system

Abstract

We provide the system. [Solution] A means of acquiring voice data to analyze the conversations of sales representatives, A means for executing an algorithm to analyze customer emotions based on the aforementioned audio data, A means for generating advice in real time based on the aforementioned analysis results, Means of utilizing virtual reality or augmented reality technology to visually provide generated advice to sales representatives, A means of evaluating whether the sales representative's behavior changed as a result of the aforementioned advice and collecting feedback on that change, A means of updating the algorithm based on feedback, A system that includes this.

Description

Technical Field

[0005]

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In business activities, it is difficult for salespersons to accurately and quickly grasp customers' feelings and interests on the spot and make optimal responses. Also, due to the lack of appropriate real-time advice, the efficiency of sales decreases, and there is a risk of losing many opportunities. As a result, there is a problem that sales performance cannot be maximized and the improvement of sales strategies is limited.

Means for Solving the Problems

[0005] This invention provides a system that acquires and analyzes voice data in real time to identify customer emotions. Furthermore, it improves sales efficiency by generating appropriate sales strategies and advice based on the analysis results and providing them visually to sales representatives using virtual reality or augmented reality technology. In addition, by collecting feedback and updating the algorithm, it enables more refined sales strategies. In this way, it helps sales representatives strengthen their on-the-ground response capabilities and improve sales performance.

[0006] "Audio data" refers to digital data that records voice communication between sales representatives and customers.

[0007] "Customer emotions" refer to the emotional state and tone that customers exhibit during conversations, and are identifiable through data analysis.

[0008] An "algorithm" is a method that includes a series of computational steps or mathematical formulas designed to complete a specific task.

[0009] "Advice" refers to advice given to sales representatives that recommends appropriate actions based on the situation at hand.

[0010] "Visual presentation" refers to providing information through visual representations, thereby enabling recipients to intuitively understand the content.

[0011] "Virtual reality technology" is a technology that allows users to experience a computer-generated three-dimensional virtual environment as if it were the real world.

[0012] Augmented reality technology is a technology that overlays digital information onto the real world, making it possible to merge the real world with digital content.

[0013] "Collecting feedback" is the process of recording information provided by system users about the actions they have taken and the results they have achieved.

[0014] "Updating an algorithm" refers to adjusting or improving an algorithm based on new data and feedback to make it function more accurately or efficiently. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] 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

[0016] 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.

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

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0032] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] This invention provides a system that enables efficient support in sales activities. This system consistently handles everything from real-time collection of voice data and customer sentiment analysis to recommending appropriate countermeasures and visually presenting those countermeasures to sales representatives. The following describes how each element works together and how the invention is implemented.

[0037] First, the terminal acquires the conversation between the sales representative and the customer as audio data in real time. This audio data includes the customer's and sales representative's statements, tone, and speed during the conversation. Next, the server analyzes this audio data using an algorithm to understand the customer's emotions. Based on this emotion analysis, the server uses AI to generate optimal sales advice.

[0038] The generated advice is delivered to the sales representative by the device through virtual reality (VR) or augmented reality (AR) visualization technology. This allows the sales representative to receive real-time, interactive, and intuitive advice.

[0039] For example, if a customer expresses interest in the price of a product, the server can instantly generate advice regarding price competitiveness. This advice is presented to the sales representative through a terminal in VR / AR format. The sales representative can immediately understand the specific approach through the visual guidance and incorporate it into their interactions with the customer. The user (sales representative) also provides feedback to the system on the customer's reaction to the actions taken. This feedback information is then used by the server to generate advice for future interactions, enabling more accurate sales support throughout the entire system.

[0040] Thus, the present invention realizes a system that enables rapid and precise responses in sales situations and contributes to improving sales performance.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The device records conversations between sales representatives and customers as audio data in real time. This recording is continuous from the start to the end of the conversation, and the necessary sound quality is ensured using a microphone.

[0044] Step 2:

[0045] The terminal encrypts the recorded audio data and sends it to the server via a secure communication channel. To minimize communication delays, the audio data is segmented and transmitted sequentially.

[0046] Step 3:

[0047] The server processes the received audio data. Using natural language processing techniques, it breaks down the content of the utterances and analyzes key phrases and customer emotions. This includes tone analysis and speed analysis.

[0048] Step 4:

[0049] The server generates optimal sales advice using an AI model based on the results of sentiment analysis. For example, if a customer is interested in price, it prepares a script to emphasize cost competitiveness.

[0050] Step 5:

[0051] The server converts the generated advice into virtual or augmented reality format and creates visualization data. This data is designed to be intuitively understandable for sales representatives.

[0052] Step 6:

[0053] The terminal uses visualization data received from the server to provide virtual or augmented reality navigation to sales representatives. This allows sales representatives to receive real-time visual advice.

[0054] Step 7:

[0055] The user (sales representative) enters feedback into the terminal regarding the results of their sales activities. This feedback includes customer reactions and sales results.

[0056] Step 8:

[0057] The server uses the collected feedback to update the AI ​​model, improving the accuracy of advice for future sales activities. This process is continuous, accelerating the system's learning.

[0058] (Example 1)

[0059] 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."

[0060] For sales representatives to engage with customers more efficiently and effectively, they need to quickly and accurately grasp customer emotions and interests and respond appropriately based on that understanding. However, with traditional methods, it was difficult for sales representatives to instantly analyze customer emotions and devise optimal responses. Furthermore, the lack of real-time advice and visualization of such information limited the potential for improving sales efficiency.

[0061] 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.

[0062] In this invention, the server includes means for acquiring the conversation between the sales representative and the customer as audio information in real time, means for converting the audio information into a digital format and transferring it to the server for analysis, and means for executing an emotion analysis algorithm using the audio information received by the server to understand the customer's emotions. This makes it possible to generate advice in real time based on emotion analysis and to provide it visually.

[0063] A "sales representative" is someone whose job is to propose and sell a company's or organization's products and services to customers.

[0064] "Audio information" refers to data recorded in sound form, including conversations between sales representatives and customers, and includes information such as the tone, speed, and content of the conversation.

[0065] A "server" is an information processing device that receives and processes voice information over a network and performs necessary analysis and generation.

[0066] An "emotion analysis algorithm" is a series of computational procedures for identifying a customer's emotions from voice information, and a method for determining the customer's psychological state based on the results.

[0067] A "generative AI model" is a framework of artificial intelligence trained to create new information based on past data, and is particularly a technology for generating advice through natural language processing.

[0068] "Virtual reality or augmented reality technology" is a technology that uses digital data to provide a visual experience that blends with the real world, and visualizes information for sales representatives in real time.

[0069] "Customer response information" refers to data that records the reactions and responses that customers gave to the actions of sales representatives.

[0070] "Feedback" refers to input information used to improve future advice provided by the system, based on customer response data.

[0071] This invention is a system designed to enable sales representatives to communicate more effectively with customers. The system supports a series of processes, from acquiring and analyzing voice information, sentiment analysis, generating advice using generative AI models, and visualizing the information using virtual or augmented reality technology.

[0072] Specifically, the terminal captures conversations between sales representatives and customers in real time, acquiring audio information. This requires a microphone for voice input and software for digital conversion of the data. The collected audio information is converted to a digital format and then securely transferred to a server.

[0073] The server receives audio information and processes it using a specific speech analysis algorithm. This algorithm utilizes open-source speech processing libraries or custom models. Based on the analysis results, the server leverages a generative AI model to generate optimal sales advice in real time. Examples of generative AI models include libraries and platforms for natural language processing.

[0074] The generated advice is visually presented to sales representatives via their devices. This presentation utilizes VR / AR technology, displaying information using platforms such as Unity and Unreal Engine. Sales representatives can then use this information to provide more effective service to customers.

[0075] For example, if a customer expresses concern about the price of a particular product, the server generates a prompt message to emphasize price competitiveness. Based on this prompt message, the generating AI model suggests an appropriate sales strategy. A prompt message such as, "The customer is dissatisfied with the price of product A. Please propose a new approach to this customer to emphasize features other than price," might be used.

[0076] Thus, the present invention is a system that combines advanced emotion analysis and generation AI technology based on voice information to enable rapid and precise responses in sales situations, and as a result supports the improvement of sales performance.

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

[0078] Step 1:

[0079] The terminal captures conversations between sales representatives and customers in real time and acquires them as audio information. Specifically, it records the conversation using an audio input device (microphone) and converts it to a digital format. The input is an analog audio signal, and the output is digital audio data. This data includes the content, tone, and speed of the conversation.

[0080] Step 2:

[0081] The terminal securely transmits the acquired digital audio data to the server. Encryption protocols such as SSL / TLS are used for data transfer. The input is digital audio data, and the output is an encrypted data stream sent to the server.

[0082] Step 3:

[0083] The server executes an emotion analysis algorithm to analyze the received audio data. Specifically, it uses an audio processing library to analyze the tone, speed, and volume patterns of the voice to identify the customer's emotional state. The input is digital audio data, and the output is the result of the emotion analysis (e.g., labeling whether the customer is satisfied, dissatisfied, or interested).

[0084] Step 4:

[0085] The server uses a generative AI model to generate optimal sales advice based on the results of sentiment analysis. Specifically, prompt sentences are input to the AI ​​model, and text regarding sales strategies is generated as output. The input consists of the sentiment analysis results and related prompt sentences, and the output is the generated advice.

[0086] Step 5:

[0087] The device provides generated advice to sales representatives using virtual reality (VR) or augmented reality (AR) technology. Specifically, it visualizes the advice using Unity or Unreal Engine and displays it within the sales representative's field of view. The input is the generated advice text, and the output is the visually represented information.

[0088] Step 6:

[0089] The user (sales representative) conducts the conversation with the customer based on the visually presented advice. They observe the customer's reactions in real time and input them into the system as feedback. The input is the customer's reaction, and the output is the feedback information.

[0090] Step 7:

[0091] The device collects user feedback information and sends it to the server. The server uses this feedback to update the algorithm and improve the performance of future generative AI models. The input is the feedback information, and the output is the parameters of the updated algorithm.

[0092] (Application Example 1)

[0093] 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."

[0094] In conversations between sales representatives and customers, accurately understanding customer emotions and interests and providing appropriate customer service strategies in real time based on that understanding is difficult. Therefore, an efficient and flexible support system is needed to maximize sales effectiveness.

[0095] 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.

[0096] In this invention, the server includes means for acquiring voice information to analyze the conversation of a sales representative, data processing means for analyzing and evaluating the customer's emotions based on the voice information and the physical environment, and display means that utilize a virtual environment or augmented reality technology to visually provide the generated advice to the sales representative. This enables the sales representative to provide a more personalized customer service approach that is tailored to the customer's emotions and environment.

[0097] A "sales representative" is someone whose job is to conduct sales activities with customers and to propose and provide products and services.

[0098] "Auditory information" refers to data obtained by recording or processing sound waves from human speech, and is used to analyze the content and tone of conversations.

[0099] "Data processing means" refers to a hardware or software system designed to analyze input information and generate useful results.

[0100] "Information generation means" refers to an algorithm or process that generates appropriate instructions or suggestions based on input data.

[0101] A "virtual environment" refers to an artificial visual world created by a computer that users can interact with.

[0102] "Augmented reality technology" is a technology that overlays digital information onto the real world, enabling users to perceive that information as reality.

[0103] "Display means" refers to devices or technologies for presenting information visually, and typically includes screens and head-mounted displays.

[0104] "Reaction" refers to the change in emotions or attitudes that a customer shows in response to the actions or words of a sales representative.

[0105] "Environmental information acquisition means" refers to sensors and devices that perceive physical and surrounding conditions and collect that information.

[0106] The system for implementing this invention consists of a visual display device (e.g., smart glasses) worn by a sales representative and a network system centered around a server.

[0107] The server acquires audio information via a microphone attached to a visual display device to record the sales representative's conversation in real time. The acquired audio information is transmitted to the server via Bluetooth through a mobile device. The server converts the audio information into text format using the Google® Cloud Speech-to-Text API and then performs sentiment analysis using the Google Cloud Natural Language API.

[0108] Furthermore, the server acquires physical environmental information from the visual display device and performs data processing to infer customer interests based on this environmental information. The results of this processing are displayed within the sales representative's field of view using augmented reality technology. This allows the sales representative to instantly understand strategies tailored to the customer's emotions and respond effectively.

[0109] As a concrete example, in a store, when a customer is inquiring about the latest home appliances, the server analyzes the customer's voice to identify a high level of curiosity and suggests to the sales representative that the features of the new product be emphasized. This information is then fed into the sales representative's field of view through a visual display.

[0110] An example of a prompt message would be, "Analyze customer conversation data in real time and provide a customer service strategy tailored to their emotions." This system, combined with the generative AI model, enables sales representatives to consistently provide appropriate and personalized customer service.

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The terminal acquires real-time audio information of conversations between sales representatives and customers. This audio information is collected via a microphone and transmitted to a server via Bluetooth through a mobile device. The input is an audio signal, and the output is data transfer to the server.

[0114] Step 2:

[0115] The server converts the received audio information into text format using the Google Cloud Speech-to-Text API. This conversion makes the audio conversation usable as text data. The input is audio data, and the output is text data.

[0116] Step 3:

[0117] The server uses the Google Cloud Natural Language API to perform sentiment analysis on text data using a generative AI model. The input is conversational text, and the output is an analysis result that includes sentiment.

[0118] Step 4:

[0119] The server analyzes environmental data transmitted from the terminal and integrates it with sentiment analysis results to infer the customer's areas of interest. This process takes environmental sensor data as input and outputs the analysis results.

[0120] Step 5:

[0121] The server utilizes a generative AI model to generate appropriate strategies for sales representatives based on the analysis results. This prompt determines a specific course of action. The input is sentiment and interest data, and the output is advice.

