system

Abstract

We provide the system. [Solution] An information processing device including a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment, A video display device for displaying the aforementioned negotiation scenario, A data processing device that records user actions and statements and generates detailed feedback using the generative model, An information provision device for providing the aforementioned feedback to the user and improving negotiation skills, Training methods to improve product promotion techniques through simulated negotiations with buyers, 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 method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Negotiation skills are very important abilities in business and daily life, but they are difficult to acquire except through experience in real situations. Also, in actual negotiation situations, failure leads to risks, so opportunities for safe and effective training involving practice are limited. Therefore, there is a need for an effective training means that allows users to practice negotiation skills in various scenarios without taking risks and learn improvement points through feedback.

Means for Solving the Problems

[0005] This invention provides a negotiation training system using a generative model and virtual or augmented reality technology. Specifically, it has a configuration in which a server, including a generative model, generates a virtual negotiation scenario and provides it to the user through a terminal. This allows the user to safely simulate a realistic negotiation experience. It also includes means for recording the user's actions and generating and providing detailed feedback, allowing the user to evaluate their own negotiation abilities and improve their skills. This system makes it possible to conduct practical negotiation training in various situations.

[0006] "Virtual reality" refers to a three-dimensional, artificial environment created using computer technology that feels as real as reality itself.

[0007] Augmented reality refers to the technology that overlays digital information onto the real world, or the resulting visual experience.

[0008] A "negotiation scenario" refers to a series of storylines that recreate a negotiation situation, including pre-defined circumstances, background, and the objectives and roles of the participants.

[0009] A "generative model" refers to an algorithm or program that has the ability to generate new content based on a large amount of data, and in this context, it is used to generate negotiation scenarios.

[0010] "Server means" refers to a combination of computer systems, hardware, and software used to provide specific functions in information processing.

[0011] "Terminal means" refers to devices that users use to connect to computer systems and networks to obtain information and perform operations.

[0012] "User behavior" refers to all activities performed by the user within a negotiation scenario, such as talking, negotiating, and responding.

[0013] "Feedback" refers to evaluation information provided to assess user behavior and indicate its strengths, weaknesses, and areas for improvement. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] 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.

[0018] 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.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] The negotiation training system of the present invention comprises a generative model, a server, a terminal, and a user interface, and is designed to enable users to effectively improve their negotiation skills in a virtual reality or augmented reality environment.

[0036] Server functions and operation

[0037] The server is the central component of this invention and is equipped with a generative model. This generative model considers user profiles and historical training data to generate realistic negotiation scenarios. Upon receiving a user request, the server dynamically creates an appropriate negotiation scenario and sends the data to the terminal. The server is also responsible for collecting and analyzing user behavior data and generating detailed feedback.

[0038] Device functions and operation

[0039] The device functions as a VR headset or AR device, rendering scenario data received from the server into a virtual or augmented reality environment. Through this device, the user participates in a virtual negotiation scene. The device also records the user's experience by transmitting their movements and statements to the server in real time.

[0040] User experience

[0041] Users attempt negotiation strategies in response to situations presented within the scenario. The system records user statements and actions in real time, using this data as the basis for later feedback. For example, when a user proposes a compromise during price negotiations, its validity and effectiveness are evaluated based on simulations.

[0042] Feedback and skill improvement

[0043] After the scenario ends, the server provides feedback using a generative model based on the user's behavioral data. This feedback includes points of success, strategies that need improvement, and advice for the next scenario. This feedback information is provided to the user via the terminal, allowing the user to continuously learn and improve their negotiation skills based on it.

[0044] Thus, the negotiation training system of the present invention provides an effective means of improving skills through diverse negotiation experiences without incurring risk. For example, a new business employee can practice contract negotiations with a virtual customer and prepare for negotiations in a real-world environment. This system goes beyond mere theoretical learning, creating an environment where users learn from experience and improve their practical abilities.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user launches the terminal and selects to start a training session. Based on the user's selection, the terminal will send a session request to the server. The request will include the user's skill level and the type of negotiation scenario they prefer.

[0048] Step 2:

[0049] Based on the received request, the server generates an appropriate negotiation scenario using a generative model. The generated scenario data includes the background of the negotiation and the characteristics of the other party, and this data is sent to the terminal.

[0050] Step 3:

[0051] The terminal receives scenario data sent from the server and renders it in a virtual or augmented reality environment. This prepares the user to experience negotiations in the virtual environment.

[0052] Step 4:

[0053] Users participate in a virtual environment provided through their terminal and negotiate according to a scenario. Their statements and actions during negotiations are recorded in real time.

[0054] Step 5:

[0055] The device sends user behavior data to the server. The server collects this data and uses it to analyze the behavior.

[0056] Step 6:

[0057] The server analyzes the collected user behavior data and generates feedback using a generative model. This feedback includes the user's negotiation strengths and areas for improvement.

[0058] Step 7:

[0059] The server sends the generated feedback to the terminal. The terminal displays this feedback to the user, providing it in a visually easy-to-understand format.

[0060] Step 8:

[0061] Users review feedback and use it to set their next learning goals to improve their negotiation skills. This enables continuous skill development.

[0062] (Example 1)

[0063] 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."

[0064] The challenge lies in providing concrete and practical training methods that effectively improve negotiation skills. In particular, there is a need for a system that allows learners to experience and learn through actual simulation environments, rather than relying solely on traditional theoretical learning.

[0065] 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.

[0066] In this invention, the server includes an information processing device means that incorporates a generation program for creating a negotiation experience in a virtual reality or augmented reality environment; an output device means for visualizing the negotiation experience; and means for collecting user behavior and statements and generating detailed improvement information using the generation program. This enables users to effectively improve their skills through actual dialogue and actions in various negotiation scenarios.

[0067] "Virtual reality" is a technology that uses computer technology to create a virtual environment that does not exist in reality, allowing users to interact within that environment.

[0068] Augmented reality is a technology that allows users to experience both real and virtual elements simultaneously by overlaying digital information onto the real environment.

[0069] An "information processing device" is a general term for devices and systems used to process data and generate or manage necessary information.

[0070] An "output device" is a device or system that presents data in a form that is understandable to humans, such as in the form of audio or video.

[0071] A "generator program" is a set of instructions or code that runs on a computer to create digital content or scenarios for a specific purpose.

[0072] "User" refers to an individual or group that seeks to improve their negotiation skills using this system.

[0073] "Improvement information" is a general term for feedback and advice given to improve skills based on the evaluation results of users' actions and statements.

[0074] This invention provides a training system for effectively improving negotiation skills in virtual reality and augmented reality environments, offering an innovative method that utilizes generative AI models.

[0075] The server functions as the core of this system, acting as an information processing device. Leveraging a generative AI model, it generates negotiation scenarios based on conditions specified by the user through prompt messages. The generative AI model generates scenarios based on a rich source of information, including historical data, ensuring they are appropriate to the user's skill level. The server also transmits these scenarios to terminals in real time via the network.

[0076] The terminal receives scenario data provided by the server and functions as an output device in a virtual reality and augmented reality environment. Specifically, it visualizes the scenario using VR headsets and AR devices, creating an environment where users can immerse themselves in the scenario and interact with it. Through this terminal, users can converse with characters in the scenario and test their actual negotiation skills.

[0077] Users experience negotiation scenarios through interactions in a virtual environment. For example, in a scenario where they negotiate the price of a new product, the user proposes a compromise to the other party. During this process, the user's actions and statements are transmitted in real time from the terminal to the server and stored.

[0078] A concrete example of a prompt message would be, "Generate a scenario in which the user negotiates the price of a new product. In this scenario, set the user as a rookie salesperson attempting their first negotiation." This allows the user to try different negotiation techniques within a realistic scenario.

[0079] Thus, the present invention provides a system that enables practical and efficient training for users to effectively improve their negotiation skills.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] The server receives a prompt from the user. The input includes the conditions of the negotiation scenario specified by the user. This input is analyzed and filtered for application to the generative AI model. As a result, the elements necessary for a detailed negotiation scenario are extracted.

[0083] Step 2:

[0084] The server generates negotiation scenarios using a generative AI model. The input information consists of user prompts and historical training data. The server combines this data to perform calculations and generate realistic negotiation scenarios. The output is negotiation scenario data appropriate to the user's skill level.

[0085] Step 3:

[0086] The server sends the generated negotiation scenario to the terminal. This scenario data is input to the terminal, which then uses it to render it in a virtual reality or augmented reality environment. The output is the negotiation scene presented to the user as a visualized 3D environment.

[0087] Step 4:

[0088] The user conducts negotiations in a virtual or augmented reality environment presented through the device. User input includes voice commands and gestures. The device captures these in real time and sends them to the server. As a result of this process, the user's behavior history is recorded as output data.

[0089] Step 5:

[0090] The server analyzes user behavior data. This process uses a generative AI model to generate detailed feedback based on recorded input data (user statements and actions). The output is feedback information provided to the user, including areas for improvement and effective strategies.

[0091] Step 6:

[0092] The server sends the generated feedback to the terminal. The terminal presents this to the user, providing information to help improve skills in subsequent scenarios. The user can use this feedback to try different strategies in the next negotiation scenario. The output is a learning-based improvement strategy.

[0093] (Application Example 1)

[0094] 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."

[0095] Traditional negotiation skills training has been limited to theoretical learning and has been insufficient in improving the practical negotiation skills of sales staff in physical stores. Furthermore, there has been a lack of systems that provide realistic negotiation scenarios and enable sales staff to improve their practical skills. Against this backdrop, there is a need for a means to effectively enhance sales staff's skills through simulated customer negotiations in a virtual environment.

[0096] 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.

[0097] In this invention, the server includes an information processing device that includes a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment, a video display device for displaying the negotiation scenarios, and a data processing device that records user actions and statements and generates detailed feedback. This makes it possible for salespeople to practically improve their product promotion techniques through negotiations with simulated buyers.

[0098] "Virtual reality" is a technology that provides a realistic experience within a computer-generated three-dimensional virtual environment.

[0099] Augmented reality is a technology that overlays computer-generated visual information onto images and information from the real world.

[0100] A "generative model" is an algorithm that automatically creates negotiation scenarios in a virtual environment based on user profiles and historical data.

[0101] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0102] A "video display device" is a device that displays images and provides visual information to the user, and includes displays and head-mounted displays.

[0103] A "data processing device" is a device that records user input data, performs analysis based on that data, and generates feedback.

[0104] A "simulated buyer" is a digital character generated by a computer within a virtual environment that behaves like a real customer.

[0105] "Product promotion techniques" refer to the skills that sellers use to propose products to customers and effectively communicate their appeal.

[0106] The server generates negotiation scenarios in a virtual or augmented reality environment using a generative model. The generative AI model within the server dynamically designs specific negotiation scenes, taking into account the user's skill level and past training data.

[0107] This system utilizes hardware such as VR headsets like the Oculus Quest 2 or smart glasses. Through these, users experience generated negotiation scenarios via video displays. Within these scenarios, users can interact with virtual buyers and hone their product promotion skills.

[0108] The device records the user's actions and statements in real time via sensors to a data processing unit, which then transmits the data to a server. The server analyzes the received data and generates detailed feedback based on the user's choices and strategies. This feedback is then sent back to the device to improve the user's negotiation skills.

[0109] As a concrete example, consider a scenario where a user proposes a smartphone to a customer in a virtual world. An example of a prompt might be, "Create a scenario in which you propose the optimal response based on the customer's reaction during price negotiations for a new product." Based on this prompt, the server generates a scenario, providing a platform where salespeople can practice under conditions similar to real-world store operations. This allows participants to effectively acquire negotiation skills that are closer to reality in a virtual space.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The server receives a request from the user. The request includes the user's skill level and training objectives as input. The server then sends a prompt to the generative AI model, initiating the generation of negotiation scenarios. The generative AI model designs a scenario tailored to the user's skills and outputs it as data.

[0113] Step 2:

[0114] The server sends the generated negotiation scenario to the terminal. The terminal renders the received scenario data into a virtual or augmented reality environment. The engine uses software such as Unity to realistically depict the virtual negotiation scene. In this process, the input is the negotiation scenario data, and the output is the virtual environment experienced by the user.

[0115] Step 3:

[0116] Users participate in virtual negotiation scenarios through their devices. This allows them to interact with a purchasing simulator and gain practical experience in improving their product promotion techniques. User actions and statements are recorded in real time by sensors. The input is user behavior data, which is sent to the server.

[0117] Step 4:

[0118] The server analyzes behavioral data submitted by the user and generates detailed feedback using a generative AI model. A data processing unit performs this task, evaluating the effectiveness and areas for improvement of the user's negotiation strategy. The output is the feedback information provided to the user.

