system

Abstract

We provide the system. [Solution] A means of receiving love-related information entered by a user using a communication terminal, An analysis means for analyzing the received information and analyzing the situation, A means for generating appropriate advice by comparing the analysis results with similar past cases, A means for creating a virtual romance simulation and presenting it to the user in an executable format, A means for analyzing the results of the simulation and providing feedback to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Love is an important element in human relationships, and many people hope for success. However, due to the involvement of complex emotions and communication, unexpected failures and anxieties are likely to occur. In addition, there is a problem that it is difficult for users to formulate countermeasures according to individual situations because there are insufficient means to attempt practice in specific scenarios and improve the success rate.

Means for Solving the Problems

[0005] This invention provides a system that receives information about love entered by a user via a communication terminal and analyzes that information. Based on the analyzed information, this system can compare it with similar past cases and generate accurate and effective advice. Furthermore, by creating a virtual love simulation and enabling the user to practice in a realistic situation, it increases the chances of future success. By further analyzing the simulation results and providing specific feedback to the user, it provides an environment in which the user can choose their actions with confidence.

[0006] A "communication terminal" is an electronic device used by users to input information or receive feedback from a system.

[0007] "Information related to romance" refers to all information based on the context of romance, including the user's personal feelings and circumstances, and data about their partner.

[0008] A "receiving means" is a mechanism that has the function of receiving information transmitted from a communication terminal.

[0009] "Analysis tools" are technologies that analyze input information and perform a process to classify and understand emotions and situations.

[0010] "Means of generating advice" refers to functions that, based on analysis results, suggest the most suitable actions and next steps for the user.

[0011] A "virtual dating simulation" is a process that provides scenarios designed to mimic real-life dating situations, allowing users to practice and learn.

[0012] A "means of providing feedback" refers to a system that communicates information to users regarding areas for improvement and next steps based on simulation results. [Brief explanation of the drawing]

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

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

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

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

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

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

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

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

[0021] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0034] The system of this invention improves the success rate of romantic relationships by allowing users to input information related to romance via a communication terminal and providing effective advice and virtual simulations based on that information.

[0035] Users use their communication devices to input text about their current relationship status and details about their partner. The device then sends this information to the server.

[0036] The server analyzes the received information. This analysis includes a process that uses natural language processing techniques to extract sentiment, topic, and context from the input text. Based on the analyzed information, the server compares it with past databases to generate advice that is most appropriate to the user's current situation.

[0037] The generated advice is sent to the user's communication terminal and provided as suggestions for effective actions and guidance for the next steps.

[0038] Furthermore, the server generates a virtual dating simulation based on the analysis results. This simulation meticulously imitates situations such as confessions and dates, providing users with a platform for practice. By repeatedly experiencing situations close to real life on the system, users can improve their ability to cope in real life.

[0039] For example, if a user enters "I feel like my partner isn't interested in me," the server analyzes the information and, based on strategies that have worked in similar cases in the past, offers advice such as "Expand on a shared hobby on your next date." At the same time, it provides a simulation scenario to try out that advice, creating an environment where the user can practice practically.

[0040] After the simulation, the server analyzes the results and provides feedback to the user. This feedback allows the user to understand areas for improvement and apply them to future attempts.

[0041] Thus, this system provides a comprehensive means to support users in their romantic endeavors and prepare them for taking concrete action.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] Users input information and questions about their current romantic situation in text format via a communication terminal. The terminal converts this input information into packets and sends them to the server.

[0045] Step 2:

[0046] The server analyzes the text data received from the terminal. Natural language processing techniques are used for the analysis, identifying and extracting sentiment, topic, and context. This process is designed to accurately understand the user's intent.

[0047] Step 3:

[0048] The server compares the analyzed data with a database of past cases. By referring to similar cases, it derives advice with a high probability of success. In this process, it applies a predictive model using machine learning algorithms.

[0049] Step 4:

[0050] The server sends the generated advice to the user's communication terminal. The terminal displays this advice to the user, providing specific action guidelines.

[0051] Step 5:

[0052] Based on the analysis results, the server generates a virtual simulation that mimics a specific romantic scene. This simulation incorporates multiple reaction patterns, allowing the user to experience each of the choices.

[0053] Step 6:

[0054] Users participate in the simulation on a communication terminal, choosing responses and actions based on the presented options and situations. The terminal continuously transmits the user's choices to the server.

[0055] Step 7:

[0056] The server analyzes the user's choices and reactions in real time during the simulation. Based on the analysis results, it repeatedly presents the next options and reactions.

[0057] Step 8:

[0058] After the simulation is complete, the server comprehensively evaluates the user's behavior and generates feedback. This feedback highlights areas for improvement and strengths, along with specific examples.

[0059] Step 9:

[0060] The server sends feedback to the user's communication device, which then displays it visually to the user. The user can use this feedback to improve their next actions and increase their chances of success.

[0061] (Example 1)

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

[0063] Traditional interpersonal relationship support systems have faced challenges in providing effective advice and concrete simulations tailored to each user's individual situation. In particular, there is a need to generate advice in real time that is appropriate to the user's emotions and specific context, and to provide a practical practice environment using virtual simulations. Solving these problems is crucial for supporting users' success in interpersonal relationships.

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

[0065] In this invention, the server includes means for receiving interpersonal relationship-related data input using an information processing device; means for analyzing the received data and evaluating the situation; means for generating appropriate guidelines by comparing the analysis results with similar past cases; means for constructing a virtual situation simulation and presenting it to the user in an executable format via the information processing device; and means for evaluating the results of the simulation and providing the user with feedback indicating areas for improvement. This makes it possible to provide advice and simulations tailored to the user's individual situation and improve the user's interpersonal skills.

[0066] An "information processing device" refers to a computer device used for inputting, analyzing, and outputting data.

[0067] "Interpersonal relationships" is a concept that refers to communication, interaction, and relationships between people.

[0068] "Data" refers to a collection of information, including strings of characters, numbers, and shapes used for analysis and processing.

[0069] "Means of receiving" refers to components that have the function of taking in information transmitted from an external source into the device.

[0070] "Analysis" is the process of examining received data in detail and extracting hidden elements and patterns.

[0071] "Evaluative analytical tools" refer to components that have the function of analyzing data and judging the state or trend based on the results.

[0072] "Means for generating guidelines" refers to components that have the function of constructing specific advice and directions for action based on the analysis results.

[0073] "Simulation" refers to the process of imitation of real-world events in a virtual environment and providing users with that experience.

[0074] "Feedback" refers to information that provides evaluations and suggestions for improvement regarding performance and behavior.

[0075] "User" refers to an individual or organization that operates a system through an information processing device and inputs or receives information.

[0076] The system of this invention is designed to provide support related to interpersonal relationships and operates primarily through information exchange and processing between users, terminals, and servers.

[0077] The user uses a terminal, which is an information processing device, to input detailed data about their interpersonal relationships. The user's input data includes their current interpersonal situation, emotions, and information about the other person. For example, the user might input data such as, "There was little talk about our shared hobbies in recent conversations."

[0078] Next, the device sends this input data to the server via a secure communication protocol (e.g., HTTPS). The server analyzes the received data using natural language processing techniques. The analysis utilizes sentiment analysis APIs and topic modeling to extract emotional nuances and key topics from the user's text.

[0079] The server compares the analysis results with similar past databases and generates appropriate guidelines for each individual user. It uses a generative AI model to derive specific advice and strategies. For example, the server might suggest, "In the next conversation, delve deeper into your shared hobbies."

[0080] Furthermore, the server constructs virtual situational simulations. This allows users to practice within a virtual environment and experience practical dialogue scenarios. The terminal then presents these simulations to the user in an executable format.

[0081] After the simulation, the server evaluates the results and provides feedback to the user. It identifies specific areas for improvement so that the user can use this information in future interpersonal situations.

[0082] A concrete example of a prompt message would be a user entering a request such as, "I want to find topics in this conversation that interest me."

[0083] This system provides users with a comprehensive and effective means to improve their interpersonal skills.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user inputs data related to interpersonal relationships into a terminal, which is an information processing device. The input data includes specific worries, questions, and feelings about the current situation. For example, the user might input, "Lately, I've been having trouble keeping conversations going with my friends." This data from the user is stored in the terminal as initial input.

[0087] Step 2:

[0088] The terminal sends the data entered by the user to the server via a security protocol. The data sent is the entire user input and is delivered to the server in text format. At this stage, the data transmission takes place and is completed.

[0089] Step 3:

[0090] The server analyzes the received text data. First, it uses natural language processing techniques to extract emotions and topics from the data. Specifically, it uses an emotion analysis API to quantify the emotional tone of the input and passes the results to a topic modeling algorithm. The output of this analysis generates an emotion score and related topics.

[0091] Step 4:

[0092] The server compares the analysis results with past database data and generates appropriate guidance for the user. This process uses a generative AI model to construct advice based on successful case studies. For example, it might generate advice such as, "Try finding a common hobby." This generated advice is then output from the server.

[0093] Step 5:

[0094] The server prepares a virtual situation simulation. Based on the analysis results, it drives the life simulator and assembles a virtual scenario that the user can practice. The simulation scenario reproduces multiple scenes to help the user understand the flow of dialogue and is prepared in a way that allows user participation.

[0095] Step 6:

[0096] The system provides the user with generated guidelines and a simulation via a terminal. The terminal notifies the user and prompts them to start the simulation. The user can experience the virtual simulation by following the guidelines and receive feedback.

[0097] Step 7:

[0098] The server evaluates the user's simulation results and generates feedback. The evaluation is performed by analyzing the user's behavior patterns and identifying specific areas for improvement. Based on these results, it generates feedback on improvement suggestions and next steps, which are then sent from the server to the terminal.

[0099] (Application Example 1)

[0100] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0101] While users seek accurate advice and virtual practice opportunities for relationship and interpersonal issues, there is a need to address the challenge of a lack of systems that adequately mimic real-world situations and provide practical feedback.

[0102] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0103] In this invention, the server includes means for receiving relationship-related information input by the user using an information processing device; means for analyzing the received information and performing sentiment analysis; means for generating appropriate responses by comparing the analysis results with past data; means for creating a virtual situation simulation and providing it to the user in an executable form; means for analyzing the results of the simulation and providing the user with improvement suggestions; and means for providing feedback to the user through actual dialogue. This enables the user to improve their success rate in romance and relationships through practical practice.

[0104] An "information processing device" is an electronic device that has the function of inputting, processing, and outputting data.

[0105] "Relationship-related information" refers to detailed data related to a user's personal relationships and romantic life.

[0106] "Means of receiving" refers to functions for acquiring data from external sources, primarily utilizing communication functions.

[0107] "Analysis tools" refer to functions that analyze input data and perform a process to understand its meaning and structure.

[0108] "Sentiment analysis" is a technique that identifies, classifies, or evaluates emotional states based on input information.

[0109] "Means for generating appropriate responses" refers to a function that creates optimal actions and advice based on analysis results.

[0110] "Virtual situation simulation" is a technology that creates a digital environment that mimics real-world situations, allowing users to have virtual experiences within that environment.

[0111] "Means of providing" refers to methods and devices for presenting generated information or results to the user.

[0112] "Means of providing improvement suggestions" refers to a function that presents users with recommendations for improvement based on the results of analysis and simulation.

[0113] "Means of providing feedback" refers to a process of giving evaluations and comments on user actions and reactions to guide the next steps.

[0114] In this system, users input relationship-related information in text format using their own information processing device. The terminal then transmits this information to the server. The server has a communication module for receiving the input information and retrieves data based on this.

[0115] The server employs software that uses natural language processing technology as its analysis method. Specifically, it utilizes the Google® Cloud Speech-to-Text API to convert speech input into text data and analyze the user's utterance as text information. Sentiment analysis is performed on the analyzed information to understand the user's emotional state and then appropriate countermeasures are generated.

[0116] The generated countermeasures are constructed by comparing them with past data using a generative AI model contained within the server. Leveraging the OpenAI model and using prompt statements, optimal advice is formulated for the user. Next, a virtual situation simulation is generated. This simulation mimics situations the user might actually experience, creating an environment for providing a realistic experience.

[0117] Users can receive these simulations through their terminals and practice real-world interactions and experiences within the system. Based on the simulation results, the server provides feedback to the user, suggesting specific improvements and next steps.

[0118] For example, if a user inputs "I've been finding recent dates boring," the server analyzes the user's emotions based on the given information and generates advice such as "suggesting a new activity." It then provides specific suggestions, such as "How about going to a cooking class together on the weekend?" Another example of a prompt is "The user is looking for new date ideas. Based on this information, what suggestions are possible?" This sentence is input into the AI ​​model to obtain an appropriate output.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The user uses an information processing device to input relationship-related information as text. The device then sends this text data to the server. The input data consists of specific details about the user's relationships with people.