[0122] Step 6:

[0123] The terminal uses augmented reality technology to visually present the advice received from the server to the sales representative. The advice is overlaid on the sales representative's field of view via the terminal's visual display. The input is advice data from the server, and the output is a visually perceptible presentation of the advice.

[0124] Step 7:

[0125] The entire system is updated when users take action through their devices and feed the results back to the server. Sales results serve as input for this feedback, and improved algorithms are output. This cyclical process continuously enhances the system's effectiveness.

[0126] 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.

[0127] This invention aims to realize a system that recognizes and analyzes user emotions during sales activities and provides effective sales support based on that analysis. The system aims to improve the quality of sales by acquiring voice data from sales representatives and customers and analyzing their emotions using an emotion engine.

[0128] First, the device records the conversation between the sales representative and the customer as audio data in real time. The acquired audio data is encrypted and sent to the server via a secure communication channel.

[0129] Next, the server analyzes the received audio data using an emotion engine to determine the emotional state of the sales representative and the customer in real time. The emotion engine uses natural language processing technology and machine learning algorithms to extract emotions from tone, speed, and volume, and tracks changes in those emotions.

[0130] Based on the analysis results, the server uses an AI model to generate optimal sales advice. This advice is formulated as specific guidance for real-time sales activities, providing options for sales strategies.

[0131] The generated advice is sent to the device as visualized data using virtual reality (VR) or augmented reality (AR) technology. The device then provides this visualized data to the sales representative, who can immediately adjust their sales approach based on this information.

[0132] For example, if a customer shows signs of losing interest in a proposal, the server will generate advice for the salesperson to change the emphasis of the proposal. The salesperson can receive this advice through an AR headset and immediately adjust their approach in the actual sales situation.

[0133] Furthermore, users (sales representatives) provide feedback on the results and impressions after sales activities and input them into the system. The server uses this feedback to continuously learn the model and improve its preparation for future sales activities.

[0134] Thus, the present invention enables dynamic sales support based on emotional changes, increases the success rate of sales activities, and supports the building of effective customer relationships.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The device records conversations between sales representatives and customers as audio data in real time. It continuously captures audio from the beginning to the end of the conversation and applies noise cancellation technology to minimize background noise.

[0138] Step 2:

[0139] The device encrypts the recorded audio data and sends it to the server via a secure communication channel. The data is divided and sent in an orderly manner to reduce waiting time for real-time processing.

[0140] Step 3:

[0141] The server inputs the received audio data into an emotion engine, which uses natural language processing and speech feature analysis to analyze the emotional states of both the salesperson and the customer. It detects the tone, speed, and volume of the voice and defines emotion labels.

[0142] Step 4:

[0143] The server uses the analyzed emotional data to drive an AI model and generate sales advice tailored to the customer's emotional state. For example, if a customer is emotionally unstable, the advice might include reassuring measures.

[0144] Step 5:

[0145] The server converts the generated sales advice into VR or AR format and prepares it as visualization data. The information is designed to be presented in a format that sales representatives can intuitively understand.

[0146] Step 6:

[0147] The terminal immediately presents visualized sales advice to sales representatives via VR / AR devices. This allows sales representatives to instantly review the advice and act accordingly.

[0148] Step 7:

[0149] The user (sales representative) inputs feedback obtained during and after sales activities into the system. This feedback includes numerical data such as customer reactions and closing rates.

[0150] Step 8:

[0151] The server uses the accumulated feedback to retrain the AI ​​model, improving its accuracy. This continuous learning process improves the quality of the sales advice generated.

[0152] (Example 2)

[0153] 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".

[0154] In sales activities, there is a need to improve sales efficiency by accurately recognizing the customer's emotional state and interests and providing appropriate sales strategies immediately based on that understanding. However, conventional methods have been insufficient in grasping emotional changes in real time and providing effective sales support based on that understanding. Furthermore, the lack of a system for utilizing feedback after sales activities has made it difficult to continuously improve quality and optimize individual processes.

[0155] 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.

[0156] In this invention, the server includes terminal means for acquiring voice information of sales representatives and customers, means for encrypting the voice information and transmitting it to the server via a communication path, means for determining emotional states using a voice analysis engine within the server, means for generating sales advice using a generation AI model based on the determined emotional states, means for visually providing the generated advice to the sales representative using virtual reality or augmented reality technology, and means for collecting feedback after sales activities and updating algorithms within the server. This makes it possible to provide appropriate sales strategies based on emotions in real time and to continuously improve sales activities.

[0157] "Terminal means" refers to the device or function used to acquire voice information between sales representatives and customers in real time and transmit it to a server.

[0158] "Audio information" refers to data that acoustically records the content of conversations between sales representatives and customers, and provides basic data for sentiment analysis.

[0159] "Encryption" refers to the process of transforming audio data into a form that cannot be deciphered in order to protect it from unauthorized access.

[0160] "Communication path" refers to the network infrastructure and protocols used when sending data from a terminal to a server.

[0161] A "server" refers to a computer system that analyzes received audio information and performs related processing.

[0162] A "voice analysis engine" refers to specialized software or algorithms used to extract emotional states and other specific information from voice data.

[0163] "Emotional state" refers to the psychological state or reaction of a customer or sales representative determined from the analyzed audio information.

[0164] A "generative AI model" refers to an artificial intelligence algorithm that learns from past data and feedback and automatically generates sales advice.

[0165] "Sales advice" refers to information that provides specific suggestions and guidelines for effectively conducting sales activities, generated by a generative AI model.

[0166] "Virtual reality technology" refers to the technology of creating a simulation environment using computer graphics.

[0167] Augmented reality technology refers to the technology of overlaying digital information onto the real environment.

[0168] "Feedback" refers to the evaluations and opinions provided to the system based on the content and results of sales activities carried out by sales representatives after the sales activity.

[0169] "Algorithm updating" refers to the process of improving the content of an algorithm based on feedback information in order to improve the performance and accuracy of the system.

[0170] This invention is a system that analyzes customer emotions in real time during sales activities and provides appropriate advice to sales representatives based on that analysis.

[0171] First, the terminal captures the conversation between the sales representative and the customer using a high-performance voice input device. This voice data is encrypted on the spot and sent to the server via a secure data transfer communication protocol (e.g., HTTPS).

[0172] On the server, a voice analysis engine is running, which uses received voice data to analyze the customer's emotional state. This engine combines natural language processing techniques and machine learning algorithms to analyze parameters such as voice tone, speed, and volume. The results of this analysis are used to determine the customer's emotional state in real time.

[0173] After the emotional state is determined, the server uses a generative AI model to automatically generate advice appropriate for the sales situation. This model learns from past sales data and feedback, and provides prompts on what actions the salesperson should take.

[0174] The generated sales advice is visualized using virtual reality (VR) and augmented reality (AR) technologies and provided to sales representatives via their devices. Sales representatives can then immediately adjust their sales approach based on this advice.

[0175] For example, if analysis reveals signs that a customer is losing interest, the server will send advice to the sales representative to restructure the proposal. The sales representative can view this advice in real time on an AR device and quickly adjust their response accordingly.

[0176] Furthermore, users (sales representatives) input feedback on their activities and results into the system after completing their sales activities. This feedback is stored on the server and used to improve the algorithm. The continuously learned generative AI model further enhances sales support in subsequent sales activities.

[0177] Example prompt:

[0178] "Input customer voice data and analyze their emotional responses to the proposal. If they show signs of disinterest, generate advice to adjust the proposal."

[0179] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0180] Step 1:

[0181] The terminal captures voice conversations between sales representatives and customers in real time using a high-performance voice input device. This process yields audio data of the sales conversation as input. This audio data is encrypted on the spot and stored securely.

[0182] Step 2:

[0183] The terminal sends encrypted voice data to the server using a communication protocol (e.g., HTTPS). This process takes encrypted voice data as input and securely transfers the data to the server as output.

[0184] Step 3:

[0185] The server decodes the received audio data and inputs it into the audio analysis engine. Here, as part of the data processing, the audio file is analyzed using natural language processing techniques and machine learning algorithms to determine the customer's emotional state. The output is the customer's emotional state.

[0186] Step 4:

[0187] Using the determined emotional state as input, the server employs a generative AI model to generate sales advice. Data calculations utilize past data and feedback to generate the optimal sales approach. The output provides advice and guidance.

[0188] Step 5:

[0189] The server visualizes the generated sales advice using virtual reality (VR) or augmented reality (AR) technology. Here, the generated advice is input and output as visual information.

[0190] Step 6:

[0191] The terminal provides visualized sales advice to sales representatives. In this step, visual information is output directly to the sales representative's device (e.g., an AR device) to help them immediately adjust their sales approach.

[0192] Step 7:

[0193] Users (sales representatives) input feedback into the system after sales activities. This input includes sales results and impressions. The server receives this feedback and updates the algorithm to improve future sales support. The output of this process is an improved AI model.

[0194] (Application Example 2)

[0195] 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".

[0196] In physical stores, sales staff are required to accurately understand customer emotions through dialogue and immediately adjust sales strategies. However, sales staff are currently unable to fully utilize real-time emotional insights, resulting in inefficient sales and suboptimal customer satisfaction. Furthermore, the security and privacy of voice data are also important issues.

[0197] 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.

[0198] In this invention, the server includes means for acquiring voice data to analyze the conversation of a salesperson, means for executing an algorithm to analyze customer emotions based on the voice data, and means for utilizing virtual reality or augmented reality technology to visually provide the generated advice to the salesperson. This enables salespeople to immediately adjust their customer interactions based on emotional insights obtained in real time, leading to more effective sales activities. Furthermore, by securely transferring and encrypting the voice data to ensure data security, and by providing emotional insights through smart glasses, it is possible to achieve both privacy protection and convenience.

[0199] A "sales representative" is a staff member of a sales organization whose role is to interact directly with customers and provide information about products and services.

[0200] "Means of analyzing dialogue" refers to a device or technology that records and analyzes conversations between sales representatives and customers and extracts important elements.

[0201] "Audio data" refers to information in which the content of what customers or sales representatives say is recorded in digital format.

[0202] An "algorithm for analyzing customer emotions" is a formula or method used to determine a customer's emotional state and level of interest from voice data.

[0203] "Methods for generating advice in real time" refer to technologies and programs that provide immediate action guidelines and suggestions based on data obtained during sales activities.

[0204] "Virtual reality or augmented reality technologies for visual presentation" are technologies that overlay computer-generated information onto the real world, conveying information to users intuitively.

[0205] "Means of collecting feedback" refers to a method or apparatus for recording the results of sales representatives modifying their actions based on advice and providing this information to the system.

[0206] "Methods for updating algorithms" refer to ways to improve sentiment analysis and advice generation techniques based on the feedback received, thereby increasing accuracy in subsequent attempts.

[0207] "Means of securely transferring voice data" refers to technologies that transmit data through encrypted or protected channels to protect it from third parties.

[0208] "Smart glasses" are glasses-type electronic devices that display information visually, allowing users to use them as portable computers.

[0209] This invention provides a system that allows sales staff to analyze customer emotions in real time during in-store sales activities and adjust their responses immediately. A server acquires voice data and analyzes customer emotions based on it. The analyzed emotion data is visually displayed on the sales staff's smart glasses using virtual reality or augmented reality technology.

[0210] The hardware consists of smart glasses with voice acquisition capabilities, and a system that encrypts the audio on a smartphone before transmitting it via 4G / 5G communication. On the server side, the Google Cloud Speech-to-Text API is used, and the analyzed data is processed using an emotion analysis algorithm based on TENSORFLOW®. As a result, sales staff are provided with advice on future actions through a visual user interface using Unity.

[0211] To give a specific example, when a salesperson in a cosmetics store is suggesting a new lipstick, if the customer shows signs of losing interest, the system can immediately provide advice such as, "Emphatically mention that this lipstick contains special ingredients." This allows the salesperson to maintain a good relationship with the customer while implementing an effective strategy.

[0212] An example of a prompt for the generating AI model is, "Based on customer sentiment data, what is the best way to engage the customer in the current conversation?" Using this prompt, the system immediately generates effective sales strategy advice.

[0213] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0214] Step 1:

[0215] The server receives voice data from the terminal. The terminal captures the conversation between the customer and the sales representative as voice data in real time, encrypts the collected voice data, and sends it to the server via a secure communication channel. In this process, the input is voice data, and the output is encrypted voice data.

[0216] Step 2:

[0217] The server decrypts the received encrypted audio data and performs speech recognition. It uses the Google Cloud Speech-to-Text API to convert the audio data into text format. In this process, the input is encrypted audio data and the output is text data.

[0218] Step 3:

[0219] The server inputs text data into an emotion analysis algorithm to analyze the emotional state of customers and sales representatives. Using TensorFlow, it extracts emotions from factors such as tone, speed, and volume, and determines changes in emotion. The input is text data, and the output is emotion data.

[0220] Step 4:

[0221] The server uses a generative AI model to generate optimal advice for sales representatives based on the analyzed sentiment data. Prompt sentences are input to the generative AI model to determine the resulting advice. In this process, the input consists of sentiment data and prompt sentences, while the output is advice data.

[0222] Step 5:

[0223] The server constructs the generated advisory data as a visual interface using Unity and transmits it to a terminal (smart glasses) using virtual reality or augmented reality technology. Sales representatives receive this information in real time through the smart glasses. The input is the advisory data, and the output is the visualized interface.

[0224] Step 6:

[0225] The user (sales representative) adjusts their sales approach and interacts with customers based on the advice data. Changes in their behavior during this process are collected as feedback from their device and sent to the server. The output is behavioral feedback data.

