System

Abstract

An object of a system according to an embodiment is to improve efficiency of customer service in a supermarket and to improve customer satisfaction.SOLUTION: A system includes a sales floor guide part, a question response part, and a sales promotion activity part. The store guide unit guides the location of the item based on the question of the customer using the generated AI. The question handling unit generates an answer to the question of the customer using the generated AI. The promotion activity unit guides the event by using the generated AI.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, customer service in supermarkets relied on human labor, making efficient operation difficult.

[0005] The system according to the embodiment aims to improve the efficiency of customer service operations in supermarkets and to increase customer satisfaction. [Means for solving the problem]

[0006] The system according to the embodiment includes a sales floor guidance unit, a question response unit, and a sales promotion unit. The sales floor guidance unit uses a generation AI to guide customers to the location of products based on their questions. The question response unit uses the generation AI to generate answers to their questions. The sales promotion unit uses the generation AI to guide customers to events. [Effects of the Invention]

[0007] The system according to the embodiment can improve the efficiency of customer service operations in supermarkets and increase customer satisfaction. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The customer service support system according to an embodiment of the present invention is a system that supports a wide range of customer service tasks in supermarkets by combining robots and generative AI. This enables the customer service support system to provide attentive customer service, which is expected to improve customer satisfaction and reduce the number of employees.

[0029] A customer service support system according to an embodiment includes a sales floor guidance unit, a question response unit, and a sales promotion activity unit. The sales floor guidance unit uses a generation AI to guide customers to the location of a product based on a customer's question. For example, the sales floor guidance unit uses the generation AI to guide customers to the location of a product they are looking for based on in-store map information and product placement information. The sales floor guidance unit also uses the generation AI to analyze the customer's question and generate appropriate guidance. For example, if a customer asks, "Where is the milk?", the sales floor guidance unit uses the generation AI to answer, "The milk is in the refrigerated section. I'll take you there," and actually guides the customer to the refrigerated section. The question response unit uses the generation AI to generate an answer to the customer's question. For example, the question response unit uses the generation AI to analyze a customer's question and generate an appropriate answer. The question response unit also uses the generation AI to generate an answer based on the customer's question. For example, if a customer asks, "What is the expiration date of this product?", the question response unit uses the generation AI to answer, "The expiration date of this product is December 31, 2023." The sales promotion department uses the generation AI to provide event information. For example, the sales promotion department uses the generation AI to provide appropriate information to customers based on the event schedule and content. The sales promotion department also uses the generation AI to generate information based on the event content. For example, the sales promotion department may provide information such as, "We are currently offering samples of new products in the tasting corner. Please stop by," and guide the customer to the tasting corner. As a result, the customer service support system according to the embodiment can provide product location information based on customer questions, generate answers to those questions, and provide event information, thereby improving customer satisfaction. For example, customers can be spared the trouble of searching for products and receive quick and accurate answers to their questions. Furthermore, information and guidance about in-store events make it easier for customers to participate in events. This is expected to improve the service quality of the supermarket as a whole and increase customer repeat business.

[0030] The sales floor guidance department can analyze a customer's purchase history and recommend the most suitable products for them. For example, the sales floor guidance department retrieves a customer's past purchase history from a database, and the generation AI analyzes that data to identify products that the customer may be interested in. For example, a new yogurt product can be recommended to a customer who has frequently purchased dairy products in the past. The generation AI can also recommend the most suitable products for a customer based on the customer's purchase history. For example, it can suggest new products related to products that the customer has previously purchased. In this way, customer satisfaction can be improved by analyzing a customer's purchase history and recommending the most suitable products.

[0031] The sales floor guidance unit can grasp the congestion situation in the store in real time and guide customers to a route that avoids crowds. For example, the sales floor guidance unit uses the generation AI to analyze data from cameras and sensors installed in the store and grasp the congestion situation in real time. For example, if a specific aisle is congested, the generation AI can guide customers to an alternative route based on that information. The sales floor guidance unit also guides customers to the optimal route based on the congestion situation. For example, it can suggest a route that avoids crowds. This can reduce stress for customers by guiding them to a route that avoids crowds.

[0032] The sales floor guidance unit can link the lighting and music in the store to create an atmosphere that lifts the customer's spirits while the guidance is being given. For example, the sales floor guidance unit can link with the lighting system in the store, and the generation AI can adjust the color and brightness of the lighting while the customer is being guided. For example, it can switch to warm lighting to create a relaxing atmosphere. The sales floor guidance unit can also link with the music system in the store, and the generation AI can adjust the music while the customer is being guided. For example, it can play relaxing music. In this way, by linking the lighting and music, it is possible to create an atmosphere that lifts the customer's spirits.