[0119] Step 5:

[0120] The server sends the generated feedback to the terminal and displays it to the user. Through this feedback, the user can learn which skills were effective and which strategies should be improved. This provides specific guidance for improving strategies in the next virtual negotiation. The output is a suggestion of specific actions the user should take next.

[0121] 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.

[0122] The system of this invention is designed to conduct negotiation training in a virtual reality or augmented reality environment and incorporates an emotion engine for recognizing and analyzing the user's emotional state. This enables more user-centered learning that takes the user's emotional responses into account.

[0123] Server functions and operation

[0124] The server, equipped with a generative model and an emotion engine, is responsible for generating negotiation scenarios and analyzing emotion data. The generative model generates appropriate negotiation scenarios based on the user's skill level and emotional responses, and sends this data to the terminal. Furthermore, it generates detailed feedback based on the emotion data collected during the user's negotiation process.

[0125] Device functions and operation

[0126] The device functions as a VR / AR device, rendering negotiation scenarios received from the server into a virtual environment. It also analyzes the user's facial expressions and tone of voice using an emotion engine and feeds that emotional state back to the server. This function allows for real-time monitoring of how the user is feeling and responding to negotiations.

[0127] User experience

[0128] Users negotiate through simulated negotiation scenarios via their devices, and during this process, an emotion engine evaluates the user's emotional state. For example, if a user is experiencing stress, the system offers new solutions to negotiation techniques by suggesting a revision of the strategy.

[0129] Integration of feedback and emotion recognition

[0130] After a user's negotiation ends, the server analyzes data from the emotion engine and behavioral records to provide feedback based on the user's emotional responses. This feedback includes the user's emotional strengths, emotional responses to issues during negotiations, and specific advice for improvement. This allows users to enhance their emotional self-awareness and improve their negotiation skills.

[0131] By implementing this system, users can integrate emotion recognition into the social skills of negotiation as part of their learning process, enabling them to acquire more flexible and effective negotiation techniques. For example, sales representatives can hone their ability to appropriately manage their emotions during negotiations with customers and to predict and improve the outcome of those negotiations. Thus, this invention goes beyond merely practicing technical skills and supports the development of comprehensive negotiation abilities that include social and emotional skills.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The user activates the device, puts on the VR / AR device, and starts the training session. This causes the device to send the user's scenario request to the server and prepare to begin processing.

[0135] Step 2:

[0136] The server receives user requests and runs a generative model to generate negotiation scenarios. Scenarios are dynamically created according to the user's skill level and objectives, and this data is transferred to the terminal.

[0137] Step 3:

[0138] The terminal renders the negotiation scenario received from the server into a VR / AR environment and presents it to the user. This allows the user to participate in a virtual negotiation situation.

[0139] Step 4:

[0140] Users negotiate through their devices, and during this process, an emotion engine built into the device analyzes the user's facial expressions and tone of voice in real time. The emotional state is evaluated on the spot and sent to the server.

[0141] Step 5:

[0142] The server receives user behavioral and emotional data in real time, integrates and analyzes the data. Based on this analysis, if the user's emotional responses during negotiations affect the scenario progression or responses, appropriate adjustments are made.

[0143] Step 6:

[0144] The user continues negotiations and receives dynamically adjusted scenarios from the server. This allows them to try out practical strategies tailored to their emotional state.

[0145] Step 7:

[0146] Once the negotiation session ends, the server generates detailed feedback based on the user's behavior and emotional data. This feedback includes an emotional rating, as well as points of success and suggestions for improvement in the negotiation.

[0147] Step 8:

[0148] The device presents the generated feedback to the user, who then uses it as guidance for learning in the next training session. The user then uses this feedback to improve their emotional management and negotiation skills.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] This invention aims to solve the problem in conventional negotiation training systems, which fail to effectively utilize users' emotional responses and thus cannot adequately improve users' skill understanding and emotional recognition. Furthermore, there is a need to provide real-time feedback based on the user's emotional state and realize an individualized learning experience.

[0152] 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.

[0153] In this invention, the server includes an information processing device means that includes a generation structure for generating negotiation scenarios in a virtual environment, an emotion analysis device means for analyzing the user's emotional state, and means for adaptively adjusting the progression of the scenario based on data from the emotion analysis device means. This enables the generation of personalized scenarios that take into account the user's emotional state and skill improvement.

[0154] A "virtual environment" is a space created using computer technology to construct a digital world different from the real world, within which users can interact and experience things.

[0155] A "negotiation scenario" is a set of hypothetical events or stories designed to simulate specific negotiation situations for learners, allowing them to practice advantageous negotiation strategies and techniques.

[0156] A "generative structure" is an algorithm or model that automatically constructs new content or procedures based on predefined prompts.

[0157] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and performs calculations and analyses according to various purposes.

[0158] "Display device means" refers to a device for visualizing information or scenarios on a computer or digital device to a user, and includes screens and displays.

[0159] "Users" refers to the collective term for individuals or organizations that operate or utilize a particular system or service.

[0160] "Emotional analysis device means" refers to technologies and devices for identifying and quantifying emotional responses from audio, video data, etc.

[0161] "Feedback" refers to information provided based on user behavior and reactions, with the aim of future improvements and enhancing learning.

[0162] Embodiments of the present invention are systems for conducting negotiation training in a virtual environment, with the aim of enabling users to more effectively improve their negotiation skills. This system consists of three main components: a server, a terminal, and a user.

[0163] Server Role

[0164] The server uses a generative AI model to create negotiation scenarios in a virtual environment. This involves using prompts that take into account the user's skill level and past negotiation results. For example, it might construct a prompt such as, "In price negotiations, propose how to respond if the customer objects that the price exceeds their budget." These generated scenarios are designed to give the user a realistic negotiation experience.

[0165] Device functions

[0166] The terminal receives negotiation scenarios sent from the server and visualizes them based on VR / AR technology. This terminal also plays a role in real-time data analysis of the user's facial expressions and voice tone using an emotion analysis device, and transmits this data to the server. This real-time data tracking makes it possible to provide adaptive feedback tailored to the user's emotional state.

[0167] User experience

[0168] Users participate in virtual negotiation scenarios via their devices, experiencing how their actions and decisions influence the scenario's progression. Detailed feedback is also provided from the server based on data collected by an emotion analysis device and records of their actions during the scenario. This allows users to learn while becoming aware of their emotional strengths and areas for improvement.

[0169] In this way, the coordinated operation of servers, terminals, and users supports not only the improvement of technical skills but also the development of emotional and social skills. This can contribute to the acquisition of practical skills, such as enabling sales representatives to flexibly adjust negotiation terms with customers.

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

[0171] Step 1:

[0172] The server receives the user's skill level and past negotiation history as input and uses a generative AI model to generate appropriate negotiation scenarios based on the prompt text. In this process, the AI ​​model generates scenarios tailored to the user's proficiency level and outputs them as scenario data. Specifically, the server refers to the user's past behavior logs and customizes the difficulty level and content.

[0173] Step 2:

[0174] The server sends the generated negotiation scenario to the terminal. The terminal takes the received scenario as input, renders the scenario in a virtual environment using VR / AR technology, and outputs it to the user as visual and auditory information. Through this operation, the user experiences a realistic negotiation situation. Specifically, the terminal loads 3D models, audio, and interaction elements to create a new negotiation scene.

[0175] Step 3:

[0176] Users participate in negotiation scenarios presented through their devices, advancing the negotiations through their statements and actions. The user's voice tone and facial expressions are continuously collected and analyzed by an emotion analysis device. This data is input from the device to the server as their current emotional state. Specifically, the device transmits user data to the server in real time, monitoring changes in the situation.

[0177] Step 4:

[0178] The server receives user emotion data and behavioral logs as input and analyzes them using a generative AI model. Based on the analysis results, it outputs suggestions to adaptively modify the scenario's progression. For example, if a high stress level is detected, the server adjusts the difficulty of the scenario to provide a more relaxed environment for the user to participate.

[0179] Step 5:

[0180] After the negotiation session ends, the server comprehensively analyzes all data, generates feedback for the user, and outputs it. This feedback includes emotional strengths, areas for improvement, and specific advice for the next session. The generated feedback is provided to the user via their terminal and used to improve future training. Specifically, the server automatically generates the feedback and sends it to the terminal.

[0181] (Application Example 2)

[0182] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0183] In recent years, virtual reality and augmented reality technologies have been used in many fields, but in training aimed at improving negotiation skills in particular, there is a lack of real-time feedback that takes into account the user's emotional state. As a result, users cannot fully understand their own emotional reactions, and comprehensive improvement of negotiation skills is difficult.

[0184] 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.

[0185] In this invention, the server includes an information processing device that includes a generation algorithm for generating a negotiation situation in a virtual reality or augmented reality environment; an information display device for displaying the negotiation situation; a device for recording the user's actions and statements and generating a detailed evaluation using the generation algorithm; a device that includes an emotion recognition engine and analyzes the user's emotional state; and a device for providing the evaluation to the user and improving negotiation skills. This makes it possible for the user to grasp their emotional reactions in real time during negotiation training and receive specific feedback based on them.

[0186] "Virtual reality" refers to an environment in a virtual three-dimensional space constructed using computer technology, within which users can have an immersive experience.

[0187] "Augmented reality" is a technology that provides an extended environment and experience of real space by overlaying computer-generated visual information onto real-world images and information.

[0188] A "generative algorithm" is a computational method that dynamically creates virtual content and scenarios based on user input or set conditions.

[0189] An "information processing device" is an electronic device that receives data, performs calculations and analyses based on that data, and outputs the necessary information.

[0190] An "information display device" is a device that presents information obtained through calculations and analyses to users visually or by other means.

[0191] An "emotion recognition engine" is a combination of software and hardware that analyzes data such as the user's facial expressions and vocalizations to determine the user's emotional state.

[0192] "Evaluation" refers to the results of judgments and diagnoses generated by analyzing information obtained based on the user's behavior and reactions.

[0193] "Negotiation skills" refer to the set of techniques and knowledge necessary to achieve one's goals through dialogue with others, and particularly include communication and negotiation skills.

[0194] This invention is configured to enable negotiation training in a virtual or augmented reality environment. The system includes an information processing device (server), an information display device (terminal), and an emotion recognition engine.

[0195] The server is responsible for dynamically generating negotiation scenarios based on the user's skill level and emotional responses using a generation algorithm. This generation algorithm utilizes open-source AI models and other tools to efficiently construct specific scenarios for the user.

[0196] The terminal functions as an information display device and outputs negotiation scenarios to the user through devices such as VR headsets and smart glasses. This allows the user to experience negotiations in real time within an interactive virtual environment. The emotion recognition engine analyzes the user's emotional state in real time based on their facial expressions and tone of voice. For example, it uses Microsoft® Azure® Face API to accurately grasp the user's emotional state.

[0197] Users will leverage the comprehensive feedback provided by these technologies to improve their negotiation skills. This feedback includes specific advice tailored to the user's emotional responses, suggesting effective negotiation strategies.

[0198] As a concrete example, users can simulate problem-solving scenarios within their home in a VR environment and learn about the impact their words have on others through sentiment analysis. The generative AI model provides examples of prompts based on the user's emotions, suggesting improvements in real time.

[0199] Examples of prompts for a generative AI model include the following:

[0200] "Assess the current situation and analyze how the user is feeling emotionally. As a reaction, suggest advice or simulated scenarios to improve negotiation skills."

[0201] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0202] Step 1:

[0203] The server generates negotiation scenarios using a generation algorithm based on the user's skill level and emotional response. It receives user profile data and past negotiation records as input, performs calculations for scenario generation, and provides optimized negotiation scenarios as output.

[0204] Step 2:

[0205] The terminal presents negotiation scenarios received from the server to the user via an information display device. Using a VR headset or smart glasses, a virtual negotiation environment is rendered and visually presented to the user.

[0206] Step 3:

[0207] Users act and speak within a virtual environment in response to the displayed negotiation scenario. Their actions and statements are captured in real time by their devices and sent to the server, allowing for concrete user feedback.

[0208] Step 4:

[0209] The server analyzes user behavior data collected from terminals through an emotion recognition engine. It uses data such as the user's facial expressions and voice tone as input, and outputs the user's emotional state as a result.

[0210] Step 5:

[0211] Based on data from the emotion recognition engine, the server utilizes a generative AI model to generate user-appropriate feedback. It receives the results of emotion analysis as input, performs data calculations to generate appropriate advice and improvement suggestions, and outputs them.