[0226] Step 7:

[0227] The server analyzes feedback data received from sales representatives and uses it to improve its sentiment analysis algorithm and generative AI model. This improves the accuracy of advice in future sales activities. The input is feedback data, and the output is the updated algorithm and generative AI model.

[0228] 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.

[0229] 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.

[0230] 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.

[0231] [Second Embodiment]

[0232] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0233] 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.

[0234] 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).

[0235] 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.

[0236] 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.

[0237] 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).

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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".

[0244] This invention provides a system that enables efficient support in sales activities. This system consistently handles everything from real-time collection of voice data and customer sentiment analysis to recommending appropriate countermeasures and visually presenting those countermeasures to sales representatives. The following describes how each element works together and how the invention is implemented.

[0245] First, the terminal acquires the conversation between the sales representative and the customer as audio data in real time. This audio data includes the customer's and sales representative's statements, tone, and speed during the conversation. Next, the server analyzes this audio data using an algorithm to understand the customer's emotions. Based on this emotion analysis, the server uses AI to generate optimal sales advice.

[0246] The generated advice is delivered to the sales representative by the device through virtual reality (VR) or augmented reality (AR) visualization technology. This allows the sales representative to receive real-time, interactive, and intuitive advice.

[0247] For example, if a customer expresses interest in the price of a product, the server can instantly generate advice regarding price competitiveness. This advice is presented to the sales representative through a terminal in VR / AR format. The sales representative can immediately understand the specific approach through the visual guidance and incorporate it into their interactions with the customer. The user (sales representative) also provides feedback to the system on the customer's reaction to the actions taken. This feedback information is then used by the server to generate advice for future interactions, enabling more accurate sales support throughout the entire system.

[0248] Thus, the present invention realizes a system that enables rapid and precise responses in sales situations and contributes to improving sales performance.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The device records conversations between sales representatives and customers as audio data in real time. This recording is continuous from the start to the end of the conversation, and the necessary sound quality is ensured using a microphone.

[0252] Step 2:

[0253] The terminal encrypts the recorded audio data and sends it to the server via a secure communication channel. To minimize communication delays, the audio data is segmented and transmitted sequentially.

[0254] Step 3:

[0255] The server processes the received audio data. Using natural language processing techniques, it breaks down the content of the utterances and analyzes key phrases and customer emotions. This includes tone analysis and speed analysis.

[0256] Step 4:

[0257] The server generates optimal sales advice using an AI model based on the results of sentiment analysis. For example, if a customer is interested in price, it prepares a script to emphasize cost competitiveness.

[0258] Step 5:

[0259] The server converts the generated advice into virtual or augmented reality format and creates visualization data. This data is designed to be intuitively understandable for sales representatives.

[0260] Step 6:

[0261] The terminal uses visualization data received from the server to provide virtual or augmented reality navigation to sales representatives. This allows sales representatives to receive real-time visual advice.

[0262] Step 7:

[0263] The user (sales representative) enters feedback into the terminal regarding the results of their sales activities. This feedback includes customer reactions and sales results.

[0264] Step 8:

[0265] The server uses the collected feedback to update the AI ​​model, improving the accuracy of advice for future sales activities. This process is continuous, accelerating the system's learning.

[0266] (Example 1)

[0267] 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."

[0268] For sales representatives to engage with customers more efficiently and effectively, they need to quickly and accurately grasp customer emotions and interests and respond appropriately based on that understanding. However, with traditional methods, it was difficult for sales representatives to instantly analyze customer emotions and devise optimal responses. Furthermore, the lack of real-time advice and visualization of such information limited the potential for improving sales efficiency.

[0269] 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.

[0270] In this invention, the server includes means for acquiring the conversation between the sales representative and the customer as audio information in real time, means for converting the audio information into a digital format and transferring it to the server for analysis, and means for executing an emotion analysis algorithm using the audio information received by the server to understand the customer's emotions. This makes it possible to generate advice in real time based on emotion analysis and to provide it visually.

[0271] A "sales representative" is someone whose job is to propose and sell a company's or organization's products and services to customers.

[0272] "Audio information" refers to data recorded in sound form, including conversations between sales representatives and customers, and includes information such as the tone, speed, and content of the conversation.

[0273] A "server" is an information processing device that receives and processes voice information over a network and performs necessary analysis and generation.

[0274] An "emotion analysis algorithm" is a series of computational procedures for identifying a customer's emotions from voice information, and a method for determining the customer's psychological state based on the results.

[0275] A "generative AI model" is a framework of artificial intelligence trained to create new information based on past data, and is particularly a technology for generating advice through natural language processing.

[0276] "Virtual reality or augmented reality technology" is a technology that uses digital data to provide a visual experience that blends with the real world, and visualizes information for sales representatives in real time.

[0277] "Customer response information" refers to data that records the reactions and responses that customers gave to the actions of sales representatives.

[0278] "Feedback" refers to input information used to improve future advice provided by the system, based on customer response data.

[0279] This invention is a system designed to enable sales representatives to communicate more effectively with customers. The system supports a series of processes, from acquiring and analyzing voice information, sentiment analysis, generating advice using generative AI models, and visualizing the information using virtual or augmented reality technology.

[0280] Specifically, the terminal captures conversations between sales representatives and customers in real time, acquiring audio information. This requires a microphone for voice input and software for digital conversion of the data. The collected audio information is converted to a digital format and then securely transferred to a server.

[0281] The server receives voice information and processes it using a specific voice analysis algorithm. Open-source voice processing libraries and custom models are used in this algorithm. Based on the analysis results, the server utilizes a generative AI model to generate optimal sales advice in real time. For example, libraries and platforms for natural language processing are utilized as the generative AI model.

[0282] The generated advice is visually provided to the sales staff through the terminal. VR / AR technology is used for this provision, and information is displayed using platforms such as Unity and Unreal Engine. The sales staff can use this information to respond more effectively to customers.

[0283] As a specific example, when a customer expresses anxiety about the price of a specific product, the server generates a prompt sentence to emphasize price competitiveness. Based on this prompt sentence, the generative AI model presents an appropriate sales strategy. Prompt sentences such as "The customer is dissatisfied with the price of Product A. I would like a new approach to emphasize features other than price for this customer." are utilized.

[0284] In this way, the present invention is a system that combines advanced sentiment analysis based on voice information and generative AI technology to enable quick and refined responses in the sales field, and as a result, supports the improvement of sales performance.

[0285] The flow of the specific processing in Example 1 will be described using FIG. 11.

[0286] Step 1:

[0287] The terminal captures conversations between sales representatives and customers in real time and acquires them as audio information. Specifically, it records the conversation using an audio input device (microphone) and converts it to a digital format. The input is an analog audio signal, and the output is digital audio data. This data includes the content, tone, and speed of the conversation.

[0288] Step 2:

[0289] The terminal securely transmits the acquired digital audio data to the server. Encryption protocols such as SSL / TLS are used for data transfer. The input is digital audio data, and the output is an encrypted data stream sent to the server.

[0290] Step 3:

[0291] The server executes an emotion analysis algorithm to analyze the received audio data. Specifically, it uses an audio processing library to analyze the tone, speed, and volume patterns of the voice to identify the customer's emotional state. The input is digital audio data, and the output is the result of the emotion analysis (e.g., labeling whether the customer is satisfied, dissatisfied, or interested).

[0292] Step 4:

[0293] The server uses a generative AI model to generate optimal sales advice based on the results of sentiment analysis. Specifically, prompt sentences are input to the AI ​​model, and text regarding sales strategies is generated as output. The input consists of the sentiment analysis results and related prompt sentences, and the output is the generated advice.

[0294] Step 5:

[0295] The device provides generated advice to sales representatives using virtual reality (VR) or augmented reality (AR) technology. Specifically, it visualizes the advice using Unity or Unreal Engine and displays it within the sales representative's field of view. The input is the generated advice text, and the output is the visually represented information.

[0296] Step 6:

[0297] The user (sales representative) conducts the conversation with the customer based on the visually presented advice. They observe the customer's reactions in real time and input them into the system as feedback. The input is the customer's reaction, and the output is the feedback information.

[0298] Step 7:

[0299] The device collects user feedback information and sends it to the server. The server uses this feedback to update the algorithm and improve the performance of future generative AI models. The input is the feedback information, and the output is the parameters of the updated algorithm.

[0300] (Application Example 1)

[0301] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0302] In conversations between sales representatives and customers, accurately understanding customer emotions and interests and providing appropriate customer service strategies in real time based on that understanding is difficult. Therefore, an efficient and flexible support system is needed to maximize sales effectiveness.

[0303] 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.

[0304] In this invention, the server includes means for acquiring voice information to analyze the conversations of sales staff, data processing means for analyzing and evaluating the emotions of customers based on the voice information and the physical environment, and display means for visually providing the generated advice to the sales staff by utilizing a virtual environment or augmented reality technology. As a result, the sales staff can adopt a more personalized customer service approach according to the emotions of the customers and the environment.

[0305] A "sales staff" is a person who is responsible for conducting sales activities towards customers and proposing and providing products and services.

[0306] "Voice information" is data obtained by recording or processing sound waves from human speech and is used to analyze the content and tone of conversations.

[0307] "Data processing means" is a hardware or software system designed to analyze input information and generate useful results.

[0308] "Information generation means" refers to an algorithm or process that generates appropriate instructions or proposals based on input data.

[0309] A "virtual environment" means an artificial visual world generated by a computer that allows users to interact.

[0310] "Augmented reality technology" is a technology that overlays digital information on the real world and enables users to view that information in reality.

[0311] "Display means" refers to devices or technologies for visually presenting information and usually includes screens and head-mounted displays.

[0312] "Reaction" means the change in emotions or attitudes shown by customers towards the actions or statements of the sales staff.

[0313] "Environmental information acquisition means" refers to sensors and devices that perceive physical and surrounding conditions and collect that information.

[0314] The system for implementing this invention consists of a visual display device (e.g., smart glasses) worn by a sales representative and a network system centered around a server.

[0315] The server acquires audio information via a microphone attached to a visual display device to record the sales representative's conversation in real time. The acquired audio information is transmitted to the server via Bluetooth through a mobile device. The server converts the audio information into text format using the Google Cloud Speech-to-Text API and then performs sentiment analysis using the Google Cloud Natural Language API.

[0316] Furthermore, the server acquires physical environmental information from the visual display device and performs data processing to infer customer interests based on this environmental information. The results of this processing are displayed within the sales representative's field of view using augmented reality technology. This allows the sales representative to instantly understand strategies tailored to the customer's emotions and respond effectively.

[0317] As a concrete example, in a store, when a customer is inquiring about the latest home appliances, the server analyzes the customer's voice to identify a high level of curiosity and suggests to the sales representative that the features of the new product be emphasized. This information is then fed into the sales representative's field of view through a visual display.

[0318] An example of a prompt message would be, "Analyze customer conversation data in real time and provide a customer service strategy tailored to their emotions." This system, combined with the generative AI model, enables sales representatives to consistently provide appropriate and personalized customer service.

[0319] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0320] Step 1:

[0321] The terminal acquires real-time audio information of conversations between sales representatives and customers. This audio information is collected via a microphone and transmitted to a server via Bluetooth through a mobile device. The input is an audio signal, and the output is data transfer to the server.

[0322] Step 2:

[0323] The server converts the received audio information into text format using the Google Cloud Speech-to-Text API. This conversion makes the audio conversation usable as text data. The input is audio data, and the output is text data.

[0324] Step 3:

[0325] The server uses the Google Cloud Natural Language API to perform sentiment analysis on text data using a generative AI model. The input is conversational text, and the output is an analysis result that includes sentiment.

[0326] Step 4:

[0327] The server analyzes environmental data transmitted from the terminal and integrates it with sentiment analysis results to infer the customer's areas of interest. This process takes environmental sensor data as input and outputs the analysis results.

[0328] Step 5:

[0329] The server utilizes a generative AI model to generate appropriate strategies for sales representatives based on the analysis results. This prompt determines a specific course of action. The input is sentiment and interest data, and the output is advice.

[0330] Step 6:

[0331] The terminal uses augmented reality technology to visually present the advice received from the server to the sales representative. The advice is overlaid on the sales representative's field of view via the terminal's visual display. The input is advice data from the server, and the output is a visually perceptible presentation of the advice.

[0332] Step 7:

[0333] The entire system is updated when users take action through their devices and feed the results back to the server. Sales results serve as input for this feedback, and improved algorithms are output. This cyclical process continuously enhances the system's effectiveness.

[0334] 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.

[0335] This invention aims to realize a system that recognizes and analyzes user emotions during sales activities and provides effective sales support based on that analysis. The system aims to improve the quality of sales by acquiring voice data from sales representatives and customers and analyzing their emotions using an emotion engine.

[0336] First, the device records the conversation between the sales representative and the customer as audio data in real time. The acquired audio data is encrypted and sent to the server via a secure communication channel.

[0337] Next, the server analyzes the received audio data using an emotion engine to determine the emotional state of the sales representative and the customer in real time. The emotion engine uses natural language processing technology and machine learning algorithms to extract emotions from tone, speed, and volume, and tracks changes in those emotions.

[0338] Based on the analysis results, the server uses an AI model to generate optimal sales advice. This advice is formulated as specific guidance for real-time sales activities, providing options for sales strategies.

[0339] The generated advice is sent to the device as visualized data using virtual reality (VR) or augmented reality (AR) technology. The device then provides this visualized data to the sales representative, who can immediately adjust their sales approach based on this information.

[0340] For example, if a customer shows signs of losing interest in a proposal, the server will generate advice for the salesperson to change the emphasis of the proposal. The salesperson can receive this advice through an AR headset and immediately adjust their approach in the actual sales situation.

[0341] Furthermore, users (sales representatives) provide feedback on the results and impressions after sales activities and input them into the system. The server uses this feedback to continuously learn the model and improve its preparation for future sales activities.

