavioral logs, facial expression data, and voice data using machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time.

[0198] AI reaction generation

[0199] The server then uses the analysis results to determine the next recommended product or coupon. Based on the estimated psychological state and past purchase data, the AI ​​generates an appropriate response and sends the results to the smartphone device in real time.

[0200] User Feedback

[0201] The smartphone terminal displays the recommendation information received from the server to the user, including product images and discount information in text, and provides an interface that prompts the user to take the next action.

[0202] Hardware and software used

[0203] Hardware: Smartphone (camera, microphone, accelerometer), server (cloud service)

[0204] Software: Machine learning algorithms (TensorFlow, PyTorch), real-time databases (Firebase, MongoDB), natural language processing (NLP) models (BERT, GPT-3)

[0205] Specific examples of processing

[0206] For example, if a user smiles while browsing a particular product, the system can infer that the product is a favorite and recommend related products. If the user is confused, the system can provide a detailed description and review of the product. Here are some examples of prompts:

[0207] Examples of prompt statements

[0208] "If a user smiles while browsing products on their phone, show them relevant product recommendations. Additionally, if they're confused, provide them with a detailed product description."

[0209] "When a user says, 'Tell me about this product,' provide more information about the product in your voice. If the user looks confused, offer discounts on related products."

[0210] This allows the system of the present invention to respond to the user's behavior and state of mind in real time, providing a personalized shopping experience.

[0211] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0212] Step 1:

[0213] Initial Setup

[0214] The server initiates the user's shopping session and manages user information. Specifically, it retrieves the user's past purchase data and browsing history from a database and provides them as input to the AI ​​to set up an initial recommendation algorithm. As a result, an initial list of recommended products is generated for the user.

[0215] Step 2:

[0216] Behavioral data collection

[0217] The device records user actions such as browsing, selection, and purchase in real time. For example, when a user views a product page or adds a product to their cart, the event is recorded as a log. This behavioral data can be sent to a server for real-time analysis. The input is the user's operation event, and the output is the behavioral log data sent to the server.

[0218] Step 3:

[0219] Facial and vocal data collection

[0220] The device uses a camera and microphone to collect the user's facial expressions and audio data. For example, if a user smiles while browsing a product page, the video information is captured. Similarly, audio data is collected by the microphone, and what the user says is sent to the server. The input is video and audio data, and the output is the transmission of this data to the server.

[0221] Step 4:

[0222] Data analysis

[0223] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it uses machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time. For example, it determines that a user who smiles a lot is likely to like a particular product. This process receives the behavioral logs and facial expression / voice data as input, and obtains the inferred psychological state as output.

[0224] Step 5:

[0225] Generating product recommendations

[0226] The server then determines the next product or coupon to recommend based on the analysis results. Using a machine learning algorithm, it generates a list of recommended products based on the user's psychological state and past purchase data, and sends it to the device in real time. The input is the estimated psychological state and past purchase data, and the output is the created product recommendation list.

[0227] Step 6:

[0228] User feedback

[0229] The device displays the recommendation information received from the server to the user, including product images and text display of discount information. For example, if a user smiles while viewing a particular product, a discount coupon will be displayed along with recommendations for related products. The input is the recommendation information received from the server, and the output is visual and audio feedback to the user.

[0230] Step 7:

[0231] Next Action Promoting Interface

[0232] The device provides an interface that prompts the user for the next action, such as a button to add related products to the cart or a link to view more information. This allows the user to easily select the next step. The input is the interface element that the user interacts with, and the output is the interface display that prompts the user to do the next action.

[0233] 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.

[0234] System Overview

[0235] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[0236] Program processing

[0237] Step 1: Initial Setup

[0238] server:

[0239] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0240] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0241] Example: A server creates a poker room, and when a player joins, it assigns the AI ​​player a personality called "Intuitive Decision Maker."

[0242] Step 2: Collect player data

[0243] Device:

[0244] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0245] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0246] Example: The device logs the actions of players exchanging cards, and at the same time, the camera captures the players' expressions of laughter or surprise, and sends the video data to the server.

[0247] Step 3: Data analysis and application of the sentiment engine

[0248] server:

[0249] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0250] 2. Use the emotion engine to recognize and track player emotions based on this data.

[0251] Example: The server analyzes the behavior of players during poker and discovers a behavioral pattern of "smiling when betting high amounts." The emotion engine recognizes the player's emotions (relief, joy).

[0252] Step 4: AI response generation

[0253] server:

[0254] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[0255] 2. The determined response is sent to the terminal in real time.

[0256] Example: The server runs an AI action decision algorithm to generate the optimal next action or statement based on the player's behavior and emotional state. The AI ​​player says, "Your facial expression suggests you have a strong hand."

[0257] Step 5: Player feedback

[0258] Device:

[0259] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0260] 2. Provide an interface to prompt the player for their next action.

[0261] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0262] Example

[0263] When this system is applied to the Werewolf game, the AI ​​analyzes the player's comments and facial expressions, and the emotion engine recognizes the player's emotions and identifies suspicious individuals. When applied to poker, the AI ​​infers the player's psychological state from their betting behavior, facial expressions, and emotional analysis by the emotion engine, and adjusts strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[0264] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0265] The processing flow will be explained below.

[0266] Step 1: Initial Setup

[0267] server:

[0268] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0269] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0270] Specific behavior:

[0271] The server creates and initializes a new game room.

[0272] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "intuitive decision maker" or "calm analyst."

[0273] Step 2: Collect player and sentiment data

[0274] Device:

[0275] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0276] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0277] Specific behavior:

[0278] The terminal logs the actions of players as they exchange cards and bet.

[0279] The device's camera captures the player's facial expressions (smile, surprise, etc.) frame by frame, and the microphone records the player's voice data in real time. These data are then sent to the server.

[0280] Step 3: Data analysis and application of the sentiment engine

[0281] server:

[0282] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0283] 2. Use the emotion engine to recognize and track player emotions based on this data.

[0284] Specific behavior:

[0285] The behavioral analysis module analyzes the player's action history and learns certain behavioral patterns (e.g., "smiling when placing high bets").

[0286] The emotion analysis module analyzes facial and voice data to recognize and track the player's emotional state (e.g., relief, joy, tension).

[0287] Step 4: AI response generation

[0288] server:

[0289] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[0290] 2. The determined response is sent to the terminal in real time.

[0291] Specific behavior:

[0292] The server runs the AI's action decision algorithm and generates the next action or statement based on the player's behavior and emotional state. For example, the AI ​​player might say, "Your facial expression suggests you have a strong hand."

[0293] The generated response is sent to the terminal for the next process.

[0294] Step 5: Player Feedback

[0295] Device:

[0296] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0297] 2. Provide an interface to prompt the player for their next action.

[0298] Specific behavior:

[0299] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[0300] Displays buttons or options that allow the player to select their next action, such as "draw next card" or "set bet amount."

[0301] Step 6: Iterate on game progression

[0302] User:

[0303] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[0304] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[0305] Specific behavior:

[0306] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[0307] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[0308] By implementing this invention, players can experience a realistic and deep psychological battle, which is different from the monotonous CPU battles of the past. This is particularly useful in strategy games such as Werewolf and Poker, and has the effect of keeping players interested for a long period of time.

[0309] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0310] Example 2

[0311] 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."

[0312] In conventional game systems, it was difficult to analyze the player's behavior and emotions in real time and generate appropriate AI responses based on that. As a result, players were forced to play against monotonous and predictable AI, which lacked realism and excitement. Furthermore, it was not possible to provide interactive responses that properly reflected the player's emotional state, which prevented players from increasing satisfaction.

[0313] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recording the player's actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data to infer the player's emotional state, means for recognizing and tracking the player's emotions using an emotion engine, means for generating an AI response based on the inferred emotional state, and means for presenting the generated AI response to the player. This enables realistic and exciting battles based on the players' emotions and actions.

[0314] A "means for recording player actions" is a device or function that records all of a player's actions and decisions during a game in real time as a log.

[0315] "Means for collecting the player's facial expressions and voice data" refers to devices or functions that use input devices such as cameras and microphones to obtain the player's facial expressions and voices.

[0316] "Means for analyzing collected data to infer the player's emotional state" refers to devices or software that use acquired behavioral logs, facial expression data, and voice data to analyze them and infer the player's psychological state.

[0317] "Means for recognizing and tracking player emotions using an emotion engine" refers to a device or function that uses a dedicated engine for emotion analysis to continuously recognize changes in a player's emotions in real time.

[0318] "Means for generating AI responses based on inferred emotional states" refers to devices or software that allow AI to determine the next appropriate action or statement based on analyzed emotional data and behavioral patterns.

[0319] "Means for presenting the generated AI's response to the player" refers to a device or function that displays or presents the response determined by the AI ​​to the player in the form of text, audio, video, etc.

[0320] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[0321] The basic configuration of this system is as follows:

[0322] Hardware:

[0323] Camera: Generic webcam (e.g. Logitech C920)

[0324] Microphone: General-purpose condenser microphone (e.g., Sony ECM-CS3)

[0325] Game server: General-purpose cloud service (e.g. AWS EC2)

[0326] software:

[0327] Game server management software: Uses Apache Kafka for data stream processing

[0328] Data analysis and emotion recognition software: TensorFlow and OpenCV

[0329] Action decision algorithm: Implemented in Python

[0330] Examples:

[0331] Below is a specific example in which this system is applied to a poker game.

[0332] 1. Server:

[0333] The server creates a poker game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a MySQL database.

[0334] When each player joins the game, the server assigns a personality to the AI. For example, the AI ​​player might be assigned the personality of "intuitive decision maker."

[0335] 2. Terminal:

[0336] As players play the game, the device logs all actions (e.g., card selection, exchanges, bets, statements) in real time.

[0337] At the same time, a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3) are used to collect the player's facial expressions and voice data, which are then sent to the server in real time.

[0338] 3. Data analysis by the server:

[0339] The server analyzes the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0340] The analysis uses TensorFlow and OpenCV, and an emotion engine is implemented to recognize and track the player's emotions.

[0341] 4. AI Response Generation:

[0342] The server determines the AI ​​player's next action and statement based on the analysis results and the emotion recognition results of the emotion engine. For example, if a player makes a high bet and smiles, the server will generate a statement such as, "Your facial expression suggests you have a strong hand."

[0343] The determined response is transmitted to the terminal in real time.

[0344] 5. User Feedback:

[0345] The device displays the AI's responses sent from the server to the player, including on-screen text and audio output.

[0346] The device then provides an interface to prompt the player for the next action, for example, by displaying a message such as "Please select your next action."

[0347] Example prompt sentence:

[0348] "Please explain how you can analyze the actions and facial expressions of players when they exchange cards, recognize their emotions with an emotion engine, and generate an appropriate AI response."

[0349] Compared to conventional monotonous and unpredictable matches against AI, this invention enables realistic and exciting matches based on the player's emotions and actions, which is expected to increase player satisfaction and enhance the realism and excitement of the game.

[0350] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0351] Step 1:

[0352] server:

[0353] The server creates a game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a database.

[0354] Input: Player's basic information (username, profile)

[0355] Data processing: The process of storing player information in a database

[0356] Output: A game room is created and the player information is saved in the database.

[0357] How it works: The server stores player data in a MySQL database, and when each player joins, it loads a personality profile, such as "intuitive decision maker," into the AI.

[0358] Step 2:

[0359] Device:

[0360] As players play the game, the device logs all actions (card selection, exchanges, bets, and statements) in real time.

[0361] Input: Player in-game actions (card selection, exchanges, bets, etc.)

[0362] Data processing: Processing that records data as a log in real time

[0363] Output: Player in-game actions are logged

[0364] Specific operation: The terminal records the player's action data in a log file and transmits the data to the server in real time.

[0365] Step 3:

[0366] Device:

[0367] Using a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3), the player's facial expressions and voice data are collected and sent to the server.

[0368] Input: Player facial expression and voice data

[0369] Data processing: The process of capturing and sending facial expression and voice data.

[0370] Output: The player's facial expression and voice data are sent to the server.

[0371] What it does: The device uses a camera and microphone to capture the player's real-time facial expressions and voice, and then transmits them to the server as a data stream.

[0372] Step 4:

[0373] server:

[0374] The server analyzes the collected action logs, facial expression data, and voice data. It extracts the player's behavioral patterns from the action logs and infers the player's emotional state by analyzing the facial expression data and voice data.

[0375] Input: Behavioral log, facial expression data, voice data

[0376] Data processing: Data analysis (extracting behavioral patterns, predicting emotional states)

[0377] Output: Player behavior patterns and emotional state

[0378] Specific operation: The server uses TensorFlow and OpenCV to analyze the behavior log and extract specific patterns (e.g., "smiling when placing a high bet"), and then uses an emotion engine to detect the player's emotions (e.g., relief, joy).

[0379] Step 5:

[0380] server:

[0381] Based on the analysis results and the emotion recognition results of the emotion engine, the AI ​​decides the next action or statement.

[0382] Input: Analysis results, emotion recognition results

[0383] Data processing: Action decision algorithms generate next actions and statements

[0384] Output: The next action or statement generated by the AI

[0385] Specific operation: The server executes an action decision algorithm implemented in Python, generates a statement such as "Your expression suggests you have a strong hand," and sends it to the device.

[0386] Step 6:

[0387] Device:

[0388] Presents the AI's responses sent from the server to the player, including on-screen text and audio output.

[0389] Input: AI-generated next action or statement

[0390] Data processing: Conversion to screen display and audio output formats

[0391] Output: Text and / or audio presented to the player

[0392] Specific operation: The device conveys the AI's statement "Your expression tells you that it's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0393] Through these steps, the system analyzes the player's actions and emotions in real time and generates appropriate AI responses based on that, providing a more exciting gaming experience.

[0394] (Application example 2)

[0395] 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."

[0396] Conventional advertising systems deliver uniform advertisements without considering the real-time psychological state of consumers, making it difficult to deploy advertisements effectively. There is also a need for a system that analyzes players' behavior and emotions in real time and provides appropriate feedback based on that analysis. The present invention aims to deliver advertisements effectively and improve the user experience by analyzing consumers' facial expressions and voice data and displaying advertisements that best fit their emotions in real time.

[0397] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for recording the player's actions, a means for collecting the player's facial expression and voice data, a means for analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state, and a system for presenting the generated AI response to the player, which includes a means for analyzing consumer emotional data and displaying optimal advertisements in real time. This makes it possible to analyze consumer emotions in real time and effectively deliver advertisements that are optimal for those emotions.

[0398] A "means for recording player actions" is a device or software that has the function of saving as data a series of operations or actions performed by a player during a game.

[0399] "Means for collecting player facial and voice data" refers to equipment or software that has the function of capturing and recording a player's facial expressions and tone of voice using devices such as a camera or microphone.

[0400] "Means of analyzing collected data to infer the player's psychological state" refers to algorithms or programs that determine the player's emotions and mental state through facial recognition and voice analysis.

[0401] "Means for generating AI responses based on inferred psychological states" refers to algorithms or programs that allow AI to determine appropriate responses or actions based on the analysis results.

[0402] A "system for presenting generated AI responses to a player" is a device or software for displaying AI-generated responses to a player in text, audio, or other form.

[0403] "A means for analyzing consumer emotional data and displaying optimal advertisements in real time" is a system that uses cameras and microphones to collect consumers' facial expressions and voices, analyzes that data to infer their emotions, and displays relevant advertisements based on the results.

[0404] "Means of setting an AI's personality and conducting psychological warfare based on that personality" refers to algorithms or programs that give an AI a specific character or personality attribute, and cause it to act and react in accordance with that personality.

[0405] "Means of analyzing consumers' facial expressions and voices and suggesting advertisements that best suit their psychological state at the time" refers to algorithms and programs that recognize consumers' emotions in real time and select and display advertisements that suit their state.

[0406] "Means of learning behavioral patterns and determining the next game strategy based on them" refers to a machine learning algorithm that analyzes a player's past behavioral data and allows the AI ​​to calculate the optimal next move.

[0407] "Means for obtaining the most suitable advertisement from an advertisement distribution server based on emotional data" refers to a program that sends a request to an advertisement server based on the consumer's emotional data, and as a result, obtains and displays the most suitable advertisement.