[0212] Step 6:

[0213] The device receives feedback from the server and presents it to the user. The user receives the feedback and uses it to improve their negotiation skills. Specifically, advice is provided through visual and auditory means.

[0214] 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.

[0215] 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.

[0216] 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.

[0217] [Second Embodiment]

[0218] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0219] 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.

[0220] 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).

[0221] 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.

[0222] 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.

[0223] 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).

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] 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".

[0230] The negotiation training system of the present invention comprises a generative model, a server, a terminal, and a user interface, and is designed to enable users to effectively improve their negotiation skills in a virtual reality or augmented reality environment.

[0231] Server functions and operation

[0232] The server is the central component of this invention and is equipped with a generative model. This generative model considers user profiles and historical training data to generate realistic negotiation scenarios. Upon receiving a user request, the server dynamically creates an appropriate negotiation scenario and sends the data to the terminal. The server is also responsible for collecting and analyzing user behavior data and generating detailed feedback.

[0233] Device functions and operation

[0234] The device functions as a VR headset or AR device, rendering scenario data received from the server into a virtual or augmented reality environment. Through this device, the user participates in a virtual negotiation scene. The device also records the user's experience by transmitting their movements and statements to the server in real time.

[0235] User experience

[0236] Users attempt negotiation strategies in response to situations presented within the scenario. The system records user statements and actions in real time, using this data as the basis for later feedback. For example, when a user proposes a compromise during price negotiations, its validity and effectiveness are evaluated based on simulations.

[0237] Feedback and skill improvement

[0238] After the scenario ends, the server provides feedback using a generative model based on the user's behavioral data. This feedback includes points of success, strategies that need improvement, and advice for the next scenario. This feedback information is delivered to the user via their device, allowing them to continuously learn and improve their negotiation skills.

[0239] Thus, the negotiation training system of the present invention provides an effective means of improving skills through diverse negotiation experiences without incurring risk. For example, a new business employee can practice contract negotiations with a virtual customer and prepare for negotiations in a real-world environment. This system goes beyond mere theoretical learning, creating an environment where users learn from experience and improve their practical abilities.

[0240] The following describes the processing flow.

[0241] Step 1:

[0242] The user launches the terminal and selects to start a training session. Based on the user's selection, the terminal will send a session request to the server. The request will include the user's skill level and the type of negotiation scenario they prefer.

[0243] Step 2:

[0244] Based on the received request, the server generates an appropriate negotiation scenario using a generative model. The generated scenario data includes the background of the negotiation and the characteristics of the other party, and this data is sent to the terminal.

[0245] Step 3:

[0246] The terminal receives scenario data sent from the server and renders it in a virtual or augmented reality environment. This prepares the user to experience negotiations in the virtual environment.

[0247] Step 4:

[0248] Users participate in a virtual environment provided through their terminal and negotiate according to a scenario. Their statements and actions during negotiations are recorded in real time.

[0249] Step 5:

[0250] The device sends user behavior data to the server. The server collects this data and uses it to analyze the behavior.

[0251] Step 6:

[0252] The server analyzes the collected user behavior data and generates feedback using a generative model. This feedback includes the user's negotiation strengths and areas for improvement.

[0253] Step 7:

[0254] The server sends the generated feedback to the terminal. The terminal displays this feedback to the user, providing it in a visually easy-to-understand format.

[0255] Step 8:

[0256] Users review feedback and use it to set their next learning goals to improve their negotiation skills. This enables continuous skill development.

[0257] (Example 1)

[0258] 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."

[0259] The challenge lies in providing concrete and practical training methods that effectively improve negotiation skills. In particular, there is a need for a system that allows learners to experience and learn through actual simulation environments, rather than relying solely on traditional theoretical learning.

[0260] 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.

[0261] In this invention, the server includes an information processing device means that incorporates a generation program for creating a negotiation experience in a virtual reality or augmented reality environment; an output device means for visualizing the negotiation experience; and means for collecting user behavior and statements and generating detailed improvement information using the generation program. This enables users to effectively improve their skills through actual dialogue and actions in various negotiation scenarios.

[0262] "Virtual reality" is a technology that uses computer technology to create a virtual environment that does not exist in reality, allowing users to interact within that environment.

[0263] Augmented reality is a technology that allows users to experience both real and virtual elements simultaneously by overlaying digital information onto the real environment.

[0264] An "information processing device" is a general term for devices and systems used to process data and generate or manage necessary information.

[0265] An "output device" is a device or system that presents data in a form that is understandable to humans, such as in the form of audio or video.

[0266] A "generator program" is a set of instructions or code that runs on a computer to create digital content or scenarios for a specific purpose.

[0267] "User" refers to an individual or group that seeks to improve their negotiation skills using this system.

[0268] "Improvement information" is a general term for feedback and advice given to improve skills based on the evaluation results of users' actions and statements.

[0269] This invention provides a training system for effectively improving negotiation skills in virtual reality and augmented reality environments, offering an innovative method that utilizes generative AI models.

[0270] The server functions as the core of this system, acting as an information processing device. Leveraging a generative AI model, it generates negotiation scenarios based on conditions specified by the user through prompt messages. The generative AI model generates scenarios based on a rich source of information, including historical data, ensuring they are appropriate to the user's skill level. The server also transmits these scenarios to terminals in real time via the network.

[0271] The terminal receives scenario data provided by the server and functions as an output device in a virtual reality and augmented reality environment. Specifically, it visualizes the scenario using VR headsets and AR devices, creating an environment where users can immerse themselves in the scenario and interact with it. Through this terminal, users can converse with characters in the scenario and test their actual negotiation skills.

[0272] Users experience negotiation scenarios through interactions in a virtual environment. For example, in a scenario where they negotiate the price of a new product, the user proposes a compromise to the other party. During this process, the user's actions and statements are transmitted in real time from the terminal to the server and stored.

[0273] A concrete example of a prompt message would be, "Generate a scenario in which the user negotiates the price of a new product. In this scenario, set the user as a rookie salesperson attempting their first negotiation." This allows the user to try different negotiation techniques within a realistic scenario.

[0274] Thus, the present invention provides a system that enables practical and efficient training for users to effectively improve their negotiation skills.

[0275] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0276] Step 1:

[0277] The server receives a prompt sentence from the user. The input includes the conditions of the negotiation scenario specified by the user. This input is analyzed and filtered for application to the generative AI model. As a result, the elements required for a detailed negotiation scenario are extracted.

[0278] Step 2:

[0279] The server uses the generative AI model to generate a negotiation scenario. The information input is the user's prompt sentence and past training data. The server combines and operates on these data to generate a realistic negotiation scenario. The output is negotiation scenario data suitable for the user's skill level.

[0280] Step 3:

[0281] The server sends the generated negotiation scenario to the terminal. This scenario data is input to the terminal, which uses it for rendering in a virtual reality or augmented reality environment. The output is a negotiation scene presented to the user as a visualized 3D environment.

[0282] Step 4:

[0283] The user conducts negotiations in the virtual reality or augmented reality environment presented through the terminal. The user's input actions include voice instructions and gestures. The terminal captures these in real-time and sends them to the server. As a result of this process, the user's action history is recorded as output data.

[0284] Step 5:

[0285] The server analyzes the user's action data. This is a process of using the generative AI model to generate detailed feedback based on the recorded input data (the user's speech and actions). The output is feedback information including points that need improvement and effective strategies provided to the user.

[0286] Step 6:

[0287] The server sends the generated feedback to the terminal. The terminal presents this to the user and provides information useful for skill improvement in subsequent scenarios. The user can use this feedback as a reference to try different strategies in the next negotiation scenario. The output is an improved strategy based on learning.

[0288] (Application Example 1)

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

[0290] Conventional negotiation skill training has remained theoretical learning and has not been sufficient for improving the practical negotiation skills of salespersons in physical stores. Also, there has been a lack of a system for providing realistic negotiation scenarios and enabling salespersons to improve their practical skills. Against this background, there is a need for a means for effectively improving skills through negotiations between salespersons and simulated customers in a virtual environment.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0292] In this invention, the server includes an information processing device including a generation model for generating a negotiation scenario in a virtual reality or augmented reality environment, a video display device for displaying the negotiation scenario, and a data processing device for recording the user's actions and speech and generating detailed feedback. This enables salespersons to practically improve their product promotion skills through negotiations with simulated purchasers.

[0293] "Virtual reality" is a technology that provides an immersive experience within a three-dimensional virtual environment generated by a computer.

[0294] Augmented reality is a technology that overlays computer-generated visual information onto images and information from the real world.

[0295] A "generative model" is an algorithm that automatically creates negotiation scenarios in a virtual environment based on user profiles and historical data.

[0296] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0297] A "video display device" is a device that displays images and provides visual information to the user, and includes displays and head-mounted displays.

[0298] A "data processing device" is a device that records user input data, performs analysis based on that data, and generates feedback.

[0299] A "simulated buyer" is a digital character generated by a computer within a virtual environment that behaves like a real customer.

[0300] "Product promotion techniques" refer to the skills that sellers use to propose products to customers and effectively communicate their appeal.

[0301] The server generates negotiation scenarios in a virtual or augmented reality environment using a generative model. The generative AI model within the server dynamically designs specific negotiation scenes, taking into account the user's skill level and past training data.

[0302] This system utilizes hardware such as VR headsets like the Oculus Quest 2 or smart glasses. Through these, users experience generated negotiation scenarios via video displays. Within these scenarios, users can interact with virtual buyers and hone their product promotion skills.

[0303] The terminal records the user's actions and statements in real time through sensors to the data processing device and sends them to the server. The server analyzes the received data and generates detailed feedback based on the user's choices and strategies. This feedback is sent back to the terminal again to improve the user's negotiation skills.

[0304] As a specific example, consider the case where a user proposes a smartphone to a customer in a virtual world. As an example of a prompt sentence, there is one that says, "Please create a scenario that proposes an optimal response based on the reaction shown by the customer in a price negotiation scenario for a new product." Based on this prompt, the server generates a scenario and provides a place where a salesperson can practice under the same conditions as in real store operations. As a result, the implementer can effectively acquire more realistic negotiation techniques in the virtual space.

[0305] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0306] Step 1:

[0307] The server receives a request from the user. The request includes the user's skill level and training purpose as input. Upon receiving this, the server starts generating a negotiation scenario by sending a prompt sentence to the generation AI model. The generation AI model designs a scenario suitable for the user's skills and outputs it as data.

[0308] Step 2:

[0309] The server sends the generated negotiation scenario to the terminal. The terminal renders the received scenario data in a virtual reality or augmented reality environment. The engine uses software such as Unity to realistically depict a virtual negotiation scene. At this time, the input is the negotiation scenario data, and the output is the virtual environment experienced by the user.

[0310] Step 3:

[0311] Users participate in virtual negotiation scenarios through their devices. This allows them to interact with a purchasing simulator and gain practical experience in improving their product promotion techniques. User actions and statements are recorded in real time by sensors. The input is user behavior data, which is sent to the server.

[0312] Step 4:

[0313] The server analyzes behavioral data submitted by the user and generates detailed feedback using a generative AI model. A data processing unit performs this task, evaluating the effectiveness and areas for improvement of the user's negotiation strategy. The output is the feedback information provided to the user.

[0314] Step 5:

[0315] The server sends the generated feedback to the terminal and displays it to the user. Through this feedback, the user can learn which skills were effective and which strategies should be improved. This provides specific guidance for improving strategies in the next virtual negotiation. The output is a suggestion of specific actions the user should take next.

[0316] 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.

[0317] The system of this invention is designed to conduct negotiation training in a virtual reality or augmented reality environment and incorporates an emotion engine for recognizing and analyzing the user's emotional state. This enables more user-centered learning that takes the user's emotional responses into account.

[0318] Server functions and operation

[0319] The server, equipped with a generative model and an emotion engine, is responsible for generating negotiation scenarios and analyzing emotion data. The generative model generates appropriate negotiation scenarios based on the user's skill level and emotional responses, and sends this data to the terminal. Furthermore, it generates detailed feedback based on the emotion data collected during the user's negotiation process.

[0320] Device functions and operation

[0321] The device functions as a VR / AR device, rendering negotiation scenarios received from the server into a virtual environment. It also analyzes the user's facial expressions and tone of voice using an emotion engine and feeds that emotional state back to the server. This function allows for real-time monitoring of how the user is feeling and responding to negotiations.

[0322] User experience

[0323] Users negotiate through simulated negotiation scenarios via their devices, and during this process, an emotion engine evaluates the user's emotional state. For example, if a user is experiencing stress, the system offers new solutions to negotiation techniques by suggesting a revision of the strategy.