[0122] Step 2:

[0123] The server first uses the Google Cloud Speech-to-Text API to convert the information received from the terminal into text data, if there is voice input. Here, the input is the voice entered by the user, and the output is a series of text converted from the voice information.

[0124] Step 3:

[0125] The server uses natural language processing techniques to perform sentiment analysis on text data. It extracts emotions from the input text data and processes the data to identify the user's psychological state. The output is an evaluation value related to the emotions in the text.

[0126] Step 4:

[0127] The server uses a generative AI model to generate prompt messages based on sentiment analysis results and inputs them into the OpenAI model. The input here is the sentiment analysis results, and the output is user-optimized advice and countermeasures.

[0128] Step 5:

[0129] The server generates virtual situation simulations and constructs scenarios that users can experience in real-world situations. The input is generated advice, and the output is a virtual dating scenario or dialogue scene based on that advice.

[0130] Step 6:

[0131] The user receives a simulation provided via their device and interacts with it. The user's actions within the simulation are fed back to the server.

[0132] Step 7:

[0133] The server re-analyzes the simulation results and generates improvement suggestions and feedback for the user. The input is the user's response data during the simulation, and the output is recommendations for the next action.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention is a system that uses an analysis system incorporating an emotion engine to sensitively grasp the user's emotional state based on love-related information entered by the user using a communication terminal, and provides appropriate advice and simulations.

[0136] The user uses a communication device to input text about their love life. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's feelings. The device then transmits this information to the server.

[0137] The server analyzes the received data using an emotion engine. This engine combines natural language processing techniques with the user's text data to infer the user's emotional state in real time. The emotion engine identifies emotional nuances and tones within the text and classifies the user's emotional state.

[0138] Based on the information obtained by the emotion engine, the server uses analytical tools to compare the user's situation with similar past relationship cases. This comparison generates advice that is best suited to the user's emotional state. The advice is adjusted according to the user's emotions, making it more empathetic and actionable.

[0139] The server also creates a virtual romance simulation that takes the user's emotional state into account. This simulation recreates specific emotional situations the user might encounter, providing an opportunity for the user to practice how to deal with those situations. The simulation provides multiple choices and response patterns, allowing the user to gain virtual experiences based on them.

[0140] For example, if a user inputs "I haven't been communicating well with my partner lately," the emotion engine identifies emotions such as anxiety and worry associated with this situation. Based on this, the server recommends "creating another opportunity for calm dialogue" and guides the user on how to proceed with the conversation. Furthermore, it runs simulations to train the user to make appropriate choices.

[0141] Thus, this system provides appropriate advice and a practice environment that takes the user's emotional state into consideration, functioning as a comprehensive tool to support practical application in realistic situations.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] Users use a communication device to input their relationship-related challenges and situations in text format. It is recommended that the content include descriptions of emotions and specific events.

[0145] Step 2:

[0146] The terminal packets the entered text information and sends it to the server. During this process, the communication is encrypted to protect the user's privacy.

[0147] Step 3:

[0148] The server passes the received text data to the emotion engine. The emotion engine uses the latest natural language processing technology to identify the emotions contained in the text and analyze the user's emotional state.

[0149] Step 4:

[0150] The emotion engine classifies the user's emotions and identifies their intensity and type (e.g., joy, anxiety, anger). This clarifies the user's emotional state.

[0151] Step 5:

[0152] The server compares the analyzed sentiment information with a database of similar past cases. This comparison allows the server to select appropriate advice based on the user's situation.

[0153] Step 6:

[0154] The server generates advice tailored to the user's emotional state and situation, and sends it to the user's communication terminal. This advice includes specific action suggestions and guidance on mindset.

[0155] Step 7:

[0156] The server then prepares a virtual romance simulation tailored to the user's emotional state. The simulation consists of scenarios based on real-life situations.

[0157] Step 8:

[0158] Users initiate a simulation on their communication terminal and choose their responses to the presented situations and options. This allows them to hone their skills in handling romantic situations through a rehearsal process.

[0159] Step 9:

[0160] Once the simulation is complete, the server evaluates the user's choices and reactions. It then uses an emotion engine to re-evaluate how the choices impact emotions.

[0161] Step 10:

[0162] The server provides feedback to the user based on the overall analysis results. This feedback includes areas for improvement and points to consider when making future choices.

[0163] Step 11:

[0164] Users will use the feedback provided to improve their behavior in real-life romantic relationships and utilize this system to build better relationships.

[0165] (Example 2)

[0166] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0167] In interpersonal relationships, it is not easy for users to understand their own emotional state and take appropriate actions based on it. Furthermore, opportunities to practice how to deal with real-world situations are limited. Therefore, there is a need for a comprehensive system that enables users to accurately grasp their emotions and learn practical responses.

[0168] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0169] In this invention, the server includes means for receiving information related to human relationships that a user inputs using a computing device, means for analyzing the received information and analyzing the emotional state, and means for generating empathetic advice by comparing the analysis results with similar past cases. This enables the user to appropriately understand their own emotional state and acquire practical responses accordingly.

[0170] A "computer" is an electronic device used for inputting and processing information, and is used by users when they input their own information.

[0171] "Information related to interpersonal relationships" refers to text data entered by users about their own emotions and circumstances, and includes various events that occur in their relationships with others.

[0172] "Means of receiving" refers to the process and equipment by which a server retrieves data transmitted from a computing device, and is responsible for the transmission and initial processing of information.

[0173] "Analysis means" refers to processes and devices for evaluating and classifying received information, and in particular includes technologies for analyzing emotional states and feelings.

[0174] "Means for generating empathetic advice" refers to a process that forms appropriate suggestions and advice tailored to the user's feelings based on analysis results, providing information that serves as a guide when users take specific actions.

[0175] A "virtual relationship simulation" is a simulated environment designed for users to practice coping with specific emotional situations, allowing them to explore different options and responses.

[0176] "A means of providing opportunities for growth" refers to a process of evaluating the results obtained through simulations and providing feedback to help users improve their skills and response methods.

[0177] This invention uses a system with emotion analysis capabilities to understand the user's emotional state based on information related to human relationships input by the user using a computing device, and provides empathetic advice and virtual human relationship simulations.

[0178] The user uses a computer to input text about their relationships. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's state of mind. The terminal transmits this user-inputted information to the server using a secure communication protocol (e.g., HTTPS).

[0179] The server analyzes the received data using an emotion analysis engine. This engine uses natural language processing techniques to analyze the user's text data, identifying emotional nuances and tones, and classifying the user's emotional state. This analysis process utilizes a generative AI model to perform real-time emotion assessment.

[0180] Based on the analysis results, the server compares the data with similar past relationship cases and generates empathetic advice best suited to the user's emotional state. This advice is tailored to the user's emotions and provides concrete, actionable suggestions. Furthermore, the server creates virtual relationship simulations that take the user's emotional state into account, simulating specific emotional situations and providing the user with an opportunity to practice how to deal with those situations. Multiple choices and response patterns are available, allowing the user to gain virtual experience based on them.

[0181] For example, if a user inputs "I haven't been communicating well with my family lately," the server uses an emotion analysis engine to identify emotions such as anxiety and loneliness. Based on the results, the server recommends "setting aside time for dialogue" and provides specific instructions on how to proceed. It also runs a simulation to help the user make effective choices.

[0182] An example of an input prompt for a generative AI model is: "User input: Communication at home has been difficult recently. Use the sentiment analysis engine to analyze the situation and show how to provide empathetic advice and simulations to the user."

[0183] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0184] Step 1:

[0185] The user uses a computing device to input text information about interpersonal relationships. This input consists of sentences that specifically describe emotions and situations. The terminal collects this information, converts it into a data format, and then sends it to the server for the next analysis process.

[0186] Step 2:

[0187] The server receives text information sent from the terminal. The input data consists of raw text messages from the user. Based on this data, the server passes it to an emotion analysis engine, which uses natural language processing techniques to identify emotional nuances and tones and classify the emotional state. The output is a numerical or categorized representation of the user's emotional state.

[0188] Step 3:

[0189] The server, upon receiving the output from the emotion analysis engine, compares it to similar past cases. Specifically, the server searches a large database of past cases to identify patterns similar to the input emotional state. The output of this comparison process is a list of suggested advice and past successful actions.

[0190] Step 4:

[0191] The server generates personalized advice for the user based on matching results with similar cases. This advice generation process involves crafting text that empathizes with the user's feelings and includes specific, helpful advice. The output of this step is the refined advice text provided to the user.

[0192] Step 5:

[0193] The server then creates a virtual relationship simulation. Based on the generated advice, it constructs scenarios that simulate specific emotional situations, providing multiple choices and response patterns. The output of this simulation is provided to the user as a virtual experience that they can try.

[0194] Step 6:

[0195] The server sends the advice and simulation results to the terminal. The input includes the output from each step taken so far. The terminal displays this information in a user interface, providing actionable information for the user. The final output is specific advice and a simulation scenario presented on the screen.

[0196] (Application Example 2)

[0197] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0198] In daily life, it is a challenging task for users to effectively understand and manage their emotions in personal conversations and relationship maintenance. To resolve problems arising from differences in emotional expression and lack of communication, support is needed to enable users to objectively evaluate their own emotions and take appropriate action. This invention aims to solve these problems.

[0199] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0200] In this invention, the server includes means for receiving information related to personal relationships entered by the user using an information processing device, means for analyzing the received information and analyzing its state, and means for creating a virtual relationship simulation and presenting it to the user in an executable form. This allows the user to understand their own emotional state and receive simulations and advice for dealing with it.

[0201] An "information processing device" is an electronic device used by users to input information and to receive, transmit, and analyze data.

[0202] "Information related to personal relationships" refers to data concerning personal relationships, such as the user's emotions, circumstances, and conversation content.

[0203] "Analysis means" refers to a process or mechanism for analyzing received information and evaluating the user's emotional state and situation.

[0204] A "virtual relationship simulation" is a device or program designed to simulate real-world situations for the purpose of providing feedback and training to users.

[0205] "Emotion analysis" is a technology that infers a user's emotions from their input information and derives an appropriate response.

[0206] "Means of generating advice" refers to processes or systems that provide users with appropriate advice or guidelines based on analysis results.

[0207] A "response pattern" refers to a system's standardized response to a user's choices or reactions, and is part of the options presented within the simulation.

[0208] The system realizing this invention centers around an analysis device that receives and analyzes personal relationship-related information input by the user using an information processing device. The analysis device analyzes the input data using natural language processing technology to infer the user's emotional state. This utilizes an emotion analysis model built in Python and libraries such as TENSORFLOW® and NLTK. Based on the data obtained from the emotion analysis, the server generates appropriate advice and a virtual relationship simulation. This simulation uses simulation development platforms such as Unity or Unreal Engine to present the user with choices and response patterns.

[0209] Furthermore, the server provides users with advice based on the analysis results, supporting them in deciding what to do next. For example, if a user inputs, "I haven't been able to communicate well with my partner lately," the server will identify the emotion "anxiety" through emotion analysis and generate advice to create an opportunity for calm dialogue. In this way, the server provides an environment where users can deeply understand their own emotional state and deal with it appropriately.

[0210] As a concrete example, a prompt sentence for a generative AI model could be, "I feel like I haven't been communicating well with my partner lately. What should I do?" This prompt allows the system to analyze the user's intent and construct an appropriate response or simulation.

[0211] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0212] Step 1:

[0213] The user inputs information about their personal relationships through an information processing terminal. This information is text data that expresses the specific situation and emotions the user is experiencing. The terminal prepares this input information as data to be sent to the server and then transmits it.

[0214] Step 2:

[0215] The server analyzes the text data it receives. In this process, the server uses natural language processing techniques to tokenize the text and then uses a Python sentiment analysis model to analyze the user's emotional state. For example, if the input is "I haven't been able to communicate well with my partner lately," the server will identify emotions such as "anxiety" and "worry" and output the results as data.

[0216] Step 3:

[0217] Based on the sentiment analysis results, the server compares the user's emotional state with similar past cases and generates appropriate advice. This involves calculating the similarity between the user's emotional state and a database of past cases, and selecting cases with a high degree of similarity. Based on the selected cases, the user receives specific advice such as "create an opportunity for calm dialogue."

[0218] Step 4:

[0219] The server generates and provides a virtual relationship simulation to the user. This simulation is built using a simulation development platform and is in a format that allows the user to experience choices and response patterns for each scenario. Different relationship scenarios are presented based on user input, and the user's responses to them are recorded as data.

[0220] Step 5:

[0221] The server analyzes the user's choices and simulation results, providing feedback. This feedback includes specific areas for improvement and guidance on next steps based on the user's choices. The analysis uses technology that compares simulation results with initial sentiment analysis results to generate optimal feedback. This allows the user to improve their coping strategies and better prepare for future situations.