[0408] MODE FOR CARRYING OUT THE INVENTION

[0409] This invention is a system for analyzing user behavior and emotions in real time and using that data to display optimal advertisements. The system includes means for recording player behavior, means for collecting facial and voice data of the player, means for analyzing the collected data to infer the player's psychological state, means for generating an AI response based on the inferred psychological state, and means for presenting the generated AI response to the player. It also includes means for analyzing consumer emotional data to display optimal advertisements in real time.

[0410] Hardware and Software Configuration

[0411] Hardware:

[0412] 1. Smartphone: Equipped with a camera and microphone, it collects the user's facial expressions and voice.

[0413] 2. Smart glasses: Equipped with a front camera and microphone, they capture the user's face and voice.

[0414] 3. Server: Central processing unit for data analysis and ad selection.

[0415] software:

[0416] 1. OpenCV: A library for processing camera images and analyzing facial expressions.

[0417] 2. Tensorflow and Keras: Use deep learning models to analyze emotions from collected data.

[0418] 3. Requests: HTTP request library for communicating with ad servers.

[0419] System Operation

[0420] The server receives data sent from the user's smartphone or smart glasses, including the user's behavior log, facial expression, and voice data. The server first processes the collected image data using OpenCV to perform facial recognition and facial expression analysis. Then, it uses Tensorflow and Keras to infer the user's emotional state.

[0421] Based on the estimated emotional state, the server uses the Requests library to send a request to the ad server to retrieve the most suitable advertisement, which is then displayed in real time on the user's smartphone or smart glasses, providing the user with the most suitable advertisement information.

[0422] Specific examples

[0423] For example, imagine a user walking through a shopping mall. The smart glasses capture the user's facial expressions and send the data to a server. The server uses an emotion engine to infer a "happy" state and sends a request to an advertising server based on the emotion data. The advertising server returns information about sales related to the "happy state" and presents it to the user.

[0424] Examples of prompts:

[0425] When users are happy, they ask for ads to show them special offers and sales information.

[0426] In this way, optimal ads can be provided in real time according to the user's emotional state, resulting in more effective ad delivery and a richer user experience.

[0427] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0428] Step 1:

[0429] The user's smartphone or smart glasses use a camera and microphone to collect facial and voice data in real time. At this stage, the user's facial images and voice clips are the input data.

[0430] Step 2:

[0431] The device sends the collected facial expression and voice data to a server, which then transfers the collected data to the server via a network and treats it as data to be analyzed.

[0432] Step 3:

[0433] The server processes the received data using OpenCV for facial recognition and facial expression analysis. Specifically, a face detection algorithm extracts facial features from the image, and the facial expressions are applied to a deep learning model to infer emotional states. The input to this process is the user's facial image, and the output is an inferred emotion (e.g., happiness, surprise, etc.).

[0434] Step 4:

[0435] The server uses Tensorflow and Keras to analyze the audio data and infer emotions from the user's voice. At this stage, the audio clip is the input data, and the audio analysis model analyzes the tone and patterns of the voice to infer the emotional state. The output is the inferred emotion.

[0436] Step 5:

[0437] The server then combines the analyzed facial expression data and voice data to determine the overall emotional state. At this point, the input data are individually estimated emotional information, and the final overall emotional state is output.

[0438] Step 6:

[0439] The server uses the Requests library to send a request to the ad serving server to retrieve the most suitable ad based on the inferred emotional state, where the input is the overall emotional state and the output is the relevant ad data returned by the ad server.

[0440] Step 7:

[0441] The server transmits the acquired advertising data to the user's smartphone or smart glasses, where it is displayed on the device and presented to the user.

[0442] Step 8:

[0443] The device again collects the user's reactions to the displayed ads and sends them to the server as a behavior log. This input is new user behavior data, which is used as feedback to improve the accuracy of the entire system.

[0444] Specific examples

[0445] For example, in step 1, the smart glasses capture the user's smile, and then in step 2, transmit the video and audio to the server. In steps 3 to 5, the server analyzes this data and infers that the user is in a "happy" state. Then, in step 6, the server transmits the "happy" emotional state to the ad distribution server, which retrieves an advertisement containing information about special offers and sales. In step 7, this advertisement is displayed on the smart glasses, and finally, in step 8, the server collects the user's response again.

[0446] This series of processes allows advertisements that are optimized to suit the user's emotions to be delivered effectively.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] [Second embodiment]

[0451] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0452] 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.

[0453] 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).

[0454] 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.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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."

[0463] System Overview

[0464] This invention provides a game system that analyzes the player's behavior and psychological state and uses AI to show more human-like responses. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the AI ​​responds appropriately based on that information, providing the player with a realistic and exciting match.

[0465] Program processing

[0466] Step 1: Initial Setup

[0467] server:

[0468] 1. Create a game room and manage player information.

[0469] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0470] Example: The server creates a Werewolf game room, and when a player joins, the AI ​​player is given the personality of a "calm analyst."

[0471] Step 2: Collect player data

[0472] Device:

[0473] 1. All player actions (card selection, exchanges, bets, conversations, etc.) are recorded as a log in real time.

[0474] 2. Using a camera and microphone, the player's facial expression and voice data are collected and sent to the server.

[0475] Example: A terminal logs the actions of players exchanging cards during a poker game, and at the same time, a camera captures the players' expressions of laughter or surprise, and sends the video data to a server.

[0476] Step 3: Data analysis

[0477] server:

[0478] 1. Analyze the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's hand habits and behavioral patterns, while the facial expression data and voice data are used as basic data to infer the player's emotional state.

[0479] 2. Analyze using machine learning algorithms to predict the player's psychological state in real time.

[0480] Example: The server analyzes the behavior of a player playing poker and discovers a behavioral pattern of "smiling when making high bets." Based on this, the server infers that the player has a strong poker hand.

[0481] Step 4: AI response generation

[0482] server:

[0483] 1. Based on the analysis results, the AI ​​player's next actions and statements are determined. The AI's responses are customized based on the inferred psychological state and behavioral patterns.

[0484] 2. The determined response is sent to the terminal in real time.

[0485] Example: The server carefully chooses the next hand and has the AI ​​player say, "You look like you have a strong hand."

[0486] Step 5: Player feedback

[0487] Device:

[0488] 1. Displaying the AI's responses received from the server to the player, including audio output and on-screen text display.

[0489] 2. Provide an interface that prompts the player to take the next action.

[0490] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0491] Example

[0492] When this system is applied to the Werewolf game, the AI ​​analyzes players' comments and facial expressions to identify suspicious individuals. When applied to poker, the AI ​​infers a player's psychological state from their betting behavior and facial expressions, and adjusts their strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[0493] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0494] The processing flow will be explained below.

[0495] Step 1: Initial Setup

[0496] server:

[0497] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0498] 2. When a player joins the game, they set a personality for each AI player, which will be the basis for the AI's behavior patterns and reactions.

[0499] Specific behavior:

[0500] The server creates and initializes a new game room.

[0501] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "calm analyst" or "intuitive decision maker."

[0502] Step 2: Collect player data

[0503] Device:

[0504] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0505] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0506] Specific behavior:

[0507] The device instantly captures each of the player's actions and saves them as an event log.

[0508] The device's camera captures the player's facial expressions frame by frame, and the microphone records audio data in real time, which is then sent to a server.

[0509] Step 3: Data analysis

[0510] server:

[0511] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0512] 2. Using machine learning algorithms, we analyze data and predict players' psychological state in real time.

[0513] Specific behavior:

[0514] The behavioral analysis module analyzes the player's action history and learns specific behavioral patterns (for example, reactions when a specific card is dealt).

[0515] The emotion analysis module analyzes facial expression and voice data to estimate the player's emotional state (tension, anxiety, joy, etc.).

[0516] Step 4: AI response generation

[0517] server:

[0518] 1. Based on the analysis results, the AI ​​player's next action or statement is determined. The optimal reaction is generated based on the inferred psychological state and behavioral patterns.

[0519] 2. The determined response is sent to the terminal in real time.

[0520] Specific behavior:

[0521] The server runs the AI's action decision algorithm and generates the optimal next action or statement based on the player's behavior and psychological state.

[0522] The generated response is sent to the terminal for the next process.

[0523] Step 5: Player Feedback

[0524] Device:

[0525] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0526] 2. Provide an interface to prompt the player for their next action.

[0527] Specific behavior:

[0528] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[0529] Displays buttons and options that allow the player to choose their next action.

[0530] Step 6: Iterate on game progression

[0531] User:

[0532] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[0533] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[0534] Specific behavior:

[0535] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[0536] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[0537] Example 1

[0538] 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."

[0539] Conventional game systems lacked sufficient analysis of player behavior and psychological state, limiting real-time responses. As a result, players easily became bored with monotonous gameplay and were unable to obtain truly exciting experiences. In particular, the lack of AI responses that accurately reflected the player's emotions and behavior patterns led to a lack of tension and realism in competitive games.

[0540] 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.

[0541] In this invention, the server includes means for recording player actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data and using a machine learning algorithm to infer the player's psychological state, means for generating an AI response based on the inferred psychological state and behavioral pattern, and means for outputting voice and displaying on a screen to present the generated AI response to the player. This allows the player to receive AI responses based on their own actions and psychological state in real time, enabling a more exciting and realistic gaming experience.

[0542] A "means for recording player actions" is a device or method for saving a series of actions and choices made by a player in a game in log form.

[0543] "Means for collecting player's facial expression and voice data" refers to a device or method that uses a camera or microphone to collect a player's facial expression and voice in real time and record that data.

[0544] "Means of using machine learning algorithms to analyze collected data and infer a player's psychological state" refers to a device or method that uses machine learning technology to analyze and infer a player's emotions and psychological characteristics based on acquired behavioral, facial, and voice data.

[0545] "Means for generating AI responses based on inferred psychological states and behavioral patterns" refers to a device or method that allows an AI to design and generate appropriate responses and actions based on the analyzed psychological states and behavioral patterns of a player.

[0546] "Means for audio output and on-screen display to present the generated AI's response to the player" refers to a device or method that outputs audio via a speaker or headset and displays text and visuals on the screen to communicate the generated AI's response to the player.

[0547] "Means for setting an AI's personality and engaging in psychological warfare based on the set personality" refers to a device or method for initially setting a specific personality or characteristics in an AI and engaging in psychological warfare with the player within the game based on that.

[0548] "Means for learning behavioral patterns and determining the next game strategy" refers to a device or method that analyzes a player's past behavioral data and uses the results to plan and determine future strategies and actions in the game.

[0549] MODE FOR CARRYING OUT THE INVENTION

[0550] The system of the present invention analyzes the player's behavior and psychological state and uses AI to provide more human-like responses, thereby providing a realistic and exciting competitive game. The components of the system and their specific implementation methods are described in detail below.

[0551] System Components

[0552] 1. A way to record player actions

[0553] Terminal: All actions that players take in the game (e.g., card selection and exchange, bets, conversations, etc.) are logged in real time using a local database such as SQLite.

[0554] 2. A means of collecting facial and audio data from players

[0555] Device: Using a camera and microphone, the player's facial expression and voice data are collected in real time. Facial expression data is analyzed using the OpenCV library, and voice data is converted to text using the Google Cloud Speech-to-Text API.

[0556] 3. Using machine learning algorithms to analyze data and infer player psychology

[0557] Server: The collected behavioral logs, facial expression data, and audio data are preprocessed using Python's pandas library, and the facial expression data is analyzed using a TensorFlow model.Furthermore, psychological states are inferred in real time using scikit-learn's random forest and neural network.

[0558] 4. A means of generating AI responses based on inferred psychological states and behavioral patterns

[0559] Server: Based on the analysis results, the server designs the next actions and statements of the AI ​​player. It customizes responses based on preset rules, conditional statements, and probability models, and transmits them to the device in real time via the WebSocket protocol.

[0560] 5. A means of outputting audio and displaying the generated AI's responses to the player

[0561] Terminal: Displays the AI's responses received from the server to the player, using Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen, and provides an interface to wait for the next action.

[0562] Specific examples

[0563] Poker game example:

[0564] During a poker game, the device logs the player's actions when exchanging cards. At the same time, the camera captures the player's expressions of laughter or surprise, and sends the video data to the server in real time. The server analyzes this and discovers a behavioral pattern: "Smiling when placing a high bet." Based on this, the AI ​​says, "Judging from your expression, that's a strong hand," and presents it to the player in real time.

[0565] Prompt Sentence Examples

[0566] Example prompts for generative AI models:

[0567] "We provide a dataset containing player behavior patterns and psychological states. Please analyze this information and infer the psychological state of a player when they smile during high bets in poker. Then, based on that inference, suggest what action the AI ​​player should take next."

[0568] In this way, the present invention analyzes the player's behavior and psychological state in real time and provides AI responses based on that analysis, thereby achieving a more realistic gaming experience.

[0569] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0570] Step 1:

[0571] server:

[0572] The server creates a game room and manages player information. When each player joins the game, it sets the AI ​​personality. For example, when player A joins, the AI ​​personality "Calm Analyst" is set, and that information is saved in a MySQL database.

[0573] Input: Player participation information

[0574] Output: Game room setting information, AI personality setting information

[0575] Specific operation: Record player information and AI personality in a MySQL database.

[0576] Step 2:

[0577] Device:

[0578] The device records the player's actions (such as card selection and exchange, betting, and conversation) in real time as a log. It also collects facial expression data using a camera and voice data using a microphone, and sends the data to the server.

[0579] Input: Player behavior data, facial expression data, voice data

[0580] Output: Data sent to the server (behavior log, facial expression data, voice data)

[0581] Specific operations: Record behavior logs in SQLite, capture facial expressions using OpenCV, convert speech to text using the Google Cloud Speech-to-Text API, and send these to the server.

[0582] Step 3:

[0583] server:

[0584] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it preprocesses the data using Python's pandas library, analyzes the facial expression data using a TensorFlow model, and then uses scikit-learn's machine learning algorithm to infer psychological states.

[0585] Input: Behavioral log, facial expression data, voice data

[0586] Output: Predicted psychological state, behavioral patterns

[0587] Specific operations: Preprocessing behavioral logs with pandas, facial expression analysis with TensorFlow, and psychological state estimation with scikit-learn.

[0588] Step 4:

[0589] server:

[0590] The server generates AI responses based on the inferred psychological state and behavioral patterns by using preset rules, conditional statements, and probability models to determine the AI's next actions and statements, and transmits them to the device in real time using the WebSocket protocol.

[0591] Input: Predicted psychological state, behavioral patterns

[0592] Output: AI response (actions and statements)

[0593] Specific operation: A response is generated based on the results of the machine learning algorithm and sent to the device via WebSocket.

[0594] Step 5:

[0595] Device:

[0596] The device displays the AI's responses received from the server to the player. Specifically, it uses Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen. It also provides an interface to prompt the player to take the next action.

[0597] Input: AI response from the server

[0598] Output: The response (audio and text) presented to the player

[0599] Specific operations: Outputs voice, displays text, and displays a GUI prompting the next action.

[0600] (Application example 1)

[0601] 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."

[0602] On conventional online shopping sites, the user's shopping experience is not personalized, and real-time responses and product recommendations based on the player's behavior and emotional state are not provided, limiting the improvement of user satisfaction. The present invention aims to revolutionize the traditional shopping experience and dramatically improve user satisfaction by collecting user behavior, facial expressions, and voice data in real time and using artificial intelligence to provide appropriate responses and product recommendations based on that data.

[0603] 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.

[0604] In this invention, the server includes means for recording user behavior, means for collecting user facial expression and voice data, means for analyzing the collected data to infer the user's psychological state, means for generating an AI response based on the inferred psychological state, means for presenting the generated AI response to the user, means for recording the user's browsing, selection, and purchase behavior, and means for recommending products based on the user's preferences and past purchase data, thereby enabling personalized recommendations and information provision that responds to the user's behavior and psychological state in real time.

[0605] "User" refers to an individual or corporation that uses the System to shop.

[0606] "Action" refers to the operations, actions, and intentional acts that users perform on the system.

[0607] "Facial expression data" refers to video information that records the user's facial movements and expressions.

[0608] "Voice Data" means acoustic information that records a user's speech or other sounds.

[0609] "Artificial intelligence" refers to a computer program that uses machine learning algorithms and data analysis techniques to understand a user's behavior and psychological state and generate appropriate responses.