[0324] Integration of feedback and emotion recognition

[0325] After a user's negotiation ends, the server analyzes data from the emotion engine and behavioral records to provide feedback based on the user's emotional responses. This feedback includes the user's emotional strengths, emotional responses to issues during negotiations, and specific advice for improvement. This allows users to enhance their emotional self-awareness and improve their negotiation skills.

[0326] By implementing this system, users can integrate emotion recognition into the social skills of negotiation as part of their learning process, enabling them to acquire more flexible and effective negotiation techniques. For example, sales representatives can hone their ability to appropriately manage their emotions during negotiations with customers and to predict and improve the outcome of those negotiations. Thus, this invention goes beyond merely practicing technical skills and supports the development of comprehensive negotiation abilities that include social and emotional skills.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The user activates the device, puts on the VR / AR device, and starts the training session. This causes the device to send the user's scenario request to the server and prepare to begin processing.

[0330] Step 2:

[0331] The server receives user requests and runs a generative model to generate negotiation scenarios. Scenarios are dynamically created according to the user's skill level and objectives, and this data is transferred to the terminal.

[0332] Step 3:

[0333] The terminal renders the negotiation scenario received from the server into a VR / AR environment and presents it to the user. This allows the user to participate in a virtual negotiation situation.

[0334] Step 4:

[0335] Users negotiate through their devices, and during this process, an emotion engine built into the device analyzes the user's facial expressions and tone of voice in real time. The emotional state is evaluated on the spot and sent to the server.

[0336] Step 5:

[0337] The server receives user behavioral and emotional data in real time, integrates and analyzes the data. Based on this analysis, if the user's emotional responses during negotiations affect the scenario progression or responses, appropriate adjustments are made.

[0338] Step 6:

[0339] The user continues negotiations and receives dynamically adjusted scenarios from the server. This allows them to try out practical strategies tailored to their emotional state.

[0340] Step 7:

[0341] Once the negotiation session ends, the server generates detailed feedback based on the user's behavior and emotional data. This feedback includes an emotional rating, as well as points of success and suggestions for improvement in the negotiation.

[0342] Step 8:

[0343] The device presents the generated feedback to the user, who then uses it as guidance for learning in the next training session. The user then uses this feedback to improve their emotional management and negotiation skills.

[0344] (Example 2)

[0345] 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".

[0346] This invention aims to solve the problem in conventional negotiation training systems, which fail to effectively utilize users' emotional responses and thus cannot adequately improve users' skill understanding and emotional recognition. Furthermore, there is a need to provide real-time feedback based on the user's emotional state and realize an individualized learning experience.

[0347] 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.

[0348] In this invention, the server includes an information processing device means that includes a generation structure for generating negotiation scenarios in a virtual environment, an emotion analysis device means for analyzing the user's emotional state, and means for adaptively adjusting the progression of the scenario based on data from the emotion analysis device means. This enables the generation of personalized scenarios that take into account the user's emotional state and skill improvement.

[0349] A "virtual environment" is a space created using computer technology to construct a digital world different from the real world, within which users can interact and experience things.

[0350] A "negotiation scenario" is a set of hypothetical events or stories designed to simulate specific negotiation situations for learners, allowing them to practice advantageous negotiation strategies and techniques.

[0351] A "generative structure" is an algorithm or model that automatically constructs new content or procedures based on predefined prompts.

[0352] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and performs calculations and analyses according to various purposes.

[0353] "Display device means" refers to a device for visualizing information or scenarios on a computer or digital device to a user, and includes screens and displays.

[0354] "Users" refers to the collective term for individuals or organizations that operate or utilize a particular system or service.

[0355] "Emotional analysis device means" refers to technologies and devices for identifying and quantifying emotional responses from audio, video data, etc.

[0356] "Feedback" refers to information provided based on user behavior and reactions, with the aim of future improvements and enhancing learning.

[0357] Embodiments of the present invention are systems for conducting negotiation training in a virtual environment, with the aim of enabling users to more effectively improve their negotiation skills. This system consists of three main components: a server, a terminal, and a user.

[0358] Server Role

[0359] The server uses a generative AI model to create negotiation scenarios in a virtual environment. This involves using prompts that take into account the user's skill level and past negotiation results. For example, it might construct a prompt such as, "In price negotiations, propose how to respond if the customer objects that the price exceeds their budget." These generated scenarios are designed to give the user a realistic negotiation experience.

[0360] Device functions

[0361] The terminal receives negotiation scenarios sent from the server and visualizes them based on VR / AR technology. This terminal also plays a role in real-time data analysis of the user's facial expressions and voice tone using an emotion analysis device, and transmits this data to the server. This real-time data tracking makes it possible to provide adaptive feedback tailored to the user's emotional state.

[0362] User experience

[0363] Users participate in virtual negotiation scenarios via their devices, experiencing how their actions and decisions influence the scenario's progression. Detailed feedback is also provided from the server based on data collected by an emotion analysis device and records of their actions during the scenario. This allows users to learn while becoming aware of their emotional strengths and areas for improvement.

[0364] In this way, the coordinated operation of servers, terminals, and users supports not only the improvement of technical skills but also the development of emotional and social skills. This can contribute to the acquisition of practical skills, such as enabling sales representatives to flexibly adjust negotiation terms with customers.

[0365] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0366] Step 1:

[0367] The server receives the user's skill level and past negotiation history as input and uses a generative AI model to generate appropriate negotiation scenarios based on the prompt text. In this process, the AI ​​model generates scenarios tailored to the user's proficiency level and outputs them as scenario data. Specifically, the server refers to the user's past behavior logs and customizes the difficulty level and content.

[0368] Step 2:

[0369] The server sends the generated negotiation scenario to the terminal. The terminal takes the received scenario as input, renders the scenario in a virtual environment using VR / AR technology, and outputs it to the user as visual and auditory information. Through this operation, the user experiences a realistic negotiation situation. Specifically, the terminal loads 3D models, audio, and interaction elements to create a new negotiation scene.

[0370] Step 3:

[0371] Users participate in negotiation scenarios presented through their devices, advancing the negotiations through their statements and actions. The user's voice tone and facial expressions are continuously collected and analyzed by an emotion analysis device. This data is input from the device to the server as their current emotional state. Specifically, the device transmits user data to the server in real time, monitoring changes in the situation.

[0372] Step 4:

[0373] The server receives user emotion data and behavioral logs as input and analyzes them using a generative AI model. Based on the analysis results, it outputs suggestions to adaptively modify the scenario's progression. For example, if a high stress level is detected, the server adjusts the difficulty of the scenario to provide a more relaxed environment for the user to participate.

[0374] Step 5:

[0375] After the negotiation session ends, the server comprehensively analyzes all data, generates feedback for the user, and outputs it. This feedback includes emotional strengths, areas for improvement, and specific advice for the next session. The generated feedback is provided to the user via their terminal and used to improve future training. Specifically, the server automatically generates the feedback and sends it to the terminal.

[0376] (Application Example 2)

[0377] 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."

[0378] In recent years, virtual reality and augmented reality technologies have been used in many fields, but in training aimed at improving negotiation skills in particular, there is a lack of real-time feedback that takes into account the user's emotional state. As a result, users cannot fully understand their own emotional reactions, and comprehensive improvement of negotiation skills is difficult.

[0379] 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.

[0380] In this invention, the server includes an information processing device that includes a generation algorithm for generating a negotiation situation in a virtual reality or augmented reality environment; an information display device for displaying the negotiation situation; a device for recording the user's actions and statements and generating a detailed evaluation using the generation algorithm; a device that includes an emotion recognition engine and analyzes the user's emotional state; and a device for providing the evaluation to the user and improving negotiation skills. This makes it possible for the user to grasp their emotional reactions in real time during negotiation training and receive specific feedback based on them.

[0381] "Virtual reality" refers to an environment in a virtual three-dimensional space constructed using computer technology, within which users can have an immersive experience.

[0382] "Augmented reality" is a technology that provides an extended environment and experience of real space by overlaying computer-generated visual information onto real-world images and information.

[0383] A "generative algorithm" is a computational method that dynamically creates virtual content and scenarios based on user input or set conditions.

[0384] An "information processing device" is an electronic device that receives data, performs calculations and analyses based on that data, and outputs the necessary information.

[0385] An "information display device" is a device that presents information obtained through calculations and analyses to users visually or by other means.

[0386] An "emotion recognition engine" is a combination of software and hardware that analyzes data such as the user's facial expressions and vocalizations to determine the user's emotional state.

[0387] "Evaluation" refers to the results of judgments and diagnoses generated by analyzing information obtained based on the user's behavior and reactions.

[0388] "Negotiation skills" refer to the set of techniques and knowledge necessary to achieve one's goals through dialogue with others, and particularly include communication and negotiation skills.

[0389] This invention is configured to enable negotiation training in a virtual or augmented reality environment. The system includes an information processing device (server), an information display device (terminal), and an emotion recognition engine.

[0390] The server is responsible for dynamically generating negotiation scenarios based on the user's skill level and emotional responses using a generation algorithm. This generation algorithm utilizes open-source AI models and other tools to efficiently construct specific scenarios for the user.

[0391] The terminal functions as an information display device, outputting negotiation scenarios to the user through devices such as VR headsets and smart glasses. This allows the user to experience negotiations in real time within an interactive virtual environment. The emotion recognition engine analyzes the user's emotional state in real time based on their facial expressions and tone of voice. For example, it uses Microsoft's Azure Face API to accurately grasp the user's emotional state.

[0392] Users will leverage the comprehensive feedback provided by these technologies to improve their negotiation skills. This feedback includes specific advice tailored to the user's emotional responses, suggesting effective negotiation strategies.

[0393] As a concrete example, users can simulate problem-solving scenarios within their home in a VR environment and learn about the impact their words have on others through sentiment analysis. The generative AI model provides examples of prompts based on the user's emotions, suggesting improvements in real time.

[0394] Examples of prompts for a generative AI model include the following:

[0395] "Assess the current situation and analyze how the user is feeling emotionally. As a reaction, suggest advice or simulated scenarios to improve negotiation skills."

[0396] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0397] Step 1:

[0398] The server generates negotiation scenarios using a generation algorithm based on the user's skill level and emotional response. It receives user profile data and past negotiation records as input, performs calculations for scenario generation, and provides optimized negotiation scenarios as output.

[0399] Step 2:

[0400] The terminal presents negotiation scenarios received from the server to the user via an information display device. Using a VR headset or smart glasses, a virtual negotiation environment is rendered and visually presented to the user.

[0401] Step 3:

[0402] Users act and speak within a virtual environment in response to the displayed negotiation scenario. Their actions and statements are captured in real time by their devices and sent to the server, allowing for concrete user feedback.

[0403] Step 4:

[0404] The server analyzes user behavior data collected from terminals through an emotion recognition engine. It uses data such as the user's facial expressions and voice tone as input, and outputs the user's emotional state as a result.

[0405] Step 5:

[0406] Based on data from the emotion recognition engine, the server utilizes a generative AI model to generate user-appropriate feedback. It receives the results of emotion analysis as input, performs data calculations to generate appropriate advice and improvement suggestions, and outputs them.

[0407] Step 6:

[0408] The device receives feedback from the server and presents it to the user. The user receives the feedback and uses it to improve their negotiation skills. Specifically, advice is provided through visual and auditory means.

[0409] 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.

[0410] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0411] 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.

[0412] [Third Embodiment]

[0413] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0414] 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.

[0415] 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).

[0416] 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.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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".

[0425] The negotiation training system of the present invention comprises a generative model, a server, a terminal, and a user interface, and is designed to enable users to effectively improve their negotiation skills in a virtual reality or augmented reality environment.

[0426] Server functions and operation

[0427] The server is the central component of this invention and is equipped with a generative model. This generative model considers user profiles and historical training data to generate realistic negotiation scenarios. Upon receiving a user request, the server dynamically creates an appropriate negotiation scenario and sends the data to the terminal. The server is also responsible for collecting and analyzing user behavior data and generating detailed feedback.

[0428] Device functions and operation

[0429] The device functions as a VR headset or AR device, rendering scenario data received from the server into a virtual or augmented reality environment. Through this device, the user participates in a virtual negotiation scene. The device also records the user's experience by transmitting their movements and statements to the server in real time.

[0430] User experience

[0431] Users attempt negotiation strategies in response to situations presented within the scenario. The system records user statements and actions in real time, using this data as the basis for later feedback. For example, when a user proposes a compromise during price negotiations, its validity and effectiveness are evaluated based on simulations.

[0432] Feedback and skill improvement

[0433] After the scenario ends, the server provides feedback using a generative model based on the user's behavioral data. This feedback includes points of success, strategies that need improvement, and advice for the next scenario. This feedback information is delivered to the user via their device, allowing them to continuously learn and improve their negotiation skills.