[0342] Thus, the present invention enables dynamic sales support based on emotional changes, increases the success rate of sales activities, and supports the building of effective customer relationships.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] The device records conversations between sales representatives and customers as audio data in real time. It continuously captures audio from the beginning to the end of the conversation and applies noise cancellation technology to minimize background noise.

[0346] Step 2:

[0347] The device encrypts the recorded audio data and sends it to the server via a secure communication channel. The data is divided and sent in an orderly manner to reduce waiting time for real-time processing.

[0348] Step 3:

[0349] The server inputs the received audio data into an emotion engine, which uses natural language processing and speech feature analysis to analyze the emotional states of both the salesperson and the customer. It detects the tone, speed, and volume of the voice and defines emotion labels.

[0350] Step 4:

[0351] The server uses the analyzed emotional data to drive an AI model and generate sales advice tailored to the customer's emotional state. For example, if a customer is emotionally unstable, the advice might include reassuring measures.

[0352] Step 5:

[0353] The server converts the generated sales advice into VR or AR format and prepares it as visualization data. The information is designed to be presented in a format that sales representatives can intuitively understand.

[0354] Step 6:

[0355] The terminal immediately presents visualized sales advice to sales representatives via VR / AR devices. This allows sales representatives to instantly review the advice and act accordingly.

[0356] Step 7:

[0357] The user (sales representative) inputs feedback obtained during and after sales activities into the system. This feedback includes numerical data such as customer reactions and closing rates.

[0358] Step 8:

[0359] The server uses the accumulated feedback to retrain the AI ​​model, improving its accuracy. This continuous learning process improves the quality of the sales advice generated.

[0360] (Example 2)

[0361] 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".

[0362] In sales activities, there is a need to improve sales efficiency by accurately recognizing the customer's emotional state and interests and providing appropriate sales strategies immediately based on that understanding. However, conventional methods have been insufficient in grasping emotional changes in real time and providing effective sales support based on that understanding. Furthermore, the lack of a system for utilizing feedback after sales activities has made it difficult to continuously improve quality and optimize individual processes.

[0363] 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.

[0364] In this invention, the server includes terminal means for acquiring voice information of sales representatives and customers, means for encrypting the voice information and transmitting it to the server via a communication path, means for determining emotional states using a voice analysis engine within the server, means for generating sales advice using a generation AI model based on the determined emotional states, means for visually providing the generated advice to the sales representative using virtual reality or augmented reality technology, and means for collecting feedback after sales activities and updating algorithms within the server. This makes it possible to provide appropriate sales strategies based on emotions in real time and to continuously improve sales activities.

[0365] "Terminal means" refers to the device or function used to acquire voice information between sales representatives and customers in real time and transmit it to a server.

[0366] "Audio information" refers to data that acoustically records the content of conversations between sales representatives and customers, and provides basic data for sentiment analysis.

[0367] "Encryption" refers to the process of transforming audio data into a form that cannot be deciphered in order to protect it from unauthorized access.

[0368] "Communication path" refers to the network infrastructure and protocols used when sending data from a terminal to a server.

[0369] A "server" refers to a computer system that analyzes received audio information and performs related processing.

[0370] A "voice analysis engine" refers to specialized software or algorithms used to extract emotional states and other specific information from voice data.

[0371] "Emotional state" refers to the psychological state or reaction of a customer or sales representative determined from the analyzed audio information.

[0372] A "generative AI model" refers to an artificial intelligence algorithm that learns from past data and feedback and automatically generates sales advice.

[0373] "Sales advice" refers to information that provides specific suggestions and guidelines for effectively conducting sales activities, generated by a generative AI model.

[0374] "Virtual reality technology" refers to the technology of creating a simulation environment using computer graphics.

[0375] Augmented reality technology refers to the technology of overlaying digital information onto the real environment.

[0376] "Feedback" refers to the evaluations and opinions provided to the system based on the content and results of sales activities carried out by sales representatives after the sales activity.

[0377] "Algorithm updating" refers to the process of improving the content of an algorithm based on feedback information in order to improve the performance and accuracy of the system.

[0378] This invention is a system that analyzes customer emotions in real time during sales activities and provides appropriate advice to sales representatives based on that analysis.

[0379] First, the terminal captures the conversation between the sales representative and the customer using a high-performance voice input device. This voice data is encrypted on the spot and sent to the server via a secure data transfer communication protocol (e.g., HTTPS).

[0380] On the server, a voice analysis engine is running, which uses received voice data to analyze the customer's emotional state. This engine combines natural language processing techniques and machine learning algorithms to analyze parameters such as voice tone, speed, and volume. The results of this analysis are used to determine the customer's emotional state in real time.

[0381] After the emotional state is determined, the server uses a generative AI model to automatically generate advice appropriate for the sales situation. This model learns from past sales data and feedback, and provides prompts on what actions the salesperson should take.

[0382] The generated sales advice is visualized using virtual reality (VR) and augmented reality (AR) technologies and provided to sales representatives via their devices. Sales representatives can then immediately adjust their sales approach based on this advice.

[0383] For example, if analysis reveals signs that a customer is losing interest, the server will send advice to the sales representative to restructure the proposal. The sales representative can view this advice in real time on an AR device and quickly adjust their response accordingly.

[0384] Furthermore, users (sales representatives) input feedback on their activities and results into the system after completing their sales activities. This feedback is stored on the server and used to improve the algorithm. The continuously learned generative AI model further enhances sales support in subsequent sales activities.

[0385] Example prompt:

[0386] "Input customer voice data and analyze their emotional responses to the proposal. If they show signs of disinterest, generate advice to adjust the proposal."

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

[0388] Step 1:

[0389] The terminal captures voice conversations between sales representatives and customers in real time using a high-performance voice input device. This process yields audio data of the sales conversation as input. This audio data is encrypted on the spot and stored securely.

[0390] Step 2:

[0391] The terminal sends encrypted voice data to the server using a communication protocol (e.g., HTTPS). This process takes encrypted voice data as input and securely transfers the data to the server as output.

[0392] Step 3:

[0393] The server decodes the received audio data and inputs it into the audio analysis engine. Here, as part of the data processing, the audio file is analyzed using natural language processing techniques and machine learning algorithms to determine the customer's emotional state. The output is the customer's emotional state.

[0394] Step 4:

[0395] Using the determined emotional state as input, the server employs a generative AI model to generate sales advice. Data calculations utilize past data and feedback to generate the optimal sales approach. The output provides advice and guidance.

[0396] Step 5:

[0397] The server visualizes the generated sales advice using virtual reality (VR) or augmented reality (AR) technology. Here, the generated advice is input and output as visual information.

[0398] Step 6:

[0399] The terminal provides visualized sales advice to sales representatives. In this step, visual information is output directly to the sales representative's device (e.g., an AR device) to help them immediately adjust their sales approach.

[0400] Step 7:

[0401] Users (sales representatives) input feedback into the system after sales activities. This input includes sales results and impressions. The server receives this feedback and updates the algorithm to improve future sales support. The output of this process is an improved AI model.

[0402] (Application Example 2)

[0403] 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."

[0404] In physical stores, sales staff are required to accurately understand customer emotions through dialogue and immediately adjust sales strategies. However, sales staff are currently unable to fully utilize real-time emotional insights, resulting in inefficient sales and suboptimal customer satisfaction. Furthermore, the security and privacy of voice data are also important issues.

[0405] 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.

[0406] In this invention, the server includes means for acquiring voice data to analyze the conversation of a salesperson, means for executing an algorithm to analyze customer emotions based on the voice data, and means for utilizing virtual reality or augmented reality technology to visually provide the generated advice to the salesperson. This enables salespeople to immediately adjust their customer interactions based on emotional insights obtained in real time, leading to more effective sales activities. Furthermore, by securely transferring and encrypting the voice data to ensure data security, and by providing emotional insights through smart glasses, it is possible to achieve both privacy protection and convenience.

[0407] A "sales representative" is a staff member of a sales organization whose role is to interact directly with customers and provide information about products and services.

[0408] "Means of analyzing dialogue" refers to a device or technology that records and analyzes conversations between sales representatives and customers and extracts important elements.

[0409] "Audio data" refers to information in which the content of what customers or sales representatives say is recorded in digital format.

[0410] An "algorithm for analyzing customer emotions" is a formula or method used to determine a customer's emotional state and level of interest from voice data.

[0411] "Methods for generating advice in real time" refer to technologies and programs that provide immediate action guidelines and suggestions based on data obtained during sales activities.

[0412] "Virtual reality or augmented reality technologies for visual presentation" are technologies that overlay computer-generated information onto the real world, conveying information to users intuitively.

[0413] "Means of collecting feedback" refers to a method or apparatus for recording the results of sales representatives modifying their actions based on advice and providing this information to the system.

[0414] "Methods for updating algorithms" refer to ways to improve sentiment analysis and advice generation techniques based on the feedback received, thereby increasing accuracy in subsequent attempts.

[0415] "Means of securely transferring voice data" refers to technologies that transmit data through encrypted or protected channels to protect it from third parties.

[0416] "Smart glasses" are glasses-type electronic devices that display information visually, allowing users to use them as portable computers.

[0417] This invention provides a system that allows sales staff to analyze customer emotions in real time during in-store sales activities and adjust their responses immediately. A server acquires voice data and analyzes customer emotions based on it. The analyzed emotion data is visually displayed on the sales staff's smart glasses using virtual reality or augmented reality technology.

[0418] The hardware consists of smart glasses with voice acquisition capabilities, and a system that encrypts the audio on a smartphone before transmitting it via 4G / 5G communication. On the server side, the Google Cloud Speech-to-Text API is used, and the analyzed data is processed by an emotion analysis algorithm using TensorFlow. As a result, sales staff are provided with advice on future actions through a visual user interface using Unity.

[0419] To give a specific example, when a salesperson in a cosmetics store is suggesting a new lipstick, if the customer shows signs of losing interest, the system can immediately provide advice such as, "Emphatically mention that this lipstick contains special ingredients." This allows the salesperson to maintain a good relationship with the customer while implementing an effective strategy.

[0420] An example of a prompt for the generating AI model is, "Based on customer sentiment data, what is the best way to engage the customer in the current conversation?" Using this prompt, the system immediately generates effective sales strategy advice.

[0421] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0422] Step 1:

[0423] The server receives voice data from the terminal. The terminal captures the conversation between the customer and the sales representative as voice data in real time, encrypts the collected voice data, and sends it to the server via a secure communication channel. In this process, the input is voice data, and the output is encrypted voice data.

[0424] Step 2:

[0425] The server decrypts the received encrypted audio data and performs speech recognition. It uses the Google Cloud Speech-to-Text API to convert the audio data into text format. In this process, the input is encrypted audio data and the output is text data.

[0426] Step 3:

[0427] The server inputs text data into an emotion analysis algorithm to analyze the emotional state of customers and sales representatives. Using TensorFlow, it extracts emotions from factors such as tone, speed, and volume, and determines changes in emotion. The input is text data, and the output is emotion data.

[0428] Step 4:

[0429] The server uses a generative AI model to generate optimal advice for sales representatives based on the analyzed sentiment data. Prompt sentences are input to the generative AI model to determine the resulting advice. In this process, the input consists of sentiment data and prompt sentences, while the output is advice data.

[0430] Step 5:

[0431] The server constructs the generated advisory data as a visual interface using Unity and transmits it to a terminal (smart glasses) using virtual reality or augmented reality technology. Sales representatives receive this information in real time through the smart glasses. The input is the advisory data, and the output is the visualized interface.

[0432] Step 6:

[0433] The user (sales representative) adjusts their sales approach and interacts with customers based on the advice data. Changes in their behavior during this process are collected as feedback from their device and sent to the server. The output is behavioral feedback data.

[0434] Step 7:

[0435] The server analyzes feedback data received from sales representatives and uses it to improve its sentiment analysis algorithm and generative AI model. This improves the accuracy of advice in future sales activities. The input is feedback data, and the output is the updated algorithm and generative AI model.

[0436] 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.

[0437] 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.

[0438] 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.

[0439] [Third Embodiment]

[0440] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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).

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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".

[0452] This invention provides a system that enables efficient support in sales activities. This system consistently handles everything from real-time collection of voice data and customer sentiment analysis to recommending appropriate countermeasures and visually presenting those countermeasures to sales representatives. The following describes how each element works together and how the invention is implemented.

[0453] First, the terminal acquires the conversation between the sales representative and the customer as audio data in real time. This audio data includes the customer's and sales representative's statements, tone, and speed during the conversation. Next, the server analyzes this audio data using an algorithm to understand the customer's emotions. Based on this emotion analysis, the server uses AI to generate optimal sales advice.

[0454] The generated advice is delivered to the sales representative by the device through virtual reality (VR) or augmented reality (AR) visualization technology. This allows the sales representative to receive real-time, interactive, and intuitive advice.

[0455] For example, if a customer expresses interest in the price of a product, the server can instantly generate advice regarding price competitiveness. This advice is presented to the sales representative through a terminal in VR / AR format. The sales representative can immediately understand the specific approach through the visual guidance and incorporate it into their interactions with the customer. The user (sales representative) also provides feedback to the system on the customer's reaction to the actions taken. This feedback information is then used by the server to generate advice for future interactions, enabling more accurate sales support throughout the entire system.

[0456] Thus, the present invention realizes a system that enables rapid and precise responses in sales situations and contributes to improving sales performance.

[0457] The following describes the processing flow.

[0458] Step 1:

[0459] The device records conversations between sales representatives and customers as audio data in real time. This recording is continuous from the start to the end of the conversation, and the necessary sound quality is ensured using a microphone.