[0610] "Reaction" refers to the responses and actions that AI generates based on the user's behavior and psychological state.

[0611] "Product recommendation" refers to artificial intelligence suggesting specific products to purchase based on user preferences and past purchase data.

[0612] "Data analysis" refers to the process of processing collected user behavioral data, facial expression data, and voice data to infer the user's psychological state and preferences.

[0613] "User information" refers comprehensively to data about users, such as personal information, behavioral history, and purchase history.

[0614] "Personalization" refers to providing services that are customized to suit the individual characteristics and preferences of each user.

[0615] "Recommendation content" refers to information about products or services suggested to users.

[0616] "System" refers to the hardware and software that analyzes user behavior and psychological state and enables artificial intelligence to generate appropriate responses and recommendations.

[0617] The system of the present invention analyzes a user's behavior and psychological state and provides personalized product recommendations based on the results. This system is mainly composed of a server, a smartphone terminal, and a machine learning algorithm. Specific embodiments are described below.

[0618] System Overview

[0619] Initial Setup

[0620] The server initiates a user's shopping session and manages user information. At the start of each session, the AI ​​sets up a recommendation algorithm based on past purchase data and browsing history.

[0621] Data collection

[0622] The smartphone device records the user's browsing, selection, purchase, and other actions in real time, and also collects facial expression and voice data using the device's built-in camera and microphone, which are then sent to a server.

[0623] Data analysis

[0624] The server analyzes the collected behavioral logs, facial expression data, and voice data using machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time.

[0625] AI reaction generation

[0626] The server then uses the analysis results to determine the next recommended product or coupon. Based on the estimated psychological state and past purchase data, the AI ​​generates an appropriate response and sends the results to the smartphone device in real time.

[0627] User Feedback

[0628] The smartphone terminal displays the recommendation information received from the server to the user, including product images and discount information in text, and provides an interface that prompts the user to take the next action.

[0629] Hardware and software used

[0630] Hardware: Smartphone (camera, microphone, accelerometer), server (cloud service)

[0631] Software: Machine learning algorithms (TensorFlow, PyTorch), real-time databases (Firebase, MongoDB), natural language processing (NLP) models (BERT, GPT-3)

[0632] Specific examples of processing

[0633] For example, if a user smiles while browsing a particular product, the system can infer that the product is a favorite and recommend related products. If the user is confused, the system can provide a detailed description and review of the product. Here are some examples of prompts:

[0634] Examples of prompt statements

[0635] "If a user smiles while browsing products on their phone, show them relevant product recommendations. Additionally, if they're confused, provide them with a detailed product description."

[0636] "When a user says, 'Tell me about this product,' provide more information about the product in your voice. If the user looks confused, offer discounts on related products."

[0637] This allows the system of the present invention to respond to the user's behavior and state of mind in real time, providing a personalized shopping experience.

[0638] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0639] Step 1:

[0640] Initial Setup

[0641] The server initiates the user's shopping session and manages user information. Specifically, it retrieves the user's past purchase data and browsing history from a database and provides them as input to the AI ​​to set up an initial recommendation algorithm. As a result, an initial list of recommended products is generated for the user.

[0642] Step 2:

[0643] Behavioral data collection

[0644] The device records user actions such as browsing, selection, and purchase in real time. For example, when a user views a product page or adds a product to their cart, the event is recorded as a log. This behavioral data can be sent to a server for real-time analysis. The input is the user's operation event, and the output is the behavioral log data sent to the server.

[0645] Step 3:

[0646] Facial and vocal data collection

[0647] The device uses a camera and microphone to collect the user's facial expressions and audio data. For example, if a user smiles while browsing a product page, the video information is captured. Similarly, audio data is collected by the microphone, and what the user says is sent to the server. The input is video and audio data, and the output is the transmission of this data to the server.

[0648] Step 4:

[0649] Data analysis

[0650] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it uses machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time. For example, it determines that a user who smiles a lot is likely to like a particular product. This process receives the behavioral logs and facial expression / voice data as input, and obtains the inferred psychological state as output.

[0651] Step 5:

[0652] Generating product recommendations

[0653] The server then determines the next product or coupon to recommend based on the analysis results. Using a machine learning algorithm, it generates a list of recommended products based on the user's psychological state and past purchase data, and sends it to the device in real time. The input is the estimated psychological state and past purchase data, and the output is the created product recommendation list.

[0654] Step 6:

[0655] User feedback

[0656] The device displays the recommendation information received from the server to the user, including product images and text display of discount information. For example, if a user smiles while viewing a particular product, a discount coupon will be displayed along with recommendations for related products. The input is the recommendation information received from the server, and the output is visual and audio feedback to the user.

[0657] Step 7:

[0658] Next Action Promoting Interface

[0659] The device provides an interface that prompts the user for the next action, such as a button to add related products to the cart or a link to view more information. This allows the user to easily select the next step. The input is the interface element that the user interacts with, and the output is the interface display that prompts the user to do the next action.

[0660] 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.

[0661] System Overview

[0662] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[0663] Program processing

[0664] Step 1: Initial Setup

[0665] server:

[0666] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0667] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0668] Example: A server creates a poker room, and when a player joins, it assigns the AI ​​player a personality called "Intuitive Decision Maker."

[0669] Step 2: Collect player data

[0670] Device:

[0671] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0672] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0673] Example: The device logs the actions of players exchanging cards, and at the same time, the camera captures the players' expressions of laughter or surprise, and sends the video data to the server.

[0674] Step 3: Data analysis and application of the sentiment engine

[0675] server:

[0676] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0677] 2. Use the emotion engine to recognize and track player emotions based on this data.

[0678] Example: The server analyzes the behavior of players during poker and discovers a behavioral pattern of "smiling when betting high amounts." The emotion engine recognizes the player's emotions (relief, joy).

[0679] Step 4: AI response generation

[0680] server:

[0681] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[0682] 2. The determined response is sent to the terminal in real time.

[0683] Example: The server runs an AI action decision algorithm to generate the optimal next action or statement based on the player's behavior and emotional state. The AI ​​player says, "Your facial expression suggests you have a strong hand."

[0684] Step 5: Player feedback

[0685] Device:

[0686] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0687] 2. Provide an interface to prompt the player for their next action.

[0688] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0689] Example

[0690] When this system is applied to the Werewolf game, the AI ​​analyzes the player's comments and facial expressions, and the emotion engine recognizes the player's emotions and identifies suspicious individuals. When applied to poker, the AI ​​infers the player's psychological state from their betting behavior, facial expressions, and emotional analysis by the emotion engine, and adjusts strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[0691] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0692] The processing flow will be explained below.

[0693] Step 1: Initial Setup

[0694] server:

[0695] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0696] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0697] Specific behavior:

[0698] The server creates and initializes a new game room.

[0699] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "intuitive decision maker" or "calm analyst."

[0700] Step 2: Collect player and sentiment data

[0701] Device:

[0702] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0703] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0704] Specific behavior:

[0705] The terminal logs the actions of players as they exchange cards and bet.

[0706] The device's camera captures the player's facial expressions (smile, surprise, etc.) frame by frame, and the microphone records the player's voice data in real time. These data are then sent to the server.

[0707] Step 3: Data analysis and application of the sentiment engine

[0708] server:

[0709] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0710] 2. Use the emotion engine to recognize and track player emotions based on this data.

[0711] Specific behavior:

[0712] The behavioral analysis module analyzes the player's action history and learns certain behavioral patterns (e.g., "smiling when placing high bets").

[0713] The emotion analysis module analyzes facial and voice data to recognize and track the player's emotional state (e.g., relief, joy, tension).

[0714] Step 4: AI response generation

[0715] server:

[0716] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[0717] 2. The determined response is sent to the terminal in real time.

[0718] Specific behavior:

[0719] The server runs the AI's action decision algorithm and generates the next action or statement based on the player's behavior and emotional state. For example, the AI ​​player might say, "Your facial expression suggests you have a strong hand."

[0720] The generated response is sent to the terminal for the next process.

[0721] Step 5: Player Feedback

[0722] Device:

[0723] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0724] 2. Provide an interface to prompt the player for their next action.

[0725] Specific behavior:

[0726] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[0727] Displays buttons or options that allow the player to select their next action, such as "draw next card" or "set bet amount."

[0728] Step 6: Iterate on game progression

[0729] User:

[0730] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[0731] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[0732] Specific behavior:

[0733] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[0734] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[0735] By implementing this invention, players can experience a realistic and deep psychological battle, which is different from the monotonous CPU battles of the past. This is particularly useful in strategy games such as Werewolf and Poker, and has the effect of keeping players interested for a long period of time.

[0736] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0737] Example 2

[0738] 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."

[0739] In conventional game systems, it was difficult to analyze the player's behavior and emotions in real time and generate appropriate AI responses based on that. As a result, players were forced to play against monotonous and predictable AI, which lacked realism and excitement. Furthermore, it was not possible to provide interactive responses that properly reflected the player's emotional state, which prevented players from increasing satisfaction.

[0740] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recording the player's actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data to infer the player's emotional state, means for recognizing and tracking the player's emotions using an emotion engine, means for generating an AI response based on the inferred emotional state, and means for presenting the generated AI response to the player. This enables realistic and exciting battles based on the players' emotions and actions.

[0741] A "means for recording player actions" is a device or function that records all of a player's actions and decisions during a game in real time as a log.

[0742] "Means for collecting the player's facial expressions and voice data" refers to devices or functions that use input devices such as cameras and microphones to obtain the player's facial expressions and voices.

[0743] "Means for analyzing collected data to infer the player's emotional state" refers to devices or software that use acquired behavioral logs, facial expression data, and voice data to analyze them and infer the player's psychological state.

[0744] "Means for recognizing and tracking player emotions using an emotion engine" refers to a device or function that uses a dedicated engine for emotion analysis to continuously recognize changes in a player's emotions in real time.

[0745] "Means for generating AI responses based on inferred emotional states" refers to devices or software that allow AI to determine the next appropriate action or statement based on analyzed emotional data and behavioral patterns.

[0746] "Means for presenting the generated AI's response to the player" refers to a device or function that displays or presents the response determined by the AI ​​to the player in the form of text, audio, video, etc.

[0747] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[0748] The basic configuration of this system is as follows:

[0749] Hardware:

[0750] Camera: Generic webcam (e.g. Logitech C920)

[0751] Microphone: General-purpose condenser microphone (e.g., Sony ECM-CS3)

[0752] Game server: General-purpose cloud service (e.g. AWS EC2)

[0753] software:

[0754] Game server management software: Uses Apache Kafka for data stream processing

[0755] Data analysis and emotion recognition software: TensorFlow and OpenCV

[0756] Action decision algorithm: Implemented in Python

[0757] Examples:

[0758] Below is a specific example in which this system is applied to a poker game.

[0759] 1. Server:

[0760] The server creates a poker game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a MySQL database.

[0761] When each player joins the game, the server assigns a personality to the AI. For example, the AI ​​player might be assigned the personality of "intuitive decision maker."

[0762] 2. Terminal:

[0763] As players play the game, the device logs all actions (e.g., card selection, exchanges, bets, statements) in real time.

[0764] At the same time, a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3) are used to collect the player's facial expressions and voice data, which are then sent to the server in real time.

[0765] 3. Data analysis by the server:

[0766] The server analyzes the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0767] The analysis uses TensorFlow and OpenCV, and an emotion engine is implemented to recognize and track the player's emotions.

[0768] 4. AI Response Generation:

[0769] The server determines the AI ​​player's next action and statement based on the analysis results and the emotion recognition results of the emotion engine. For example, if a player makes a high bet and smiles, the server will generate a statement such as, "Your facial expression suggests you have a strong hand."

[0770] The determined response is transmitted to the terminal in real time.

[0771] 5. User Feedback:

[0772] The device displays the AI's responses sent from the server to the player, including on-screen text and audio output.

[0773] The device then provides an interface to prompt the player for the next action, for example, by displaying a message such as "Please select your next action."

[0774] Example prompt sentence:

[0775] "Please explain how you can analyze the actions and facial expressions of players when they exchange cards, recognize their emotions with an emotion engine, and generate an appropriate AI response."

[0776] Compared to conventional monotonous and unpredictable matches against AI, this invention enables realistic and exciting matches based on the player's emotions and actions, which is expected to increase player satisfaction and enhance the realism and excitement of the game.

[0777] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0778] Step 1:

[0779] server:

[0780] The server creates a game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a database.

[0781] Input: Player's basic information (username, profile)

[0782] Data processing: The process of storing player information in a database

[0783] Output: A game room is created and the player information is saved in the database.

[0784] How it works: The server stores player data in a MySQL database, and when each player joins, it loads a personality profile, such as "intuitive decision maker," into the AI.

[0785] Step 2:

[0786] Device:

[0787] As players play the game, the device logs all actions (card selection, exchanges, bets, and statements) in real time.

[0788] Input: Player in-game actions (card selection, exchanges, bets, etc.)

[0789] Data processing: Processing that records data as a log in real time

[0790] Output: Player in-game actions are logged

[0791] Specific operation: The terminal records the player's action data in a log file and transmits the data to the server in real time.

[0792] Step 3:

[0793] Device:

[0794] Using a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3), the player's facial expressions and voice data are collected and sent to the server.

[0795] Input: Player facial expression and voice data

[0796] Data processing: The process of capturing and sending facial expression and voice data.

[0797] Output: The player's facial expression and voice data are sent to the server.

[0798] What it does: The device uses a camera and microphone to capture the player's real-time facial expressions and voice, and then transmits them to the server as a data stream.

[0799] Step 4:

[0800] server:

[0801] The server analyzes the collected action logs, facial expression data, and voice data. It extracts the player's behavioral patterns from the action logs and infers the player's emotional state by analyzing the facial expression data and voice data.

[0802] Input: Behavioral log, facial expression data, voice data

[0803] Data processing: Data analysis (extracting behavioral patterns, predicting emotional states)

[0804] Output: Player behavior patterns and emotional state

[0805] Specific operation: The server uses TensorFlow and OpenCV to analyze the behavior log and extract specific patterns (e.g., "smiling when placing a high bet"), and then uses an emotion engine to detect the player's emotions (e.g., relief, joy).

[0806] Step 5:

[0807] server:

[0808] Based on the analysis results and the emotion recognition results of the emotion engine, the AI ​​decides the next action or statement.

[0809] Input: Analysis results, emotion recognition results

[0810] Data processing: Action decision algorithms generate next actions and statements

[0811] Output: The next action or statement generated by the AI

[0812] Specific operation: The server executes an action decision algorithm implemented in Python, generates a statement such as "Your expression suggests you have a strong hand," and sends it to the device.

[0813] Step 6:

[0814] Device:

[0815] Presents the AI's responses sent from the server to the player, including on-screen text and audio output.

[0816] Input: AI-generated next action or statement

[0817] Data processing: Conversion to screen display and audio output formats

[0818] Output: Text and / or audio presented to the player

[0819] Specific operation: The device conveys the AI's statement "Your expression tells you that it's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0820] Through these steps, the system analyzes the player's actions and emotions in real time and generates appropriate AI responses based on that, providing a more exciting gaming experience.

[0821] (Application example 2)

[0822] 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."

[0823] Conventional advertising systems deliver uniform advertisements without considering the real-time psychological state of consumers, making it difficult to deploy advertisements effectively. There is also a need for a system that analyzes players' behavior and emotions in real time and provides appropriate feedback based on that analysis. The present invention aims to deliver advertisements effectively and improve the user experience by analyzing consumers' facial expressions and voice data and displaying advertisements that best fit their emotions in real time.

[0824] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for recording the player's actions, a means for collecting the player's facial expression and voice data, a means for analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state, and a system for presenting the generated AI response to the player, which includes a means for analyzing consumer emotional data and displaying optimal advertisements in real time. This makes it possible to analyze consumer emotions in real time and effectively deliver advertisements that are optimal for those emotions.

[0825] A "means for recording player actions" is a device or software that has the function of saving as data a series of operations or actions performed by a player during a game.

[0826] "Means for collecting player facial and voice data" refers to equipment or software that has the function of capturing and recording a player's facial expressions and tone of voice using devices such as a camera or microphone.

[0827] "Means of analyzing collected data to infer the player's psychological state" refers to algorithms or programs that determine the player's emotions and mental state through facial recognition and voice analysis.