[0222] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0223] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0224] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0225] [Second Embodiment]

[0226] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0227] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0228] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0229] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0230] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0231] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0232] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0233] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0234] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0235] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0236] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0237] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0238] The system of this invention improves the success rate of romantic relationships by allowing users to input information related to romance via a communication terminal and providing effective advice and virtual simulations based on that information.

[0239] Users use their communication devices to input text about their current relationship status and details about their partner. The device then sends this information to the server.

[0240] The server analyzes the received information. This analysis includes a process that uses natural language processing techniques to extract sentiment, topic, and context from the input text. Based on the analyzed information, the server compares it with past databases to generate advice that is most appropriate to the user's current situation.

[0241] The generated advice is sent to the user's communication terminal and provided as suggestions for effective actions and guidance for the next steps.

[0242] Furthermore, the server generates a virtual dating simulation based on the analysis results. This simulation meticulously imitates situations such as confessions and dates, providing users with a platform for practice. By repeatedly experiencing situations close to real life on the system, users can improve their ability to cope in real life.

[0243] For example, if a user enters "I feel like my partner isn't interested in me," the server analyzes the information and, based on strategies that have worked in similar cases in the past, offers advice such as "Expand on a shared hobby on your next date." At the same time, it provides a simulation scenario to try out that advice, creating an environment where the user can practice practically.

[0244] After the simulation, the server analyzes the results and provides feedback to the user. This feedback allows the user to understand areas for improvement and apply them to future attempts.

[0245] Thus, this system provides a comprehensive means to support users in their romantic endeavors and prepare them for taking concrete action.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] Users input information and questions about their current romantic situation in text format via a communication terminal. The terminal converts this input information into packets and sends them to the server.

[0249] Step 2:

[0250] The server analyzes the text data received from the terminal. Natural language processing techniques are used for the analysis, identifying and extracting sentiment, topic, and context. This process is designed to accurately understand the user's intent.

[0251] Step 3:

[0252] The server compares the analyzed data with a database of past cases. By referring to similar cases, it derives advice with a high probability of success. In this process, it applies a predictive model using machine learning algorithms.

[0253] Step 4:

[0254] The server sends the generated advice to the user's communication terminal. The terminal displays this advice to the user, providing specific action guidelines.

[0255] Step 5:

[0256] Based on the analysis results, the server generates a virtual simulation that mimics a specific romantic scene. This simulation incorporates multiple reaction patterns, allowing the user to experience each of the choices.

[0257] Step 6:

[0258] Users participate in the simulation on a communication terminal, choosing responses and actions based on the presented options and situations. The terminal continuously transmits the user's choices to the server.

[0259] Step 7:

[0260] The server analyzes the user's choices and reactions in real time during the simulation. Based on the analysis results, it repeatedly presents the next options and reactions.

[0261] Step 8:

[0262] After the simulation is complete, the server comprehensively evaluates the user's behavior and generates feedback. This feedback highlights areas for improvement and strengths, along with specific examples.

[0263] Step 9:

[0264] The server sends feedback to the user's communication device, which then displays it visually to the user. The user can use this feedback to improve their next actions and increase their chances of success.

[0265] (Example 1)

[0266] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0267] Traditional interpersonal relationship support systems have faced challenges in providing effective advice and concrete simulations tailored to each user's individual situation. In particular, there is a need to generate advice in real time that is appropriate to the user's emotions and specific context, and to provide a practical practice environment using virtual simulations. Solving these problems is crucial for supporting users' success in interpersonal relationships.

[0268] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0269] In this invention, the server includes means for receiving interpersonal relationship-related data input using an information processing device; means for analyzing the received data and evaluating the situation; means for generating appropriate guidelines by comparing the analysis results with similar past cases; means for constructing a virtual situation simulation and presenting it to the user in an executable format via the information processing device; and means for evaluating the results of the simulation and providing the user with feedback indicating areas for improvement. This makes it possible to provide advice and simulations tailored to the user's individual situation and improve the user's interpersonal skills.

[0270] An "information processing device" refers to a computer device used for inputting, analyzing, and outputting data.

[0271] "Interpersonal relationships" is a concept that refers to communication, interaction, and relationships between people.

[0272] "Data" refers to a collection of information, including strings of characters, numbers, and shapes used for analysis and processing.

[0273] "Means of receiving" refers to components that have the function of taking in information transmitted from an external source into the device.

[0274] "Analysis" is the process of examining received data in detail and extracting hidden elements and patterns.

[0275] "Evaluative analytical tools" refer to components that have the function of analyzing data and judging the state or trend based on the results.

[0276] "Means for generating guidelines" refers to components that have the function of constructing specific advice and directions for action based on the analysis results.

[0277] "Simulation" refers to the process of imitation of real-world events in a virtual environment and providing users with that experience.

[0278] "Feedback" refers to information that presents evaluations or improvement suggestions regarding performance or actions.

[0279] "User" means an individual or organization that operates a system through an information processing device and inputs or receives information.

[0280] The system of the present invention is for providing support related to interpersonal relationships and operates centered on information exchange and processing among users, terminals, and servers.

[0281] The user uses a terminal, which is an information processing device, to input detailed data related to interpersonal relationships. The user's input data includes information about the current interpersonal situation, emotions, and the other party. For example, the user inputs data such as "There was little talk about common hobbies in the recent conversation."

[0282] Next, the terminal transmits this input data to the server via a secure communication protocol (e.g., HTTPS). The server analyzes the received data based on natural language processing technology. For the analysis, sentiment analysis APIs and topic modeling are utilized to extract the nuances of emotions and major topics from the user's text.

[0283] The server compares the analysis results with a past similar database and generates appropriate guidelines for individual users. A generative AI model is used to derive specific advice and strategies. At this time, the server makes a proposal such as "Dig deeper into common hobbies in the next conversation" as a guideline.

[0284] Furthermore, the server constructs a virtual situation simulation. As a result, the user can practice within the virtual environment and experience practical conversation scenarios. The terminal presents these simulations to the user in an executable form.

[0285] After the simulation, the server evaluates the results and provides feedback to the user. It shows specific points for improvement so that they can be applied to the next interpersonal relationship scenario.

[0286] As a specific example of a prompt sentence, it is conceivable that the user inputs a request such as "I want to find a topic that interests me in this conversation."

[0287] This system provides a comprehensive and effective means for users to improve their interpersonal relationship skills.

[0288] The flow of the specific process in Example 1 will be described using FIG. 11.

[0289] Step 1:

[0290] The user inputs data related to interpersonal relationships into a terminal, which is an information processing device. The data to be input includes specific troubles, doubts, and emotions in the current situation. For example, the user inputs "Recently, conversations with friends don't last long." This data from the user is stored in the terminal as initial input.

[0291] Step 2:

[0292] The terminal sends the data input by the user to the server via a security protocol. The data to be sent is the entire user input and is passed to the server in text format. At this stage, the data transmission is carried out and completed.

[0293] Step 3:

[0294] The server analyzes the received text data. First, it uses natural language processing technology to extract emotions and topics from the data. Specifically, it utilizes an emotion analysis API to quantify the emotional tone of the input and passes the result to a topic modeling algorithm. As the output of this analysis, an emotion score and related topics are generated.

[0295] Step 4:

[0296] The server compares the analysis results with past database data and generates appropriate guidance for the user. This process uses a generative AI model to construct advice based on successful case studies. For example, it might generate advice such as, "Try finding a common hobby." This generated advice is then output from the server.

[0297] Step 5:

[0298] The server prepares a virtual situation simulation. Based on the analysis results, it drives the life simulator and assembles a virtual scenario that the user can practice. The simulation scenario reproduces multiple scenes to help the user understand the flow of dialogue and is prepared in a way that allows user participation.

[0299] Step 6:

[0300] The system provides the user with generated guidelines and a simulation via a terminal. The terminal notifies the user and prompts them to start the simulation. The user can experience the virtual simulation by following the guidelines and receive feedback.

[0301] Step 7:

[0302] The server evaluates the user's simulation results and generates feedback. The evaluation is performed by analyzing the user's behavior patterns and identifying specific areas for improvement. Based on these results, it generates feedback on improvement suggestions and next steps, which are then sent from the server to the terminal.

[0303] (Application Example 1)

[0304] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0305] While users seek accurate advice and a virtual practice ground for problems in love and human relationships, there is a need to solve the problem that there is a lack of a system that sufficiently mimics the real situation and provides practical feedback.

[0306] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0307] In this invention, the server includes means for receiving information related to relationships input by the user using an information processing device, analysis means for analyzing the received information and performing sentiment analysis, means for generating an appropriate response by comparing with past data based on the analysis result, means for creating a virtual situation simulation and providing it to the user in an executable form, means for analyzing the result of the simulation and giving improvement suggestions to the user, and means for providing feedback to the user through an actual conversation. Thereby, the user can improve the success rate in love and human relationships through practical practice.

[0308] The "information processing device" refers to an electronic device having functions for inputting, processing, and outputting data.

[0309] The "information related to relationships" refers to detailed data related to the user's personal human relationships and love.

[0310] The "means for receiving" refers to a function for acquiring data from the outside, mainly using a communication function.

[0311] The "analysis means" is a function for performing a process of analyzing the input data and understanding its meaning and structure.

[0312] "Sentiment analysis" is a technology for identifying, classifying, or evaluating the emotional state from the input information. [[ID=二十九]]

[0313] "Means for generating appropriate responses" refers to a function that creates optimal actions and advice based on analysis results.

[0314] "Virtual situation simulation" is a technology that creates a digital environment that mimics real-world situations, allowing users to have virtual experiences within that environment.

[0315] "Means of providing" refers to methods and devices for presenting generated information or results to the user.

[0316] "Means of providing improvement suggestions" refers to a function that presents users with recommendations for improvement based on the results of analysis and simulation.

[0317] "Means of providing feedback" refers to a process of giving evaluations and comments on user actions and reactions to guide the next steps.

[0318] In this system, users input relationship-related information in text format using their own information processing device. The terminal then transmits this information to the server. The server has a communication module for receiving the input information and retrieves data based on this.

[0319] The server employs software that uses natural language processing technology as its analysis method. Specifically, it utilizes the Google Cloud Speech-to-Text API to convert speech input into text data and analyze the user's utterance as text information. Sentiment analysis is then performed on the analyzed information to understand the user's emotional state and generate appropriate countermeasures.

[0320] The generated countermeasures are constructed by comparing them with past data using a generative AI model contained within the server. Leveraging the OpenAI model and using prompt statements, optimal advice is formulated for the user. Next, a virtual situation simulation is generated. This simulation mimics situations the user might actually experience, creating an environment for providing a realistic experience.

[0321] Users can receive these simulations through their terminals and practice real-world interactions and experiences within the system. Based on the simulation results, the server provides feedback to the user, suggesting specific improvements and next steps.

[0322] For example, if a user inputs "I've been finding recent dates boring," the server analyzes the user's emotions based on the given information and generates advice such as "suggesting a new activity." It then provides specific suggestions, such as "How about going to a cooking class together on the weekend?" Another example of a prompt is "The user is looking for new date ideas. Based on this information, what suggestions are possible?" This sentence is input into the AI ​​model to obtain an appropriate output.

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The user uses an information processing device to input relationship-related information as text. The device then sends this text data to the server. The input data consists of specific details about the user's relationships with people.

[0326] Step 2:

[0327] The server first uses the Google Cloud Speech-to-Text API to convert the information received from the terminal into text data, if there is voice input. Here, the input is the voice entered by the user, and the output is a series of text converted from the voice information.

[0328] Step 3:

[0329] The server uses natural language processing techniques to perform sentiment analysis on text data. It extracts emotions from the input text data and processes the data to identify the user's psychological state. The output is an evaluation value related to the emotions in the text.

[0330] Step 4:

[0331] The server uses a generative AI model to generate prompt messages based on sentiment analysis results and inputs them into the OpenAI model. The input here is the sentiment analysis results, and the output is user-optimized advice and countermeasures.

[0332] Step 5:

[0333] The server generates virtual situation simulations and constructs scenarios that users can experience in real-world situations. The input is generated advice, and the output is a virtual dating scenario or dialogue scene based on that advice.

[0334] Step 6:

[0335] The user receives a simulation provided via their device and interacts with it. The user's actions within the simulation are fed back to the server.

[0336] Step 7:

[0337] The server re-analyzes the simulation results and generates improvement suggestions and feedback for the user. The input is the user's response data during the simulation, and the output is recommendations for the next action.

[0338] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0339] This invention is a system that uses an analysis system incorporating an emotion engine to sensitively grasp the user's emotional state based on love-related information entered by the user using a communication terminal, and provides appropriate advice and simulations.

[0340] The user uses a communication device to input text about their love life. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's feelings. The device then transmits this information to the server.