[0434] Thus, the negotiation training system of the present invention provides an effective means of improving skills through diverse negotiation experiences without incurring risk. For example, a new business employee can practice contract negotiations with a virtual customer and prepare for negotiations in a real-world environment. This system goes beyond mere theoretical learning, creating an environment where users learn from experience and improve their practical abilities.

[0435] The following describes the processing flow.

[0436] Step 1:

[0437] The user launches the terminal and selects to start a training session. Based on the user's selection, the terminal will send a session request to the server. The request will include the user's skill level and the type of negotiation scenario they prefer.

[0438] Step 2:

[0439] Based on the received request, the server generates an appropriate negotiation scenario using a generative model. The generated scenario data includes the background of the negotiation and the characteristics of the other party, and this data is sent to the terminal.

[0440] Step 3:

[0441] The terminal receives scenario data sent from the server and renders it in a virtual or augmented reality environment. This prepares the user to experience negotiations in the virtual environment.

[0442] Step 4:

[0443] Users participate in a virtual environment provided through their terminal and negotiate according to a scenario. Their statements and actions during negotiations are recorded in real time.

[0444] Step 5:

[0445] The device sends user behavior data to the server. The server collects this data and uses it to analyze the behavior.

[0446] Step 6:

[0447] The server analyzes the collected user behavior data and generates feedback using a generative model. This feedback includes the user's negotiation strengths and areas for improvement.

[0448] Step 7:

[0449] The server sends the generated feedback to the terminal. The terminal displays this feedback to the user, providing it in a visually easy-to-understand format.

[0450] Step 8:

[0451] Users review feedback and use it to set their next learning goals to improve their negotiation skills. This enables continuous skill development.

[0452] (Example 1)

[0453] 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."

[0454] The challenge lies in providing concrete and practical training methods that effectively improve negotiation skills. In particular, there is a need for a system that allows learners to experience and learn through actual simulation environments, rather than relying solely on traditional theoretical learning.

[0455] 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.

[0456] In this invention, the server includes an information processing device means that incorporates a generation program for creating a negotiation experience in a virtual reality or augmented reality environment; an output device means for visualizing the negotiation experience; and means for collecting user behavior and statements and generating detailed improvement information using the generation program. This enables users to effectively improve their skills through actual dialogue and actions in various negotiation scenarios.

[0457] "Virtual reality" is a technology that uses computer technology to create a virtual environment that does not exist in reality, allowing users to interact within that environment.

[0458] Augmented reality is a technology that allows users to experience both real and virtual elements simultaneously by overlaying digital information onto the real environment.

[0459] An "information processing device" is a general term for devices and systems used to process data and generate or manage necessary information.

[0460] An "output device" is a device or system that presents data in a form that is understandable to humans, such as in the form of audio or video.

[0461] A "generator program" is a set of instructions or code that runs on a computer to create digital content or scenarios for a specific purpose.

[0462] "User" refers to an individual or group that seeks to improve their negotiation skills using this system.

[0463] "Improvement information" is a general term for feedback and advice given to improve skills based on the evaluation results of users' actions and statements.

[0464] This invention provides a training system for effectively improving negotiation skills in virtual reality and augmented reality environments, offering an innovative method that utilizes generative AI models.

[0465] The server functions as the core of this system, acting as an information processing device. Leveraging a generative AI model, it generates negotiation scenarios based on conditions specified by the user through prompt messages. The generative AI model generates scenarios based on a rich source of information, including historical data, ensuring they are appropriate to the user's skill level. The server also transmits these scenarios to terminals in real time via the network.

[0466] The terminal receives scenario data provided by the server and functions as an output device in a virtual reality and augmented reality environment. Specifically, it visualizes the scenario using VR headsets and AR devices, creating an environment where users can immerse themselves in the scenario and interact with it. Through this terminal, users can converse with characters in the scenario and test their actual negotiation skills.

[0467] Users experience negotiation scenarios through interactions in a virtual environment. For example, in a scenario where they negotiate the price of a new product, the user proposes a compromise to the other party. During this process, the user's actions and statements are transmitted in real time from the terminal to the server and stored.

[0468] A concrete example of a prompt message would be, "Generate a scenario in which the user negotiates the price of a new product. In this scenario, set the user as a rookie salesperson attempting their first negotiation." This allows the user to try different negotiation techniques within a realistic scenario.

[0469] Thus, the present invention provides a system that enables practical and efficient training for users to effectively improve their negotiation skills.

[0470] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0471] Step 1:

[0472] The server receives a prompt from the user. The input includes the conditions of the negotiation scenario specified by the user. This input is analyzed and filtered for application to the generative AI model. As a result, the elements necessary for a detailed negotiation scenario are extracted.

[0473] Step 2:

[0474] The server generates negotiation scenarios using a generative AI model. The input information consists of user prompts and historical training data. The server combines this data to perform calculations and generate realistic negotiation scenarios. The output is negotiation scenario data appropriate to the user's skill level.

[0475] Step 3:

[0476] The server sends the generated negotiation scenario to the terminal. This scenario data is input to the terminal, which then uses it to render it in a virtual reality or augmented reality environment. The output is the negotiation scene presented to the user as a visualized 3D environment.

[0477] Step 4:

[0478] The user conducts negotiations in a virtual or augmented reality environment presented through the device. User input includes voice commands and gestures. The device captures these in real time and sends them to the server. As a result of this process, the user's behavior history is recorded as output data.

[0479] Step 5:

[0480] The server analyzes user behavior data. This process uses a generative AI model to generate detailed feedback based on recorded input data (user statements and actions). The output is feedback information provided to the user, including areas for improvement and effective strategies.

[0481] Step 6:

[0482] The server sends the generated feedback to the terminal. The terminal presents this to the user, providing information to help improve skills in subsequent scenarios. The user can use this feedback to try different strategies in the next negotiation scenario. The output is a learning-based improvement strategy.

[0483] (Application Example 1)

[0484] 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."

[0485] Traditional negotiation skills training has been limited to theoretical learning and has been insufficient in improving the practical negotiation skills of sales staff in physical stores. Furthermore, there has been a lack of systems that provide realistic negotiation scenarios and enable sales staff to improve their practical skills. Against this backdrop, there is a need for a means to effectively enhance sales staff's skills through simulated customer negotiations in a virtual environment.

[0486] 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.

[0487] In this invention, the server includes an information processing device that includes a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment, a video display device for displaying the negotiation scenarios, and a data processing device that records user actions and statements and generates detailed feedback. This makes it possible for salespeople to practically improve their product promotion techniques through negotiations with simulated buyers.

[0488] "Virtual reality" is a technology that provides a realistic experience within a computer-generated three-dimensional virtual environment.

[0489] Augmented reality is a technology that overlays computer-generated visual information onto images and information from the real world.

[0490] A "generative model" is an algorithm that automatically creates negotiation scenarios in a virtual environment based on user profiles and historical data.

[0491] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0492] A "video display device" is a device that displays images and provides visual information to the user, and includes displays and head-mounted displays.

[0493] A "data processing device" is a device that records user input data, performs analysis based on that data, and generates feedback.

[0494] A "simulated buyer" is a digital character generated by a computer within a virtual environment that behaves like a real customer.

[0495] "Product promotion techniques" refer to the skills that sellers use to propose products to customers and effectively communicate their appeal.

[0496] The server generates negotiation scenarios in a virtual or augmented reality environment using a generative model. The generative AI model within the server dynamically designs specific negotiation scenes, taking into account the user's skill level and past training data.

[0497] This system utilizes hardware such as VR headsets like the Oculus Quest 2 or smart glasses. Through these, users experience generated negotiation scenarios via video displays. Within these scenarios, users can interact with virtual buyers and hone their product promotion skills.

[0498] The device records the user's actions and statements in real time via sensors to a data processing unit, which then transmits the data to a server. The server analyzes the received data and generates detailed feedback based on the user's choices and strategies. This feedback is then sent back to the device to improve the user's negotiation skills.

[0499] As a concrete example, consider a scenario where a user proposes a smartphone to a customer in a virtual world. An example of a prompt might be, "Create a scenario in which you propose the optimal response based on the customer's reaction during price negotiations for a new product." Based on this prompt, the server generates a scenario, providing a platform where salespeople can practice under conditions similar to real-world store operations. This allows participants to effectively acquire negotiation skills that are closer to reality in a virtual space.

[0500] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0501] Step 1:

[0502] The server receives a request from the user. The request includes the user's skill level and training objectives as input. The server then sends a prompt to the generative AI model, initiating the generation of negotiation scenarios. The generative AI model designs a scenario tailored to the user's skills and outputs it as data.

[0503] Step 2:

[0504] The server sends the generated negotiation scenario to the terminal. The terminal renders the received scenario data into a virtual or augmented reality environment. The engine uses software such as Unity to realistically depict the virtual negotiation scene. In this process, the input is the negotiation scenario data, and the output is the virtual environment experienced by the user.

[0505] Step 3:

[0506] Users participate in virtual negotiation scenarios through their devices. This allows them to interact with a purchasing simulator and gain practical experience in improving their product promotion techniques. User actions and statements are recorded in real time by sensors. The input is user behavior data, which is sent to the server.

[0507] Step 4:

[0508] The server analyzes behavioral data submitted by the user and generates detailed feedback using a generative AI model. A data processing unit performs this task, evaluating the effectiveness and areas for improvement of the user's negotiation strategy. The output is the feedback information provided to the user.

[0509] Step 5:

[0510] The server sends the generated feedback to the terminal and displays it to the user. Through this feedback, the user can learn which skills were effective and which strategies should be improved. This provides specific guidance for improving strategies in the next virtual negotiation. The output is a suggestion of specific actions the user should take next.

[0511] 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.

[0512] The system of this invention is designed to conduct negotiation training in a virtual reality or augmented reality environment and incorporates an emotion engine for recognizing and analyzing the user's emotional state. This enables more user-centered learning that takes the user's emotional responses into account.

[0513] Server functions and operation

[0514] The server, equipped with a generative model and an emotion engine, is responsible for generating negotiation scenarios and analyzing emotion data. The generative model generates appropriate negotiation scenarios based on the user's skill level and emotional responses, and sends this data to the terminal. Furthermore, it generates detailed feedback based on the emotion data collected during the user's negotiation process.

[0515] Device functions and operation

[0516] The device functions as a VR / AR device, rendering negotiation scenarios received from the server into a virtual environment. It also analyzes the user's facial expressions and tone of voice using an emotion engine and feeds that emotional state back to the server. This function allows for real-time monitoring of how the user is feeling and responding to negotiations.

[0517] User experience

[0518] Users negotiate through simulated negotiation scenarios via their devices, and during this process, an emotion engine evaluates the user's emotional state. For example, if a user is experiencing stress, the system offers new solutions to negotiation techniques by suggesting a revision of the strategy.

[0519] Integration of feedback and emotion recognition

[0520] After a user's negotiation ends, the server analyzes data from the emotion engine and behavioral records to provide feedback based on the user's emotional responses. This feedback includes the user's emotional strengths, emotional responses to issues during negotiations, and specific advice for improvement. This allows users to enhance their emotional self-awareness and improve their negotiation skills.

[0521] By implementing this system, users can integrate emotion recognition into the social skills of negotiation as part of their learning process, enabling them to acquire more flexible and effective negotiation techniques. For example, sales representatives can hone their ability to appropriately manage their emotions during negotiations with customers and to predict and improve the outcome of those negotiations. Thus, this invention goes beyond merely practicing technical skills and supports the development of comprehensive negotiation abilities that include social and emotional skills.

[0522] The following describes the processing flow.

[0523] Step 1:

[0524] The user activates the device, puts on the VR / AR device, and starts the training session. This causes the device to send the user's scenario request to the server and prepare to begin processing.

[0525] Step 2:

[0526] The server receives user requests and runs a generative model to generate negotiation scenarios. Scenarios are dynamically created according to the user's skill level and objectives, and this data is transferred to the terminal.

[0527] Step 3:

[0528] The terminal renders the negotiation scenario received from the server into a VR / AR environment and presents it to the user. This allows the user to participate in a virtual negotiation situation.

[0529] Step 4:

[0530] Users negotiate through their devices, and during this process, an emotion engine built into the device analyzes the user's facial expressions and tone of voice in real time. The emotional state is evaluated on the spot and sent to the server.

[0531] Step 5:

[0532] The server receives user behavioral and emotional data in real time, integrates and analyzes the data. Based on this analysis, if the user's emotional responses during negotiations affect the scenario progression or responses, appropriate adjustments are made.