[0828] "Means for generating AI responses based on inferred psychological states" refers to algorithms or programs that allow AI to determine appropriate responses or actions based on the analysis results.

[0829] A "system for presenting generated AI responses to a player" is a device or software for displaying AI-generated responses to a player in text, audio, or other form.

[0830] "A means for analyzing consumer emotional data and displaying optimal advertisements in real time" is a system that uses cameras and microphones to collect consumers' facial expressions and voices, analyzes that data to infer their emotions, and displays relevant advertisements based on the results.

[0831] "Means of setting an AI's personality and conducting psychological warfare based on that personality" refers to algorithms or programs that give an AI a specific character or personality attribute, and cause it to act and react in accordance with that personality.

[0832] "Means of analyzing consumers' facial expressions and voices and suggesting advertisements that best suit their psychological state at the time" refers to algorithms and programs that recognize consumers' emotions in real time and select and display advertisements that suit their state.

[0833] "Means of learning behavioral patterns and determining the next game strategy based on them" refers to a machine learning algorithm that analyzes a player's past behavioral data and allows the AI ​​to calculate the optimal next move.

[0834] "Means for obtaining the most suitable advertisement from an advertisement distribution server based on emotional data" refers to a program that sends a request to an advertisement server based on the consumer's emotional data, and as a result, obtains and displays the most suitable advertisement.

[0835] MODE FOR CARRYING OUT THE INVENTION

[0836] This invention is a system for analyzing user behavior and emotions in real time and using that data to display optimal advertisements. The system includes means for recording player behavior, means for collecting facial and voice data of the player, means for analyzing the collected data to infer the player's psychological state, means for generating an AI response based on the inferred psychological state, and means for presenting the generated AI response to the player. It also includes means for analyzing consumer emotional data to display optimal advertisements in real time.

[0837] Hardware and Software Configuration

[0838] Hardware:

[0839] 1. Smartphone: Equipped with a camera and microphone, it collects the user's facial expressions and voice.

[0840] 2. Smart glasses: Equipped with a front camera and microphone, they capture the user's face and voice.

[0841] 3. Server: Central processing unit for data analysis and ad selection.

[0842] software:

[0843] 1. OpenCV: A library for processing camera images and analyzing facial expressions.

[0844] 2. Tensorflow and Keras: Use deep learning models to analyze emotions from collected data.

[0845] 3. Requests: HTTP request library for communicating with ad servers.

[0846] System Operation

[0847] The server receives data sent from the user's smartphone or smart glasses, including the user's behavior log, facial expression, and voice data. The server first processes the collected image data using OpenCV to perform facial recognition and facial expression analysis. Then, it uses Tensorflow and Keras to infer the user's emotional state.

[0848] Based on the estimated emotional state, the server uses the Requests library to send a request to the ad server to retrieve the most suitable advertisement, which is then displayed in real time on the user's smartphone or smart glasses, providing the user with the most suitable advertisement information.

[0849] Specific examples

[0850] For example, imagine a user walking through a shopping mall. The smart glasses capture the user's facial expressions and send the data to a server. The server uses an emotion engine to infer a "happy" state and sends a request to an advertising server based on the emotion data. The advertising server returns information about sales related to the "happy state" and presents it to the user.

[0851] Examples of prompts:

[0852] When users are happy, they ask for ads to show them special offers and sales information.

[0853] In this way, optimal ads can be provided in real time according to the user's emotional state, resulting in more effective ad delivery and a richer user experience.

[0854] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0855] Step 1:

[0856] The user's smartphone or smart glasses use a camera and microphone to collect facial and voice data in real time. At this stage, the user's facial images and voice clips are the input data.

[0857] Step 2:

[0858] The device sends the collected facial expression and voice data to a server, which then transfers the collected data to the server via a network and treats it as data to be analyzed.

[0859] Step 3:

[0860] The server processes the received data using OpenCV for facial recognition and facial expression analysis. Specifically, a face detection algorithm extracts facial features from the image, and the facial expressions are applied to a deep learning model to infer emotional states. The input to this process is the user's facial image, and the output is an inferred emotion (e.g., happiness, surprise, etc.).

[0861] Step 4:

[0862] The server uses Tensorflow and Keras to analyze the audio data and infer emotions from the user's voice. At this stage, the audio clip is the input data, and the audio analysis model analyzes the tone and patterns of the voice to infer the emotional state. The output is the inferred emotion.

[0863] Step 5:

[0864] The server then combines the analyzed facial expression data and voice data to determine the overall emotional state. At this point, the input data are individually estimated emotional information, and the final overall emotional state is output.

[0865] Step 6:

[0866] The server uses the Requests library to send a request to the ad serving server to retrieve the most suitable ad based on the inferred emotional state, where the input is the overall emotional state and the output is the relevant ad data returned by the ad server.

[0867] Step 7:

[0868] The server transmits the acquired advertising data to the user's smartphone or smart glasses, where it is displayed on the device and presented to the user.

[0869] Step 8:

[0870] The device again collects the user's reactions to the displayed ads and sends them to the server as a behavior log. This input is new user behavior data, which is used as feedback to improve the accuracy of the entire system.

[0871] Specific examples

[0872] For example, in step 1, the smart glasses capture the user's smile, and then in step 2, transmit the video and audio to the server. In steps 3 to 5, the server analyzes this data and infers that the user is in a "happy" state. Then, in step 6, the server transmits the "happy" emotional state to the ad distribution server, which retrieves an advertisement containing information about special offers and sales. In step 7, this advertisement is displayed on the smart glasses, and finally, in step 8, the server collects the user's response again.

[0873] This series of processes allows advertisements that are optimized to suit the user's emotions to be delivered effectively.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] [Third embodiment]

[0878] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0879] 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.

[0880] 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).

[0881] 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.

[0882] 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.

[0883] 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).

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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."

[0890] System Overview

[0891] This invention provides a game system that analyzes the player's behavior and psychological state and uses AI to show more human-like responses. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the AI ​​responds appropriately based on that information, providing the player with a realistic and exciting match.

[0892] Program processing

[0893] Step 1: Initial Setup

[0894] server:

[0895] 1. Create a game room and manage player information.

[0896] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[0897] Example: The server creates a Werewolf game room, and when a player joins, the AI ​​player is given the personality of a "calm analyst."

[0898] Step 2: Collect player data

[0899] Device:

[0900] 1. All player actions (card selection, exchanges, bets, conversations, etc.) are recorded as a log in real time.

[0901] 2. Using a camera and microphone, the player's facial expression and voice data are collected and sent to the server.

[0902] Example: A terminal logs the actions of players exchanging cards during a poker game, and at the same time, a camera captures the players' expressions of laughter or surprise, and sends the video data to a server.

[0903] Step 3: Data analysis

[0904] server:

[0905] 1. Analyze the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's hand habits and behavioral patterns, while the facial expression data and voice data are used as basic data to infer the player's emotional state.

[0906] 2. Analyze using machine learning algorithms to predict the player's psychological state in real time.

[0907] Example: The server analyzes the behavior of a player playing poker and discovers a behavioral pattern of "smiling when making high bets." Based on this, the server infers that the player has a strong poker hand.

[0908] Step 4: AI response generation

[0909] server:

[0910] 1. Based on the analysis results, the AI ​​player's next actions and statements are determined. The AI's responses are customized based on the inferred psychological state and behavioral patterns.

[0911] 2. The determined response is sent to the terminal in real time.

[0912] Example: The server carefully chooses the next hand and has the AI ​​player say, "You look like you have a strong hand."

[0913] Step 5: Player feedback

[0914] Device:

[0915] 1. Displaying the AI's responses received from the server to the player, including audio output and on-screen text display.

[0916] 2. Provide an interface that prompts the player to take the next action.

[0917] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[0918] Example

[0919] When this system is applied to the Werewolf game, the AI ​​analyzes players' comments and facial expressions to identify suspicious individuals. When applied to poker, the AI ​​infers a player's psychological state from their betting behavior and facial expressions, and adjusts their strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[0920] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[0921] The processing flow will be explained below.

[0922] Step 1: Initial Setup

[0923] server:

[0924] 1. Create a game room and manage player information (usernames, profiles, etc.).

[0925] 2. When a player joins the game, they set a personality for each AI player, which will be the basis for the AI's behavior patterns and reactions.

[0926] Specific behavior:

[0927] The server creates and initializes a new game room.

[0928] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "calm analyst" or "intuitive decision maker."

[0929] Step 2: Collect player data

[0930] Device:

[0931] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[0932] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[0933] Specific behavior:

[0934] The device instantly captures each of the player's actions and saves them as an event log.

[0935] The device's camera captures the player's facial expressions frame by frame, and the microphone records audio data in real time, which is then sent to a server.

[0936] Step 3: Data analysis

[0937] server:

[0938] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[0939] 2. Using machine learning algorithms, we analyze data and predict players' psychological state in real time.

[0940] Specific behavior:

[0941] The behavioral analysis module analyzes the player's action history and learns specific behavioral patterns (for example, reactions when a specific card is dealt).

[0942] The emotion analysis module analyzes facial expression and voice data to estimate the player's emotional state (tension, anxiety, joy, etc.).

[0943] Step 4: AI response generation

[0944] server:

[0945] 1. Based on the analysis results, the AI ​​player's next action or statement is determined. The optimal reaction is generated based on the inferred psychological state and behavioral patterns.

[0946] 2. The determined response is sent to the terminal in real time.

[0947] Specific behavior:

[0948] The server runs the AI's action decision algorithm and generates the optimal next action or statement based on the player's behavior and psychological state.

[0949] The generated response is sent to the terminal for the next process.

[0950] Step 5: Player Feedback

[0951] Device:

[0952] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[0953] 2. Provide an interface to prompt the player for their next action.

[0954] Specific behavior:

[0955] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[0956] Displays buttons and options that allow the player to choose their next action.

[0957] Step 6: Iterate on game progression

[0958] User:

[0959] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[0960] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[0961] Specific behavior:

[0962] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[0963] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[0964] Example 1

[0965] 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."

[0966] Conventional game systems lacked sufficient analysis of player behavior and psychological state, limiting real-time responses. As a result, players easily became bored with monotonous gameplay and were unable to obtain truly exciting experiences. In particular, the lack of AI responses that accurately reflected the player's emotions and behavior patterns led to a lack of tension and realism in competitive games.

[0967] 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.

[0968] In this invention, the server includes means for recording player actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data and using a machine learning algorithm to infer the player's psychological state, means for generating an AI response based on the inferred psychological state and behavioral pattern, and means for outputting voice and displaying on a screen to present the generated AI response to the player. This allows the player to receive AI responses based on their own actions and psychological state in real time, enabling a more exciting and realistic gaming experience.

[0969] A "means for recording player actions" is a device or method for saving a series of actions and choices made by a player in a game in log form.

[0970] "Means for collecting player's facial expression and voice data" refers to a device or method that uses a camera or microphone to collect a player's facial expression and voice in real time and record that data.

[0971] "Means of using machine learning algorithms to analyze collected data and infer a player's psychological state" refers to a device or method that uses machine learning technology to analyze and infer a player's emotions and psychological characteristics based on acquired behavioral, facial, and voice data.

[0972] "Means for generating AI responses based on inferred psychological states and behavioral patterns" refers to a device or method that allows an AI to design and generate appropriate responses and actions based on the analyzed psychological states and behavioral patterns of a player.

[0973] "Means for audio output and on-screen display to present the generated AI's response to the player" refers to a device or method that outputs audio via a speaker or headset and displays text and visuals on the screen to communicate the generated AI's response to the player.

[0974] "Means for setting an AI's personality and engaging in psychological warfare based on the set personality" refers to a device or method for initially setting a specific personality or characteristics in an AI and engaging in psychological warfare with the player within the game based on that.

[0975] "Means for learning behavioral patterns and determining the next game strategy" refers to a device or method that analyzes a player's past behavioral data and uses the results to plan and determine future strategies and actions in the game.

[0976] MODE FOR CARRYING OUT THE INVENTION

[0977] The system of the present invention analyzes the player's behavior and psychological state and uses AI to provide more human-like responses, thereby providing a realistic and exciting competitive game. The components of the system and their specific implementation methods are described in detail below.

[0978] System Components

[0979] 1. A way to record player actions

[0980] Terminal: All actions that players take in the game (e.g., card selection and exchange, bets, conversations, etc.) are logged in real time using a local database such as SQLite.

[0981] 2. A means of collecting facial and audio data from players

[0982] Device: Using a camera and microphone, the player's facial expression and voice data are collected in real time. Facial expression data is analyzed using the OpenCV library, and voice data is converted to text using the Google Cloud Speech-to-Text API.

[0983] 3. Using machine learning algorithms to analyze data and infer player psychology

[0984] Server: The collected behavioral logs, facial expression data, and audio data are preprocessed using Python's pandas library, and the facial expression data is analyzed using a TensorFlow model.Furthermore, psychological states are inferred in real time using scikit-learn's random forest and neural network.

[0985] 4. A means of generating AI responses based on inferred psychological states and behavioral patterns

[0986] Server: Based on the analysis results, the server designs the next actions and statements of the AI ​​player. It customizes responses based on preset rules, conditional statements, and probability models, and transmits them to the device in real time via the WebSocket protocol.

[0987] 5. A means of outputting audio and displaying the generated AI's responses to the player

[0988] Terminal: Displays the AI's responses received from the server to the player, using Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen, and provides an interface to wait for the next action.

[0989] Specific examples

[0990] Poker game example:

[0991] During a poker game, the device logs the player's actions when exchanging cards. At the same time, the camera captures the player's expressions of laughter or surprise, and sends the video data to the server in real time. The server analyzes this and discovers a behavioral pattern: "Smiling when placing a high bet." Based on this, the AI ​​says, "Judging from your expression, that's a strong hand," and presents it to the player in real time.

[0992] Prompt Sentence Examples

[0993] Example prompts for generative AI models:

[0994] "We provide a dataset containing player behavior patterns and psychological states. Please analyze this information and infer the psychological state of a player when they smile during high bets in poker. Then, based on that inference, suggest what action the AI ​​player should take next."

[0995] In this way, the present invention analyzes the player's behavior and psychological state in real time and provides AI responses based on that analysis, thereby achieving a more realistic gaming experience.

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

[0997] Step 1:

[0998] server:

[0999] The server creates a game room and manages player information. When each player joins the game, it sets the AI ​​personality. For example, when player A joins, the AI ​​personality "Calm Analyst" is set, and that information is saved in a MySQL database.

[1000] Input: Player participation information

[1001] Output: Game room setting information, AI personality setting information

[1002] Specific operation: Record player information and AI personality in a MySQL database.

[1003] Step 2:

[1004] Device:

[1005] The device records the player's actions (such as card selection and exchange, betting, and conversation) in real time as a log. It also collects facial expression data using a camera and voice data using a microphone, and sends the data to the server.

[1006] Input: Player behavior data, facial expression data, voice data

[1007] Output: Data sent to the server (behavior log, facial expression data, voice data)

[1008] Specific operations: Record behavior logs in SQLite, capture facial expressions using OpenCV, convert speech to text using the Google Cloud Speech-to-Text API, and send these to the server.

[1009] Step 3:

[1010] server:

[1011] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it preprocesses the data using Python's pandas library, analyzes the facial expression data using a TensorFlow model, and then uses scikit-learn's machine learning algorithm to infer psychological states.

[1012] Input: Behavioral log, facial expression data, voice data

[1013] Output: Predicted psychological state, behavioral patterns

[1014] Specific operations: Preprocessing behavioral logs with pandas, facial expression analysis with TensorFlow, and psychological state estimation with scikit-learn.

[1015] Step 4:

[1016] server:

[1017] The server generates AI responses based on the inferred psychological state and behavioral patterns by using preset rules, conditional statements, and probability models to determine the AI's next actions and statements, and transmits them to the device in real time using the WebSocket protocol.

[1018] Input: Predicted psychological state, behavioral patterns

[1019] Output: AI response (actions and statements)

[1020] Specific operation: A response is generated based on the results of the machine learning algorithm and sent to the device via WebSocket.

[1021] Step 5:

[1022] Device:

[1023] The device displays the AI's responses received from the server to the player. Specifically, it uses Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen. It also provides an interface to prompt the player to take the next action.