[0341] The server analyzes the received data using an emotion engine. This engine combines natural language processing techniques with the user's text data to infer the user's emotional state in real time. The emotion engine identifies emotional nuances and tones within the text and classifies the user's emotional state.

[0342] Based on the information obtained by the emotion engine, the server uses analytical tools to compare the user's situation with similar past relationship cases. This comparison generates advice that is best suited to the user's emotional state. The advice is adjusted according to the user's emotions, making it more empathetic and actionable.

[0343] The server also creates a virtual romance simulation that takes the user's emotional state into account. This simulation recreates specific emotional situations the user might encounter, providing an opportunity for the user to practice how to deal with those situations. The simulation provides multiple choices and response patterns, allowing the user to gain virtual experiences based on them.

[0344] For example, if a user inputs "I haven't been communicating well with my partner lately," the emotion engine identifies emotions such as anxiety and worry associated with this situation. Based on this, the server recommends "creating another opportunity for calm dialogue" and guides the user on how to proceed with the conversation. Furthermore, it runs simulations to train the user to make appropriate choices.

[0345] Thus, this system provides appropriate advice and a practice environment that takes the user's emotional state into consideration, functioning as a comprehensive tool to support practical application in realistic situations.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] Users use a communication device to input their relationship-related challenges and situations in text format. It is recommended that the content include descriptions of emotions and specific events.

[0349] Step 2:

[0350] The terminal packets the entered text information and sends it to the server. During this process, the communication is encrypted to protect the user's privacy.

[0351] Step 3:

[0352] The server passes the received text data to the emotion engine. The emotion engine uses the latest natural language processing technology to identify the emotions contained in the text and analyze the user's emotional state.

[0353] Step 4:

[0354] The emotion engine classifies the user's emotions and identifies their intensity and type (e.g., joy, anxiety, anger). This clarifies the user's emotional state.

[0355] Step 5:

[0356] The server compares the analyzed sentiment information with a database of similar past cases. This comparison allows the server to select appropriate advice based on the user's situation.

[0357] Step 6:

[0358] The server generates advice tailored to the user's emotional state and situation, and sends it to the user's communication terminal. This advice includes specific action suggestions and guidance on mindset.

[0359] Step 7:

[0360] The server then prepares a virtual romance simulation tailored to the user's emotional state. The simulation consists of scenarios based on real-life situations.

[0361] Step 8:

[0362] Users initiate a simulation on their communication terminal and choose their responses to the presented situations and options. This allows them to hone their skills in handling romantic situations through a rehearsal process.

[0363] Step 9:

[0364] Once the simulation is complete, the server evaluates the user's choices and reactions. It then uses an emotion engine to re-evaluate how the choices impact emotions.

[0365] Step 10:

[0366] The server provides feedback to the user based on the overall analysis results. This feedback includes areas for improvement and points to consider when making future choices.

[0367] Step 11:

[0368] Users will use the feedback provided to improve their behavior in real-life romantic relationships and utilize this system to build better relationships.

[0369] (Example 2)

[0370] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0371] In interpersonal relationships, it is not easy for users to understand their own emotional state and take appropriate actions based on it. Furthermore, opportunities to practice how to deal with real-world situations are limited. Therefore, there is a need for a comprehensive system that enables users to accurately grasp their emotions and learn practical responses.

[0372] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0373] In this invention, the server includes means for receiving information related to human relationships that a user inputs using a computing device, means for analyzing the received information and analyzing the emotional state, and means for generating empathetic advice by comparing the analysis results with similar past cases. This enables the user to appropriately understand their own emotional state and acquire practical responses accordingly.

[0374] A "computer" is an electronic device used for inputting and processing information, and is used by users when they input their own information.

[0375] "Information related to interpersonal relationships" refers to text data entered by users about their own emotions and circumstances, and includes various events that occur in their relationships with others.

[0376] "Means of receiving" refers to the process and equipment by which a server retrieves data transmitted from a computing device, and is responsible for the transmission and initial processing of information.

[0377] "Analysis means" refers to processes and devices for evaluating and classifying received information, and in particular includes technologies for analyzing emotional states and feelings.

[0378] "Means for generating empathetic advice" refers to a process that forms appropriate suggestions and advice tailored to the user's feelings based on analysis results, providing information that serves as a guide when users take specific actions.

[0379] A "virtual relationship simulation" is a simulated environment designed for users to practice coping with specific emotional situations, allowing them to explore different options and responses.

[0380] "A means of providing opportunities for growth" refers to a process of evaluating the results obtained through simulations and providing feedback to help users improve their skills and response methods.

[0381] This invention uses a system with emotion analysis capabilities to understand the user's emotional state based on information related to human relationships input by the user using a computing device, and provides empathetic advice and virtual human relationship simulations.

[0382] The user uses a computer to input text about their relationships. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's state of mind. The terminal transmits this user-inputted information to the server using a secure communication protocol (e.g., HTTPS).

[0383] The server analyzes the received data using an emotion analysis engine. This engine uses natural language processing techniques to analyze the user's text data, identifying emotional nuances and tones, and classifying the user's emotional state. This analysis process utilizes a generative AI model to perform real-time emotion assessment.

[0384] Based on the analysis results, the server compares the data with similar past relationship cases and generates empathetic advice best suited to the user's emotional state. This advice is tailored to the user's emotions and provides concrete, actionable suggestions. Furthermore, the server creates virtual relationship simulations that take the user's emotional state into account, simulating specific emotional situations and providing the user with an opportunity to practice how to deal with those situations. Multiple choices and response patterns are available, allowing the user to gain virtual experience based on them.

[0385] For example, if a user inputs "I haven't been communicating well with my family lately," the server uses an emotion analysis engine to identify emotions such as anxiety and loneliness. Based on the results, the server recommends "setting aside time for dialogue" and provides specific instructions on how to proceed. It also runs a simulation to help the user make effective choices.

[0386] An example of an input prompt for a generative AI model is: "User input: Communication at home has been difficult recently. Use the sentiment analysis engine to analyze the situation and show how to provide empathetic advice and simulations to the user."

[0387] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0388] Step 1:

[0389] The user uses a computing device to input text information about interpersonal relationships. This input consists of sentences that specifically describe emotions and situations. The terminal collects this information, converts it into a data format, and then sends it to the server for the next analysis process.

[0390] Step 2:

[0391] The server receives text information sent from the terminal. The input data consists of raw text messages from the user. Based on this data, the server passes it to an emotion analysis engine, which uses natural language processing techniques to identify emotional nuances and tones and classify the emotional state. The output is a numerical or categorized representation of the user's emotional state.

[0392] Step 3:

[0393] The server, upon receiving the output from the emotion analysis engine, compares it to similar past cases. Specifically, the server searches a large database of past cases to identify patterns similar to the input emotional state. The output of this comparison process is a list of suggested advice and past successful actions.

[0394] Step 4:

[0395] The server generates personalized advice for the user based on matching results with similar cases. This advice generation process involves crafting text that empathizes with the user's feelings and includes specific, helpful advice. The output of this step is the refined advice text provided to the user.

[0396] Step 5:

[0397] The server then creates a virtual relationship simulation. Based on the generated advice, it constructs scenarios that simulate specific emotional situations, providing multiple choices and response patterns. The output of this simulation is provided to the user as a virtual experience that they can try.

[0398] Step 6:

[0399] The server sends the advice and simulation results to the terminal. The input includes the output from each step taken so far. The terminal displays this information in a user interface, providing actionable information for the user. The final output is specific advice and a simulation scenario presented on the screen.

[0400] (Application Example 2)

[0401] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0402] In daily life, it is a challenging task for users to effectively understand and manage their emotions in personal conversations and relationship maintenance. To resolve problems arising from differences in emotional expression and lack of communication, support is needed to enable users to objectively evaluate their own emotions and take appropriate action. This invention aims to solve these problems.

[0403] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0404] In this invention, the server includes means for receiving information related to personal relationships entered by the user using an information processing device, means for analyzing the received information and analyzing its state, and means for creating a virtual relationship simulation and presenting it to the user in an executable form. This allows the user to understand their own emotional state and receive simulations and advice for dealing with it.

[0405] An "information processing device" is an electronic device used by users to input information and to receive, transmit, and analyze data.

[0406] "Information related to personal relationships" refers to data concerning personal relationships, such as the user's emotions, circumstances, and conversation content.

[0407] "Analysis means" refers to a process or mechanism for analyzing received information and evaluating the user's emotional state and situation.

[0408] A "virtual relationship simulation" is a device or program designed to simulate real-world situations for the purpose of providing feedback and training to users.

[0409] "Emotion analysis" is a technology that infers a user's emotions from their input information and derives an appropriate response.

[0410] "Means of generating advice" refers to processes or systems that provide users with appropriate advice or guidelines based on analysis results.

[0411] A "response pattern" refers to a system's standardized response to a user's choices or reactions, and is part of the options presented within the simulation.

[0412] The system realizing this invention centers around an analysis device that receives and analyzes personal relationship-related information input by the user using an information processing device. The analysis device analyzes the input data using natural language processing technology to infer the user's emotional state. This utilizes an emotion analysis model built in Python and libraries such as TensorFlow and NLTK. Based on the data obtained from the emotion analysis, the server generates appropriate advice and a virtual relationship simulation. This simulation uses simulation development platforms such as Unity or Unreal Engine to present the user with choices and response patterns.

[0413] Furthermore, the server provides users with advice based on the analysis results, supporting them in deciding what to do next. For example, if a user inputs, "I haven't been able to communicate well with my partner lately," the server will identify the emotion "anxiety" through emotion analysis and generate advice to create an opportunity for calm dialogue. In this way, the server provides an environment where users can deeply understand their own emotional state and deal with it appropriately.

[0414] As a concrete example, a prompt sentence for a generative AI model could be, "I feel like I haven't been communicating well with my partner lately. What should I do?" This prompt allows the system to analyze the user's intent and construct an appropriate response or simulation.

[0415] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0416] Step 1:

[0417] The user inputs information about their personal relationships through an information processing terminal. This information is text data that expresses the specific situation and emotions the user is experiencing. The terminal prepares this input information as data to be sent to the server and then transmits it.

[0418] Step 2:

[0419] The server analyzes the text data it receives. In this process, the server uses natural language processing techniques to tokenize the text and then uses a Python sentiment analysis model to analyze the user's emotional state. For example, if the input is "I haven't been able to communicate well with my partner lately," the server will identify emotions such as "anxiety" and "worry" and output the results as data.

[0420] Step 3:

[0421] Based on the sentiment analysis results, the server compares the user's emotional state with similar past cases and generates appropriate advice. This involves calculating the similarity between the user's emotional state and a database of past cases, and selecting cases with a high degree of similarity. Based on the selected cases, the user receives specific advice such as "create an opportunity for calm dialogue."

[0422] Step 4:

[0423] The server generates and provides a virtual relationship simulation to the user. This simulation is built using a simulation development platform and is in a format that allows the user to experience choices and response patterns for each scenario. Different relationship scenarios are presented based on user input, and the user's responses to them are recorded as data.

[0424] Step 5:

[0425] The server analyzes the user's choices and simulation results, providing feedback. This feedback includes specific areas for improvement and guidance on next steps based on the user's choices. The analysis uses technology that compares simulation results with initial sentiment analysis results to generate optimal feedback. This allows the user to improve their coping strategies and better prepare for future situations.

[0426] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0427] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0428] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0429] [Third Embodiment]

[0430] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0431] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0432] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0433] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0434] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0435] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0436] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0437] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0438] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0439] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0440] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0441] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0442] The system of this invention improves the success rate of romantic relationships by allowing users to input information related to romance via a communication terminal and providing effective advice and virtual simulations based on that information.

[0443] Users use their communication devices to input text about their current relationship status and details about their partner. The device then sends this information to the server.

[0444] The server analyzes the received information. This analysis includes a process that uses natural language processing techniques to extract sentiment, topic, and context from the input text. Based on the analyzed information, the server compares it with past databases to generate advice that is most appropriate to the user's current situation.

[0445] The generated advice is sent to the user's communication terminal and provided as suggestions for effective actions and guidance for the next steps.

[0446] Furthermore, the server generates a virtual dating simulation based on the analysis results. This simulation meticulously imitates situations such as confessions and dates, providing users with a platform for practice. By repeatedly experiencing situations close to real life on the system, users can improve their ability to cope in real life.

[0447] For example, if a user enters "I feel like my partner isn't interested in me," the server analyzes the information and, based on strategies that have worked in similar cases in the past, offers advice such as "Expand on a shared hobby on your next date." At the same time, it provides a simulation scenario to try out that advice, creating an environment where the user can practice practically.

[0448] After the simulation, the server analyzes the results and provides feedback to the user. This feedback allows the user to understand areas for improvement and apply them to future attempts.

[0449] Thus, this system provides a comprehensive means to support users in their romantic endeavors and prepare them for taking concrete action.