[0533] Step 6:

[0534] The user continues negotiations and receives dynamically adjusted scenarios from the server. This allows them to try out practical strategies tailored to their emotional state.

[0535] Step 7:

[0536] Once the negotiation session ends, the server generates detailed feedback based on the user's behavior and emotional data. This feedback includes an emotional rating, as well as points of success and suggestions for improvement in the negotiation.

[0537] Step 8:

[0538] The device presents the generated feedback to the user, who then uses it as guidance for learning in the next training session. The user then uses this feedback to improve their emotional management and negotiation skills.

[0539] (Example 2)

[0540] 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."

[0541] This invention aims to solve the problem in conventional negotiation training systems, which fail to effectively utilize users' emotional responses and thus cannot adequately improve users' skill understanding and emotional recognition. Furthermore, there is a need to provide real-time feedback based on the user's emotional state and realize an individualized learning experience.

[0542] 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.

[0543] In this invention, the server includes an information processing device means that includes a generation structure for generating negotiation scenarios in a virtual environment, an emotion analysis device means for analyzing the user's emotional state, and means for adaptively adjusting the progression of the scenario based on data from the emotion analysis device means. This enables the generation of personalized scenarios that take into account the user's emotional state and skill improvement.

[0544] A "virtual environment" is a space created using computer technology to construct a digital world different from the real world, within which users can interact and experience things.

[0545] A "negotiation scenario" is a set of hypothetical events or stories designed to simulate specific negotiation situations for learners, allowing them to practice advantageous negotiation strategies and techniques.

[0546] A "generative structure" is an algorithm or model that automatically constructs new content or procedures based on predefined prompts.

[0547] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and performs calculations and analyses according to various purposes.

[0548] "Display device means" refers to a device for visualizing information or scenarios on a computer or digital device to a user, and includes screens and displays.

[0549] "Users" refers to the collective term for individuals or organizations that operate or utilize a particular system or service.

[0550] "Emotional analysis device means" refers to technologies and devices for identifying and quantifying emotional responses from audio, video data, etc.

[0551] "Feedback" refers to information provided based on user behavior and reactions, with the aim of future improvements and enhancing learning.

[0552] Embodiments of the present invention are systems for conducting negotiation training in a virtual environment, with the aim of enabling users to more effectively improve their negotiation skills. This system consists of three main components: a server, a terminal, and a user.

[0553] Server Role

[0554] The server uses a generative AI model to create negotiation scenarios in a virtual environment. This involves using prompts that take into account the user's skill level and past negotiation results. For example, it might construct a prompt such as, "In price negotiations, propose how to respond if the customer objects that the price exceeds their budget." These generated scenarios are designed to give the user a realistic negotiation experience.

[0555] Device functions

[0556] The terminal receives negotiation scenarios sent from the server and visualizes them based on VR / AR technology. This terminal also plays a role in real-time data analysis of the user's facial expressions and voice tone using an emotion analysis device, and transmits this data to the server. This real-time data tracking makes it possible to provide adaptive feedback tailored to the user's emotional state.

[0557] User experience

[0558] Users participate in virtual negotiation scenarios via their devices, experiencing how their actions and decisions influence the scenario's progression. Detailed feedback is also provided from the server based on data collected by an emotion analysis device and records of their actions during the scenario. This allows users to learn while becoming aware of their emotional strengths and areas for improvement.

[0559] In this way, the coordinated operation of servers, terminals, and users supports not only the improvement of technical skills but also the development of emotional and social skills. This can contribute to the acquisition of practical skills, such as enabling sales representatives to flexibly adjust negotiation terms with customers.

[0560] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0561] Step 1:

[0562] The server receives the user's skill level and past negotiation history as input and uses a generative AI model to generate appropriate negotiation scenarios based on the prompt text. In this process, the AI ​​model generates scenarios tailored to the user's proficiency level and outputs them as scenario data. Specifically, the server refers to the user's past behavior logs and customizes the difficulty level and content.

[0563] Step 2:

[0564] The server sends the generated negotiation scenario to the terminal. The terminal takes the received scenario as input, renders the scenario in a virtual environment using VR / AR technology, and outputs it to the user as visual and auditory information. Through this operation, the user experiences a realistic negotiation situation. Specifically, the terminal loads 3D models, audio, and interaction elements to create a new negotiation scene.

[0565] Step 3:

[0566] Users participate in negotiation scenarios presented through their devices, advancing the negotiations through their statements and actions. The user's voice tone and facial expressions are continuously collected and analyzed by an emotion analysis device. This data is input from the device to the server as their current emotional state. Specifically, the device transmits user data to the server in real time, monitoring changes in the situation.

[0567] Step 4:

[0568] The server receives user emotion data and behavioral logs as input and analyzes them using a generative AI model. Based on the analysis results, it outputs suggestions to adaptively modify the scenario's progression. For example, if a high stress level is detected, the server adjusts the difficulty of the scenario to provide a more relaxed environment for the user to participate.

[0569] Step 5:

[0570] After the negotiation session ends, the server comprehensively analyzes all data, generates feedback for the user, and outputs it. This feedback includes emotional strengths, areas for improvement, and specific advice for the next session. The generated feedback is provided to the user via their terminal and used to improve future training. Specifically, the server automatically generates the feedback and sends it to the terminal.

[0571] (Application Example 2)

[0572] 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."

[0573] In recent years, virtual reality and augmented reality technologies have been used in many fields, but in training aimed at improving negotiation skills in particular, there is a lack of real-time feedback that takes into account the user's emotional state. As a result, users cannot fully understand their own emotional reactions, and comprehensive improvement of negotiation skills is difficult.

[0574] 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.

[0575] In this invention, the server includes an information processing device that includes a generation algorithm for generating a negotiation situation in a virtual reality or augmented reality environment; an information display device for displaying the negotiation situation; a device for recording the user's actions and statements and generating a detailed evaluation using the generation algorithm; a device that includes an emotion recognition engine and analyzes the user's emotional state; and a device for providing the evaluation to the user and improving negotiation skills. This makes it possible for the user to grasp their emotional reactions in real time during negotiation training and receive specific feedback based on them.

[0576] "Virtual reality" refers to an environment in a virtual three-dimensional space constructed using computer technology, within which users can have an immersive experience.

[0577] "Augmented reality" is a technology that provides an extended environment and experience of real space by overlaying computer-generated visual information onto real-world images and information.

[0578] A "generative algorithm" is a computational method that dynamically creates virtual content and scenarios based on user input or set conditions.

[0579] An "information processing device" is an electronic device that receives data, performs calculations and analyses based on that data, and outputs the necessary information.

[0580] An "information display device" is a device that presents information obtained through calculations and analyses to users visually or by other means.

[0581] An "emotion recognition engine" is a combination of software and hardware that analyzes data such as the user's facial expressions and vocalizations to determine the user's emotional state.

[0582] "Evaluation" refers to the results of judgments and diagnoses generated by analyzing information obtained based on the user's behavior and reactions.

[0583] "Negotiation skills" refer to the set of techniques and knowledge necessary to achieve one's goals through dialogue with others, and particularly include communication and negotiation skills.

[0584] This invention is configured to enable negotiation training in a virtual or augmented reality environment. The system includes an information processing device (server), an information display device (terminal), and an emotion recognition engine.

[0585] The server is responsible for dynamically generating negotiation scenarios based on the user's skill level and emotional responses using a generation algorithm. This generation algorithm utilizes open-source AI models and other tools to efficiently construct specific scenarios for the user.

[0586] The terminal functions as an information display device, outputting negotiation scenarios to the user through devices such as VR headsets and smart glasses. This allows the user to experience negotiations in real time within an interactive virtual environment. The emotion recognition engine analyzes the user's emotional state in real time based on their facial expressions and tone of voice. For example, it uses Microsoft's Azure Face API to accurately grasp the user's emotional state.

[0587] Users will leverage the comprehensive feedback provided by these technologies to improve their negotiation skills. This feedback includes specific advice tailored to the user's emotional responses, suggesting effective negotiation strategies.

[0588] As a concrete example, users can simulate problem-solving scenarios within their home in a VR environment and learn about the impact their words have on others through sentiment analysis. The generative AI model provides examples of prompts based on the user's emotions, suggesting improvements in real time.

[0589] Examples of prompts for a generative AI model include the following:

[0590] "Assess the current situation and analyze how the user is feeling emotionally. As a reaction, suggest advice or simulated scenarios to improve negotiation skills."

[0591] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0592] Step 1:

[0593] The server generates negotiation scenarios using a generation algorithm based on the user's skill level and emotional response. It receives user profile data and past negotiation records as input, performs calculations for scenario generation, and provides optimized negotiation scenarios as output.

[0594] Step 2:

[0595] The terminal presents negotiation scenarios received from the server to the user via an information display device. Using a VR headset or smart glasses, a virtual negotiation environment is rendered and visually presented to the user.

[0596] Step 3:

[0597] Users act and speak within a virtual environment in response to the displayed negotiation scenario. Their actions and statements are captured in real time by their devices and sent to the server, allowing for concrete user feedback.

[0598] Step 4:

[0599] The server analyzes user behavior data collected from terminals through an emotion recognition engine. It uses data such as the user's facial expressions and voice tone as input, and outputs the user's emotional state as a result.

[0600] Step 5:

[0601] Based on data from the emotion recognition engine, the server utilizes a generative AI model to generate user-appropriate feedback. It receives the results of emotion analysis as input, performs data calculations to generate appropriate advice and improvement suggestions, and outputs them.

[0602] Step 6:

[0603] The device receives feedback from the server and presents it to the user. The user receives the feedback and uses it to improve their negotiation skills. Specifically, advice is provided through visual and auditory means.

[0604] 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.

[0605] 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.

[0606] 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.

[0607] [Fourth Embodiment]

[0608] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0609] 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.

[0610] 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).

[0611] 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.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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".

[0621] The negotiation training system of the present invention comprises a generative model, a server, a terminal, and a user interface, and is designed to enable users to effectively improve their negotiation skills in a virtual reality or augmented reality environment.

[0622] Server functions and operation

[0623] The server is the central component of this invention and is equipped with a generative model. This generative model considers user profiles and historical training data to generate realistic negotiation scenarios. Upon receiving a user request, the server dynamically creates an appropriate negotiation scenario and sends the data to the terminal. The server is also responsible for collecting and analyzing user behavior data and generating detailed feedback.

[0624] Device functions and operation

[0625] The device functions as a VR headset or AR device, rendering scenario data received from the server into a virtual or augmented reality environment. Through this device, the user participates in a virtual negotiation scene. The device also records the user's experience by transmitting their movements and statements to the server in real time.

[0626] User experience

[0627] Users attempt negotiation strategies in response to situations presented within the scenario. The system records user statements and actions in real time, using this data as the basis for later feedback. For example, when a user proposes a compromise during price negotiations, its validity and effectiveness are evaluated based on simulations.

[0628] Feedback and skill improvement

[0629] After the scenario ends, the server provides feedback using a generative model based on the user's behavioral data. This feedback includes points of success, strategies that need improvement, and advice for the next scenario. This feedback information is delivered to the user via their device, allowing them to continuously learn and improve their negotiation skills.

[0630] Thus, the negotiation training system of the present invention provides an effective means of improving skills through diverse negotiation experiences without incurring risk. For example, a new business employee can practice contract negotiations with a virtual customer and prepare for negotiations in a real-world environment. This system goes beyond mere theoretical learning, creating an environment where users learn from experience and improve their practical abilities.

[0631] The following describes the processing flow.

[0632] Step 1:

[0633] The user launches the terminal and selects to start a training session. Based on the user's selection, the terminal will send a session request to the server. The request will include the user's skill level and the type of negotiation scenario they prefer.

[0634] Step 2:

[0635] Based on the received request, the server generates an appropriate negotiation scenario using a generative model. The generated scenario data includes the background of the negotiation and the characteristics of the other party, and this data is sent to the terminal.

[0636] Step 3:

[0637] The terminal receives scenario data sent from the server and renders it in a virtual or augmented reality environment. This prepares the user to experience negotiations in the virtual environment.

[0638] Step 4:

[0639] Users participate in a virtual environment provided through their terminal and negotiate according to a scenario. Their statements and actions during negotiations are recorded in real time.

[0640] Step 5:

[0641] The device sends user behavior data to the server. The server collects this data and uses it to analyze the behavior.

[0642] Step 6:

[0643] The server analyzes the collected user behavior data and generates feedback using a generative model. This feedback includes the user's negotiation strengths and areas for improvement.

[0644] Step 7:

[0645] The server sends the generated feedback to the terminal. The terminal displays this feedback to the user, providing it in a visually easy-to-understand format.