[1024] Input: AI response from the server

[1025] Output: The response (audio and text) presented to the player

[1026] Specific operations: Outputs voice, displays text, and displays a GUI prompting the next action.

[1027] (Application example 1)

[1028] 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."

[1029] On conventional online shopping sites, the user's shopping experience is not personalized, and real-time responses and product recommendations based on the player's behavior and emotional state are not provided, limiting the improvement of user satisfaction. The present invention aims to revolutionize the traditional shopping experience and dramatically improve user satisfaction by collecting user behavior, facial expressions, and voice data in real time and using artificial intelligence to provide appropriate responses and product recommendations based on that data.

[1030] 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.

[1031] In this invention, the server includes means for recording user behavior, means for collecting user facial expression and voice data, means for analyzing the collected data to infer the user's psychological state, means for generating an AI response based on the inferred psychological state, means for presenting the generated AI response to the user, means for recording the user's browsing, selection, and purchase behavior, and means for recommending products based on the user's preferences and past purchase data, thereby enabling personalized recommendations and information provision that responds to the user's behavior and psychological state in real time.

[1032] "User" refers to an individual or corporation that uses the System to shop.

[1033] "Action" refers to the operations, actions, and intentional acts that users perform on the system.

[1034] "Facial expression data" refers to video information that records the user's facial movements and expressions.

[1035] "Voice Data" means acoustic information that records a user's speech or other sounds.

[1036] "Artificial intelligence" refers to a computer program that uses machine learning algorithms and data analysis techniques to understand a user's behavior and psychological state and generate appropriate responses.

[1037] "Reaction" refers to the responses and actions that AI generates based on the user's behavior and psychological state.

[1038] "Product recommendation" refers to artificial intelligence suggesting specific products to purchase based on user preferences and past purchase data.

[1039] "Data analysis" refers to the process of processing collected user behavioral data, facial expression data, and voice data to infer the user's psychological state and preferences.

[1040] "User information" refers comprehensively to data about users, such as personal information, behavioral history, and purchase history.

[1041] "Personalization" refers to providing services that are customized to suit the individual characteristics and preferences of each user.

[1042] "Recommendation content" refers to information about products or services suggested to users.

[1043] "System" refers to the hardware and software that analyzes user behavior and psychological state and enables artificial intelligence to generate appropriate responses and recommendations.

[1044] The system of the present invention analyzes a user's behavior and psychological state and provides personalized product recommendations based on the results. This system is mainly composed of a server, a smartphone terminal, and a machine learning algorithm. Specific embodiments are described below.

[1045] System Overview

[1046] Initial Setup

[1047] The server initiates a user's shopping session and manages user information. At the start of each session, the AI ​​sets up a recommendation algorithm based on past purchase data and browsing history.

[1048] Data collection

[1049] The smartphone device records the user's browsing, selection, purchase, and other actions in real time, and also collects facial expression and voice data using the device's built-in camera and microphone, which are then sent to a server.

[1050] Data analysis

[1051] The server analyzes the collected behavioral logs, facial expression data, and voice data using machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time.

[1052] AI reaction generation

[1053] The server then uses the analysis results to determine the next recommended product or coupon. Based on the estimated psychological state and past purchase data, the AI ​​generates an appropriate response and sends the results to the smartphone device in real time.

[1054] User Feedback

[1055] The smartphone terminal displays the recommendation information received from the server to the user, including product images and discount information in text, and provides an interface that prompts the user to take the next action.

[1056] Hardware and software used

[1057] Hardware: Smartphone (camera, microphone, accelerometer), server (cloud service)

[1058] Software: Machine learning algorithms (TensorFlow, PyTorch), real-time databases (Firebase, MongoDB), natural language processing (NLP) models (BERT, GPT-3)

[1059] Specific examples of processing

[1060] For example, if a user smiles while browsing a particular product, the system can infer that the product is a favorite and recommend related products. If the user is confused, the system can provide a detailed description and review of the product. Here are some examples of prompts:

[1061] Examples of prompt statements

[1062] "If a user smiles while browsing products on their phone, show them relevant product recommendations. Additionally, if they're confused, provide them with a detailed product description."

[1063] "When a user says, 'Tell me about this product,' provide more information about the product in your voice. If the user looks confused, offer discounts on related products."

[1064] This allows the system of the present invention to respond to the user's behavior and state of mind in real time, providing a personalized shopping experience.

[1065] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1066] Step 1:

[1067] Initial Setup

[1068] The server initiates the user's shopping session and manages user information. Specifically, it retrieves the user's past purchase data and browsing history from a database and provides them as input to the AI ​​to set up an initial recommendation algorithm. As a result, an initial list of recommended products is generated for the user.

[1069] Step 2:

[1070] Behavioral data collection

[1071] The device records user actions such as browsing, selection, and purchase in real time. For example, when a user views a product page or adds a product to their cart, the event is recorded as a log. This behavioral data can be sent to a server for real-time analysis. The input is the user's operation event, and the output is the behavioral log data sent to the server.

[1072] Step 3:

[1073] Facial and vocal data collection

[1074] The device uses a camera and microphone to collect the user's facial expressions and audio data. For example, if a user smiles while browsing a product page, the video information is captured. Similarly, audio data is collected by the microphone, and what the user says is sent to the server. The input is video and audio data, and the output is the transmission of this data to the server.

[1075] Step 4:

[1076] Data analysis

[1077] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it uses machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time. For example, it determines that a user who smiles a lot is likely to like a particular product. This process receives the behavioral logs and facial expression / voice data as input, and obtains the inferred psychological state as output.

[1078] Step 5:

[1079] Generating product recommendations

[1080] The server then determines the next product or coupon to recommend based on the analysis results. Using a machine learning algorithm, it generates a list of recommended products based on the user's psychological state and past purchase data, and sends it to the device in real time. The input is the estimated psychological state and past purchase data, and the output is the created product recommendation list.

[1081] Step 6:

[1082] User feedback

[1083] The device displays the recommendation information received from the server to the user, including product images and text display of discount information. For example, if a user smiles while viewing a particular product, a discount coupon will be displayed along with recommendations for related products. The input is the recommendation information received from the server, and the output is visual and audio feedback to the user.

[1084] Step 7:

[1085] Next Action Promoting Interface

[1086] The device provides an interface that prompts the user for the next action, such as a button to add related products to the cart or a link to view more information. This allows the user to easily select the next step. The input is the interface element that the user interacts with, and the output is the interface display that prompts the user to do the next action.

[1087] 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.

[1088] System Overview

[1089] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[1090] Program processing

[1091] Step 1: Initial Setup

[1092] server:

[1093] 1. Create a game room and manage player information (usernames, profiles, etc.).

[1094] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[1095] Example: A server creates a poker room, and when a player joins, it assigns the AI ​​player a personality called "Intuitive Decision Maker."

[1096] Step 2: Collect player data

[1097] Device:

[1098] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[1099] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[1100] Example: The device logs the actions of players exchanging cards, and at the same time, the camera captures the players' expressions of laughter or surprise, and sends the video data to the server.

[1101] Step 3: Data analysis and application of the sentiment engine

[1102] server:

[1103] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1104] 2. Use the emotion engine to recognize and track player emotions based on this data.

[1105] Example: The server analyzes the behavior of players during poker and discovers a behavioral pattern of "smiling when betting high amounts." The emotion engine recognizes the player's emotions (relief, joy).

[1106] Step 4: AI response generation

[1107] server:

[1108] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[1109] 2. The determined response is sent to the terminal in real time.

[1110] Example: The server runs an AI action decision algorithm to generate the optimal next action or statement based on the player's behavior and emotional state. The AI ​​player says, "Your facial expression suggests you have a strong hand."

[1111] Step 5: Player feedback

[1112] Device:

[1113] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[1114] 2. Provide an interface to prompt the player for their next action.

[1115] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[1116] Example

[1117] When this system is applied to the Werewolf game, the AI ​​analyzes the player's comments and facial expressions, and the emotion engine recognizes the player's emotions and identifies suspicious individuals. When applied to poker, the AI ​​infers the player's psychological state from their betting behavior, facial expressions, and emotional analysis by the emotion engine, and adjusts strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[1118] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[1119] The processing flow will be explained below.

[1120] Step 1: Initial Setup

[1121] server:

[1122] 1. Create a game room and manage player information (usernames, profiles, etc.).

[1123] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[1124] Specific behavior:

[1125] The server creates and initializes a new game room.

[1126] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "intuitive decision maker" or "calm analyst."

[1127] Step 2: Collect player and sentiment data

[1128] Device:

[1129] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[1130] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[1131] Specific behavior:

[1132] The terminal logs the actions of players as they exchange cards and bet.

[1133] The device's camera captures the player's facial expressions (smile, surprise, etc.) frame by frame, and the microphone records the player's voice data in real time. These data are then sent to the server.

[1134] Step 3: Data analysis and application of the sentiment engine

[1135] server:

[1136] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1137] 2. Use the emotion engine to recognize and track player emotions based on this data.

[1138] Specific behavior:

[1139] The behavioral analysis module analyzes the player's action history and learns certain behavioral patterns (e.g., "smiling when placing high bets").

[1140] The emotion analysis module analyzes facial and voice data to recognize and track the player's emotional state (e.g., relief, joy, tension).

[1141] Step 4: AI response generation

[1142] server:

[1143] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[1144] 2. The determined response is sent to the terminal in real time.

[1145] Specific behavior:

[1146] The server runs the AI's action decision algorithm and generates the next action or statement based on the player's behavior and emotional state. For example, the AI ​​player might say, "Your facial expression suggests you have a strong hand."

[1147] The generated response is sent to the terminal for the next process.

[1148] Step 5: Player Feedback

[1149] Device:

[1150] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[1151] 2. Provide an interface to prompt the player for their next action.

[1152] Specific behavior:

[1153] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[1154] Displays buttons or options that allow the player to select their next action, such as "draw next card" or "set bet amount."

[1155] Step 6: Iterate on game progression

[1156] User:

[1157] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[1158] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[1159] Specific behavior:

[1160] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[1161] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[1162] By implementing this invention, players can experience a realistic and deep psychological battle, which is different from the monotonous CPU battles of the past. This is particularly useful in strategy games such as Werewolf and Poker, and has the effect of keeping players interested for a long period of time.

[1163] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[1164] Example 2

[1165] 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."

[1166] In conventional game systems, it was difficult to analyze the player's behavior and emotions in real time and generate appropriate AI responses based on that. As a result, players were forced to play against monotonous and predictable AI, which lacked realism and excitement. Furthermore, it was not possible to provide interactive responses that properly reflected the player's emotional state, which prevented players from increasing satisfaction.

[1167] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recording the player's actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data to infer the player's emotional state, means for recognizing and tracking the player's emotions using an emotion engine, means for generating an AI response based on the inferred emotional state, and means for presenting the generated AI response to the player. This enables realistic and exciting battles based on the players' emotions and actions.

[1168] A "means for recording player actions" is a device or function that records all of a player's actions and decisions during a game in real time as a log.

[1169] "Means for collecting the player's facial expressions and voice data" refers to devices or functions that use input devices such as cameras and microphones to obtain the player's facial expressions and voices.

[1170] "Means for analyzing collected data to infer the player's emotional state" refers to devices or software that use acquired behavioral logs, facial expression data, and voice data to analyze them and infer the player's psychological state.

[1171] "Means for recognizing and tracking player emotions using an emotion engine" refers to a device or function that uses a dedicated engine for emotion analysis to continuously recognize changes in a player's emotions in real time.

[1172] "Means for generating AI responses based on inferred emotional states" refers to devices or software that allow AI to determine the next appropriate action or statement based on analyzed emotional data and behavioral patterns.

[1173] "Means for presenting the generated AI's response to the player" refers to a device or function that displays or presents the response determined by the AI ​​to the player in the form of text, audio, video, etc.

[1174] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[1175] The basic configuration of this system is as follows:

[1176] Hardware:

[1177] Camera: Generic webcam (e.g. Logitech C920)

[1178] Microphone: General-purpose condenser microphone (e.g., Sony ECM-CS3)

[1179] Game server: General-purpose cloud service (e.g. AWS EC2)

[1180] software:

[1181] Game server management software: Uses Apache Kafka for data stream processing

[1182] Data analysis and emotion recognition software: TensorFlow and OpenCV

[1183] Action decision algorithm: Implemented in Python

[1184] Examples:

[1185] Below is a specific example in which this system is applied to a poker game.

[1186] 1. Server:

[1187] The server creates a poker game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a MySQL database.

[1188] When each player joins the game, the server assigns a personality to the AI. For example, the AI ​​player might be assigned the personality of "intuitive decision maker."

[1189] 2. Terminal:

[1190] As players play the game, the device logs all actions (e.g., card selection, exchanges, bets, statements) in real time.

[1191] At the same time, a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3) are used to collect the player's facial expressions and voice data, which are then sent to the server in real time.

[1192] 3. Data analysis by the server:

[1193] The server analyzes the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1194] The analysis uses TensorFlow and OpenCV, and an emotion engine is implemented to recognize and track the player's emotions.

[1195] 4. AI Response Generation:

[1196] The server determines the AI ​​player's next action and statement based on the analysis results and the emotion recognition results of the emotion engine. For example, if a player makes a high bet and smiles, the server will generate a statement such as, "Your facial expression suggests you have a strong hand."

[1197] The determined response is transmitted to the terminal in real time.

[1198] 5. User Feedback:

[1199] The device displays the AI's responses sent from the server to the player, including on-screen text and audio output.

[1200] The device then provides an interface to prompt the player for the next action, for example, by displaying a message such as "Please select your next action."

[1201] Example prompt sentence:

[1202] "Please explain how you can analyze the actions and facial expressions of players when they exchange cards, recognize their emotions with an emotion engine, and generate an appropriate AI response."

[1203] Compared to conventional monotonous and unpredictable matches against AI, this invention enables realistic and exciting matches based on the player's emotions and actions, which is expected to increase player satisfaction and enhance the realism and excitement of the game.

[1204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1205] Step 1:

[1206] server:

[1207] The server creates a game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a database.

[1208] Input: Player's basic information (username, profile)

[1209] Data processing: The process of storing player information in a database

[1210] Output: A game room is created and the player information is saved in the database.

[1211] How it works: The server stores player data in a MySQL database, and when each player joins, it loads a personality profile, such as "intuitive decision maker," into the AI.

[1212] Step 2:

[1213] Device:

[1214] As players play the game, the device logs all actions (card selection, exchanges, bets, and statements) in real time.

[1215] Input: Player in-game actions (card selection, exchanges, bets, etc.)

[1216] Data processing: Processing that records data as a log in real time

[1217] Output: Player in-game actions are logged

[1218] Specific operation: The terminal records the player's action data in a log file and transmits the data to the server in real time.

[1219] Step 3:

[1220] Device:

[1221] Using a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3), the player's facial expressions and voice data are collected and sent to the server.

[1222] Input: Player facial expression and voice data

[1223] Data processing: The process of capturing and sending facial expression and voice data.

[1224] Output: The player's facial expression and voice data are sent to the server.

[1225] What it does: The device uses a camera and microphone to capture the player's real-time facial expressions and voice, and then transmits them to the server as a data stream.

[1226] Step 4:

[1227] server:

[1228] The server analyzes the collected action logs, facial expression data, and voice data. It extracts the player's behavioral patterns from the action logs and infers the player's emotional state by analyzing the facial expression data and voice data.

[1229] Input: Behavioral log, facial expression data, voice data

[1230] Data processing: Data analysis (extracting behavioral patterns, predicting emotional states)

[1231] Output: Player behavior patterns and emotional state

[1232] Specific operation: The server uses TensorFlow and OpenCV to analyze the behavior log and extract specific patterns (e.g., "smiling when placing a high bet"), and then uses an emotion engine to detect the player's emotions (e.g., relief, joy).

[1233] Step 5:

[1234] server:

[1235] Based on the analysis results and the emotion recognition results of the emotion engine, the AI ​​decides the next action or statement.

[1236] Input: Analysis results, emotion recognition results

[1237] Data processing: Action decision algorithms generate next actions and statements

[1238] Output: The next action or statement generated by the AI

[1239] Specific operation: The server executes an action decision algorithm implemented in Python, generates a statement such as "Your expression suggests you have a strong hand," and sends it to the device.