[0450] The following describes the processing flow.

[0451] Step 1:

[0452] Users input information and questions about their current romantic situation in text format via a communication terminal. The terminal converts this input information into packets and sends them to the server.

[0453] Step 2:

[0454] The server analyzes the text data received from the terminal. Natural language processing techniques are used for the analysis, identifying and extracting sentiment, topic, and context. This process is designed to accurately understand the user's intent.

[0455] Step 3:

[0456] The server compares the analyzed data with a database of past cases. By referring to similar cases, it derives advice with a high probability of success. In this process, it applies a predictive model using machine learning algorithms.

[0457] Step 4:

[0458] The server sends the generated advice to the user's communication terminal. The terminal displays this advice to the user, providing specific action guidelines.

[0459] Step 5:

[0460] Based on the analysis results, the server generates a virtual simulation that mimics a specific romantic scene. This simulation incorporates multiple reaction patterns, allowing the user to experience each of the choices.

[0461] Step 6:

[0462] Users participate in the simulation on a communication terminal, choosing responses and actions based on the presented options and situations. The terminal continuously transmits the user's choices to the server.

[0463] Step 7:

[0464] The server analyzes the user's choices and reactions in real time during the simulation. Based on the analysis results, it repeatedly presents the next options and reactions.

[0465] Step 8:

[0466] After the simulation is complete, the server comprehensively evaluates the user's behavior and generates feedback. This feedback highlights areas for improvement and strengths, along with specific examples.

[0467] Step 9:

[0468] The server sends feedback to the user's communication device, which then displays it visually to the user. The user can use this feedback to improve their next actions and increase their chances of success.

[0469] (Example 1)

[0470] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Traditional interpersonal relationship support systems have faced challenges in providing effective advice and concrete simulations tailored to each user's individual situation. In particular, there is a need to generate advice in real time that is appropriate to the user's emotions and specific context, and to provide a practical practice environment using virtual simulations. Solving these problems is crucial for supporting users' success in interpersonal relationships.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0473] In this invention, the server includes means for receiving interpersonal relationship-related data input using an information processing device; means for analyzing the received data and evaluating the situation; means for generating appropriate guidelines by comparing the analysis results with similar past cases; means for constructing a virtual situation simulation and presenting it to the user in an executable format via the information processing device; and means for evaluating the results of the simulation and providing the user with feedback indicating areas for improvement. This makes it possible to provide advice and simulations tailored to the user's individual situation and improve the user's interpersonal skills.

[0474] An "information processing device" refers to a computer device used for inputting, analyzing, and outputting data.

[0475] "Interpersonal relationships" is a concept that refers to communication, interaction, and relationships between people.

[0476] "Data" refers to a collection of information, including strings of characters, numbers, and shapes used for analysis and processing.

[0477] "Means of receiving" refers to components that have the function of taking in information transmitted from an external source into the device.

[0478] "Analysis" is the process of examining received data in detail and extracting hidden elements and patterns.

[0479] "Evaluative analytical tools" refer to components that have the function of analyzing data and judging the state or trend based on the results.

[0480] "Means for generating guidelines" refers to components that have the function of constructing specific advice and directions for action based on the analysis results.

[0481] "Simulation" refers to the process of imitation of real-world events in a virtual environment and providing users with that experience.

[0482] "Feedback" refers to information that provides evaluations and suggestions for improvement regarding performance and behavior.

[0483] "User" refers to an individual or organization that operates a system through an information processing device and inputs or receives information.

[0484] The system of this invention is designed to provide support related to interpersonal relationships and operates primarily through information exchange and processing between users, terminals, and servers.

[0485] The user uses a terminal, which is an information processing device, to input detailed data about their interpersonal relationships. The user's input data includes their current interpersonal situation, emotions, and information about the other person. For example, the user might input data such as, "There was little talk about our shared hobbies in recent conversations."

[0486] Next, the device sends this input data to the server via a secure communication protocol (e.g., HTTPS). The server analyzes the received data using natural language processing techniques. The analysis utilizes sentiment analysis APIs and topic modeling to extract emotional nuances and key topics from the user's text.

[0487] The server compares the analysis results with similar past databases and generates appropriate guidelines for each individual user. It uses a generative AI model to derive specific advice and strategies. For example, the server might suggest, "In the next conversation, delve deeper into your shared hobbies."

[0488] Furthermore, the server constructs virtual situational simulations. This allows users to practice within a virtual environment and experience practical dialogue scenarios. The terminal then presents these simulations to the user in an executable format.

[0489] After the simulation, the server evaluates the results and provides feedback to the user. It identifies specific areas for improvement so that the user can use this information in future interpersonal situations.

[0490] A concrete example of a prompt message would be a user entering a request such as, "I want to find topics in this conversation that interest me."

[0491] This system provides users with a comprehensive and effective means to improve their interpersonal skills.

[0492] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0493] Step 1:

[0494] The user inputs data related to interpersonal relationships into a terminal, which is an information processing device. The input data includes specific worries, questions, and feelings about the current situation. For example, the user might input, "Lately, I've been having trouble keeping conversations going with my friends." This data from the user is stored in the terminal as initial input.

[0495] Step 2:

[0496] The terminal sends the data entered by the user to the server via a security protocol. The data sent is the entire user input and is delivered to the server in text format. At this stage, the data transmission takes place and is completed.

[0497] Step 3:

[0498] The server analyzes the received text data. First, it uses natural language processing techniques to extract emotions and topics from the data. Specifically, it uses an emotion analysis API to quantify the emotional tone of the input and passes the results to a topic modeling algorithm. The output of this analysis generates an emotion score and related topics.

[0499] Step 4:

[0500] The server compares the analysis results with past database data and generates appropriate guidance for the user. This process uses a generative AI model to construct advice based on successful case studies. For example, it might generate advice such as, "Try finding a common hobby." This generated advice is then output from the server.

[0501] Step 5:

[0502] The server prepares a virtual situation simulation. Based on the analysis results, it drives the life simulator and assembles a virtual scenario that the user can practice. The simulation scenario reproduces multiple scenes to help the user understand the flow of dialogue and is prepared in a way that allows user participation.

[0503] Step 6:

[0504] The system provides the user with generated guidelines and a simulation via a terminal. The terminal notifies the user and prompts them to start the simulation. The user can experience the virtual simulation by following the guidelines and receive feedback.

[0505] Step 7:

[0506] The server evaluates the user's simulation results and generates feedback. The evaluation is performed by analyzing the user's behavior patterns and identifying specific areas for improvement. Based on these results, it generates feedback on improvement suggestions and next steps, which are then sent from the server to the terminal.

[0507] (Application Example 1)

[0508] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0509] While users seek accurate advice and virtual practice opportunities for relationship and interpersonal issues, there is a need to address the challenge of a lack of systems that adequately mimic real-world situations and provide practical feedback.

[0510] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0511] In this invention, the server includes means for receiving relationship-related information input by the user using an information processing device; means for analyzing the received information and performing sentiment analysis; means for generating appropriate responses by comparing the analysis results with past data; means for creating a virtual situation simulation and providing it to the user in an executable form; means for analyzing the results of the simulation and providing the user with improvement suggestions; and means for providing feedback to the user through actual dialogue. This enables the user to improve their success rate in romance and relationships through practical practice.

[0512] An "information processing device" is an electronic device that has the function of inputting, processing, and outputting data.

[0513] "Relationship-related information" refers to detailed data related to a user's personal relationships and romantic life.

[0514] "Means of receiving" refers to functions for acquiring data from external sources, primarily utilizing communication functions.

[0515] "Analysis tools" refer to functions that analyze input data and perform a process to understand its meaning and structure.

[0516] "Sentiment analysis" is a technique that identifies, classifies, or evaluates emotional states based on input information.

[0517] "Means for generating appropriate responses" refers to a function that creates optimal actions and advice based on analysis results.

[0518] "Virtual situation simulation" is a technology that creates a digital environment that mimics real-world situations, allowing users to have virtual experiences within that environment.

[0519] "Means of providing" refers to methods and devices for presenting generated information or results to the user.

[0520] "Means of providing improvement suggestions" refers to a function that presents users with recommendations for improvement based on the results of analysis and simulation.

[0521] "Means of providing feedback" refers to a process of giving evaluations and comments on user actions and reactions to guide the next steps.

[0522] In this system, users input relationship-related information in text format using their own information processing device. The terminal then transmits this information to the server. The server has a communication module for receiving the input information and retrieves data based on this.

[0523] The server employs software that uses natural language processing technology as its analysis method. Specifically, it utilizes the Google Cloud Speech-to-Text API to convert speech input into text data and analyze the user's utterance as text information. Sentiment analysis is then performed on the analyzed information to understand the user's emotional state and generate appropriate countermeasures.

[0524] The generated countermeasures are constructed by comparing them with past data using a generative AI model contained within the server. Leveraging the OpenAI model and using prompt statements, optimal advice is formulated for the user. Next, a virtual situation simulation is generated. This simulation mimics situations the user might actually experience, creating an environment for providing a realistic experience.

[0525] Users can receive these simulations through their terminals and practice real-world interactions and experiences within the system. Based on the simulation results, the server provides feedback to the user, suggesting specific improvements and next steps.

[0526] For example, if a user inputs "I've been finding recent dates boring," the server analyzes the user's emotions based on the given information and generates advice such as "suggesting a new activity." It then provides specific suggestions, such as "How about going to a cooking class together on the weekend?" Another example of a prompt is "The user is looking for new date ideas. Based on this information, what suggestions are possible?" This sentence is input into the AI ​​model to obtain an appropriate output.

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The user uses an information processing device to input relationship-related information as text. The device then sends this text data to the server. The input data consists of specific details about the user's relationships with people.

[0530] Step 2:

[0531] The server first uses the Google Cloud Speech-to-Text API to convert the information received from the terminal into text data, if there is voice input. Here, the input is the voice entered by the user, and the output is a series of text converted from the voice information.

[0532] Step 3:

[0533] The server uses natural language processing techniques to perform sentiment analysis on text data. It extracts emotions from the input text data and processes the data to identify the user's psychological state. The output is an evaluation value related to the emotions in the text.

[0534] Step 4:

[0535] The server uses a generative AI model to generate prompt messages based on sentiment analysis results and inputs them into the OpenAI model. The input here is the sentiment analysis results, and the output is user-optimized advice and countermeasures.

[0536] Step 5:

[0537] The server generates virtual situation simulations and constructs scenarios that users can experience in real-world situations. The input is generated advice, and the output is a virtual dating scenario or dialogue scene based on that advice.

[0538] Step 6:

[0539] The user receives a simulation provided via their device and interacts with it. The user's actions within the simulation are fed back to the server.

[0540] Step 7:

[0541] The server re-analyzes the simulation results and generates improvement suggestions and feedback for the user. The input is the user's response data during the simulation, and the output is recommendations for the next action.

[0542] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0543] This invention is a system that uses an analysis system incorporating an emotion engine to sensitively grasp the user's emotional state based on love-related information entered by the user using a communication terminal, and provides appropriate advice and simulations.

[0544] The user uses a communication device to input text about their love life. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's feelings. The device then transmits this information to the server.

[0545] The server analyzes the received data using an emotion engine. This engine combines natural language processing techniques with the user's text data to infer the user's emotional state in real time. The emotion engine identifies emotional nuances and tones within the text and classifies the user's emotional state.

[0546] Based on the information obtained by the emotion engine, the server uses analytical tools to compare the user's situation with similar past relationship cases. This comparison generates advice that is best suited to the user's emotional state. The advice is adjusted according to the user's emotions, making it more empathetic and actionable.

[0547] The server also creates a virtual romance simulation that takes the user's emotional state into account. This simulation recreates specific emotional situations the user might encounter, providing an opportunity for the user to practice how to deal with those situations. The simulation provides multiple choices and response patterns, allowing the user to gain virtual experiences based on them.

[0548] For example, if a user inputs "I haven't been communicating well with my partner lately," the emotion engine identifies emotions such as anxiety and worry associated with this situation. Based on this, the server recommends "creating another opportunity for calm dialogue" and guides the user on how to proceed with the conversation. Furthermore, it runs simulations to train the user to make appropriate choices.

[0549] Thus, this system provides appropriate advice and a practice environment that takes the user's emotional state into consideration, functioning as a comprehensive tool to support practical application in realistic situations.

[0550] The following describes the processing flow.

[0551] Step 1:

[0552] Users use a communication device to input their relationship-related challenges and situations in text format. It is recommended that the content include descriptions of emotions and specific events.

[0553] Step 2:

[0554] The terminal packets the entered text information and sends it to the server. During this process, the communication is encrypted to protect the user's privacy.

[0555] Step 3:

[0556] The server passes the received text data to the emotion engine. The emotion engine uses the latest natural language processing technology to identify the emotions contained in the text and analyze the user's emotional state.