[0460] Step 2:

[0461] The terminal encrypts the recorded audio data and sends it to the server via a secure communication channel. To minimize communication delays, the audio data is segmented and transmitted sequentially.

[0462] Step 3:

[0463] The server processes the received audio data. Using natural language processing techniques, it breaks down the content of the utterances and analyzes key phrases and customer emotions. This includes tone analysis and speed analysis.

[0464] Step 4:

[0465] The server generates optimal sales advice using an AI model based on the results of sentiment analysis. For example, if a customer is interested in price, it prepares a script to emphasize cost competitiveness.

[0466] Step 5:

[0467] The server converts the generated advice into virtual or augmented reality format and creates visualization data. This data is designed to be intuitively understandable for sales representatives.

[0468] Step 6:

[0469] The terminal uses visualization data received from the server to provide virtual or augmented reality navigation to sales representatives. This allows sales representatives to receive real-time visual advice.

[0470] Step 7:

[0471] The user (sales representative) enters feedback into the terminal regarding the results of their sales activities. This feedback includes customer reactions and sales results.

[0472] Step 8:

[0473] The server uses the collected feedback to update the AI ​​model, improving the accuracy of advice for future sales activities. This process is continuous, accelerating the system's learning.

[0474] (Example 1)

[0475] 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."

[0476] For sales representatives to engage with customers more efficiently and effectively, they need to quickly and accurately grasp customer emotions and interests and respond appropriately based on that understanding. However, with traditional methods, it was difficult for sales representatives to instantly analyze customer emotions and devise optimal responses. Furthermore, the lack of real-time advice and visualization of such information limited the potential for improving sales efficiency.

[0477] 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.

[0478] In this invention, the server includes means for acquiring the conversation between the sales representative and the customer as audio information in real time, means for converting the audio information into a digital format and transferring it to the server for analysis, and means for executing an emotion analysis algorithm using the audio information received by the server to understand the customer's emotions. This makes it possible to generate advice in real time based on emotion analysis and to provide it visually.

[0479] A "sales representative" is someone whose job is to propose and sell a company's or organization's products and services to customers.

[0480] "Audio information" refers to data recorded in sound form, including conversations between sales representatives and customers, and includes information such as the tone, speed, and content of the conversation.

[0481] A "server" is an information processing device that receives and processes voice information over a network and performs necessary analysis and generation.

[0482] An "emotion analysis algorithm" is a series of computational procedures for identifying a customer's emotions from voice information, and a method for determining the customer's psychological state based on the results.

[0483] A "generative AI model" is a framework of artificial intelligence trained to create new information based on past data, and is particularly a technology for generating advice through natural language processing.

[0484] "Virtual reality or augmented reality technology" is a technology that uses digital data to provide a visual experience that blends with the real world, and visualizes information for sales representatives in real time.

[0485] "Customer response information" refers to data that records the reactions and responses that customers gave to the actions of sales representatives.

[0486] "Feedback" refers to input information used to improve future advice provided by the system, based on customer response data.

[0487] This invention is a system designed to enable sales representatives to communicate more effectively with customers. The system supports a series of processes, from acquiring and analyzing voice information, sentiment analysis, generating advice using generative AI models, and visualizing the information using virtual or augmented reality technology.

[0488] Specifically, the terminal captures conversations between sales representatives and customers in real time, acquiring audio information. This requires a microphone for voice input and software for digital conversion of the data. The collected audio information is converted to a digital format and then securely transferred to a server.

[0489] The server receives audio information and processes it using a specific speech analysis algorithm. This algorithm utilizes open-source speech processing libraries or custom models. Based on the analysis results, the server leverages a generative AI model to generate optimal sales advice in real time. Examples of generative AI models include libraries and platforms for natural language processing.

[0490] The generated advice is visually presented to sales representatives via their devices. This presentation utilizes VR / AR technology, displaying information using platforms such as Unity and Unreal Engine. Sales representatives can then use this information to provide more effective service to customers.

[0491] For example, if a customer expresses concern about the price of a particular product, the server generates a prompt message to emphasize price competitiveness. Based on this prompt message, the generating AI model suggests an appropriate sales strategy. A prompt message such as, "The customer is dissatisfied with the price of product A. Please propose a new approach to this customer to emphasize features other than price," might be used.

[0492] Thus, the present invention is a system that combines advanced emotion analysis and generation AI technology based on voice information to enable rapid and precise responses in sales situations, and as a result supports the improvement of sales performance.

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] The terminal captures conversations between sales representatives and customers in real time and acquires them as audio information. Specifically, it records the conversation using an audio input device (microphone) and converts it to a digital format. The input is an analog audio signal, and the output is digital audio data. This data includes the content, tone, and speed of the conversation.

[0496] Step 2:

[0497] The terminal securely transmits the acquired digital audio data to the server. Encryption protocols such as SSL / TLS are used for data transfer. The input is digital audio data, and the output is an encrypted data stream sent to the server.

[0498] Step 3:

[0499] The server executes an emotion analysis algorithm to analyze the received audio data. Specifically, it uses an audio processing library to analyze the tone, speed, and volume patterns of the voice to identify the customer's emotional state. The input is digital audio data, and the output is the result of the emotion analysis (e.g., labeling whether the customer is satisfied, dissatisfied, or interested).

[0500] Step 4:

[0501] The server uses a generative AI model to generate optimal sales advice based on the results of sentiment analysis. Specifically, prompt sentences are input to the AI ​​model, and text regarding sales strategies is generated as output. The input consists of the sentiment analysis results and related prompt sentences, and the output is the generated advice.

[0502] Step 5:

[0503] The device provides generated advice to sales representatives using virtual reality (VR) or augmented reality (AR) technology. Specifically, it visualizes the advice using Unity or Unreal Engine and displays it within the sales representative's field of view. The input is the generated advice text, and the output is the visually represented information.

[0504] Step 6:

[0505] The user (sales representative) conducts the conversation with the customer based on the visually presented advice. They observe the customer's reactions in real time and input them into the system as feedback. The input is the customer's reaction, and the output is the feedback information.

[0506] Step 7:

[0507] The device collects user feedback information and sends it to the server. The server uses this feedback to update the algorithm and improve the performance of future generative AI models. The input is the feedback information, and the output is the parameters of the updated algorithm.

[0508] (Application Example 1)

[0509] 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."

[0510] In conversations between sales representatives and customers, accurately understanding customer emotions and interests and providing appropriate customer service strategies in real time based on that understanding is difficult. Therefore, an efficient and flexible support system is needed to maximize sales effectiveness.

[0511] 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.

[0512] In this invention, the server includes means for acquiring voice information to analyze the conversation of a sales representative, data processing means for analyzing and evaluating the customer's emotions based on the voice information and the physical environment, and display means that utilize a virtual environment or augmented reality technology to visually provide the generated advice to the sales representative. This enables the sales representative to provide a more personalized customer service approach that is tailored to the customer's emotions and environment.

[0513] A "sales representative" is someone whose job is to conduct sales activities with customers and to propose and provide products and services.

[0514] "Auditory information" refers to data obtained by recording or processing sound waves from human speech, and is used to analyze the content and tone of conversations.

[0515] "Data processing means" refers to a hardware or software system designed to analyze input information and generate useful results.

[0516] "Information generation means" refers to an algorithm or process that generates appropriate instructions or suggestions based on input data.

[0517] A "virtual environment" refers to an artificial visual world created by a computer that users can interact with.

[0518] "Augmented reality technology" is a technology that overlays digital information onto the real world, enabling users to perceive that information as reality.

[0519] "Display means" refers to devices or technologies for presenting information visually, and typically includes screens and head-mounted displays.

[0520] "Reaction" refers to the change in emotions or attitudes that a customer shows in response to the actions or words of a sales representative.

[0521] "Environmental information acquisition means" refers to sensors and devices that perceive physical and surrounding conditions and collect that information.

[0522] The system for implementing this invention consists of a visual display device (e.g., smart glasses) worn by a sales representative and a network system centered around a server.

[0523] The server acquires audio information via a microphone attached to a visual display device to record the sales representative's conversation in real time. The acquired audio information is transmitted to the server via Bluetooth through a mobile device. The server converts the audio information into text format using the Google Cloud Speech-to-Text API and then performs sentiment analysis using the Google Cloud Natural Language API.

[0524] Furthermore, the server acquires physical environmental information from the visual display device and performs data processing to infer customer interests based on this environmental information. The results of this processing are displayed within the sales representative's field of view using augmented reality technology. This allows the sales representative to instantly understand strategies tailored to the customer's emotions and respond effectively.

[0525] As a concrete example, in a store, when a customer is inquiring about the latest home appliances, the server analyzes the customer's voice to identify a high level of curiosity and suggests to the sales representative that the features of the new product be emphasized. This information is then fed into the sales representative's field of view through a visual display.

[0526] An example of a prompt message would be, "Analyze customer conversation data in real time and provide a customer service strategy tailored to their emotions." This system, combined with the generative AI model, enables sales representatives to consistently provide appropriate and personalized customer service.

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

[0528] Step 1:

[0529] The terminal acquires real-time audio information of conversations between sales representatives and customers. This audio information is collected via a microphone and transmitted to a server via Bluetooth through a mobile device. The input is an audio signal, and the output is data transfer to the server.

[0530] Step 2:

[0531] The server converts the received audio information into text format using the Google Cloud Speech-to-Text API. This conversion makes the audio conversation usable as text data. The input is audio data, and the output is text data.

[0532] Step 3:

[0533] The server uses the Google Cloud Natural Language API to perform sentiment analysis on text data using a generative AI model. The input is conversational text, and the output is an analysis result that includes sentiment.

[0534] Step 4:

[0535] The server analyzes environmental data transmitted from the terminal and integrates it with sentiment analysis results to infer the customer's areas of interest. This process takes environmental sensor data as input and outputs the analysis results.

[0536] Step 5:

[0537] The server utilizes a generative AI model to generate appropriate strategies for sales representatives based on the analysis results. This prompt determines a specific course of action. The input is sentiment and interest data, and the output is advice.

[0538] Step 6:

[0539] The terminal uses augmented reality technology to visually present the advice received from the server to the sales representative. The advice is overlaid on the sales representative's field of view via the terminal's visual display. The input is advice data from the server, and the output is a visually perceptible presentation of the advice.

[0540] Step 7:

[0541] The entire system is updated when users take action through their devices and feed the results back to the server. Sales results serve as input for this feedback, and improved algorithms are output. This cyclical process continuously enhances the system's effectiveness.

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

[0543] This invention aims to realize a system that recognizes and analyzes user emotions during sales activities and provides effective sales support based on that analysis. The system aims to improve the quality of sales by acquiring voice data from sales representatives and customers and analyzing their emotions using an emotion engine.

[0544] First, the device records the conversation between the sales representative and the customer as audio data in real time. The acquired audio data is encrypted and sent to the server via a secure communication channel.

[0545] Next, the server analyzes the received audio data using an emotion engine to determine the emotional state of the sales representative and the customer in real time. The emotion engine uses natural language processing technology and machine learning algorithms to extract emotions from tone, speed, and volume, and tracks changes in those emotions.

[0546] Based on the analysis results, the server uses an AI model to generate optimal sales advice. This advice is formulated as specific guidance for real-time sales activities, providing options for sales strategies.

[0547] The generated advice is sent to the device as visualized data using virtual reality (VR) or augmented reality (AR) technology. The device then provides this visualized data to the sales representative, who can immediately adjust their sales approach based on this information.

[0548] For example, if a customer shows signs of losing interest in a proposal, the server will generate advice for the salesperson to change the emphasis of the proposal. The salesperson can receive this advice through an AR headset and immediately adjust their approach in the actual sales situation.

[0549] Furthermore, users (sales representatives) provide feedback on the results and impressions after sales activities and input them into the system. The server uses this feedback to continuously learn the model and improve its preparation for future sales activities.

[0550] Thus, the present invention enables dynamic sales support based on emotional changes, increases the success rate of sales activities, and supports the building of effective customer relationships.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] The device records conversations between sales representatives and customers as audio data in real time. It continuously captures audio from the beginning to the end of the conversation and applies noise cancellation technology to minimize background noise.

[0554] Step 2:

[0555] The device encrypts the recorded audio data and sends it to the server via a secure communication channel. The data is divided and sent in an orderly manner to reduce waiting time for real-time processing.

[0556] Step 3:

[0557] The server inputs the received audio data into an emotion engine, which uses natural language processing and speech feature analysis to analyze the emotional states of both the salesperson and the customer. It detects the tone, speed, and volume of the voice and defines emotion labels.

[0558] Step 4:

[0559] The server uses the analyzed emotional data to drive an AI model and generate sales advice tailored to the customer's emotional state. For example, if a customer is emotionally unstable, the advice might include reassuring measures.

[0560] Step 5:

[0561] The server converts the generated sales advice into VR or AR format and prepares it as visualization data. The information is designed to be presented in a format that sales representatives can intuitively understand.

[0562] Step 6:

[0563] The terminal immediately presents visualized sales advice to sales representatives via VR / AR devices. This allows sales representatives to instantly review the advice and act accordingly.

[0564] Step 7:

[0565] The user (sales representative) inputs feedback obtained during and after sales activities into the system. This feedback includes numerical data such as customer reactions and closing rates.

[0566] Step 8:

[0567] The server uses the accumulated feedback to retrain the AI ​​model, improving its accuracy. This continuous learning process improves the quality of the sales advice generated.

[0568] (Example 2)

[0569] 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."

[0570] In sales activities, there is a need to improve sales efficiency by accurately recognizing the customer's emotional state and interests and providing appropriate sales strategies immediately based on that understanding. However, conventional methods have been insufficient in grasping emotional changes in real time and providing effective sales support based on that understanding. Furthermore, the lack of a system for utilizing feedback after sales activities has made it difficult to continuously improve quality and optimize individual processes.