[1240] Step 6:

[1241] Device:

[1242] Presents the AI's responses sent from the server to the player, including on-screen text and audio output.

[1243] Input: AI-generated next action or statement

[1244] Data processing: Conversion to screen display and audio output formats

[1245] Output: Text and / or audio presented to the player

[1246] Specific operation: The device conveys the AI's statement "Your expression tells you that it's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[1247] Through these steps, the system analyzes the player's actions and emotions in real time and generates appropriate AI responses based on that, providing a more exciting gaming experience.

[1248] (Application example 2)

[1249] 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."

[1250] Conventional advertising systems deliver uniform advertisements without considering the real-time psychological state of consumers, making it difficult to deploy advertisements effectively. There is also a need for a system that analyzes players' behavior and emotions in real time and provides appropriate feedback based on that analysis. The present invention aims to deliver advertisements effectively and improve the user experience by analyzing consumers' facial expressions and voice data and displaying advertisements that best fit their emotions in real time.

[1251] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for recording the player's actions, a means for collecting the player's facial expression and voice data, a means for analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state, and a system for presenting the generated AI response to the player, which includes a means for analyzing consumer emotional data and displaying optimal advertisements in real time. This makes it possible to analyze consumer emotions in real time and effectively deliver advertisements that are optimal for those emotions.

[1252] A "means for recording player actions" is a device or software that has the function of saving as data a series of operations or actions performed by a player during a game.

[1253] "Means for collecting player facial and voice data" refers to equipment or software that has the function of capturing and recording a player's facial expressions and tone of voice using devices such as a camera or microphone.

[1254] "Means of analyzing collected data to infer the player's psychological state" refers to algorithms or programs that determine the player's emotions and mental state through facial recognition and voice analysis.

[1255] "Means for generating AI responses based on inferred psychological states" refers to algorithms or programs that allow AI to determine appropriate responses or actions based on the analysis results.

[1256] A "system for presenting generated AI responses to a player" is a device or software for displaying AI-generated responses to a player in text, audio, or other form.

[1257] "A means for analyzing consumer emotional data and displaying optimal advertisements in real time" is a system that uses cameras and microphones to collect consumers' facial expressions and voices, analyzes that data to infer their emotions, and displays relevant advertisements based on the results.

[1258] "Means of setting an AI's personality and conducting psychological warfare based on that personality" refers to algorithms or programs that give an AI a specific character or personality attribute, and cause it to act and react in accordance with that personality.

[1259] "Means of analyzing consumers' facial expressions and voices and suggesting advertisements that best suit their psychological state at the time" refers to algorithms and programs that recognize consumers' emotions in real time and select and display advertisements that suit their state.

[1260] "Means of learning behavioral patterns and determining the next game strategy based on them" refers to a machine learning algorithm that analyzes a player's past behavioral data and allows the AI ​​to calculate the optimal next move.

[1261] "Means for obtaining the most suitable advertisement from an advertisement distribution server based on emotional data" refers to a program that sends a request to an advertisement server based on the consumer's emotional data, and as a result, obtains and displays the most suitable advertisement.

[1262] MODE FOR CARRYING OUT THE INVENTION

[1263] This invention is a system for analyzing user behavior and emotions in real time and using that data to display optimal advertisements. The system includes means for recording player behavior, means for collecting facial and voice data of the player, means for analyzing the collected data to infer the player's psychological state, means for generating an AI response based on the inferred psychological state, and means for presenting the generated AI response to the player. It also includes means for analyzing consumer emotional data to display optimal advertisements in real time.

[1264] Hardware and Software Configuration

[1265] Hardware:

[1266] 1. Smartphone: Equipped with a camera and microphone, it collects the user's facial expressions and voice.

[1267] 2. Smart glasses: Equipped with a front camera and microphone, they capture the user's face and voice.

[1268] 3. Server: Central processing unit for data analysis and ad selection.

[1269] software:

[1270] 1. OpenCV: A library for processing camera images and analyzing facial expressions.

[1271] 2. Tensorflow and Keras: Use deep learning models to analyze emotions from collected data.

[1272] 3. Requests: HTTP request library for communicating with ad servers.

[1273] System Operation

[1274] The server receives data sent from the user's smartphone or smart glasses, including the user's behavior log, facial expression, and voice data. The server first processes the collected image data using OpenCV to perform facial recognition and facial expression analysis. Then, it uses Tensorflow and Keras to infer the user's emotional state.

[1275] Based on the estimated emotional state, the server uses the Requests library to send a request to the ad server to retrieve the most suitable advertisement, which is then displayed in real time on the user's smartphone or smart glasses, providing the user with the most suitable advertisement information.

[1276] Specific examples

[1277] For example, imagine a user walking through a shopping mall. The smart glasses capture the user's facial expressions and send the data to a server. The server uses an emotion engine to infer a "happy" state and sends a request to an advertising server based on the emotion data. The advertising server returns information about sales related to the "happy state" and presents it to the user.

[1278] Examples of prompts:

[1279] When users are happy, they ask for ads to show them special offers and sales information.

[1280] In this way, optimal ads can be provided in real time according to the user's emotional state, resulting in more effective ad delivery and a richer user experience.

[1281] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1282] Step 1:

[1283] The user's smartphone or smart glasses use a camera and microphone to collect facial and voice data in real time. At this stage, the user's facial images and voice clips are the input data.

[1284] Step 2:

[1285] The device sends the collected facial expression and voice data to a server, which then transfers the collected data to the server via a network and treats it as data to be analyzed.

[1286] Step 3:

[1287] The server processes the received data using OpenCV for facial recognition and facial expression analysis. Specifically, a face detection algorithm extracts facial features from the image, and the facial expressions are applied to a deep learning model to infer emotional states. The input to this process is the user's facial image, and the output is an inferred emotion (e.g., happiness, surprise, etc.).

[1288] Step 4:

[1289] The server uses Tensorflow and Keras to analyze the audio data and infer emotions from the user's voice. At this stage, the audio clip is the input data, and the audio analysis model analyzes the tone and patterns of the voice to infer the emotional state. The output is the inferred emotion.

[1290] Step 5:

[1291] The server then combines the analyzed facial expression data and voice data to determine the overall emotional state. At this point, the input data are individually estimated emotional information, and the final overall emotional state is output.

[1292] Step 6:

[1293] The server uses the Requests library to send a request to the ad serving server to retrieve the most suitable ad based on the inferred emotional state, where the input is the overall emotional state and the output is the relevant ad data returned by the ad server.

[1294] Step 7:

[1295] The server transmits the acquired advertising data to the user's smartphone or smart glasses, where it is displayed on the device and presented to the user.

[1296] Step 8:

[1297] The device again collects the user's reactions to the displayed ads and sends them to the server as a behavior log. This input is new user behavior data, which is used as feedback to improve the accuracy of the entire system.

[1298] Specific examples

[1299] For example, in step 1, the smart glasses capture the user's smile, and then in step 2, transmit the video and audio to the server. In steps 3 to 5, the server analyzes this data and infers that the user is in a "happy" state. Then, in step 6, the server transmits the "happy" emotional state to the ad distribution server, which retrieves an advertisement containing information about special offers and sales. In step 7, this advertisement is displayed on the smart glasses, and finally, in step 8, the server collects the user's response again.

[1300] This series of processes allows advertisements that are optimized to suit the user's emotions to be delivered effectively.

[1301] 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.

[1302] 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.

[1303] 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.

[1304] [Fourth embodiment]

[1305] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1306] 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.

[1307] 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).

[1308] 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.

[1309] 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.

[1310] 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).

[1311] 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.

[1312] 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.

[1313] 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.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] 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."

[1318] System Overview

[1319] This invention provides a game system that analyzes the player's behavior and psychological state and uses AI to show more human-like responses. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the AI ​​responds appropriately based on that information, providing the player with a realistic and exciting match.

[1320] Program processing

[1321] Step 1: Initial Setup

[1322] server:

[1323] 1. Create a game room and manage player information.

[1324] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[1325] Example: The server creates a Werewolf game room, and when a player joins, the AI ​​player is given the personality of a "calm analyst."

[1326] Step 2: Collect player data

[1327] Device:

[1328] 1. All player actions (card selection, exchanges, bets, conversations, etc.) are recorded as a log in real time.

[1329] 2. Using a camera and microphone, the player's facial expression and voice data are collected and sent to the server.

[1330] Example: A terminal logs the actions of players exchanging cards during a poker game, and at the same time, a camera captures the players' expressions of laughter or surprise, and sends the video data to a server.

[1331] Step 3: Data analysis

[1332] server:

[1333] 1. Analyze the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's hand habits and behavioral patterns, while the facial expression data and voice data are used as basic data to infer the player's emotional state.

[1334] 2. Analyze using machine learning algorithms to predict the player's psychological state in real time.

[1335] Example: The server analyzes the behavior of a player playing poker and discovers a behavioral pattern of "smiling when making high bets." Based on this, the server infers that the player has a strong poker hand.

[1336] Step 4: AI response generation

[1337] server:

[1338] 1. Based on the analysis results, the AI ​​player's next actions and statements are determined. The AI's responses are customized based on the inferred psychological state and behavioral patterns.

[1339] 2. The determined response is sent to the terminal in real time.

[1340] Example: The server carefully chooses the next hand and has the AI ​​player say, "You look like you have a strong hand."

[1341] Step 5: Player feedback

[1342] Device:

[1343] 1. Displaying the AI's responses received from the server to the player, including audio output and on-screen text display.

[1344] 2. Provide an interface that prompts the player to take the next action.

[1345] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[1346] Example

[1347] When this system is applied to the Werewolf game, the AI ​​analyzes players' comments and facial expressions to identify suspicious individuals. When applied to poker, the AI ​​infers a player's psychological state from their betting behavior and facial expressions, and adjusts their strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[1348] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[1349] The processing flow will be explained below.

[1350] Step 1: Initial Setup

[1351] server:

[1352] 1. Create a game room and manage player information (usernames, profiles, etc.).

[1353] 2. When a player joins the game, they set a personality for each AI player, which will be the basis for the AI's behavior patterns and reactions.

[1354] Specific behavior:

[1355] The server creates and initializes a new game room.

[1356] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "calm analyst" or "intuitive decision maker."

[1357] Step 2: Collect player data

[1358] Device:

[1359] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[1360] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[1361] Specific behavior:

[1362] The device instantly captures each of the player's actions and saves them as an event log.

[1363] The device's camera captures the player's facial expressions frame by frame, and the microphone records audio data in real time, which is then sent to a server.

[1364] Step 3: Data analysis

[1365] server:

[1366] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1367] 2. Using machine learning algorithms, we analyze data and predict players' psychological state in real time.

[1368] Specific behavior:

[1369] The behavioral analysis module analyzes the player's action history and learns specific behavioral patterns (for example, reactions when a specific card is dealt).

[1370] The emotion analysis module analyzes facial expression and voice data to estimate the player's emotional state (tension, anxiety, joy, etc.).

[1371] Step 4: AI response generation

[1372] server:

[1373] 1. Based on the analysis results, the AI ​​player's next action or statement is determined. The optimal reaction is generated based on the inferred psychological state and behavioral patterns.

[1374] 2. The determined response is sent to the terminal in real time.

[1375] Specific behavior:

[1376] The server runs the AI's action decision algorithm and generates the optimal next action or statement based on the player's behavior and psychological state.

[1377] The generated response is sent to the terminal for the next process.

[1378] Step 5: Player Feedback

[1379] Device:

[1380] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[1381] 2. Provide an interface to prompt the player for their next action.

[1382] Specific behavior:

[1383] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[1384] Displays buttons and options that allow the player to choose their next action.

[1385] Step 6: Iterate on game progression

[1386] User:

[1387] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[1388] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[1389] Specific behavior:

[1390] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[1391] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[1392] Example 1

[1393] 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."

[1394] Conventional game systems lacked sufficient analysis of player behavior and psychological state, limiting real-time responses. As a result, players easily became bored with monotonous gameplay and were unable to obtain truly exciting experiences. In particular, the lack of AI responses that accurately reflected the player's emotions and behavior patterns led to a lack of tension and realism in competitive games.

[1395] 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.

[1396] In this invention, the server includes means for recording player actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data and using a machine learning algorithm to infer the player's psychological state, means for generating an AI response based on the inferred psychological state and behavioral pattern, and means for outputting voice and displaying on a screen to present the generated AI response to the player. This allows the player to receive AI responses based on their own actions and psychological state in real time, enabling a more exciting and realistic gaming experience.

[1397] A "means for recording player actions" is a device or method for saving a series of actions and choices made by a player in a game in log form.

[1398] "Means for collecting player's facial expression and voice data" refers to a device or method that uses a camera or microphone to collect a player's facial expression and voice in real time and record that data.

[1399] "Means of using machine learning algorithms to analyze collected data and infer a player's psychological state" refers to a device or method that uses machine learning technology to analyze and infer a player's emotions and psychological characteristics based on acquired behavioral, facial, and voice data.

[1400] "Means for generating AI responses based on inferred psychological states and behavioral patterns" refers to a device or method that allows an AI to design and generate appropriate responses and actions based on the analyzed psychological states and behavioral patterns of a player.

[1401] "Means for audio output and on-screen display to present the generated AI's response to the player" refers to a device or method that outputs audio via a speaker or headset and displays text and visuals on the screen to communicate the generated AI's response to the player.

[1402] "Means for setting an AI's personality and engaging in psychological warfare based on the set personality" refers to a device or method for initially setting a specific personality or characteristics in an AI and engaging in psychological warfare with the player within the game based on that.

[1403] "Means for learning behavioral patterns and determining the next game strategy" refers to a device or method that analyzes a player's past behavioral data and uses the results to plan and determine future strategies and actions in the game.

[1404] MODE FOR CARRYING OUT THE INVENTION

[1405] The system of the present invention analyzes the player's behavior and psychological state and uses AI to provide more human-like responses, thereby providing a realistic and exciting competitive game. The components of the system and their specific implementation methods are described in detail below.

[1406] System Components

[1407] 1. A way to record player actions

[1408] Terminal: All actions that players take in the game (e.g., card selection and exchange, bets, conversations, etc.) are logged in real time using a local database such as SQLite.

[1409] 2. A means of collecting facial and audio data from players

[1410] Device: Using a camera and microphone, the player's facial expression and voice data are collected in real time. Facial expression data is analyzed using the OpenCV library, and voice data is converted to text using the Google Cloud Speech-to-Text API.

[1411] 3. Using machine learning algorithms to analyze data and infer player psychology

[1412] Server: The collected behavioral logs, facial expression data, and audio data are preprocessed using Python's pandas library, and the facial expression data is analyzed using a TensorFlow model.Furthermore, psychological states are inferred in real time using scikit-learn's random forest and neural network.

[1413] 4. A means of generating AI responses based on inferred psychological states and behavioral patterns

[1414] Server: Based on the analysis results, the server designs the next actions and statements of the AI ​​player. It customizes responses based on preset rules, conditional statements, and probability models, and transmits them to the device in real time via the WebSocket protocol.

[1415] 5. A means of outputting audio and displaying the generated AI's responses to the player

[1416] Terminal: Displays the AI's responses received from the server to the player, using Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen, and provides an interface to wait for the next action.

[1417] Specific examples

[1418] Poker game example:

[1419] During a poker game, the device logs the player's actions when exchanging cards. At the same time, the camera captures the player's expressions of laughter or surprise, and sends the video data to the server in real time. The server analyzes this and discovers a behavioral pattern: "Smiling when placing a high bet." Based on this, the AI ​​says, "Judging from your expression, that's a strong hand," and presents it to the player in real time.

[1420] Prompt Sentence Examples

[1421] Example prompts for generative AI models:

[1422] "We provide a dataset containing player behavior patterns and psychological states. Please analyze this information and infer the psychological state of a player when they smile during high bets in poker. Then, based on that inference, suggest what action the AI ​​player should take next."

[1423] In this way, the present invention analyzes the player's behavior and psychological state in real time and provides AI responses based on that analysis, thereby achieving a more realistic gaming experience.

[1424] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1425] Step 1:

[1426] server:

[1427] The server creates a game room and manages player information. When each player joins the game, it sets the AI ​​personality. For example, when player A joins, the AI ​​personality "Calm Analyst" is set, and that information is saved in a MySQL database.