[0646] Step 8:

[0647] Users review feedback and use it to set their next learning goals to improve their negotiation skills. This enables continuous skill development.

[0648] (Example 1)

[0649] 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".

[0650] The challenge lies in providing concrete and practical training methods that effectively improve negotiation skills. In particular, there is a need for a system that allows learners to experience and learn through actual simulation environments, rather than relying solely on traditional theoretical learning.

[0651] 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.

[0652] In this invention, the server includes an information processing device means that incorporates a generation program for creating a negotiation experience in a virtual reality or augmented reality environment; an output device means for visualizing the negotiation experience; and means for collecting user behavior and statements and generating detailed improvement information using the generation program. This enables users to effectively improve their skills through actual dialogue and actions in various negotiation scenarios.

[0653] "Virtual reality" is a technology that uses computer technology to create a virtual environment that does not exist in reality, allowing users to interact within that environment.

[0654] Augmented reality is a technology that allows users to experience both real and virtual elements simultaneously by overlaying digital information onto the real environment.

[0655] An "information processing device" is a general term for devices and systems used to process data and generate or manage necessary information.

[0656] An "output device" is a device or system that presents data in a form that is understandable to humans, such as in the form of audio or video.

[0657] A "generator program" is a set of instructions or code that runs on a computer to create digital content or scenarios for a specific purpose.

[0658] "User" refers to an individual or group that seeks to improve their negotiation skills using this system.

[0659] "Improvement information" is a general term for feedback and advice given to improve skills based on the evaluation results of users' actions and statements.

[0660] This invention provides a training system for effectively improving negotiation skills in virtual reality and augmented reality environments, offering an innovative method that utilizes generative AI models.

[0661] The server functions as the core of this system, acting as an information processing device. Leveraging a generative AI model, it generates negotiation scenarios based on conditions specified by the user through prompt messages. The generative AI model generates scenarios based on a rich source of information, including historical data, ensuring they are appropriate to the user's skill level. The server also transmits these scenarios to terminals in real time via the network.

[0662] The terminal receives scenario data provided by the server and functions as an output device in a virtual reality and augmented reality environment. Specifically, it visualizes the scenario using VR headsets and AR devices, creating an environment where users can immerse themselves in the scenario and interact with it. Through this terminal, users can converse with characters in the scenario and test their actual negotiation skills.

[0663] Users experience negotiation scenarios through interactions in a virtual environment. For example, in a scenario where they negotiate the price of a new product, the user proposes a compromise to the other party. During this process, the user's actions and statements are transmitted in real time from the terminal to the server and stored.

[0664] A concrete example of a prompt message would be, "Generate a scenario in which the user negotiates the price of a new product. In this scenario, set the user as a rookie salesperson attempting their first negotiation." This allows the user to try different negotiation techniques within a realistic scenario.

[0665] Thus, the present invention provides a system that enables practical and efficient training for users to effectively improve their negotiation skills.

[0666] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0667] Step 1:

[0668] The server receives a prompt from the user. The input includes the conditions of the negotiation scenario specified by the user. This input is analyzed and filtered for application to the generative AI model. As a result, the elements necessary for a detailed negotiation scenario are extracted.

[0669] Step 2:

[0670] The server generates negotiation scenarios using a generative AI model. The input information consists of user prompts and historical training data. The server combines this data to perform calculations and generate realistic negotiation scenarios. The output is negotiation scenario data appropriate to the user's skill level.

[0671] Step 3:

[0672] The server sends the generated negotiation scenario to the terminal. This scenario data is input to the terminal, which then uses it to render it in a virtual reality or augmented reality environment. The output is the negotiation scene presented to the user as a visualized 3D environment.

[0673] Step 4:

[0674] The user conducts negotiations in a virtual or augmented reality environment presented through the device. User input includes voice commands and gestures. The device captures these in real time and sends them to the server. As a result of this process, the user's behavior history is recorded as output data.

[0675] Step 5:

[0676] The server analyzes user behavior data. This process uses a generative AI model to generate detailed feedback based on recorded input data (user statements and actions). The output is feedback information provided to the user, including areas for improvement and effective strategies.

[0677] Step 6:

[0678] The server sends the generated feedback to the terminal. The terminal presents this to the user, providing information to help improve skills in subsequent scenarios. The user can use this feedback to try different strategies in the next negotiation scenario. The output is a learning-based improvement strategy.

[0679] (Application Example 1)

[0680] 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".

[0681] Traditional negotiation skills training has been limited to theoretical learning and has been insufficient in improving the practical negotiation skills of sales staff in physical stores. Furthermore, there has been a lack of systems that provide realistic negotiation scenarios and enable sales staff to improve their practical skills. Against this backdrop, there is a need for a means to effectively enhance sales staff's skills through simulated customer negotiations in a virtual environment.

[0682] 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.

[0683] In this invention, the server includes an information processing device that includes a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment, a video display device for displaying the negotiation scenarios, and a data processing device that records user actions and statements and generates detailed feedback. This makes it possible for salespeople to practically improve their product promotion techniques through negotiations with simulated buyers.

[0684] "Virtual reality" is a technology that provides a realistic experience within a computer-generated three-dimensional virtual environment.

[0685] Augmented reality is a technology that overlays computer-generated visual information onto images and information from the real world.

[0686] A "generative model" is an algorithm that automatically creates negotiation scenarios in a virtual environment based on user profiles and historical data.

[0687] An "information processing device" is a device that uses a computer to collect, process, and analyze data.

[0688] A "video display device" is a device that displays images and provides visual information to the user, and includes displays and head-mounted displays.

[0689] A "data processing device" is a device that records user input data, performs analysis based on that data, and generates feedback.

[0690] A "simulated buyer" is a digital character generated by a computer within a virtual environment that behaves like a real customer.

[0691] "Product promotion techniques" refer to the skills that sellers use to propose products to customers and effectively communicate their appeal.

[0692] The server generates negotiation scenarios in a virtual or augmented reality environment using a generative model. The generative AI model within the server dynamically designs specific negotiation scenes, taking into account the user's skill level and past training data.

[0693] This system utilizes hardware such as VR headsets like the Oculus Quest 2 or smart glasses. Through these, users experience generated negotiation scenarios via video displays. Within these scenarios, users can interact with virtual buyers and hone their product promotion skills.

[0694] The device records the user's actions and statements in real time via sensors to a data processing unit, which then transmits the data to a server. The server analyzes the received data and generates detailed feedback based on the user's choices and strategies. This feedback is then sent back to the device to improve the user's negotiation skills.

[0695] As a concrete example, consider a scenario where a user proposes a smartphone to a customer in a virtual world. An example of a prompt might be, "Create a scenario in which you propose the optimal response based on the customer's reaction during price negotiations for a new product." Based on this prompt, the server generates a scenario, providing a platform where salespeople can practice under conditions similar to real-world store operations. This allows participants to effectively acquire negotiation skills that are closer to reality in a virtual space.

[0696] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0697] Step 1:

[0698] The server receives a request from the user. The request includes the user's skill level and training objectives as input. The server then sends a prompt to the generative AI model, initiating the generation of negotiation scenarios. The generative AI model designs a scenario tailored to the user's skills and outputs it as data.

[0699] Step 2:

[0700] The server sends the generated negotiation scenario to the terminal. The terminal renders the received scenario data into a virtual or augmented reality environment. The engine uses software such as Unity to realistically depict the virtual negotiation scene. In this process, the input is the negotiation scenario data, and the output is the virtual environment experienced by the user.

[0701] Step 3:

[0702] Users participate in virtual negotiation scenarios through their devices. This allows them to interact with a purchasing simulator and gain practical experience in improving their product promotion techniques. User actions and statements are recorded in real time by sensors. The input is user behavior data, which is sent to the server.

[0703] Step 4:

[0704] The server analyzes behavioral data submitted by the user and generates detailed feedback using a generative AI model. A data processing unit performs this task, evaluating the effectiveness and areas for improvement of the user's negotiation strategy. The output is the feedback information provided to the user.

[0705] Step 5:

[0706] The server sends the generated feedback to the terminal and displays it to the user. Through this feedback, the user can learn which skills were effective and which strategies should be improved. This provides specific guidance for improving strategies in the next virtual negotiation. The output is a suggestion of specific actions the user should take next.

[0707] 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.

[0708] The system of this invention is designed to conduct negotiation training in a virtual reality or augmented reality environment and incorporates an emotion engine for recognizing and analyzing the user's emotional state. This enables more user-centered learning that takes the user's emotional responses into account.

[0709] Server functions and operation

[0710] The server, equipped with a generative model and an emotion engine, is responsible for generating negotiation scenarios and analyzing emotion data. The generative model generates appropriate negotiation scenarios based on the user's skill level and emotional responses, and sends this data to the terminal. Furthermore, it generates detailed feedback based on the emotion data collected during the user's negotiation process.

[0711] Device functions and operation

[0712] The device functions as a VR / AR device, rendering negotiation scenarios received from the server into a virtual environment. It also analyzes the user's facial expressions and tone of voice using an emotion engine and feeds that emotional state back to the server. This function allows for real-time monitoring of how the user is feeling and responding to negotiations.

[0713] User experience

[0714] Users negotiate through simulated negotiation scenarios via their devices, and during this process, an emotion engine evaluates the user's emotional state. For example, if a user is experiencing stress, the system offers new solutions to negotiation techniques by suggesting a revision of the strategy.

[0715] Integration of feedback and emotion recognition

[0716] After a user's negotiation ends, the server analyzes data from the emotion engine and behavioral records to provide feedback based on the user's emotional responses. This feedback includes the user's emotional strengths, emotional responses to issues during negotiations, and specific advice for improvement. This allows users to enhance their emotional self-awareness and improve their negotiation skills.

[0717] By implementing this system, users can integrate emotion recognition into the social skills of negotiation as part of their learning process, enabling them to acquire more flexible and effective negotiation techniques. For example, sales representatives can hone their ability to appropriately manage their emotions during negotiations with customers and to predict and improve the outcome of those negotiations. Thus, this invention goes beyond merely practicing technical skills and supports the development of comprehensive negotiation abilities that include social and emotional skills.

[0718] The following describes the processing flow.

[0719] Step 1:

[0720] The user activates the device, puts on the VR / AR device, and starts the training session. This causes the device to send the user's scenario request to the server and prepare to begin processing.

[0721] Step 2:

[0722] The server receives user requests and runs a generative model to generate negotiation scenarios. Scenarios are dynamically created according to the user's skill level and objectives, and this data is transferred to the terminal.

[0723] Step 3:

[0724] The terminal renders the negotiation scenario received from the server into a VR / AR environment and presents it to the user. This allows the user to participate in a virtual negotiation situation.

[0725] Step 4:

[0726] Users negotiate through their devices, and during this process, an emotion engine built into the device analyzes the user's facial expressions and tone of voice in real time. The emotional state is evaluated on the spot and sent to the server.

[0727] Step 5:

[0728] The server receives user behavioral and emotional data in real time, integrates and analyzes the data. Based on this analysis, if the user's emotional responses during negotiations affect the scenario progression or responses, appropriate adjustments are made.

[0729] Step 6:

[0730] The user continues negotiations and receives dynamically adjusted scenarios from the server. This allows them to try out practical strategies tailored to their emotional state.

[0731] Step 7:

[0732] Once the negotiation session ends, the server generates detailed feedback based on the user's behavior and emotional data. This feedback includes an emotional rating, as well as points of success and suggestions for improvement in the negotiation.

[0733] Step 8:

[0734] The device presents the generated feedback to the user, who then uses it as guidance for learning in the next training session. The user then uses this feedback to improve their emotional management and negotiation skills.

[0735] (Example 2)

[0736] 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".

[0737] This invention aims to solve the problem in conventional negotiation training systems, which fail to effectively utilize users' emotional responses and thus cannot adequately improve users' skill understanding and emotional recognition. Furthermore, there is a need to provide real-time feedback based on the user's emotional state and realize an individualized learning experience.

[0738] 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.

[0739] In this invention, the server includes an information processing device means that includes a generation structure for generating negotiation scenarios in a virtual environment, an emotion analysis device means for analyzing the user's emotional state, and means for adaptively adjusting the progression of the scenario based on data from the emotion analysis device means. This enables the generation of personalized scenarios that take into account the user's emotional state and skill improvement.

[0740] A "virtual environment" is a space created using computer technology to construct a digital world different from the real world, within which users can interact and experience things.

[0741] A "negotiation scenario" is a set of hypothetical events or stories designed to simulate specific negotiation situations for learners, allowing them to practice advantageous negotiation strategies and techniques.