[0557] Step 4:

[0558] The emotion engine classifies the user's emotions and identifies their intensity and type (e.g., joy, anxiety, anger). This clarifies the user's emotional state.

[0559] Step 5:

[0560] The server compares the analyzed sentiment information with a database of similar past cases. This comparison allows the server to select appropriate advice based on the user's situation.

[0561] Step 6:

[0562] The server generates advice tailored to the user's emotional state and situation, and sends it to the user's communication terminal. This advice includes specific action suggestions and guidance on mindset.

[0563] Step 7:

[0564] The server then prepares a virtual romance simulation tailored to the user's emotional state. The simulation consists of scenarios based on real-life situations.

[0565] Step 8:

[0566] Users initiate a simulation on their communication terminal and choose their responses to the presented situations and options. This allows them to hone their skills in handling romantic situations through a rehearsal process.

[0567] Step 9:

[0568] Once the simulation is complete, the server evaluates the user's choices and reactions. It then uses an emotion engine to re-evaluate how the choices impact emotions.

[0569] Step 10:

[0570] The server provides feedback to the user based on the overall analysis results. This feedback includes areas for improvement and points to consider when making future choices.

[0571] Step 11:

[0572] Users will use the feedback provided to improve their behavior in real-life romantic relationships and utilize this system to build better relationships.

[0573] (Example 2)

[0574] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0575] In interpersonal relationships, it is not easy for users to understand their own emotional state and take appropriate actions based on it. Furthermore, opportunities to practice how to deal with real-world situations are limited. Therefore, there is a need for a comprehensive system that enables users to accurately grasp their emotions and learn practical responses.

[0576] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0577] In this invention, the server includes means for receiving information related to human relationships that a user inputs using a computing device, means for analyzing the received information and analyzing the emotional state, and means for generating empathetic advice by comparing the analysis results with similar past cases. This enables the user to appropriately understand their own emotional state and acquire practical responses accordingly.

[0578] A "computer" is an electronic device used for inputting and processing information, and is used by users when they input their own information.

[0579] "Information related to interpersonal relationships" refers to text data entered by users about their own emotions and circumstances, and includes various events that occur in their relationships with others.

[0580] "Means of receiving" refers to the process and equipment by which a server retrieves data transmitted from a computing device, and is responsible for the transmission and initial processing of information.

[0581] "Analysis means" refers to processes and devices for evaluating and classifying received information, and in particular includes technologies for analyzing emotional states and feelings.

[0582] "Means for generating empathetic advice" refers to a process that forms appropriate suggestions and advice tailored to the user's feelings based on analysis results, providing information that serves as a guide when users take specific actions.

[0583] A "virtual relationship simulation" is a simulated environment designed for users to practice coping with specific emotional situations, allowing them to explore different options and responses.

[0584] "A means of providing opportunities for growth" refers to a process of evaluating the results obtained through simulations and providing feedback to help users improve their skills and response methods.

[0585] This invention uses a system with emotion analysis capabilities to understand the user's emotional state based on information related to human relationships input by the user using a computing device, and provides empathetic advice and virtual human relationship simulations.

[0586] The user uses a computer to input text about their relationships. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's state of mind. The terminal transmits this user-inputted information to the server using a secure communication protocol (e.g., HTTPS).

[0587] The server analyzes the received data using an emotion analysis engine. This engine uses natural language processing techniques to analyze the user's text data, identifying emotional nuances and tones, and classifying the user's emotional state. This analysis process utilizes a generative AI model to perform real-time emotion assessment.

[0588] Based on the analysis results, the server compares the data with similar past relationship cases and generates empathetic advice best suited to the user's emotional state. This advice is tailored to the user's emotions and provides concrete, actionable suggestions. Furthermore, the server creates virtual relationship simulations that take the user's emotional state into account, simulating specific emotional situations and providing the user with an opportunity to practice how to deal with those situations. Multiple choices and response patterns are available, allowing the user to gain virtual experience based on them.

[0589] For example, if a user inputs "I haven't been communicating well with my family lately," the server uses an emotion analysis engine to identify emotions such as anxiety and loneliness. Based on the results, the server recommends "setting aside time for dialogue" and provides specific instructions on how to proceed. It also runs a simulation to help the user make effective choices.

[0590] An example of an input prompt for a generative AI model is: "User input: Communication at home has been difficult recently. Use the sentiment analysis engine to analyze the situation and show how to provide empathetic advice and simulations to the user."

[0591] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0592] Step 1:

[0593] The user uses a computing device to input text information about interpersonal relationships. This input consists of sentences that specifically describe emotions and situations. The terminal collects this information, converts it into a data format, and then sends it to the server for the next analysis process.

[0594] Step 2:

[0595] The server receives text information sent from the terminal. The input data consists of raw text messages from the user. Based on this data, the server passes it to an emotion analysis engine, which uses natural language processing techniques to identify emotional nuances and tones and classify the emotional state. The output is a numerical or categorized representation of the user's emotional state.

[0596] Step 3:

[0597] The server, upon receiving the output from the emotion analysis engine, compares it to similar past cases. Specifically, the server searches a large database of past cases to identify patterns similar to the input emotional state. The output of this comparison process is a list of suggested advice and past successful actions.

[0598] Step 4:

[0599] The server generates personalized advice for the user based on matching results with similar cases. This advice generation process involves crafting text that empathizes with the user's feelings and includes specific, helpful advice. The output of this step is the refined advice text provided to the user.

[0600] Step 5:

[0601] The server then creates a virtual relationship simulation. Based on the generated advice, it constructs scenarios that simulate specific emotional situations, providing multiple choices and response patterns. The output of this simulation is provided to the user as a virtual experience that they can try.

[0602] Step 6:

[0603] The server sends the advice and simulation results to the terminal. The input includes the output from each step taken so far. The terminal displays this information in a user interface, providing actionable information for the user. The final output is specific advice and a simulation scenario presented on the screen.

[0604] (Application Example 2)

[0605] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0606] In daily life, it is a challenging task for users to effectively understand and manage their emotions in personal conversations and relationship maintenance. To resolve problems arising from differences in emotional expression and lack of communication, support is needed to enable users to objectively evaluate their own emotions and take appropriate action. This invention aims to solve these problems.

[0607] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0608] In this invention, the server includes means for receiving information related to personal relationships entered by the user using an information processing device, means for analyzing the received information and analyzing its state, and means for creating a virtual relationship simulation and presenting it to the user in an executable form. This allows the user to understand their own emotional state and receive simulations and advice for dealing with it.

[0609] An "information processing device" is an electronic device used by users to input information and to receive, transmit, and analyze data.

[0610] "Information related to personal relationships" refers to data concerning personal relationships, such as the user's emotions, circumstances, and conversation content.

[0611] "Analysis means" refers to a process or mechanism for analyzing received information and evaluating the user's emotional state and situation.

[0612] A "virtual relationship simulation" is a device or program designed to simulate real-world situations for the purpose of providing feedback and training to users.

[0613] "Emotion analysis" is a technology that infers a user's emotions from their input information and derives an appropriate response.

[0614] "Means of generating advice" refers to processes or systems that provide users with appropriate advice or guidelines based on analysis results.

[0615] A "response pattern" refers to a system's standardized response to a user's choices or reactions, and is part of the options presented within the simulation.

[0616] The system realizing this invention centers around an analysis device that receives and analyzes personal relationship-related information input by the user using an information processing device. The analysis device analyzes the input data using natural language processing technology to infer the user's emotional state. This utilizes an emotion analysis model built in Python and libraries such as TensorFlow and NLTK. Based on the data obtained from the emotion analysis, the server generates appropriate advice and a virtual relationship simulation. This simulation uses simulation development platforms such as Unity or Unreal Engine to present the user with choices and response patterns.

[0617] Furthermore, the server provides users with advice based on the analysis results, supporting them in deciding what to do next. For example, if a user inputs, "I haven't been able to communicate well with my partner lately," the server will identify the emotion "anxiety" through emotion analysis and generate advice to create an opportunity for calm dialogue. In this way, the server provides an environment where users can deeply understand their own emotional state and deal with it appropriately.

[0618] As a concrete example, a prompt sentence for a generative AI model could be, "I feel like I haven't been communicating well with my partner lately. What should I do?" This prompt allows the system to analyze the user's intent and construct an appropriate response or simulation.

[0619] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0620] Step 1:

[0621] The user inputs information about their personal relationships through an information processing terminal. This information is text data that expresses the specific situation and emotions the user is experiencing. The terminal prepares this input information as data to be sent to the server and then transmits it.

[0622] Step 2:

[0623] The server analyzes the text data it receives. In this process, the server uses natural language processing techniques to tokenize the text and then uses a Python sentiment analysis model to analyze the user's emotional state. For example, if the input is "I haven't been able to communicate well with my partner lately," the server will identify emotions such as "anxiety" and "worry" and output the results as data.

[0624] Step 3:

[0625] Based on the sentiment analysis results, the server compares the user's emotional state with similar past cases and generates appropriate advice. This involves calculating the similarity between the user's emotional state and a database of past cases, and selecting cases with a high degree of similarity. Based on the selected cases, the user receives specific advice such as "create an opportunity for calm dialogue."

[0626] Step 4:

[0627] The server generates and provides a virtual relationship simulation to the user. This simulation is built using a simulation development platform and is in a format that allows the user to experience choices and response patterns for each scenario. Different relationship scenarios are presented based on user input, and the user's responses to them are recorded as data.

[0628] Step 5:

[0629] The server analyzes the user's choices and simulation results, providing feedback. This feedback includes specific areas for improvement and guidance on next steps based on the user's choices. The analysis uses technology that compares simulation results with initial sentiment analysis results to generate optimal feedback. This allows the user to improve their coping strategies and better prepare for future situations.

[0630] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0631] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0632] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0633] [Fourth Embodiment]

[0634] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0635] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0636] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0637] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0638] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0639] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0640] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0641] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0642] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0643] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0644] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0645] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0646] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0647] The system of this invention improves the success rate of romantic relationships by allowing users to input information related to romance via a communication terminal and providing effective advice and virtual simulations based on that information.

[0648] Users use their communication devices to input text about their current relationship status and details about their partner. The device then sends this information to the server.

[0649] The server analyzes the received information. This analysis includes a process that uses natural language processing techniques to extract sentiment, topic, and context from the input text. Based on the analyzed information, the server compares it with past databases to generate advice that is most appropriate to the user's current situation.

[0650] The generated advice is sent to the user's communication terminal and provided as suggestions for effective actions and guidance for the next steps.

[0651] Furthermore, the server generates a virtual dating simulation based on the analysis results. This simulation meticulously imitates situations such as confessions and dates, providing users with a platform for practice. By repeatedly experiencing situations close to real life on the system, users can improve their ability to cope in real life.

[0652] For example, if a user enters "I feel like my partner isn't interested in me," the server analyzes the information and, based on strategies that have worked in similar cases in the past, offers advice such as "Expand on a shared hobby on your next date." At the same time, it provides a simulation scenario to try out that advice, creating an environment where the user can practice practically.

[0653] After the simulation, the server analyzes the results and provides feedback to the user. This feedback allows the user to understand areas for improvement and apply them to future attempts.

[0654] Thus, this system provides a comprehensive means to support users in their romantic endeavors and prepare them for taking concrete action.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] Users input information and questions about their current romantic situation in text format via a communication terminal. The terminal converts this input information into packets and sends them to the server.

[0658] Step 2:

[0659] The server analyzes the text data received from the terminal. Natural language processing techniques are used for the analysis, identifying and extracting sentiment, topic, and context. This process is designed to accurately understand the user's intent.

[0660] Step 3:

[0661] The server compares the analyzed data with a database of past cases. By referring to similar cases, it derives advice with a high probability of success. In this process, it applies a predictive model using machine learning algorithms.

[0662] Step 4:

[0663] The server sends the generated advice to the user's communication terminal. The terminal displays this advice to the user, providing specific action guidelines.

[0664] Step 5:

[0665] Based on the analysis results, the server generates a virtual simulation that mimics a specific romantic scene. This simulation incorporates multiple reaction patterns, allowing the user to experience each of the choices.

[0666] Step 6:

[0667] Users participate in the simulation on a communication terminal, choosing responses and actions based on the presented options and situations. The terminal continuously transmits the user's choices to the server.

[0668] Step 7:

[0669] The server analyzes the user's choices and reactions in real time during the simulation. Based on the analysis results, it repeatedly presents the next options and reactions.

[0670] Step 8:

[0671] After the simulation is complete, the server comprehensively evaluates the user's behavior and generates feedback. This feedback highlights areas for improvement and strengths, along with specific examples.

[0672] Step 9:

[0673] The server sends feedback to the user's communication device, which then displays it visually to the user. The user can use this feedback to improve their next actions and increase their chances of success.