[0571] 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.

[0572] In this invention, the server includes terminal means for acquiring voice information of sales representatives and customers, means for encrypting the voice information and transmitting it to the server via a communication path, means for determining emotional states using a voice analysis engine within the server, means for generating sales advice using a generation AI model based on the determined emotional states, means for visually providing the generated advice to the sales representative using virtual reality or augmented reality technology, and means for collecting feedback after sales activities and updating algorithms within the server. This makes it possible to provide appropriate sales strategies based on emotions in real time and to continuously improve sales activities.

[0573] "Terminal means" refers to the device or function used to acquire voice information between sales representatives and customers in real time and transmit it to a server.

[0574] "Audio information" refers to data that acoustically records the content of conversations between sales representatives and customers, and provides basic data for sentiment analysis.

[0575] "Encryption" refers to the process of transforming audio data into a form that cannot be deciphered in order to protect it from unauthorized access.

[0576] "Communication path" refers to the network infrastructure and protocols used when sending data from a terminal to a server.

[0577] A "server" refers to a computer system that analyzes received audio information and performs related processing.

[0578] A "voice analysis engine" refers to specialized software or algorithms used to extract emotional states and other specific information from voice data.

[0579] "Emotional state" refers to the psychological state or reaction of a customer or sales representative determined from the analyzed audio information.

[0580] A "generative AI model" refers to an artificial intelligence algorithm that learns from past data and feedback and automatically generates sales advice.

[0581] "Sales advice" refers to information that provides specific suggestions and guidelines for effectively conducting sales activities, generated by a generative AI model.

[0582] "Virtual reality technology" refers to the technology of creating a simulation environment using computer graphics.

[0583] Augmented reality technology refers to the technology of overlaying digital information onto the real environment.

[0584] "Feedback" refers to the evaluations and opinions provided to the system based on the content and results of sales activities carried out by sales representatives after the sales activity.

[0585] "Algorithm updating" refers to the process of improving the content of an algorithm based on feedback information in order to improve the performance and accuracy of the system.

[0586] This invention is a system that analyzes customer emotions in real time during sales activities and provides appropriate advice to sales representatives based on that analysis.

[0587] First, the terminal captures the conversation between the sales representative and the customer using a high-performance voice input device. This voice data is encrypted on the spot and sent to the server via a secure data transfer communication protocol (e.g., HTTPS).

[0588] On the server, a voice analysis engine is running, which uses received voice data to analyze the customer's emotional state. This engine combines natural language processing techniques and machine learning algorithms to analyze parameters such as voice tone, speed, and volume. The results of this analysis are used to determine the customer's emotional state in real time.

[0589] After the emotional state is determined, the server uses a generative AI model to automatically generate advice appropriate for the sales situation. This model learns from past sales data and feedback, and provides prompts on what actions the salesperson should take.

[0590] The generated sales advice is visualized using virtual reality (VR) and augmented reality (AR) technologies and provided to sales representatives via their devices. Sales representatives can then immediately adjust their sales approach based on this advice.

[0591] For example, if analysis reveals signs that a customer is losing interest, the server will send advice to the sales representative to restructure the proposal. The sales representative can view this advice in real time on an AR device and quickly adjust their response accordingly.

[0592] Furthermore, users (sales representatives) input feedback on their activities and results into the system after completing their sales activities. This feedback is stored on the server and used to improve the algorithm. The continuously learned generative AI model further enhances sales support in subsequent sales activities.

[0593] Example prompt:

[0594] "Input customer voice data and analyze their emotional responses to the proposal. If they show signs of disinterest, generate advice to adjust the proposal."

[0595] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0596] Step 1:

[0597] The terminal captures voice conversations between sales representatives and customers in real time using a high-performance voice input device. This process yields audio data of the sales conversation as input. This audio data is encrypted on the spot and stored securely.

[0598] Step 2:

[0599] The terminal sends encrypted voice data to the server using a communication protocol (e.g., HTTPS). This process takes encrypted voice data as input and securely transfers the data to the server as output.

[0600] Step 3:

[0601] The server decodes the received audio data and inputs it into the audio analysis engine. Here, as part of the data processing, the audio file is analyzed using natural language processing techniques and machine learning algorithms to determine the customer's emotional state. The output is the customer's emotional state.

[0602] Step 4:

[0603] Using the determined emotional state as input, the server employs a generative AI model to generate sales advice. Data calculations utilize past data and feedback to generate the optimal sales approach. The output provides advice and guidance.

[0604] Step 5:

[0605] The server visualizes the generated sales advice using virtual reality (VR) or augmented reality (AR) technology. Here, the generated advice is input and output as visual information.

[0606] Step 6:

[0607] The terminal provides visualized sales advice to sales representatives. In this step, visual information is output directly to the sales representative's device (e.g., an AR device) to help them immediately adjust their sales approach.

[0608] Step 7:

[0609] Users (sales representatives) input feedback into the system after sales activities. This input includes sales results and impressions. The server receives this feedback and updates the algorithm to improve future sales support. The output of this process is an improved AI model.

[0610] (Application Example 2)

[0611] 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."

[0612] In physical stores, sales staff are required to accurately understand customer emotions through dialogue and immediately adjust sales strategies. However, sales staff are currently unable to fully utilize real-time emotional insights, resulting in inefficient sales and suboptimal customer satisfaction. Furthermore, the security and privacy of voice data are also important issues.

[0613] 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.

[0614] In this invention, the server includes means for acquiring voice data to analyze the conversation of a salesperson, means for executing an algorithm to analyze customer emotions based on the voice data, and means for utilizing virtual reality or augmented reality technology to visually provide the generated advice to the salesperson. This enables salespeople to immediately adjust their customer interactions based on emotional insights obtained in real time, leading to more effective sales activities. Furthermore, by securely transferring and encrypting the voice data to ensure data security, and by providing emotional insights through smart glasses, it is possible to achieve both privacy protection and convenience.

[0615] A "sales representative" is a staff member of a sales organization whose role is to interact directly with customers and provide information about products and services.

[0616] "Means of analyzing dialogue" refers to a device or technology that records and analyzes conversations between sales representatives and customers and extracts important elements.

[0617] "Audio data" refers to information in which the content of what customers or sales representatives say is recorded in digital format.

[0618] An "algorithm for analyzing customer emotions" is a formula or method used to determine a customer's emotional state and level of interest from voice data.

[0619] "Methods for generating advice in real time" refer to technologies and programs that provide immediate action guidelines and suggestions based on data obtained during sales activities.

[0620] "Virtual reality or augmented reality technologies for visual presentation" are technologies that overlay computer-generated information onto the real world, conveying information to users intuitively.

[0621] "Means of collecting feedback" refers to a method or apparatus for recording the results of sales representatives modifying their actions based on advice and providing this information to the system.

[0622] "Methods for updating algorithms" refer to ways to improve sentiment analysis and advice generation techniques based on the feedback received, thereby increasing accuracy in subsequent attempts.

[0623] "Means of securely transferring voice data" refers to technologies that transmit data through encrypted or protected channels to protect it from third parties.

[0624] "Smart glasses" are glasses-type electronic devices that display information visually, allowing users to use them as portable computers.

[0625] This invention provides a system that allows sales staff to analyze customer emotions in real time during in-store sales activities and adjust their responses immediately. A server acquires voice data and analyzes customer emotions based on it. The analyzed emotion data is visually displayed on the sales staff's smart glasses using virtual reality or augmented reality technology.

[0626] The hardware consists of smart glasses with voice acquisition capabilities, and a system that encrypts the audio on a smartphone before transmitting it via 4G / 5G communication. On the server side, the Google Cloud Speech-to-Text API is used, and the analyzed data is processed by an emotion analysis algorithm using TensorFlow. As a result, sales staff are provided with advice on future actions through a visual user interface using Unity.

[0627] To give a specific example, when a salesperson in a cosmetics store is suggesting a new lipstick, if the customer shows signs of losing interest, the system can immediately provide advice such as, "Emphatically mention that this lipstick contains special ingredients." This allows the salesperson to maintain a good relationship with the customer while implementing an effective strategy.

[0628] An example of a prompt for the generating AI model is, "Based on customer sentiment data, what is the best way to engage the customer in the current conversation?" Using this prompt, the system immediately generates effective sales strategy advice.

[0629] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0630] Step 1:

[0631] The server receives voice data from the terminal. The terminal captures the conversation between the customer and the sales representative as voice data in real time, encrypts the collected voice data, and sends it to the server via a secure communication channel. In this process, the input is voice data, and the output is encrypted voice data.

[0632] Step 2:

[0633] The server decrypts the received encrypted audio data and performs speech recognition. It uses the Google Cloud Speech-to-Text API to convert the audio data into text format. In this process, the input is encrypted audio data and the output is text data.

[0634] Step 3:

[0635] The server inputs text data into an emotion analysis algorithm to analyze the emotional state of customers and sales representatives. Using TensorFlow, it extracts emotions from factors such as tone, speed, and volume, and determines changes in emotion. The input is text data, and the output is emotion data.

[0636] Step 4:

[0637] The server uses a generative AI model to generate optimal advice for sales representatives based on the analyzed sentiment data. Prompt sentences are input to the generative AI model to determine the resulting advice. In this process, the input consists of sentiment data and prompt sentences, while the output is advice data.

[0638] Step 5:

[0639] The server constructs the generated advisory data as a visual interface using Unity and transmits it to a terminal (smart glasses) using virtual reality or augmented reality technology. Sales representatives receive this information in real time through the smart glasses. The input is the advisory data, and the output is the visualized interface.

[0640] Step 6:

[0641] The user (sales representative) adjusts their sales approach and interacts with customers based on the advice data. Changes in their behavior during this process are collected as feedback from their device and sent to the server. The output is behavioral feedback data.

[0642] Step 7:

[0643] The server analyzes feedback data received from sales representatives and uses it to improve its sentiment analysis algorithm and generative AI model. This improves the accuracy of advice in future sales activities. The input is feedback data, and the output is the updated algorithm and generative AI model.

[0644] 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.

[0645] 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.

[0646] 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.

[0647] [Fourth Embodiment]

[0648] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0649] 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.

[0650] 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).

[0651] 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.

[0652] 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.

[0653] 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).

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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.

[0660] 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".

[0661] This invention provides a system that enables efficient support in sales activities. This system consistently handles everything from real-time collection of voice data and customer sentiment analysis to recommending appropriate countermeasures and visually presenting those countermeasures to sales representatives. The following describes how each element works together and how the invention is implemented.

[0662] First, the terminal acquires the conversation between the sales representative and the customer as audio data in real time. This audio data includes the customer's and sales representative's statements, tone, and speed during the conversation. Next, the server analyzes this audio data using an algorithm to understand the customer's emotions. Based on this emotion analysis, the server uses AI to generate optimal sales advice.

[0663] The generated advice is delivered to the sales representative by the device through virtual reality (VR) or augmented reality (AR) visualization technology. This allows the sales representative to receive real-time, interactive, and intuitive advice.

[0664] For example, if a customer expresses interest in the price of a product, the server can instantly generate advice regarding price competitiveness. This advice is presented to the sales representative through a terminal in VR / AR format. The sales representative can immediately understand the specific approach through the visual guidance and incorporate it into their interactions with the customer. The user (sales representative) also provides feedback to the system on the customer's reaction to the actions taken. This feedback information is then used by the server to generate advice for future interactions, enabling more accurate sales support throughout the entire system.

[0665] Thus, the present invention realizes a system that enables rapid and precise responses in sales situations and contributes to improving sales performance.

[0666] The following describes the processing flow.

[0667] Step 1:

[0668] The device records conversations between sales representatives and customers as audio data in real time. This recording is continuous from the start to the end of the conversation, and the necessary sound quality is ensured using a microphone.

[0669] Step 2:

[0670] The terminal encrypts the recorded audio data and sends it to the server via a secure communication channel. To minimize communication delays, the audio data is segmented and transmitted sequentially.

[0671] Step 3:

[0672] The server processes the received audio data. Using natural language processing techniques, it breaks down the content of the utterances and analyzes key phrases and customer emotions. This includes tone analysis and speed analysis.

[0673] Step 4:

[0674] The server generates optimal sales advice using an AI model based on the results of sentiment analysis. For example, if a customer is interested in price, it prepares a script to emphasize cost competitiveness.

[0675] Step 5:

[0676] The server converts the generated advice into virtual or augmented reality format and creates visualization data. This data is designed to be intuitively understandable for sales representatives.

[0677] Step 6:

[0678] The terminal uses visualization data received from the server to provide virtual or augmented reality navigation to sales representatives. This allows sales representatives to receive real-time visual advice.

[0679] Step 7:

[0680] The user (sales representative) enters feedback into the terminal regarding the results of their sales activities. This feedback includes customer reactions and sales results.

[0681] Step 8:

[0682] The server uses the collected feedback to update the AI ​​model, improving the accuracy of advice for future sales activities. This process is continuous, accelerating the system's learning.

[0683] (Example 1)

[0684] 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".

[0685] For sales representatives to engage with customers more efficiently and effectively, they need to quickly and accurately grasp customer emotions and interests and respond appropriately based on that understanding. However, with traditional methods, it was difficult for sales representatives to instantly analyze customer emotions and devise optimal responses. Furthermore, the lack of real-time advice and visualization of such information limited the potential for improving sales efficiency.

[0686] 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.

[0687] In this invention, the server includes means for acquiring the conversation between the sales representative and the customer as audio information in real time, means for converting the audio information into a digital format and transferring it to the server for analysis, and means for executing an emotion analysis algorithm using the audio information received by the server to understand the customer's emotions. This makes it possible to generate advice in real time based on emotion analysis and to provide it visually.