[0742] A "generative structure" is an algorithm or model that automatically constructs new content or procedures based on predefined prompts.

[0743] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and performs calculations and analyses according to various purposes.

[0744] "Display device means" refers to a device for visualizing information or scenarios on a computer or digital device to a user, and includes screens and displays.

[0745] "Users" refers to the collective term for individuals or organizations that operate or utilize a particular system or service.

[0746] "Emotional analysis device means" refers to technologies and devices for identifying and quantifying emotional responses from audio, video data, etc.

[0747] "Feedback" refers to information provided based on user behavior and reactions, with the aim of future improvements and enhancing learning.

[0748] Embodiments of the present invention are systems for conducting negotiation training in a virtual environment, with the aim of enabling users to more effectively improve their negotiation skills. This system consists of three main components: a server, a terminal, and a user.

[0749] Server Role

[0750] The server uses a generative AI model to create negotiation scenarios in a virtual environment. This involves using prompts that take into account the user's skill level and past negotiation results. For example, it might construct a prompt such as, "In price negotiations, propose how to respond if the customer objects that the price exceeds their budget." These generated scenarios are designed to give the user a realistic negotiation experience.

[0751] Device functions

[0752] The terminal receives negotiation scenarios sent from the server and visualizes them based on VR / AR technology. This terminal also plays a role in real-time data analysis of the user's facial expressions and voice tone using an emotion analysis device, and transmits this data to the server. This real-time data tracking makes it possible to provide adaptive feedback tailored to the user's emotional state.

[0753] User experience

[0754] Users participate in virtual negotiation scenarios via their devices, experiencing how their actions and decisions influence the scenario's progression. Detailed feedback is also provided from the server based on data collected by an emotion analysis device and records of their actions during the scenario. This allows users to learn while becoming aware of their emotional strengths and areas for improvement.

[0755] In this way, the coordinated operation of servers, terminals, and users supports not only the improvement of technical skills but also the development of emotional and social skills. This can contribute to the acquisition of practical skills, such as enabling sales representatives to flexibly adjust negotiation terms with customers.

[0756] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0757] Step 1:

[0758] The server receives the user's skill level and past negotiation history as input and uses a generative AI model to generate appropriate negotiation scenarios based on the prompt text. In this process, the AI ​​model generates scenarios tailored to the user's proficiency level and outputs them as scenario data. Specifically, the server refers to the user's past behavior logs and customizes the difficulty level and content.

[0759] Step 2:

[0760] The server sends the generated negotiation scenario to the terminal. The terminal takes the received scenario as input, renders the scenario in a virtual environment using VR / AR technology, and outputs it to the user as visual and auditory information. Through this operation, the user experiences a realistic negotiation situation. Specifically, the terminal loads 3D models, audio, and interaction elements to create a new negotiation scene.

[0761] Step 3:

[0762] Users participate in negotiation scenarios presented through their devices, advancing the negotiations through their statements and actions. The user's voice tone and facial expressions are continuously collected and analyzed by an emotion analysis device. This data is input from the device to the server as their current emotional state. Specifically, the device transmits user data to the server in real time, monitoring changes in the situation.

[0763] Step 4:

[0764] The server receives user emotion data and behavioral logs as input and analyzes them using a generative AI model. Based on the analysis results, it outputs suggestions to adaptively modify the scenario's progression. For example, if a high stress level is detected, the server adjusts the difficulty of the scenario to provide a more relaxed environment for the user to participate.

[0765] Step 5:

[0766] After the negotiation session ends, the server comprehensively analyzes all data, generates feedback for the user, and outputs it. This feedback includes emotional strengths, areas for improvement, and specific advice for the next session. The generated feedback is provided to the user via their terminal and used to improve future training. Specifically, the server automatically generates the feedback and sends it to the terminal.

[0767] (Application Example 2)

[0768] 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".

[0769] In recent years, virtual reality and augmented reality technologies have been used in many fields, but in training aimed at improving negotiation skills in particular, there is a lack of real-time feedback that takes into account the user's emotional state. As a result, users cannot fully understand their own emotional reactions, and comprehensive improvement of negotiation skills is difficult.

[0770] 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.

[0771] In this invention, the server includes an information processing device that includes a generation algorithm for generating a negotiation situation in a virtual reality or augmented reality environment; an information display device for displaying the negotiation situation; a device for recording the user's actions and statements and generating a detailed evaluation using the generation algorithm; a device that includes an emotion recognition engine and analyzes the user's emotional state; and a device for providing the evaluation to the user and improving negotiation skills. This makes it possible for the user to grasp their emotional reactions in real time during negotiation training and receive specific feedback based on them.

[0772] "Virtual reality" refers to an environment in a virtual three-dimensional space constructed using computer technology, within which users can have an immersive experience.

[0773] "Augmented reality" is a technology that provides an extended environment and experience of real space by overlaying computer-generated visual information onto real-world images and information.

[0774] A "generative algorithm" is a computational method that dynamically creates virtual content and scenarios based on user input or set conditions.

[0775] An "information processing device" is an electronic device that receives data, performs calculations and analyses based on that data, and outputs the necessary information.

[0776] An "information display device" is a device that presents information obtained through calculations and analyses to users visually or by other means.

[0777] An "emotion recognition engine" is a combination of software and hardware that analyzes data such as the user's facial expressions and vocalizations to determine the user's emotional state.

[0778] "Evaluation" refers to the results of judgments and diagnoses generated by analyzing information obtained based on the user's behavior and reactions.

[0779] "Negotiation skills" refer to the set of techniques and knowledge necessary to achieve one's goals through dialogue with others, and particularly include communication and negotiation skills.

[0780] This invention is configured to enable negotiation training in a virtual or augmented reality environment. The system includes an information processing device (server), an information display device (terminal), and an emotion recognition engine.

[0781] The server is responsible for dynamically generating negotiation scenarios based on the user's skill level and emotional responses using a generation algorithm. This generation algorithm utilizes open-source AI models and other tools to efficiently construct specific scenarios for the user.

[0782] The terminal functions as an information display device, outputting negotiation scenarios to the user through devices such as VR headsets and smart glasses. This allows the user to experience negotiations in real time within an interactive virtual environment. The emotion recognition engine analyzes the user's emotional state in real time based on their facial expressions and tone of voice. For example, it uses Microsoft's Azure Face API to accurately grasp the user's emotional state.

[0783] Users will leverage the comprehensive feedback provided by these technologies to improve their negotiation skills. This feedback includes specific advice tailored to the user's emotional responses, suggesting effective negotiation strategies.

[0784] As a concrete example, users can simulate problem-solving scenarios within their home in a VR environment and learn about the impact their words have on others through sentiment analysis. The generative AI model provides examples of prompts based on the user's emotions, suggesting improvements in real time.

[0785] Examples of prompts for a generative AI model include the following:

[0786] "Assess the current situation and analyze how the user is feeling emotionally. As a reaction, suggest advice or simulated scenarios to improve negotiation skills."

[0787] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0788] Step 1:

[0789] The server generates negotiation scenarios using a generation algorithm based on the user's skill level and emotional response. It receives user profile data and past negotiation records as input, performs calculations for scenario generation, and provides optimized negotiation scenarios as output.

[0790] Step 2:

[0791] The terminal presents negotiation scenarios received from the server to the user via an information display device. Using a VR headset or smart glasses, a virtual negotiation environment is rendered and visually presented to the user.

[0792] Step 3:

[0793] Users act and speak within a virtual environment in response to the displayed negotiation scenario. Their actions and statements are captured in real time by their devices and sent to the server, allowing for concrete user feedback.

[0794] Step 4:

[0795] The server analyzes user behavior data collected from terminals through an emotion recognition engine. It uses data such as the user's facial expressions and voice tone as input, and outputs the user's emotional state as a result.

[0796] Step 5:

[0797] Based on data from the emotion recognition engine, the server utilizes a generative AI model to generate user-appropriate feedback. It receives the results of emotion analysis as input, performs data calculations to generate appropriate advice and improvement suggestions, and outputs them.

[0798] Step 6:

[0799] The device receives feedback from the server and presents it to the user. The user receives the feedback and uses it to improve their negotiation skills. Specifically, advice is provided through visual and auditory means.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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."

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] The following is further disclosed regarding the embodiments described above.

[0822] (Claim 1)

[0823] A server means including a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment,

[0824] A terminal means for displaying the aforementioned negotiation scenario,

[0825] A means for recording user behavior and statements and generating detailed feedback using the generative model,

[0826] The aforementioned feedback is provided to the user as a means to improve negotiation skills,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, wherein the generation model further comprises means for adjusting negotiation scenarios based on the user's skill level.

[0830] (Claim 3)

[0831] The system according to claim 1, wherein the terminal means further comprises means for reflecting the user's choices and actions in a negotiation scenario in real time and providing feedback to the server.

[0832] "Example 1"

[0833] (Claim 1)

[0834] Information processing device means that incorporates a generation program for creating a negotiation experience in a virtual reality or augmented reality environment,

[0835] Output device means for visualizing the aforementioned negotiation experience,

[0836] A means for collecting user behavior and statements and generating detailed improvement information using the generation program,

[0837] The aforementioned improvement information is presented to the user as a means to improve negotiation skills,

[0838] ...

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, wherein the generation program further comprises means for adjusting the negotiation experience based on the user's skill level.

[0842] (Claim 3)

[0843] The system according to claim 1, wherein the output device means further comprises means for immediately reflecting the user's choices and behavior in the negotiation experience and returning them to the information processing device.

[0844] "Application Example 1"

[0845] (Claim 1)

[0846] An information processing device including a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment,

[0847] A video display device for displaying the aforementioned negotiation scenario,

[0848] A data processing device that records user actions and statements and generates detailed feedback using the generative model,

[0849] An information provision device for providing the aforementioned feedback to the user and improving negotiation skills,

[0850] Training methods to improve product promotion techniques through simulated negotiations with buyers,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, wherein the generation model further comprises data adjustment means for adjusting negotiation scenarios based on the user's skill level.

[0854] (Claim 3)

[0855] The system according to claim 1, wherein the video display device further comprises data communication means for reflecting the user's choices and actions in a negotiation scenario in real time and feeding them back to the information processing device.

[0856] "Example 2 of combining an emotion engine"

[0857] (Claim 1)

[0858] Information processing device means including a generation structure for generating negotiation scenarios in a virtual environment,

[0859] A display device for displaying the aforementioned negotiation scenario,

[0860] A means for recording user behavior and statements, and generating detailed information using the aforementioned generation structure,

[0861] The aforementioned information is provided to users as a means to improve their skills,

[0862] An emotion analysis device means for analyzing the emotional state of a user,

[0863] A means for adaptively adjusting the progression of the scenario based on data from the aforementioned emotion analysis device means,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, wherein the generation structure further comprises means for adjusting negotiation scenarios based on the user's ability level and emotional response.

[0867] (Claim 3)

[0868] The system according to claim 1, wherein the display device means further comprises means for reflecting the user's choices and actions in a negotiation scenario in real time and feeding them back to the information processing device.

[0869] "Application example 2 when combining with an emotional engine"

[0870] (Claim 1)

[0871] An information processing device including a generation algorithm for generating negotiation situations in a virtual reality or augmented reality environment,

[0872] An information display device for displaying the negotiation status,

[0873] A device that records the user's actions and statements and generates a detailed evaluation using the generation algorithm,

[0874] A device that includes an emotion recognition engine and analyzes the user's emotional state,

[0875] The aforementioned evaluation is provided to the user, and the device is for improving negotiation skills.

[0876] A system that includes this.

[0877] (Claim 2)

[0878] The system according to claim 1, wherein the generation algorithm further comprises a device that adjusts the negotiation situation based on the user's skill level and emotional response.

[0879] (Claim 3)

[0880] The system according to claim 1, wherein the information display device further comprises a device that immediately reflects the user's choices and actions in the negotiation situation and returns the evaluation to the information processing device. [Explanation of Symbols]

[0881] 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. An information processing device including a generative model for generating negotiation scenarios in a virtual reality or augmented reality environment, A video display device for displaying the aforementioned negotiation scenario, A data processing device that records user behavior and statements and generates detailed feedback using the generative model, An information provision device for providing the aforementioned feedback to the user and improving negotiation skills, Training methods to improve product promotion techniques through simulated negotiations with buyers, A system that includes this.

2. The system according to claim 1, wherein the generation model further comprises data adjustment means for adjusting negotiation scenarios based on the user's skill level.

3. The system according to claim 1, wherein the video display device further comprises data communication means for reflecting the user's choices and actions in a negotiation scenario in real time and feeding them back to the information processing device.

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