[0674] (Example 1)

[0675] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] Traditional interpersonal relationship support systems have faced challenges in providing effective advice and concrete simulations tailored to each user's individual situation. In particular, there is a need to generate advice in real time that is appropriate to the user's emotions and specific context, and to provide a practical practice environment using virtual simulations. Solving these problems is crucial for supporting users' success in interpersonal relationships.

[0677] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0678] In this invention, the server includes means for receiving interpersonal relationship-related data input using an information processing device; means for analyzing the received data and evaluating the situation; means for generating appropriate guidelines by comparing the analysis results with similar past cases; means for constructing a virtual situation simulation and presenting it to the user in an executable format via the information processing device; and means for evaluating the results of the simulation and providing the user with feedback indicating areas for improvement. This makes it possible to provide advice and simulations tailored to the user's individual situation and improve the user's interpersonal skills.

[0679] An "information processing device" refers to a computer device used for inputting, analyzing, and outputting data.

[0680] "Interpersonal relationships" is a concept that refers to communication, interaction, and relationships between people.

[0681] "Data" refers to a collection of information, including strings of characters, numbers, and shapes used for analysis and processing.

[0682] "Means of receiving" refers to components that have the function of taking in information transmitted from an external source into the device.

[0683] "Analysis" is the process of examining received data in detail and extracting hidden elements and patterns.

[0684] "Evaluative analytical tools" refer to components that have the function of analyzing data and judging the state or trend based on the results.

[0685] "Means for generating guidelines" refers to components that have the function of constructing specific advice and directions for action based on the analysis results.

[0686] "Simulation" refers to the process of imitation of real-world events in a virtual environment and providing users with that experience.

[0687] "Feedback" refers to information that provides evaluations and suggestions for improvement regarding performance and behavior.

[0688] "User" refers to an individual or organization that operates a system through an information processing device and inputs or receives information.

[0689] The system of this invention is designed to provide support related to interpersonal relationships and operates primarily through information exchange and processing between users, terminals, and servers.

[0690] The user uses a terminal, which is an information processing device, to input detailed data about their interpersonal relationships. The user's input data includes their current interpersonal situation, emotions, and information about the other person. For example, the user might input data such as, "There was little talk about our shared hobbies in recent conversations."

[0691] Next, the device sends this input data to the server via a secure communication protocol (e.g., HTTPS). The server analyzes the received data using natural language processing techniques. The analysis utilizes sentiment analysis APIs and topic modeling to extract emotional nuances and key topics from the user's text.

[0692] The server compares the analysis results with similar past databases and generates appropriate guidelines for each individual user. It uses a generative AI model to derive specific advice and strategies. For example, the server might suggest, "In the next conversation, delve deeper into your shared hobbies."

[0693] Furthermore, the server constructs virtual situational simulations. This allows users to practice within a virtual environment and experience practical dialogue scenarios. The terminal then presents these simulations to the user in an executable format.

[0694] After the simulation, the server evaluates the results and provides feedback to the user. It identifies specific areas for improvement so that the user can use this information in future interpersonal situations.

[0695] A concrete example of a prompt message would be a user entering a request such as, "I want to find topics in this conversation that interest me."

[0696] This system provides users with a comprehensive and effective means to improve their interpersonal skills.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] The user inputs data related to interpersonal relationships into a terminal, which is an information processing device. The input data includes specific worries, questions, and feelings about the current situation. For example, the user might input, "Lately, I've been having trouble keeping conversations going with my friends." This data from the user is stored in the terminal as initial input.

[0700] Step 2:

[0701] The terminal sends the data entered by the user to the server via a security protocol. The data sent is the entire user input and is delivered to the server in text format. At this stage, the data transmission takes place and is completed.

[0702] Step 3:

[0703] The server analyzes the received text data. First, it uses natural language processing techniques to extract emotions and topics from the data. Specifically, it uses an emotion analysis API to quantify the emotional tone of the input and passes the results to a topic modeling algorithm. The output of this analysis generates an emotion score and related topics.

[0704] Step 4:

[0705] The server compares the analysis results with past database data and generates appropriate guidance for the user. This process uses a generative AI model to construct advice based on successful case studies. For example, it might generate advice such as, "Try finding a common hobby." This generated advice is then output from the server.

[0706] Step 5:

[0707] The server prepares a virtual situation simulation. Based on the analysis results, it drives the life simulator and assembles a virtual scenario that the user can practice. The simulation scenario reproduces multiple scenes to help the user understand the flow of dialogue and is prepared in a way that allows user participation.

[0708] Step 6:

[0709] The system provides the user with generated guidelines and a simulation via a terminal. The terminal notifies the user and prompts them to start the simulation. The user can experience the virtual simulation by following the guidelines and receive feedback.

[0710] Step 7:

[0711] The server evaluates the user's simulation results and generates feedback. The evaluation is performed by analyzing the user's behavior patterns and identifying specific areas for improvement. Based on these results, it generates feedback on improvement suggestions and next steps, which are then sent from the server to the terminal.

[0712] (Application Example 1)

[0713] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0714] While users seek accurate advice and virtual practice opportunities for relationship and interpersonal issues, there is a need to address the challenge of a lack of systems that adequately mimic real-world situations and provide practical feedback.

[0715] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0716] In this invention, the server includes means for receiving relationship-related information input by the user using an information processing device; means for analyzing the received information and performing sentiment analysis; means for generating appropriate responses by comparing the analysis results with past data; means for creating a virtual situation simulation and providing it to the user in an executable form; means for analyzing the results of the simulation and providing the user with improvement suggestions; and means for providing feedback to the user through actual dialogue. This enables the user to improve their success rate in romance and relationships through practical practice.

[0717] An "information processing device" is an electronic device that has the function of inputting, processing, and outputting data.

[0718] "Relationship-related information" refers to detailed data related to a user's personal relationships and romantic life.

[0719] "Means of receiving" refers to functions for acquiring data from external sources, primarily utilizing communication functions.

[0720] "Analysis tools" refer to functions that analyze input data and perform a process to understand its meaning and structure.

[0721] "Sentiment analysis" is a technique that identifies, classifies, or evaluates emotional states based on input information.

[0722] "Means for generating appropriate responses" refers to a function that creates optimal actions and advice based on analysis results.

[0723] "Virtual situation simulation" is a technology that creates a digital environment that mimics real-world situations, allowing users to have virtual experiences within that environment.

[0724] "Means of providing" refers to methods and devices for presenting generated information or results to the user.

[0725] "Means of providing improvement suggestions" refers to a function that presents users with recommendations for improvement based on the results of analysis and simulation.

[0726] "Means of providing feedback" refers to a process of giving evaluations and comments on user actions and reactions to guide the next steps.

[0727] In this system, users input relationship-related information in text format using their own information processing device. The terminal then transmits this information to the server. The server has a communication module for receiving the input information and retrieves data based on this.

[0728] The server employs software that uses natural language processing technology as its analysis method. Specifically, it utilizes the Google Cloud Speech-to-Text API to convert speech input into text data and analyze the user's utterance as text information. Sentiment analysis is then performed on the analyzed information to understand the user's emotional state and generate appropriate countermeasures.

[0729] The generated countermeasures are constructed by comparing them with past data using a generative AI model contained within the server. Leveraging the OpenAI model and using prompt statements, optimal advice is formulated for the user. Next, a virtual situation simulation is generated. This simulation mimics situations the user might actually experience, creating an environment for providing a realistic experience.

[0730] Users can receive these simulations through their terminals and practice real-world interactions and experiences within the system. Based on the simulation results, the server provides feedback to the user, suggesting specific improvements and next steps.

[0731] For example, if a user inputs "I've been finding recent dates boring," the server analyzes the user's emotions based on the given information and generates advice such as "suggesting a new activity." It then provides specific suggestions, such as "How about going to a cooking class together on the weekend?" Another example of a prompt is "The user is looking for new date ideas. Based on this information, what suggestions are possible?" This sentence is input into the AI ​​model to obtain an appropriate output.

[0732] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0733] Step 1:

[0734] The user uses an information processing device to input relationship-related information as text. The device then sends this text data to the server. The input data consists of specific details about the user's relationships with people.

[0735] Step 2:

[0736] The server first uses the Google Cloud Speech-to-Text API to convert the information received from the terminal into text data, if there is voice input. Here, the input is the voice entered by the user, and the output is a series of text converted from the voice information.

[0737] Step 3:

[0738] The server uses natural language processing techniques to perform sentiment analysis on text data. It extracts emotions from the input text data and processes the data to identify the user's psychological state. The output is an evaluation value related to the emotions in the text.

[0739] Step 4:

[0740] The server uses a generative AI model to generate prompt messages based on sentiment analysis results and inputs them into the OpenAI model. The input here is the sentiment analysis results, and the output is user-optimized advice and countermeasures.

[0741] Step 5:

[0742] The server generates virtual situation simulations and constructs scenarios that users can experience in real-world situations. The input is generated advice, and the output is a virtual dating scenario or dialogue scene based on that advice.

[0743] Step 6:

[0744] The user receives a simulation provided via their device and interacts with it. The user's actions within the simulation are fed back to the server.

[0745] Step 7:

[0746] The server re-analyzes the simulation results and generates improvement suggestions and feedback for the user. The input is the user's response data during the simulation, and the output is recommendations for the next action.

[0747] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0748] This invention is a system that uses an analysis system incorporating an emotion engine to sensitively grasp the user's emotional state based on love-related information entered by the user using a communication terminal, and provides appropriate advice and simulations.

[0749] The user uses a communication device to input text about their love life. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's feelings. The device then transmits this information to the server.

[0750] The server analyzes the received data using an emotion engine. This engine combines natural language processing techniques with the user's text data to infer the user's emotional state in real time. The emotion engine identifies emotional nuances and tones within the text and classifies the user's emotional state.

[0751] Based on the information obtained by the emotion engine, the server uses analytical tools to compare the user's situation with similar past relationship cases. This comparison generates advice that is best suited to the user's emotional state. The advice is adjusted according to the user's emotions, making it more empathetic and actionable.

[0752] The server also creates a virtual romance simulation that takes the user's emotional state into account. This simulation recreates specific emotional situations the user might encounter, providing an opportunity for the user to practice how to deal with those situations. The simulation provides multiple choices and response patterns, allowing the user to gain virtual experiences based on them.

[0753] For example, if a user inputs "I haven't been communicating well with my partner lately," the emotion engine identifies emotions such as anxiety and worry associated with this situation. Based on this, the server recommends "creating another opportunity for calm dialogue" and guides the user on how to proceed with the conversation. Furthermore, it runs simulations to train the user to make appropriate choices.

[0754] Thus, this system provides appropriate advice and a practice environment that takes the user's emotional state into consideration, functioning as a comprehensive tool to support practical application in realistic situations.

[0755] The following describes the processing flow.

[0756] Step 1:

[0757] Users use a communication device to input their relationship-related challenges and situations in text format. It is recommended that the content include descriptions of emotions and specific events.

[0758] Step 2:

[0759] The terminal packets the entered text information and sends it to the server. During this process, the communication is encrypted to protect the user's privacy.

[0760] Step 3:

[0761] The server passes the received text data to the emotion engine. The emotion engine uses the latest natural language processing technology to identify the emotions contained in the text and analyze the user's emotional state.

[0762] Step 4:

[0763] The emotion engine classifies the user's emotions and identifies their intensity and type (e.g., joy, anxiety, anger). This clarifies the user's emotional state.

[0764] Step 5:

[0765] The server compares the analyzed sentiment information with a database of similar past cases. This comparison allows the server to select appropriate advice based on the user's situation.

[0766] Step 6:

[0767] The server generates advice tailored to the user's emotional state and situation, and sends it to the user's communication terminal. This advice includes specific action suggestions and guidance on mindset.

[0768] Step 7:

[0769] The server then prepares a virtual romance simulation tailored to the user's emotional state. The simulation consists of scenarios based on real-life situations.

[0770] Step 8:

[0771] Users initiate a simulation on their communication terminal and choose their responses to the presented situations and options. This allows them to hone their skills in handling romantic situations through a rehearsal process.

[0772] Step 9:

[0773] Once the simulation is complete, the server evaluates the user's choices and reactions. It then uses an emotion engine to re-evaluate how the choices impact emotions.

[0774] Step 10:

[0775] The server provides feedback to the user based on the overall analysis results. This feedback includes areas for improvement and points to consider when making future choices.

[0776] Step 11:

[0777] Users will use the feedback provided to improve their behavior in real-life romantic relationships and utilize this system to build better relationships.

[0778] (Example 2)

[0779] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0780] In interpersonal relationships, it is not easy for users to understand their own emotional state and take appropriate actions based on it. Furthermore, opportunities to practice how to deal with real-world situations are limited. Therefore, there is a need for a comprehensive system that enables users to accurately grasp their emotions and learn practical responses.