[0033] The sales floor guidance unit can work in conjunction with other robots in the store, allowing multiple robots to work together to guide customers. For example, the sales floor guidance unit may involve multiple robots placed in the store working together, with the generation AI giving instructions to each robot. For example, when a customer moves to a different area, the next robot takes over. The sales floor guidance unit may also involve the generation AI coordinating multiple robots to provide optimal guidance to customers. For example, the robots may work together to guide customers. This improves the efficiency of guidance by allowing multiple robots to work together to guide customers.

[0034] The question response unit uses a generation AI to provide answers to customer questions in multiple languages, making it possible to accommodate foreign customers as well. For example, the generation AI in the question response unit analyzes customer questions and generates answers in multiple languages. For example, answers are provided in major languages ​​such as English, Chinese, and Spanish. The question response unit also uses a generation AI to generate answers in multiple languages, making it possible to accommodate foreign customers as well. For example, answers are provided in multiple languages ​​to customer questions. This makes it possible to accommodate foreign customers by providing answers in multiple languages.

[0035] The question response unit can provide detailed information and reviews of related products depending on the content of the question. For example, the generation AI in the question response unit analyzes the customer's question and provides detailed information about related products. For example, it provides detailed explanations of the product's ingredients, usage, price, etc. The generation AI in the question response unit also provides reviews of related products based on the content of the customer's question. For example, it introduces ratings and comments from other customers. This makes it possible to increase the customer's desire to purchase by providing detailed information and reviews depending on the content of the question.

[0036] When answering a question, the question response unit can provide relevant coupons and special offer information to increase purchasing motivation. For example, the generation AI in the question response unit analyzes the content of a customer's question and provides relevant coupons and special offer information. For example, in response to a question about a specific product, it will provide information on coupons that can be used for that product. In addition, the question response unit can provide special offer information based on the content of the customer's question through the generation AI. For example, in response to a question about a specific product, it will provide information on special offers. In this way, by providing coupons and special offer information, it is possible to increase the customer's purchasing motivation.

[0037] The question response unit can record the content of the question and send a personalized follow-up email to the customer at a later date. In the question response unit, for example, the generation AI records the content of the customer's question and sends a personalized follow-up email based on that information. For example, it provides additional information in response to the question or guidance on related products. In addition, the question response unit can send a follow-up email based on the content of the customer's question using the generation AI. For example, it makes a personalized suggestion in response to the customer's question. In this way, by recording the content of the question and sending a personalized follow-up email, customer satisfaction can be improved.

[0038] The sales promotion department can use the generation AI to analyze customers' purchasing history and preferences, and provide the most suitable promotional information to each individual customer. For example, the sales promotion department retrieves a customer's purchasing history from a database, and the generation AI analyzes that data to provide the customer with the most suitable promotional information. For example, it may provide coupons related to products previously purchased. The sales promotion department also uses the generation AI to provide the most suitable promotional information based on the customer's preferences. For example, it may introduce new products that the customer may be interested in. In this way, by analyzing a customer's purchasing history and preferences and providing the most suitable promotional information, it is possible to increase the customer's desire to purchase.

[0039] The sales promotion department can update the in-store event schedule in real time and provide customers with the latest information. For example, the sales promotion department updates the in-store event schedule in real time, and the generation AI provides customers with the latest event information based on that information. For example, it notifies them of the start times of limited-time special offers and tasting events. The sales promotion department also provides customers with the latest information based on the event schedule using the generation AI. For example, it notifies them of changes and additional information about events in real time. In this way, by updating the event schedule in real time and providing the latest information, it is possible to increase customers' motivation to participate.

[0040] The sales promotion department can provide visually appealing promotional information by linking with in-store displays and digital signage. For example, the sales promotion department can link with in-store displays and digital signage, and the generation AI can provide visually appealing promotional information. For example, it can play a promotional video for a new product. The sales promotion department can also use the generation AI to provide visually appealing information by using displays and digital signage. For example, it can display information about special offers and discounts. In this way, by linking with displays and digital signage, it can provide visually appealing promotional information.