[0688] A "sales representative" is someone whose job is to propose and sell a company's or organization's products and services to customers.

[0689] "Audio information" refers to data recorded in sound form, including conversations between sales representatives and customers, and includes information such as the tone, speed, and content of the conversation.

[0690] A "server" is an information processing device that receives and processes voice information over a network and performs necessary analysis and generation.

[0691] An "emotion analysis algorithm" is a series of computational procedures for identifying a customer's emotions from voice information, and a method for determining the customer's psychological state based on the results.

[0692] A "generative AI model" is a framework of artificial intelligence trained to create new information based on past data, and is particularly a technology for generating advice through natural language processing.

[0693] "Virtual reality or augmented reality technology" is a technology that uses digital data to provide a visual experience that blends with the real world, and visualizes information for sales representatives in real time.

[0694] "Customer response information" refers to data that records the reactions and responses that customers gave to the actions of sales representatives.

[0695] "Feedback" refers to input information used to improve future advice provided by the system, based on customer response data.

[0696] This invention is a system designed to enable sales representatives to communicate more effectively with customers. The system supports a series of processes, from acquiring and analyzing voice information, sentiment analysis, generating advice using generative AI models, and visualizing the information using virtual or augmented reality technology.

[0697] Specifically, the terminal captures conversations between sales representatives and customers in real time, acquiring audio information. This requires a microphone for voice input and software for digital conversion of the data. The collected audio information is converted to a digital format and then securely transferred to a server.

[0698] The server receives audio information and processes it using a specific speech analysis algorithm. This algorithm utilizes open-source speech processing libraries or custom models. Based on the analysis results, the server leverages a generative AI model to generate optimal sales advice in real time. Examples of generative AI models include libraries and platforms for natural language processing.

[0699] The generated advice is visually presented to sales representatives via their devices. This presentation utilizes VR / AR technology, displaying information using platforms such as Unity and Unreal Engine. Sales representatives can then use this information to provide more effective service to customers.

[0700] For example, if a customer expresses concern about the price of a particular product, the server generates a prompt message to emphasize price competitiveness. Based on this prompt message, the generating AI model suggests an appropriate sales strategy. A prompt message such as, "The customer is dissatisfied with the price of product A. Please propose a new approach to this customer to emphasize features other than price," might be used.

[0701] Thus, the present invention is a system that combines advanced emotion analysis and generation AI technology based on voice information to enable rapid and precise responses in sales situations, and as a result supports the improvement of sales performance.

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] The terminal captures conversations between sales representatives and customers in real time and acquires them as audio information. Specifically, it records the conversation using an audio input device (microphone) and converts it to a digital format. The input is an analog audio signal, and the output is digital audio data. This data includes the content, tone, and speed of the conversation.

[0705] Step 2:

[0706] The terminal securely transmits the acquired digital audio data to the server. Encryption protocols such as SSL / TLS are used for data transfer. The input is digital audio data, and the output is an encrypted data stream sent to the server.

[0707] Step 3:

[0708] The server executes an emotion analysis algorithm to analyze the received audio data. Specifically, it uses an audio processing library to analyze the tone, speed, and volume patterns of the voice to identify the customer's emotional state. The input is digital audio data, and the output is the result of the emotion analysis (e.g., labeling whether the customer is satisfied, dissatisfied, or interested).

[0709] Step 4:

[0710] The server uses a generative AI model to generate optimal sales advice based on the results of sentiment analysis. Specifically, prompt sentences are input to the AI ​​model, and text regarding sales strategies is generated as output. The input consists of the sentiment analysis results and related prompt sentences, and the output is the generated advice.

[0711] Step 5:

[0712] The device provides generated advice to sales representatives using virtual reality (VR) or augmented reality (AR) technology. Specifically, it visualizes the advice using Unity or Unreal Engine and displays it within the sales representative's field of view. The input is the generated advice text, and the output is the visually represented information.

[0713] Step 6:

[0714] The user (sales representative) conducts the conversation with the customer based on the visually presented advice. They observe the customer's reactions in real time and input them into the system as feedback. The input is the customer's reaction, and the output is the feedback information.

[0715] Step 7:

[0716] The device collects user feedback information and sends it to the server. The server uses this feedback to update the algorithm and improve the performance of future generative AI models. The input is the feedback information, and the output is the parameters of the updated algorithm.

[0717] (Application Example 1)

[0718] 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".

[0719] In conversations between sales representatives and customers, accurately understanding customer emotions and interests and providing appropriate customer service strategies in real time based on that understanding is difficult. Therefore, an efficient and flexible support system is needed to maximize sales effectiveness.

[0720] 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.

[0721] In this invention, the server includes means for acquiring voice information to analyze the conversation of a sales representative, data processing means for analyzing and evaluating the customer's emotions based on the voice information and the physical environment, and display means that utilize a virtual environment or augmented reality technology to visually provide the generated advice to the sales representative. This enables the sales representative to provide a more personalized customer service approach that is tailored to the customer's emotions and environment.

[0722] A "sales representative" is someone whose job is to conduct sales activities with customers and to propose and provide products and services.

[0723] "Auditory information" refers to data obtained by recording or processing sound waves from human speech, and is used to analyze the content and tone of conversations.

[0724] "Data processing means" refers to a hardware or software system designed to analyze input information and generate useful results.

[0725] "Information generation means" refers to an algorithm or process that generates appropriate instructions or suggestions based on input data.

[0726] A "virtual environment" refers to an artificial visual world created by a computer that users can interact with.

[0727] "Augmented reality technology" is a technology that overlays digital information onto the real world, enabling users to perceive that information as reality.

[0728] "Display means" refers to devices or technologies for presenting information visually, and typically includes screens and head-mounted displays.

[0729] "Reaction" refers to the change in emotions or attitudes that a customer shows in response to the actions or words of a sales representative.

[0730] "Environmental information acquisition means" refers to sensors and devices that perceive physical and surrounding conditions and collect that information.

[0731] The system for implementing this invention consists of a visual display device (e.g., smart glasses) worn by a sales representative and a network system centered around a server.

[0732] The server acquires audio information via a microphone attached to a visual display device to record the sales representative's conversation in real time. The acquired audio information is transmitted to the server via Bluetooth through a mobile device. The server converts the audio information into text format using the Google Cloud Speech-to-Text API and then performs sentiment analysis using the Google Cloud Natural Language API.

[0733] Furthermore, the server acquires physical environmental information from the visual display device and performs data processing to infer customer interests based on this environmental information. The results of this processing are displayed within the sales representative's field of view using augmented reality technology. This allows the sales representative to instantly understand strategies tailored to the customer's emotions and respond effectively.

[0734] As a concrete example, in a store, when a customer is inquiring about the latest home appliances, the server analyzes the customer's voice to identify a high level of curiosity and suggests to the sales representative that the features of the new product be emphasized. This information is then fed into the sales representative's field of view through a visual display.

[0735] An example of a prompt message would be, "Analyze customer conversation data in real time and provide a customer service strategy tailored to their emotions." This system, combined with the generative AI model, enables sales representatives to consistently provide appropriate and personalized customer service.

[0736] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0737] Step 1:

[0738] The terminal acquires real-time audio information of conversations between sales representatives and customers. This audio information is collected via a microphone and transmitted to a server via Bluetooth through a mobile device. The input is an audio signal, and the output is data transfer to the server.

[0739] Step 2:

[0740] The server converts the received audio information into text format using the Google Cloud Speech-to-Text API. This conversion makes the audio conversation usable as text data. The input is audio data, and the output is text data.

[0741] Step 3:

[0742] The server uses the Google Cloud Natural Language API to perform sentiment analysis on text data using a generative AI model. The input is conversational text, and the output is an analysis result that includes sentiment.

[0743] Step 4:

[0744] The server analyzes environmental data transmitted from the terminal and integrates it with sentiment analysis results to infer the customer's areas of interest. This process takes environmental sensor data as input and outputs the analysis results.

[0745] Step 5:

[0746] The server utilizes a generative AI model to generate appropriate strategies for sales representatives based on the analysis results. This prompt determines a specific course of action. The input is sentiment and interest data, and the output is advice.

[0747] Step 6:

[0748] The terminal uses augmented reality technology to visually present the advice received from the server to the sales representative. The advice is overlaid on the sales representative's field of view via the terminal's visual display. The input is advice data from the server, and the output is a visually perceptible presentation of the advice.

[0749] Step 7:

[0750] The entire system is updated when users take action through their devices and feed the results back to the server. Sales results serve as input for this feedback, and improved algorithms are output. This cyclical process continuously enhances the system's effectiveness.

[0751] 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.

[0752] This invention aims to realize a system that recognizes and analyzes user emotions during sales activities and provides effective sales support based on that analysis. The system aims to improve the quality of sales by acquiring voice data from sales representatives and customers and analyzing their emotions using an emotion engine.

[0753] First, the device records the conversation between the sales representative and the customer as audio data in real time. The acquired audio data is encrypted and sent to the server via a secure communication channel.

[0754] Next, the server analyzes the received audio data using an emotion engine to determine the emotional state of the sales representative and the customer in real time. The emotion engine uses natural language processing technology and machine learning algorithms to extract emotions from tone, speed, and volume, and tracks changes in those emotions.

[0755] Based on the analysis results, the server uses an AI model to generate optimal sales advice. This advice is formulated as specific guidance for real-time sales activities, providing options for sales strategies.

[0756] The generated advice is sent to the device as visualized data using virtual reality (VR) or augmented reality (AR) technology. The device then provides this visualized data to the sales representative, who can immediately adjust their sales approach based on this information.

[0757] For example, if a customer shows signs of losing interest in a proposal, the server will generate advice for the salesperson to change the emphasis of the proposal. The salesperson can receive this advice through an AR headset and immediately adjust their approach in the actual sales situation.

[0758] Furthermore, users (sales representatives) provide feedback on the results and impressions after sales activities and input them into the system. The server uses this feedback to continuously learn the model and improve its preparation for future sales activities.

[0759] Thus, the present invention enables dynamic sales support based on emotional changes, increases the success rate of sales activities, and supports the building of effective customer relationships.

[0760] The following describes the processing flow.

[0761] Step 1:

[0762] The device records conversations between sales representatives and customers as audio data in real time. It continuously captures audio from the beginning to the end of the conversation and applies noise cancellation technology to minimize background noise.

[0763] Step 2:

[0764] The device encrypts the recorded audio data and sends it to the server via a secure communication channel. The data is divided and sent in an orderly manner to reduce waiting time for real-time processing.

[0765] Step 3:

[0766] The server inputs the received audio data into an emotion engine, which uses natural language processing and speech feature analysis to analyze the emotional states of both the salesperson and the customer. It detects the tone, speed, and volume of the voice and defines emotion labels.

[0767] Step 4:

[0768] The server uses the analyzed emotional data to drive an AI model and generate sales advice tailored to the customer's emotional state. For example, if a customer is emotionally unstable, the advice might include reassuring measures.

[0769] Step 5:

[0770] The server converts the generated sales advice into VR or AR format and prepares it as visualization data. The information is designed to be presented in a format that sales representatives can intuitively understand.

[0771] Step 6:

[0772] The terminal immediately presents visualized sales advice to sales representatives via VR / AR devices. This allows sales representatives to instantly review the advice and act accordingly.

[0773] Step 7:

[0774] The user (sales representative) inputs feedback obtained during and after sales activities into the system. This feedback includes numerical data such as customer reactions and closing rates.

[0775] Step 8:

[0776] The server uses the accumulated feedback to retrain the AI ​​model, improving its accuracy. This continuous learning process improves the quality of the sales advice generated.

[0777] (Example 2)

[0778] 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".

[0779] In sales activities, there is a need to improve sales efficiency by accurately recognizing the customer's emotional state and interests and providing appropriate sales strategies immediately based on that understanding. However, conventional methods have been insufficient in grasping emotional changes in real time and providing effective sales support based on that understanding. Furthermore, the lack of a system for utilizing feedback after sales activities has made it difficult to continuously improve quality and optimize individual processes.

[0780] 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.

[0781] In this invention, the server includes terminal means for acquiring voice information of sales representatives and customers, means for encrypting the voice information and transmitting it to the server via a communication path, means for determining emotional states using a voice analysis engine within the server, means for generating sales advice using a generation AI model based on the determined emotional states, means for visually providing the generated advice to the sales representative using virtual reality or augmented reality technology, and means for collecting feedback after sales activities and updating algorithms within the server. This makes it possible to provide appropriate sales strategies based on emotions in real time and to continuously improve sales activities.

[0782] "Terminal means" refers to the device or function used to acquire voice information between sales representatives and customers in real time and transmit it to a server.

[0783] "Audio information" refers to data that acoustically records the content of conversations between sales representatives and customers, and provides basic data for sentiment analysis.

[0784] "Encryption" refers to the process of transforming audio data into a form that cannot be deciphered in order to protect it from unauthorized access.

[0785] "Communication path" refers to the network infrastructure and protocols used when sending data from a terminal to a server.

[0786] A "server" refers to a computer system that analyzes received audio information and performs related processing.

[0787] A "voice analysis engine" refers to specialized software or algorithms used to extract emotional states and other specific information from voice data.

[0788] "Emotional state" refers to the psychological state or reaction of a customer or sales representative determined from the analyzed audio information.

[0789] A "generative AI model" refers to an artificial intelligence algorithm that learns from past data and feedback and automatically generates sales advice.

[0790] "Sales advice" refers to information that provides specific suggestions and guidelines for effectively conducting sales activities, generated by a generative AI model.

[0791] "Virtual reality technology" refers to the technology of creating a simulation environment using computer graphics.

[0792] Augmented reality technology refers to the technology of overlaying digital information onto the real environment.