[0781] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0782] In this invention, the server includes means for receiving information related to human relationships that a user inputs using a computing device, means for analyzing the received information and analyzing the emotional state, and means for generating empathetic advice by comparing the analysis results with similar past cases. This enables the user to appropriately understand their own emotional state and acquire practical responses accordingly.

[0783] A "computer" is an electronic device used for inputting and processing information, and is used by users when they input their own information.

[0784] "Information related to interpersonal relationships" refers to text data entered by users about their own emotions and circumstances, and includes various events that occur in their relationships with others.

[0785] "Means of receiving" refers to the process and equipment by which a server retrieves data transmitted from a computing device, and is responsible for the transmission and initial processing of information.

[0786] "Analysis means" refers to processes and devices for evaluating and classifying received information, and in particular includes technologies for analyzing emotional states and feelings.

[0787] "Means for generating empathetic advice" refers to a process that forms appropriate suggestions and advice tailored to the user's feelings based on analysis results, providing information that serves as a guide when users take specific actions.

[0788] A "virtual relationship simulation" is a simulated environment designed for users to practice coping with specific emotional situations, allowing them to explore different options and responses.

[0789] "A means of providing opportunities for growth" refers to a process of evaluating the results obtained through simulations and providing feedback to help users improve their skills and response methods.

[0790] This invention uses a system with emotion analysis capabilities to understand the user's emotional state based on information related to human relationships input by the user using a computing device, and provides empathetic advice and virtual human relationship simulations.

[0791] The user uses a computer to input text about their relationships. This text includes specific situational descriptions, questions, and emotional expressions, reflecting the user's state of mind. The terminal transmits this user-inputted information to the server using a secure communication protocol (e.g., HTTPS).

[0792] The server analyzes the received data using an emotion analysis engine. This engine uses natural language processing techniques to analyze the user's text data, identifying emotional nuances and tones, and classifying the user's emotional state. This analysis process utilizes a generative AI model to perform real-time emotion assessment.

[0793] Based on the analysis results, the server compares the data with similar past relationship cases and generates empathetic advice best suited to the user's emotional state. This advice is tailored to the user's emotions and provides concrete, actionable suggestions. Furthermore, the server creates virtual relationship simulations that take the user's emotional state into account, simulating specific emotional situations and providing the user with an opportunity to practice how to deal with those situations. Multiple choices and response patterns are available, allowing the user to gain virtual experience based on them.

[0794] For example, if a user inputs "I haven't been communicating well with my family lately," the server uses an emotion analysis engine to identify emotions such as anxiety and loneliness. Based on the results, the server recommends "setting aside time for dialogue" and provides specific instructions on how to proceed. It also runs a simulation to help the user make effective choices.

[0795] An example of an input prompt for a generative AI model is: "User input: Communication at home has been difficult recently. Use the sentiment analysis engine to analyze the situation and show how to provide empathetic advice and simulations to the user."

[0796] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0797] Step 1:

[0798] The user uses a computing device to input text information about interpersonal relationships. This input consists of sentences that specifically describe emotions and situations. The terminal collects this information, converts it into a data format, and then sends it to the server for the next analysis process.

[0799] Step 2:

[0800] The server receives text information sent from the terminal. The input data consists of raw text messages from the user. Based on this data, the server passes it to an emotion analysis engine, which uses natural language processing techniques to identify emotional nuances and tones and classify the emotional state. The output is a numerical or categorized representation of the user's emotional state.

[0801] Step 3:

[0802] The server, upon receiving the output from the emotion analysis engine, compares it to similar past cases. Specifically, the server searches a large database of past cases to identify patterns similar to the input emotional state. The output of this comparison process is a list of suggested advice and past successful actions.

[0803] Step 4:

[0804] The server generates personalized advice for the user based on matching results with similar cases. This advice generation process involves crafting text that empathizes with the user's feelings and includes specific, helpful advice. The output of this step is the refined advice text provided to the user.

[0805] Step 5:

[0806] The server then creates a virtual relationship simulation. Based on the generated advice, it constructs scenarios that simulate specific emotional situations, providing multiple choices and response patterns. The output of this simulation is provided to the user as a virtual experience that they can try.

[0807] Step 6:

[0808] The server sends the advice and simulation results to the terminal. The input includes the output from each step taken so far. The terminal displays this information in a user interface, providing actionable information for the user. The final output is specific advice and a simulation scenario presented on the screen.

[0809] (Application Example 2)

[0810] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0811] In daily life, it is a challenging task for users to effectively understand and manage their emotions in personal conversations and relationship maintenance. To resolve problems arising from differences in emotional expression and lack of communication, support is needed to enable users to objectively evaluate their own emotions and take appropriate action. This invention aims to solve these problems.

[0812] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0813] In this invention, the server includes means for receiving information related to personal relationships entered by the user using an information processing device, means for analyzing the received information and analyzing its state, and means for creating a virtual relationship simulation and presenting it to the user in an executable form. This allows the user to understand their own emotional state and receive simulations and advice for dealing with it.

[0814] An "information processing device" is an electronic device used by users to input information and to receive, transmit, and analyze data.

[0815] "Information related to personal relationships" refers to data concerning personal relationships, such as the user's emotions, circumstances, and conversation content.

[0816] "Analysis means" refers to a process or mechanism for analyzing received information and evaluating the user's emotional state and situation.

[0817] A "virtual relationship simulation" is a device or program designed to simulate real-world situations for the purpose of providing feedback and training to users.

[0818] "Emotion analysis" is a technology that infers a user's emotions from their input information and derives an appropriate response.

[0819] "Means of generating advice" refers to processes or systems that provide users with appropriate advice or guidelines based on analysis results.

[0820] A "response pattern" refers to a system's standardized response to a user's choices or reactions, and is part of the options presented within the simulation.

[0821] The system realizing this invention centers around an analysis device that receives and analyzes personal relationship-related information input by the user using an information processing device. The analysis device analyzes the input data using natural language processing technology to infer the user's emotional state. This utilizes an emotion analysis model built in Python and libraries such as TensorFlow and NLTK. Based on the data obtained from the emotion analysis, the server generates appropriate advice and a virtual relationship simulation. This simulation uses simulation development platforms such as Unity or Unreal Engine to present the user with choices and response patterns.

[0822] Furthermore, the server provides users with advice based on the analysis results, supporting them in deciding what to do next. For example, if a user inputs, "I haven't been able to communicate well with my partner lately," the server will identify the emotion "anxiety" through emotion analysis and generate advice to create an opportunity for calm dialogue. In this way, the server provides an environment where users can deeply understand their own emotional state and deal with it appropriately.

[0823] As a concrete example, a prompt sentence for a generative AI model could be, "I feel like I haven't been communicating well with my partner lately. What should I do?" This prompt allows the system to analyze the user's intent and construct an appropriate response or simulation.

[0824] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0825] Step 1:

[0826] The user inputs information about their personal relationships through an information processing terminal. This information is text data that expresses the specific situation and emotions the user is experiencing. The terminal prepares this input information as data to be sent to the server and then transmits it.

[0827] Step 2:

[0828] The server analyzes the text data it receives. In this process, the server uses natural language processing techniques to tokenize the text and then uses a Python sentiment analysis model to analyze the user's emotional state. For example, if the input is "I haven't been able to communicate well with my partner lately," the server will identify emotions such as "anxiety" and "worry" and output the results as data.

[0829] Step 3:

[0830] Based on the sentiment analysis results, the server compares the user's emotional state with similar past cases and generates appropriate advice. This involves calculating the similarity between the user's emotional state and a database of past cases, and selecting cases with a high degree of similarity. Based on the selected cases, the user receives specific advice such as "create an opportunity for calm dialogue."

[0831] Step 4:

[0832] The server generates and provides a virtual relationship simulation to the user. This simulation is built using a simulation development platform and is in a format that allows the user to experience choices and response patterns for each scenario. Different relationship scenarios are presented based on user input, and the user's responses to them are recorded as data.

[0833] Step 5:

[0834] The server analyzes the user's choices and simulation results, providing feedback. This feedback includes specific areas for improvement and guidance on next steps based on the user's choices. The analysis uses technology that compares simulation results with initial sentiment analysis results to generate optimal feedback. This allows the user to improve their coping strategies and better prepare for future situations.

[0835] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0836] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0837] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0838] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0839] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0840] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0841] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0842] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0843] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0844] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0845] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0846] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0847] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0848] 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.

[0849] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0850] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0851] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0852] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0853] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0854] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0855] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0856] The following is further disclosed regarding the embodiments described above.

[0857] (Claim 1)

[0858] A means of receiving love-related information entered by a user using a communication terminal,

[0859] An analysis means for analyzing the received information and analyzing the situation,

[0860] A means for generating appropriate advice by comparing the analysis results with similar past cases,

[0861] A means for creating a virtual romance simulation and presenting it to the user in an executable format,

[0862] A means for analyzing the results of the simulation and providing feedback to the user,

[0863] A system that includes this.

[0864] (Claim 2)

[0865] The system according to claim 1, wherein the analysis means uses natural language processing technology to classify the user's input information into emotion and situation.

[0866] (Claim 3)

[0867] The system according to claim 1, wherein the simulation means generates multiple reaction patterns under a virtual situation and presents the user with options for the next step.

[0868] "Example 1"

[0869] (Claim 1)

[0870] A means for receiving interpersonal relationship-related data input using an information processing device,

[0871] An analysis means for analyzing the received data and evaluating the situation,

[0872] Based on the aforementioned analysis results, a means for generating appropriate guidelines by comparing them with similar past cases,

[0873] A means for constructing a virtual situation simulation and presenting it to the user in an executable format via the information processing device,

[0874] A means for evaluating the results of the simulation and providing the user with feedback indicating areas for improvement,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, wherein the analysis means subdivides the user input data into emotions and situations using natural language processing technology.

[0878] (Claim 3)

[0879] The system according to claim 1, wherein the simulation means generates multiple response patterns in a virtual environment and presents the user with an option to select next.

[0880] "Application Example 1"

[0881] (Claim 1)

[0882] A means for receiving relationship-related information input by a user using an information processing device,

[0883] An analytical means for analyzing the received information and performing sentiment analysis,

[0884] Based on the aforementioned analysis results, a means for generating appropriate responses by comparing them with past data,

[0885] A means for creating a virtual situation simulation and providing it to the user in an executable format,

[0886] A means for analyzing the results of the simulation and providing improvement suggestions to the user,

[0887] A means of providing feedback to the aforementioned user through actual dialogue,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, wherein the analysis means classifies the input information from the user using language processing technology.

[0891] (Claim 3)

[0892] The system according to claim 1, wherein the simulation means generates a plurality of response patterns in a virtual environment and presents the user with a choice of actions.

[0893] "Example 2 of combining an emotion engine"

[0894] (Claim 1)

[0895] A means of receiving information related to human relationships that a user inputs using a computer,

[0896] An analysis means that analyzes the received information and analyzes the emotional state,

[0897] Based on the aforementioned analysis results, a means for generating empathetic advice by comparing it with similar past cases,

[0898] A means for creating a virtual human relationship simulation and presenting it to the user in an executable format,

[0899] A means for analyzing the results of the simulation and providing the user with opportunities for growth,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, wherein the analysis means classifies the user input information into emotions and feelings using automatic language processing technology.

[0903] (Claim 3)

[0904] The system according to claim 1, wherein the simulation means generates multiple response patterns under a virtual situation and presents the user with options for the next step.

[0905] "Application example 2 when combining with an emotional engine"

[0906] (Claim 1)

[0907] A means for receiving information related to personal relationships that a user inputs using an information processing device,

[0908] An analysis means for analyzing the received information and analyzing the state,

[0909] A means for generating appropriate advice by comparing the analysis results with similar past cases,

[0910] A means for creating a virtual relationship simulation and presenting it to the user in an executable format,

[0911] A means by which a computer analyzes the user's voice or text input, analyzes their emotions, and presents multiple options when generating advice,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, wherein the analysis means classifies the user input information into emotions and states using language processing technology.

[0915] (Claim 3)

[0916] The system according to claim 1, wherein the simulation means generates multiple response patterns under a virtual situation and presents the user with options for the next step. [Explanation of Symbols]

[0917] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving love-related information entered by a user using a communication terminal, An analysis means for analyzing the received information and analyzing the situation, A means for generating appropriate advice by comparing the analysis results with similar past cases, A means for creating a virtual romance simulation and presenting it to the user in an executable format, A means for analyzing the results of the simulation and providing feedback to the user, A system that includes this.

2. The system according to claim 1, wherein the analysis means classifies the user's input information into emotion and situation using natural language processing technology.

3. The system according to claim 1, wherein the simulation means generates multiple reaction patterns under a virtual situation and presents the user with options for the next step.

Images