[1428] Input: Player participation information

[1429] Output: Game room setting information, AI personality setting information

[1430] Specific operation: Record player information and AI personality in a MySQL database.

[1431] Step 2:

[1432] Device:

[1433] The device records the player's actions (such as card selection and exchange, betting, and conversation) in real time as a log. It also collects facial expression data using a camera and voice data using a microphone, and sends the data to the server.

[1434] Input: Player behavior data, facial expression data, voice data

[1435] Output: Data sent to the server (behavior log, facial expression data, voice data)

[1436] Specific operations: Record behavior logs in SQLite, capture facial expressions using OpenCV, convert speech to text using the Google Cloud Speech-to-Text API, and send these to the server.

[1437] Step 3:

[1438] server:

[1439] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it preprocesses the data using Python's pandas library, analyzes the facial expression data using a TensorFlow model, and then uses scikit-learn's machine learning algorithm to infer psychological states.

[1440] Input: Behavioral log, facial expression data, voice data

[1441] Output: Predicted psychological state, behavioral patterns

[1442] Specific operations: Preprocessing behavioral logs with pandas, facial expression analysis with TensorFlow, and psychological state estimation with scikit-learn.

[1443] Step 4:

[1444] server:

[1445] The server generates AI responses based on the inferred psychological state and behavioral patterns by using preset rules, conditional statements, and probability models to determine the AI's next actions and statements, and transmits them to the device in real time using the WebSocket protocol.

[1446] Input: Predicted psychological state, behavioral patterns

[1447] Output: AI response (actions and statements)

[1448] Specific operation: A response is generated based on the results of the machine learning algorithm and sent to the device via WebSocket.

[1449] Step 5:

[1450] Device:

[1451] The device displays the AI's responses received from the server to the player. Specifically, it uses Amazon Polly to output voice and HTML5 and JavaScript to display text on the screen. It also provides an interface to prompt the player to take the next action.

[1452] Input: AI response from the server

[1453] Output: The response (audio and text) presented to the player

[1454] Specific operations: Outputs voice, displays text, and displays a GUI prompting the next action.

[1455] (Application example 1)

[1456] 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."

[1457] On conventional online shopping sites, the user's shopping experience is not personalized, and real-time responses and product recommendations based on the player's behavior and emotional state are not provided, limiting the improvement of user satisfaction. The present invention aims to revolutionize the traditional shopping experience and dramatically improve user satisfaction by collecting user behavior, facial expressions, and voice data in real time and using artificial intelligence to provide appropriate responses and product recommendations based on that data.

[1458] 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.

[1459] In this invention, the server includes means for recording user behavior, means for collecting user facial expression and voice data, means for analyzing the collected data to infer the user's psychological state, means for generating an AI response based on the inferred psychological state, means for presenting the generated AI response to the user, means for recording the user's browsing, selection, and purchase behavior, and means for recommending products based on the user's preferences and past purchase data, thereby enabling personalized recommendations and information provision that responds to the user's behavior and psychological state in real time.

[1460] "User" refers to an individual or corporation that uses the System to shop.

[1461] "Action" refers to the operations, actions, and intentional acts that users perform on the system.

[1462] "Facial expression data" refers to video information that records the user's facial movements and expressions.

[1463] "Voice Data" means acoustic information that records a user's speech or other sounds.

[1464] "Artificial intelligence" refers to a computer program that uses machine learning algorithms and data analysis techniques to understand a user's behavior and psychological state and generate appropriate responses.

[1465] "Reaction" refers to the responses and actions that AI generates based on the user's behavior and psychological state.

[1466] "Product recommendation" refers to artificial intelligence suggesting specific products to purchase based on user preferences and past purchase data.

[1467] "Data analysis" refers to the process of processing collected user behavioral data, facial expression data, and voice data to infer the user's psychological state and preferences.

[1468] "User information" refers comprehensively to data about users, such as personal information, behavioral history, and purchase history.

[1469] "Personalization" refers to providing services that are customized to suit the individual characteristics and preferences of each user.

[1470] "Recommendation content" refers to information about products or services suggested to users.

[1471] "System" refers to the hardware and software that analyzes user behavior and psychological state and enables artificial intelligence to generate appropriate responses and recommendations.

[1472] The system of the present invention analyzes a user's behavior and psychological state and provides personalized product recommendations based on the results. This system is mainly composed of a server, a smartphone terminal, and a machine learning algorithm. Specific embodiments are described below.

[1473] System Overview

[1474] Initial Setup

[1475] The server initiates a user's shopping session and manages user information. At the start of each session, the AI ​​sets up a recommendation algorithm based on past purchase data and browsing history.

[1476] Data collection

[1477] The smartphone device records the user's browsing, selection, purchase, and other actions in real time, and also collects facial expression and voice data using the device's built-in camera and microphone, which are then sent to a server.

[1478] Data analysis

[1479] The server analyzes the collected behavioral logs, facial expression data, and voice data using machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time.

[1480] AI reaction generation

[1481] The server then uses the analysis results to determine the next recommended product or coupon. Based on the estimated psychological state and past purchase data, the AI ​​generates an appropriate response and sends the results to the smartphone device in real time.

[1482] User Feedback

[1483] The smartphone terminal displays the recommendation information received from the server to the user, including product images and discount information in text, and provides an interface that prompts the user to take the next action.

[1484] Hardware and software used

[1485] Hardware: Smartphone (camera, microphone, accelerometer), server (cloud service)

[1486] Software: Machine learning algorithms (TensorFlow, PyTorch), real-time databases (Firebase, MongoDB), natural language processing (NLP) models (BERT, GPT-3)

[1487] Specific examples of processing

[1488] For example, if a user smiles while browsing a particular product, the system can infer that the product is a favorite and recommend related products. If the user is confused, the system can provide a detailed description and review of the product. Here are some examples of prompts:

[1489] Examples of prompt statements

[1490] "If a user smiles while browsing products on their phone, show them relevant product recommendations. Additionally, if they're confused, provide them with a detailed product description."

[1491] "When a user says, 'Tell me about this product,' provide more information about the product in your voice. If the user looks confused, offer discounts on related products."

[1492] This allows the system of the present invention to respond to the user's behavior and state of mind in real time, providing a personalized shopping experience.

[1493] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1494] Step 1:

[1495] Initial Setup

[1496] The server initiates the user's shopping session and manages user information. Specifically, it retrieves the user's past purchase data and browsing history from a database and provides them as input to the AI ​​to set up an initial recommendation algorithm. As a result, an initial list of recommended products is generated for the user.

[1497] Step 2:

[1498] Behavioral data collection

[1499] The device records user actions such as browsing, selection, and purchase in real time. For example, when a user views a product page or adds a product to their cart, the event is recorded as a log. This behavioral data can be sent to a server for real-time analysis. The input is the user's operation event, and the output is the behavioral log data sent to the server.

[1500] Step 3:

[1501] Facial and vocal data collection

[1502] The device uses a camera and microphone to collect the user's facial expressions and audio data. For example, if a user smiles while browsing a product page, the video information is captured. Similarly, audio data is collected by the microphone, and what the user says is sent to the server. The input is video and audio data, and the output is the transmission of this data to the server.

[1503] Step 4:

[1504] Data analysis

[1505] The server analyzes the collected behavioral logs, facial expression data, and voice data. Specifically, it uses machine learning algorithms (e.g., TensorFlow, PyTorch) to infer the user's psychological state and preferences in real time. For example, it determines that a user who smiles a lot is likely to like a particular product. This process receives the behavioral logs and facial expression / voice data as input, and obtains the inferred psychological state as output.

[1506] Step 5:

[1507] Generating product recommendations

[1508] The server then determines the next product or coupon to recommend based on the analysis results. Using a machine learning algorithm, it generates a list of recommended products based on the user's psychological state and past purchase data, and sends it to the device in real time. The input is the estimated psychological state and past purchase data, and the output is the created product recommendation list.

[1509] Step 6:

[1510] User feedback

[1511] The device displays the recommendation information received from the server to the user, including product images and text display of discount information. For example, if a user smiles while viewing a particular product, a discount coupon will be displayed along with recommendations for related products. The input is the recommendation information received from the server, and the output is visual and audio feedback to the user.

[1512] Step 7:

[1513] Next Action Promoting Interface

[1514] The device provides an interface that prompts the user for the next action, such as a button to add related products to the cart or a link to view more information. This allows the user to easily select the next step. The input is the interface element that the user interacts with, and the output is the interface display that prompts the user to do the next action.

[1515] 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.

[1516] System Overview

[1517] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[1518] Program processing

[1519] Step 1: Initial Setup

[1520] server:

[1521] 1. Create a game room and manage player information (usernames, profiles, etc.).

[1522] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[1523] Example: A server creates a poker room, and when a player joins, it assigns the AI ​​player a personality called "Intuitive Decision Maker."

[1524] Step 2: Collect player data

[1525] Device:

[1526] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[1527] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[1528] Example: The device logs the actions of players exchanging cards, and at the same time, the camera captures the players' expressions of laughter or surprise, and sends the video data to the server.

[1529] Step 3: Data analysis and application of the sentiment engine

[1530] server:

[1531] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1532] 2. Use the emotion engine to recognize and track player emotions based on this data.

[1533] Example: The server analyzes the behavior of players during poker and discovers a behavioral pattern of "smiling when betting high amounts." The emotion engine recognizes the player's emotions (relief, joy).

[1534] Step 4: AI response generation

[1535] server:

[1536] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[1537] 2. The determined response is sent to the terminal in real time.

[1538] Example: The server runs an AI action decision algorithm to generate the optimal next action or statement based on the player's behavior and emotional state. The AI ​​player says, "Your facial expression suggests you have a strong hand."

[1539] Step 5: Player feedback

[1540] Device:

[1541] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[1542] 2. Provide an interface to prompt the player for their next action.

[1543] Example: The device communicates the AI's statement "Your expression tells you that's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[1544] Example

[1545] When this system is applied to the Werewolf game, the AI ​​analyzes the player's comments and facial expressions, and the emotion engine recognizes the player's emotions and identifies suspicious individuals. When applied to poker, the AI ​​infers the player's psychological state from their betting behavior, facial expressions, and emotional analysis by the emotion engine, and adjusts strategy accordingly. This allows players to enjoy a more intense psychological battle, unlike the monotonous CPU battles of the past.

[1546] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[1547] The processing flow will be explained below.

[1548] Step 1: Initial Setup

[1549] server:

[1550] 1. Create a game room and manage player information (usernames, profiles, etc.).

[1551] 2. When each player joins the game, they set the AI's personality. The AI's personality is a characteristic that is individually set by the player and is the basis for determining the AI's reactions and behavior patterns.

[1552] Specific behavior:

[1553] The server creates and initializes a new game room.

[1554] Each player's participation information is recorded in a log, and the AI ​​player is given a personality such as "intuitive decision maker" or "calm analyst."

[1555] Step 2: Collect player and sentiment data

[1556] Device:

[1557] 1. All player actions (e.g., card selection, exchanges, bets, statements) are logged in real time.

[1558] 2. Using a camera and microphone, the player's facial expressions and voice data are collected and sent to the server.

[1559] Specific behavior:

[1560] The terminal logs the actions of players as they exchange cards and bet.

[1561] The device's camera captures the player's facial expressions (smile, surprise, etc.) frame by frame, and the microphone records the player's voice data in real time. These data are then sent to the server.

[1562] Step 3: Data analysis and application of the sentiment engine

[1563] server:

[1564] 1. Analyze the collected behavior log, facial expression data, and voice data. The behavior log is used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1565] 2. Use the emotion engine to recognize and track player emotions based on this data.

[1566] Specific behavior:

[1567] The behavioral analysis module analyzes the player's action history and learns certain behavioral patterns (e.g., "smiling when placing high bets").

[1568] The emotion analysis module analyzes facial and voice data to recognize and track the player's emotional state (e.g., relief, joy, tension).

[1569] Step 4: AI response generation

[1570] server:

[1571] 1. Determine the AI ​​player's next action or statement based on the analysis results and emotion recognition results from the emotion engine. Generate the optimal reaction based on the inferred psychological state, behavioral patterns, and emotional state.

[1572] 2. The determined response is sent to the terminal in real time.

[1573] Specific behavior:

[1574] The server runs the AI's action decision algorithm and generates the next action or statement based on the player's behavior and emotional state. For example, the AI ​​player might say, "Your facial expression suggests you have a strong hand."

[1575] The generated response is sent to the terminal for the next process.

[1576] Step 5: Player Feedback

[1577] Device:

[1578] 1. Present the AI's responses sent from the server to the player, including on-screen text and audio output.

[1579] 2. Provide an interface to prompt the player for their next action.

[1580] Specific behavior:

[1581] The device displays messages received from the server on the screen and, in some cases, plays back the AI's statements aloud.

[1582] Displays buttons or options that allow the player to select their next action, such as "draw next card" or "set bet amount."

[1583] Step 6: Iterate on game progression

[1584] User:

[1585] 1. The player observes the AI's reactions and chooses their next action. This system provides real-time feedback, allowing for psychological tactics.

[1586] 2. The selected action is reflected again throughout the system, and the next data collection and analysis cycle begins.

[1587] Specific behavior:

[1588] Players perform actions such as selecting their next hand, setting a bet amount, and speaking to other players or the AI.

[1589] These actions are then incorporated into the overall system, initiating subsequent processing cycles.

[1590] By implementing this invention, players can experience a realistic and deep psychological battle, which is different from the monotonous CPU battles of the past. This is particularly useful in strategy games such as Werewolf and Poker, and has the effect of keeping players interested for a long period of time.

[1591] Although an embodiment of the present invention has been described above, the present invention is not limited to this embodiment and can be applied to other games and scenarios.

[1592] Example 2

[1593] 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."

[1594] In conventional game systems, it was difficult to analyze the player's behavior and emotions in real time and generate appropriate AI responses based on that. As a result, players were forced to play against monotonous and predictable AI, which lacked realism and excitement. Furthermore, it was not possible to provide interactive responses that properly reflected the player's emotional state, which prevented players from increasing satisfaction.

[1595] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for recording the player's actions, means for collecting facial expression and voice data of the player, means for analyzing the collected data to infer the player's emotional state, means for recognizing and tracking the player's emotions using an emotion engine, means for generating an AI response based on the inferred emotional state, and means for presenting the generated AI response to the player. This enables realistic and exciting battles based on the players' emotions and actions.

[1596] A "means for recording player actions" is a device or function that records all of a player's actions and decisions during a game in real time as a log.

[1597] "Means for collecting the player's facial expressions and voice data" refers to devices or functions that use input devices such as cameras and microphones to obtain the player's facial expressions and voices.

[1598] "Means for analyzing collected data to infer the player's emotional state" refers to devices or software that use acquired behavioral logs, facial expression data, and voice data to analyze them and infer the player's psychological state.

[1599] "Means for recognizing and tracking player emotions using an emotion engine" refers to a device or function that uses a dedicated engine for emotion analysis to continuously recognize changes in a player's emotions in real time.

[1600] "Means for generating AI responses based on inferred emotional states" refers to devices or software that allow AI to determine the next appropriate action or statement based on analyzed emotional data and behavioral patterns.

[1601] "Means for presenting the generated AI's response to the player" refers to a device or function that displays or presents the response determined by the AI ​​to the player in the form of text, audio, video, etc.

[1602] This invention provides a game system that uses AI to show more human-like reactions by analyzing the player's behavior and psychological state and using an emotion engine to recognize and track the user's emotions. Specifically, the system collects and analyzes the player's behavioral patterns, facial expressions, and voice data in real time, and the emotion engine recognizes the user's emotions. Based on this information, the AI ​​responds appropriately, providing the player with a realistic and exciting match.

[1603] The basic configuration of this system is as follows:

[1604] Hardware:

[1605] Camera: Generic webcam (e.g. Logitech C920)

[1606] Microphone: General-purpose condenser microphone (e.g., Sony ECM-CS3)

[1607] Game server: General-purpose cloud service (e.g. AWS EC2)

[1608] software:

[1609] Game server management software: Uses Apache Kafka for data stream processing

[1610] Data analysis and emotion recognition software: TensorFlow and OpenCV

[1611] Action decision algorithm: Implemented in Python

[1612] Examples:

[1613] Below is a specific example in which this system is applied to a poker game.