[0793] "Feedback" refers to the evaluations and opinions provided to the system based on the content and results of sales activities carried out by sales representatives after the sales activity.

[0794] "Algorithm updating" refers to the process of improving the content of an algorithm based on feedback information in order to improve the performance and accuracy of the system.

[0795] This invention is a system that analyzes customer emotions in real time during sales activities and provides appropriate advice to sales representatives based on that analysis.

[0796] First, the terminal captures the conversation between the sales representative and the customer using a high-performance voice input device. This voice data is encrypted on the spot and sent to the server via a secure data transfer communication protocol (e.g., HTTPS).

[0797] On the server, a voice analysis engine is running, which uses received voice data to analyze the customer's emotional state. This engine combines natural language processing techniques and machine learning algorithms to analyze parameters such as voice tone, speed, and volume. The results of this analysis are used to determine the customer's emotional state in real time.

[0798] After the emotional state is determined, the server uses a generative AI model to automatically generate advice appropriate for the sales situation. This model learns from past sales data and feedback, and provides prompts on what actions the salesperson should take.

[0799] The generated sales advice is visualized using virtual reality (VR) and augmented reality (AR) technologies and provided to sales representatives via their devices. Sales representatives can then immediately adjust their sales approach based on this advice.

[0800] For example, if analysis reveals signs that a customer is losing interest, the server will send advice to the sales representative to restructure the proposal. The sales representative can view this advice in real time on an AR device and quickly adjust their response accordingly.

[0801] Furthermore, users (sales representatives) input feedback on their activities and results into the system after completing their sales activities. This feedback is stored on the server and used to improve the algorithm. The continuously learned generative AI model further enhances sales support in subsequent sales activities.

[0802] Example prompt:

[0803] "Input customer voice data and analyze their emotional responses to the proposal. If they show signs of disinterest, generate advice to adjust the proposal."

[0804] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0805] Step 1:

[0806] The terminal captures voice conversations between sales representatives and customers in real time using a high-performance voice input device. This process yields audio data of the sales conversation as input. This audio data is encrypted on the spot and stored securely.

[0807] Step 2:

[0808] The terminal sends encrypted voice data to the server using a communication protocol (e.g., HTTPS). This process takes encrypted voice data as input and securely transfers the data to the server as output.

[0809] Step 3:

[0810] The server decodes the received audio data and inputs it into the audio analysis engine. Here, as part of the data processing, the audio file is analyzed using natural language processing techniques and machine learning algorithms to determine the customer's emotional state. The output is the customer's emotional state.

[0811] Step 4:

[0812] Using the determined emotional state as input, the server employs a generative AI model to generate sales advice. Data calculations utilize past data and feedback to generate the optimal sales approach. The output provides advice and guidance.

[0813] Step 5:

[0814] The server visualizes the generated sales advice using virtual reality (VR) or augmented reality (AR) technology. Here, the generated advice is input and output as visual information.

[0815] Step 6:

[0816] The terminal provides visualized sales advice to sales representatives. In this step, visual information is output directly to the sales representative's device (e.g., an AR device) to help them immediately adjust their sales approach.

[0817] Step 7:

[0818] Users (sales representatives) input feedback into the system after sales activities. This input includes sales results and impressions. The server receives this feedback and updates the algorithm to improve future sales support. The output of this process is an improved AI model.

[0819] (Application Example 2)

[0820] 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".

[0821] In physical stores, sales staff are required to accurately understand customer emotions through dialogue and immediately adjust sales strategies. However, sales staff are currently unable to fully utilize real-time emotional insights, resulting in inefficient sales and suboptimal customer satisfaction. Furthermore, the security and privacy of voice data are also important issues.

[0822] 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.

[0823] In this invention, the server includes means for acquiring voice data to analyze the conversation of a salesperson, means for executing an algorithm to analyze customer emotions based on the voice data, and means for utilizing virtual reality or augmented reality technology to visually provide the generated advice to the salesperson. This enables salespeople to immediately adjust their customer interactions based on emotional insights obtained in real time, leading to more effective sales activities. Furthermore, by securely transferring and encrypting the voice data to ensure data security, and by providing emotional insights through smart glasses, it is possible to achieve both privacy protection and convenience.

[0824] A "sales representative" is a staff member of a sales organization whose role is to interact directly with customers and provide information about products and services.

[0825] "Means of analyzing dialogue" refers to a device or technology that records and analyzes conversations between sales representatives and customers and extracts important elements.

[0826] "Audio data" refers to information in which the content of what customers or sales representatives say is recorded in digital format.

[0827] An "algorithm for analyzing customer emotions" is a formula or method used to determine a customer's emotional state and level of interest from voice data.

[0828] "Methods for generating advice in real time" refer to technologies and programs that provide immediate action guidelines and suggestions based on data obtained during sales activities.

[0829] "Virtual reality or augmented reality technologies for visual presentation" are technologies that overlay computer-generated information onto the real world, conveying information to users intuitively.

[0830] "Means of collecting feedback" refers to a method or apparatus for recording the results of sales representatives modifying their actions based on advice and providing this information to the system.

[0831] "Methods for updating algorithms" refer to ways to improve sentiment analysis and advice generation techniques based on the feedback received, thereby increasing accuracy in subsequent attempts.

[0832] "Means of securely transferring voice data" refers to technologies that transmit data through encrypted or protected channels to protect it from third parties.

[0833] "Smart glasses" are glasses-type electronic devices that display information visually, allowing users to use them as portable computers.

[0834] This invention provides a system that allows sales staff to analyze customer emotions in real time during in-store sales activities and adjust their responses immediately. A server acquires voice data and analyzes customer emotions based on it. The analyzed emotion data is visually displayed on the sales staff's smart glasses using virtual reality or augmented reality technology.

[0835] The hardware consists of smart glasses with voice acquisition capabilities, and a system that encrypts the audio on a smartphone before transmitting it via 4G / 5G communication. On the server side, the Google Cloud Speech-to-Text API is used, and the analyzed data is processed by an emotion analysis algorithm using TensorFlow. As a result, sales staff are provided with advice on future actions through a visual user interface using Unity.

[0836] To give a specific example, when a salesperson in a cosmetics store is suggesting a new lipstick, if the customer shows signs of losing interest, the system can immediately provide advice such as, "Emphatically mention that this lipstick contains special ingredients." This allows the salesperson to maintain a good relationship with the customer while implementing an effective strategy.

[0837] An example of a prompt for the generating AI model is, "Based on customer sentiment data, what is the best way to engage the customer in the current conversation?" Using this prompt, the system immediately generates effective sales strategy advice.

[0838] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0839] Step 1:

[0840] The server receives voice data from the terminal. The terminal captures the conversation between the customer and the sales representative as voice data in real time, encrypts the collected voice data, and sends it to the server via a secure communication channel. In this process, the input is voice data, and the output is encrypted voice data.

[0841] Step 2:

[0842] The server decrypts the received encrypted audio data and performs speech recognition. It uses the Google Cloud Speech-to-Text API to convert the audio data into text format. In this process, the input is encrypted audio data and the output is text data.

[0843] Step 3:

[0844] The server inputs text data into an emotion analysis algorithm to analyze the emotional state of customers and sales representatives. Using TensorFlow, it extracts emotions from factors such as tone, speed, and volume, and determines changes in emotion. The input is text data, and the output is emotion data.

[0845] Step 4:

[0846] The server uses a generative AI model to generate optimal advice for sales representatives based on the analyzed sentiment data. Prompt sentences are input to the generative AI model to determine the resulting advice. In this process, the input consists of sentiment data and prompt sentences, while the output is advice data.

[0847] Step 5:

[0848] The server constructs the generated advisory data as a visual interface using Unity and transmits it to a terminal (smart glasses) using virtual reality or augmented reality technology. Sales representatives receive this information in real time through the smart glasses. The input is the advisory data, and the output is the visualized interface.

[0849] Step 6:

[0850] The user (sales representative) adjusts their sales approach and interacts with customers based on the advice data. Changes in their behavior during this process are collected as feedback from their device and sent to the server. The output is behavioral feedback data.

[0851] Step 7:

[0852] The server analyzes feedback data received from sales representatives and uses it to improve its sentiment analysis algorithm and generative AI model. This improves the accuracy of advice in future sales activities. The input is feedback data, and the output is the updated algorithm and generative AI model.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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."

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0874] The following is further disclosed regarding the embodiments described above.

[0875] (Claim 1)

[0876] A means of acquiring voice data to analyze the conversations of sales representatives,

[0877] A means for executing an algorithm to analyze customer emotions based on the aforementioned audio data,

[0878] A means for generating advice in real time based on the aforementioned analysis results,

[0879] Means of utilizing virtual reality or augmented reality technology to visually provide generated advice to sales representatives,

[0880] A means of evaluating whether the sales representative's behavior changed as a result of the aforementioned advice and collecting feedback on that change,

[0881] A means of updating the algorithm based on feedback,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, further comprising means for acquiring physical environmental data and analyzing the environmental data to infer customer interests.

[0885] (Claim 3)

[0886] The system according to claim 1, further comprising means for evaluating the responses and actions of sales representatives and recommending efficient sales strategies based on the evaluation results.

[0887] "Example 1"

[0888] (Claim 1)

[0889] A means of acquiring real-time audio information of conversations between sales representatives and customers,

[0890] A means for converting the aforementioned audio information into a digital format and transferring it to a server for analysis,

[0891] The server uses the voice information it receives to execute an emotion analysis algorithm and obtain a means for understanding the customer's emotions.

[0892] A means for generating advice in real time using a generated AI model based on the aforementioned analysis results,

[0893] A means of providing the generated advice to sales representatives visually using virtual reality or augmented reality technology,

[0894] A means of having sales representatives interact with customers based on the advice they receive and collecting the resulting customer responses,

[0895] A means for sending the aforementioned customer response information to a server as feedback and updating the algorithm,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, further comprising means for acquiring physical environmental information and analyzing that information to infer customer interests.

[0899] (Claim 3)

[0900] The system according to claim 1, further comprising means for evaluating the responses of sales representatives and proposing an efficient sales strategy based on the evaluation results.

[0901] "Application Example 1"

[0902] (Claim 1)

[0903] A means of acquiring voice information in order to analyze the conversations of sales representatives,

[0904] A data processing means for analyzing customer emotions based on the aforementioned audio information,

[0905] Information generation means that generates advice in real time based on the aforementioned analysis results,

[0906] A display means that utilizes a virtual environment or augmented reality technology to visually provide the generated advice to sales representatives,

[0907] A recording means for evaluating whether the sales representative's behavior changed as a result of the aforementioned advice and for collecting their response,

[0908] A means for updating data processing means based on collected responses,

[0909] An environmental information acquisition means for analyzing audio information and simultaneously evaluating the physical environment,

[0910] An information generation means that predicts customer interests based on environmental information and adjusts customer service methods in real time,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, which provides advice via a visual display device that can be worn by a sales representative.

[0914] (Claim 3)

[0915] The system according to claim 1, further comprising a decision-making means for evaluating the responses and actions of sales representatives and recommending efficient sales policies based on the evaluation results.

[0916] "Example 2 of combining an emotion engine"

[0917] (Claim 1)

[0918] A terminal device for acquiring voice information of sales representatives and customers,

[0919] Means for encrypting the aforementioned audio information and transmitting it to a server via a communication path,

[0920] The server includes means for determining emotional state using a voice analysis engine,

[0921] A means of generating sales advice using a generative AI model based on the determined emotional state,

[0922] A means of visually providing the generated advice to sales representatives using virtual reality or augmented reality technology,

[0923] A means of collecting feedback after sales activities and updating the algorithm within the server,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, further comprising means for acquiring physical environment information and inferring customer interests.

[0927] (Claim 3)

[0928] The system according to claim 1, further comprising means for evaluating the actions of sales representatives and providing an optimal sales strategy based on the evaluation results.

[0929] "Application example 2 when combining with an emotional engine"

[0930] (Claim 1)

[0931] A means of acquiring voice data to analyze the conversations of sales representatives,

[0932] A means for executing an algorithm to analyze customer emotions based on the aforementioned audio data,

[0933] A means for generating advice in real time based on the aforementioned analysis results,

[0934] Means of utilizing virtual reality or augmented reality technology to visually provide generated advice to sales representatives,

[0935] A means of evaluating whether the sales representative's behavior changed as a result of the aforementioned advice and collecting feedback on that change,

[0936] A means of updating the algorithm based on feedback,

[0937] A means of securely transferring audio data and encrypting it for subsequent analysis,

[0938] A method for using smart glasses as a display device for sales staff to receive emotional insights from customers in a physical store environment,

[0939] A system that includes this.

[0940] (Claim 2)

[0941] The system according to claim 1, further comprising means for acquiring physical environmental data and analyzing the environmental data to infer customer interests.

[0942] (Claim 3)

[0943] The system according to claim 1, further comprising means for evaluating the responses and actions of sales representatives and recommending efficient sales strategies based on the evaluation results. [Explanation of Symbols]

[0944] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring voice data to analyze the conversations of sales representatives, A means for executing an algorithm to analyze customer emotions based on the aforementioned audio data, A means for generating advice in real time based on the aforementioned analysis results, Means of utilizing virtual reality or augmented reality technology to visually provide generated advice to sales representatives, A means of evaluating whether the sales representative's behavior changed as a result of the aforementioned advice and collecting feedback on that change, A means of updating the algorithm based on feedback, A system that includes this.

2. The system according to claim 1, further comprising means for acquiring physical environmental data and analyzing the environmental data to infer customer interests.

3. The system according to claim 1, further comprising means for evaluating the responses and actions of sales representatives and recommending efficient sales strategies based on the evaluation results.

Images