[1614] 1. Server:

[1615] The server creates a poker game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a MySQL database.

[1616] When each player joins the game, the server assigns a personality to the AI. For example, the AI ​​player might be assigned the personality of "intuitive decision maker."

[1617] 2. Terminal:

[1618] As players play the game, the device logs all actions (e.g., card selection, exchanges, bets, statements) in real time.

[1619] At the same time, a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3) are used to collect the player's facial expressions and voice data, which are then sent to the server in real time.

[1620] 3. Data analysis by the server:

[1621] The server analyzes the collected action logs, facial expression data, and voice data. The action logs are used to extract the player's behavioral patterns, and the facial expression data and voice data are used to infer the player's emotional state.

[1622] The analysis uses TensorFlow and OpenCV, and an emotion engine is implemented to recognize and track the player's emotions.

[1623] 4. AI Response Generation:

[1624] The server determines the AI ​​player's next action and statement based on the analysis results and the emotion recognition results of the emotion engine. For example, if a player makes a high bet and smiles, the server will generate a statement such as, "Your facial expression suggests you have a strong hand."

[1625] The determined response is transmitted to the terminal in real time.

[1626] 5. User Feedback:

[1627] The device displays the AI's responses sent from the server to the player, including on-screen text and audio output.

[1628] The device then provides an interface to prompt the player for the next action, for example, by displaying a message such as "Please select your next action."

[1629] Example prompt sentence:

[1630] "Please explain how you can analyze the actions and facial expressions of players when they exchange cards, recognize their emotions with an emotion engine, and generate an appropriate AI response."

[1631] Compared to conventional monotonous and unpredictable matches against AI, this invention enables realistic and exciting matches based on the player's emotions and actions, which is expected to increase player satisfaction and enhance the realism and excitement of the game.

[1632] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1633] Step 1:

[1634] server:

[1635] The server creates a game room on an AWS EC2 instance and stores player information (username, profile, etc.) in a database.

[1636] Input: Player's basic information (username, profile)

[1637] Data processing: The process of storing player information in a database

[1638] Output: A game room is created and the player information is saved in the database.

[1639] How it works: The server stores player data in a MySQL database, and when each player joins, it loads a personality profile, such as "intuitive decision maker," into the AI.

[1640] Step 2:

[1641] Device:

[1642] As players play the game, the device logs all actions (card selection, exchanges, bets, and statements) in real time.

[1643] Input: Player in-game actions (card selection, exchanges, bets, etc.)

[1644] Data processing: Processing that records data as a log in real time

[1645] Output: Player in-game actions are logged

[1646] Specific operation: The terminal records the player's action data in a log file and transmits the data to the server in real time.

[1647] Step 3:

[1648] Device:

[1649] Using a camera (e.g., Logitech C920) and a microphone (e.g., Sony ECM-CS3), the player's facial expressions and voice data are collected and sent to the server.

[1650] Input: Player facial expression and voice data

[1651] Data processing: The process of capturing and sending facial expression and voice data.

[1652] Output: The player's facial expression and voice data are sent to the server.

[1653] What it does: The device uses a camera and microphone to capture the player's real-time facial expressions and voice, and then transmits them to the server as a data stream.

[1654] Step 4:

[1655] server:

[1656] The server analyzes the collected action logs, facial expression data, and voice data. It extracts the player's behavioral patterns from the action logs and infers the player's emotional state by analyzing the facial expression data and voice data.

[1657] Input: Behavioral log, facial expression data, voice data

[1658] Data processing: Data analysis (extracting behavioral patterns, predicting emotional states)

[1659] Output: Player behavior patterns and emotional state

[1660] Specific operation: The server uses TensorFlow and OpenCV to analyze the behavior log and extract specific patterns (e.g., "smiling when placing a high bet"), and then uses an emotion engine to detect the player's emotions (e.g., relief, joy).

[1661] Step 5:

[1662] server:

[1663] Based on the analysis results and the emotion recognition results of the emotion engine, the AI ​​decides the next action or statement.

[1664] Input: Analysis results, emotion recognition results

[1665] Data processing: Action decision algorithms generate next actions and statements

[1666] Output: The next action or statement generated by the AI

[1667] Specific operation: The server executes an action decision algorithm implemented in Python, generates a statement such as "Your expression suggests you have a strong hand," and sends it to the device.

[1668] Step 6:

[1669] Device:

[1670] Presents the AI's responses sent from the server to the player, including on-screen text and audio output.

[1671] Input: AI-generated next action or statement

[1672] Data processing: Conversion to screen display and audio output formats

[1673] Output: Text and / or audio presented to the player

[1674] Specific operation: The device conveys the AI's statement "Your expression tells you that it's a strong move" to the player via voice and text, and displays a message waiting for the next action.

[1675] Through these steps, the system analyzes the player's actions and emotions in real time and generates appropriate AI responses based on that, providing a more exciting gaming experience.

[1676] (Application example 2)

[1677] 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."

[1678] Conventional advertising systems deliver uniform advertisements without considering the real-time psychological state of consumers, making it difficult to deploy advertisements effectively. There is also a need for a system that analyzes players' behavior and emotions in real time and provides appropriate feedback based on that analysis. The present invention aims to deliver advertisements effectively and improve the user experience by analyzing consumers' facial expressions and voice data and displaying advertisements that best fit their emotions in real time.

[1679] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for recording the player's actions, a means for collecting the player's facial expression and voice data, a means for analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state, and a system for presenting the generated AI response to the player, which includes a means for analyzing consumer emotional data and displaying optimal advertisements in real time. This makes it possible to analyze consumer emotions in real time and effectively deliver advertisements that are optimal for those emotions.

[1680] A "means for recording player actions" is a device or software that has the function of saving as data a series of operations or actions performed by a player during a game.

[1681] "Means for collecting player facial and voice data" refers to equipment or software that has the function of capturing and recording a player's facial expressions and tone of voice using devices such as a camera or microphone.

[1682] "Means of analyzing collected data to infer the player's psychological state" refers to algorithms or programs that determine the player's emotions and mental state through facial recognition and voice analysis.

[1683] "Means for generating AI responses based on inferred psychological states" refers to algorithms or programs that allow AI to determine appropriate responses or actions based on the analysis results.

[1684] A "system for presenting generated AI responses to a player" is a device or software for displaying AI-generated responses to a player in text, audio, or other form.

[1685] "A means for analyzing consumer emotional data and displaying optimal advertisements in real time" is a system that uses cameras and microphones to collect consumers' facial expressions and voices, analyzes that data to infer their emotions, and displays relevant advertisements based on the results.

[1686] "Means of setting an AI's personality and conducting psychological warfare based on that personality" refers to algorithms or programs that give an AI a specific character or personality attribute, and cause it to act and react in accordance with that personality.

[1687] "Means of analyzing consumers' facial expressions and voices and suggesting advertisements that best suit their psychological state at the time" refers to algorithms and programs that recognize consumers' emotions in real time and select and display advertisements that suit their state.

[1688] "Means of learning behavioral patterns and determining the next game strategy based on them" refers to a machine learning algorithm that analyzes a player's past behavioral data and allows the AI ​​to calculate the optimal next move.

[1689] "Means for obtaining the most suitable advertisement from an advertisement distribution server based on emotional data" refers to a program that sends a request to an advertisement server based on the consumer's emotional data, and as a result, obtains and displays the most suitable advertisement.

[1690] MODE FOR CARRYING OUT THE INVENTION

[1691] This invention is a system for analyzing user behavior and emotions in real time and using that data to display optimal advertisements. The system includes means for recording player behavior, means for collecting facial and voice data of the player, means for analyzing the collected data to infer the player's psychological state, means for generating an AI response based on the inferred psychological state, and means for presenting the generated AI response to the player. It also includes means for analyzing consumer emotional data to display optimal advertisements in real time.

[1692] Hardware and Software Configuration

[1693] Hardware:

[1694] 1. Smartphone: Equipped with a camera and microphone, it collects the user's facial expressions and voice.

[1695] 2. Smart glasses: Equipped with a front camera and microphone, they capture the user's face and voice.

[1696] 3. Server: Central processing unit for data analysis and ad selection.

[1697] software:

[1698] 1. OpenCV: A library for processing camera images and analyzing facial expressions.

[1699] 2. Tensorflow and Keras: Use deep learning models to analyze emotions from collected data.

[1700] 3. Requests: HTTP request library for communicating with ad servers.

[1701] System Operation

[1702] The server receives data sent from the user's smartphone or smart glasses, including the user's behavior log, facial expression, and voice data. The server first processes the collected image data using OpenCV to perform facial recognition and facial expression analysis. Then, it uses Tensorflow and Keras to infer the user's emotional state.

[1703] Based on the estimated emotional state, the server uses the Requests library to send a request to the ad server to retrieve the most suitable advertisement, which is then displayed in real time on the user's smartphone or smart glasses, providing the user with the most suitable advertisement information.

[1704] Specific examples

[1705] For example, imagine a user walking through a shopping mall. The smart glasses capture the user's facial expressions and send the data to a server. The server uses an emotion engine to infer a "happy" state and sends a request to an advertising server based on the emotion data. The advertising server returns information about sales related to the "happy state" and presents it to the user.

[1706] Examples of prompts:

[1707] When users are happy, they ask for ads to show them special offers and sales information.

[1708] In this way, optimal ads can be provided in real time according to the user's emotional state, resulting in more effective ad delivery and a richer user experience.

[1709] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1710] Step 1:

[1711] The user's smartphone or smart glasses use a camera and microphone to collect facial and voice data in real time. At this stage, the user's facial images and voice clips are the input data.

[1712] Step 2:

[1713] The device sends the collected facial expression and voice data to a server, which then transfers the collected data to the server via a network and treats it as data to be analyzed.

[1714] Step 3:

[1715] The server processes the received data using OpenCV for facial recognition and facial expression analysis. Specifically, a face detection algorithm extracts facial features from the image, and the facial expressions are applied to a deep learning model to infer emotional states. The input to this process is the user's facial image, and the output is an inferred emotion (e.g., happiness, surprise, etc.).

[1716] Step 4:

[1717] The server uses Tensorflow and Keras to analyze the audio data and infer emotions from the user's voice. At this stage, the audio clip is the input data, and the audio analysis model analyzes the tone and patterns of the voice to infer the emotional state. The output is the inferred emotion.

[1718] Step 5:

[1719] The server then combines the analyzed facial expression data and voice data to determine the overall emotional state. At this point, the input data are individually estimated emotional information, and the final overall emotional state is output.

[1720] Step 6:

[1721] The server uses the Requests library to send a request to the ad serving server to retrieve the most suitable ad based on the inferred emotional state, where the input is the overall emotional state and the output is the relevant ad data returned by the ad server.

[1722] Step 7:

[1723] The server transmits the acquired advertising data to the user's smartphone or smart glasses, where it is displayed on the device and presented to the user.

[1724] Step 8:

[1725] The device again collects the user's reactions to the displayed ads and sends them to the server as a behavior log. This input is new user behavior data, which is used as feedback to improve the accuracy of the entire system.

[1726] Specific examples

[1727] For example, in step 1, the smart glasses capture the user's smile, and then in step 2, transmit the video and audio to the server. In steps 3 to 5, the server analyzes this data and infers that the user is in a "happy" state. Then, in step 6, the server transmits the "happy" emotional state to the ad distribution server, which retrieves an advertisement containing information about special offers and sales. In step 7, this advertisement is displayed on the smart glasses, and finally, in step 8, the server collects the user's response again.

[1728] This series of processes allows advertisements that are optimized to suit the user's emotions to be delivered effectively.

[1729] 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.

[1730] 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.

[1731] 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.

[1732] 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.

[1733] 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.

[1734] 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.

[1735] 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).

[1736] 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.

[1737] 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."

[1738] 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.

[1739] 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).

[1740] 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.

[1741] 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.

[1742] 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.

[1743] 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.

[1744] 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.

[1745] 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.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] The following is further disclosed regarding the above embodiment.

[1751] (Claim 1)

[1752] a means of recording player actions;

[1753] a means for collecting facial and voice data of a player;

[1754] A means of analyzing the collected data to infer the player's psychological state,

[1755] a means for generating an AI response based on the inferred psychological state;

[1756] A means to present the generated AI's responses to the player,

[1757] A system including:

[1758] (Claim 2)

[1759] The system according to claim 1, further comprising means for setting a personality of the AI ​​and conducting psychological warfare based on the set personality.

[1760] (Claim 3)

[1761] 10. The system according to claim 1, further comprising means for learning behavioral patterns and determining a next game strategy based thereon.

[1762] "Example 1"

[1763] (Claim 1)

[1764] a means of recording player actions;

[1765] a means for collecting facial and voice data of a player;

[1766] using machine learning algorithms to analyze the collected data and infer the player's psychological state; and

[1767] a means for generating an AI response based on the inferred psychological state and behavioral patterns;

[1768] a means for outputting audio and displaying on a screen to present the reaction of the generated AI to the player;

[1769] A system including:

[1770] (Claim 2)

[1771] The system according to claim 1, further comprising means for setting a personality of the AI ​​and conducting psychological warfare based on the set personality.

[1772] (Claim 3)

[1773] 2. The system according to claim 1, further comprising means for learning a behavioral pattern based on the player's behavioral data and facial expression data, and determining a next game strategy.

[1774] "Application Example 1"

[1775] (Claim 1)

[1776] a means of recording user behavior;

[1777] means for collecting facial and voice data of a user;

[1778] A means of analyzing the collected data to infer the user's psychological state;

[1779] means for generating an artificial intelligence response based on the inferred psychological state;

[1780] A means for presenting the generated response of the artificial intelligence to the user;

[1781] A means of recording your browsing, selection and purchasing behavior;

[1782] A means of recommending products based on user preferences and past purchase data, and

[1783] A system including:

[1784] (Claim 2)

[1785] 2. The system according to claim 1, further comprising means for setting a personality of the artificial intelligence and for interacting with the user based on the set personality.

[1786] (Claim 3)

[1787] 10. The system of claim 1, further comprising means for learning behavioral patterns and determining subsequent recommendations based thereon.

[1788] "Example 2: Combining Emotion Engines"

[1789] (Claim 1)

[1790] a means of recording player actions;

[1791] a means for collecting facial and voice data of a player;

[1792] A means of analyzing the collected data to infer the player's emotional state;

[1793] means for recognizing and tracking player emotions using an emotion engine;

[1794] a means for generating a response of the AI ​​based on the inferred emotional state;

[1795] A means to present the generated AI's responses to the player,

[1796] A system including:

[1797] (Claim 2)

[1798] The system according to claim 1, further comprising means for setting a personality of the AI ​​and conducting psychological warfare based on the set personality.

[1799] (Claim 3)

[1800] 10. The system according to claim 1, further comprising means for learning behavioral patterns and determining a next game strategy based thereon.

[1801] "Application example 2 when combining emotion engines"

[1802] (Claim 1)

[1803] a means of recording player actions;

[1804] a means for collecting facial and voice data of a player;

[1805] A means of analyzing the collected data to infer the player's psychological state,

[1806] a means for generating an AI response based on the inferred psychological state;

[1807] A system that presents the generated AI's response to a player,

[1808] A means to analyze consumer sentiment data and display optimal advertisements in real time,

[1809] A system including:

[1810] (Claim 2)

[1811] A means of setting the personality of the AI ​​and conducting psychological warfare based on the set personality,

[1812] 2. The system according to claim 1, further comprising means for analyzing the consumer's facial expressions and voice and suggesting advertisements that are most suited to the consumer's psychological state at that time.

[1813] (Claim 3)

[1814] A means for learning behavioral patterns and determining the next game strategy based on the patterns;

[1815] 2. The system according to claim 1, further comprising means for acquiring an optimal advertisement from an advertisement distribution server based on the emotion data. [Explanation of symbols]

[1816] 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. a means of recording player actions; a means for collecting facial and voice data of a player; A means of analyzing the collected data to infer the player's psychological state, a means for generating an AI response based on the inferred psychological state; A means to present the generated AI's responses to the player, A system including:

2. The system according to claim 1, further comprising means for setting a personality of the AI ​​and conducting psychological warfare based on the set personality.

3. 2. The system according to claim 1, further comprising means for learning a behavioral pattern and determining a next game strategy based thereon.

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