[0041] The sales promotion department can work in conjunction with other robots in the store, allowing multiple robots to cooperate in sales promotion activities. For example, the sales promotion department allows multiple robots placed in the store to work together, with the generation AI giving instructions to each robot. For example, the robots work together to provide information about a tasting event. In addition, the sales promotion department allows the generation AI to cooperate with multiple robots to provide optimal sales promotion activities to customers. For example, the robots work together to provide information about special offers to customers. In this way, the efficiency of sales promotion activities is improved by having multiple robots cooperate in sales promotion activities.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The customer service support system can further include a health management unit that monitors the customer's health condition. For example, the health management unit analyzes the customer's walking speed and posture to estimate their health condition. If it determines that the customer is tired, it guides the customer to a rest area. The health management unit can also suggest healthy products based on the customer's health condition. For example, it can suggest foods rich in vitamins or low-calorie snacks. This makes it possible to provide services that take the customer's health condition into consideration, thereby improving customer satisfaction.

[0044] Customer service support systems can also incorporate game elements to further increase customer motivation to purchase. For example, customers can earn points by purchasing specific products and use those points to exchange for prizes. They can also earn bonus points by following specific routes within the store. Furthermore, a ranking system can be introduced in which customers compete with other customers, and special benefits can be offered to customers who rank highly. In this way, incorporating game elements can increase customer motivation to purchase.

[0045] The customer service support system can also be equipped with a recipe suggestion unit that suggests optimal recipes to customers based on their purchasing history. For example, a generation AI can generate recipes based on ingredients purchased in the past by the customer and suggest them to the customer. The recipe suggestion unit can also suggest optimal recipes taking into account the customer's preferences and allergy information. Furthermore, the recipe suggestion unit can also provide information about ingredients needed for the suggested recipes in the store. This makes it possible to improve customer satisfaction by utilizing the customer's purchasing history to suggest optimal recipes to customers.

[0046] The customer service support system can also be equipped with a gift suggestion unit that suggests the most suitable gift to a customer based on the customer's purchase history. For example, the generation AI suggests gifts based on the customer's past purchases and preferences. The gift suggestion unit can also suggest the most suitable gift by taking into account the customer's budget and information about the recipient. Furthermore, the gift suggestion unit can provide detailed information about the suggested gift and instructions on how to purchase it. This makes it possible to improve customer satisfaction by utilizing the customer's purchase history to suggest the most suitable gift to the customer.

[0047] The customer service support system can further include a travel suggestion unit that proposes optimal travel plans to customers based on their purchasing history. For example, the generation AI proposes travel plans based on the customer's past purchases and preferences. The travel suggestion unit can also propose optimal travel plans taking into account the customer's budget and travel destination information. Furthermore, the travel suggestion unit can provide detailed information about the proposed travel plan and instructions on how to make reservations. This makes it possible to improve customer satisfaction by utilizing the customer's purchasing history to propose optimal travel plans to customers.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The sales floor guidance department uses generation AI to guide the customer to the location of the product based on the customer's question. For example, the sales floor guidance department uses generation AI to guide the customer to the location of the product they are looking for based on in-store map information and product layout information. The sales floor guidance department also uses generation AI to analyze the customer's question and generate appropriate guidance. For example, if a customer asks, "Where is the milk?", the sales floor guidance department uses generation AI to answer, "The milk is in the refrigerated section. We will show you there," and actually guide the customer to the refrigerated section. Step 2: The question response unit uses the generation AI to generate an answer to the customer's question. For example, the generation AI in the question response unit analyzes the question from the customer and generates an appropriate answer. The generation AI in the question response unit also generates an answer based on the content of the customer's question. For example, if a customer asks, "When is the expiration date of this product?", the question response unit uses the generation AI to answer, "The expiration date of this product is December 31, 2023." Step 3: The sales promotion department uses the generation AI to provide information about the event. For example, the generation AI in the sales promotion department provides appropriate information to customers based on the event schedule and content. The generation AI in the sales promotion department also generates information based on the content of the event. For example, the sales promotion department may provide information such as, "We are currently offering samples of our new products in the tasting corner. Please stop by," and guide customers to the tasting corner.

[0050] (Example 2) The customer service support system according to an embodiment of the present invention is a system that supports a wide range of customer service tasks in supermarkets by combining robots and generative AI. This enables the customer service support system to provide attentive customer service, which is expected to improve customer satisfaction and reduce the number of employees.

[0051] A customer service support system according to an embodiment includes a sales floor guidance unit, a question response unit, and a sales promotion activity unit. The sales floor guidance unit uses a generation AI to guide customers to the location of a product based on a customer's question. For example, the sales floor guidance unit uses the generation AI to guide customers to the location of a product they are looking for based on in-store map information and product placement information. The sales floor guidance unit also uses the generation AI to analyze the customer's question and generate appropriate guidance. For example, if a customer asks, "Where is the milk?", the sales floor guidance unit uses the generation AI to answer, "The milk is in the refrigerated section. I'll take you there," and actually guides the customer to the refrigerated section. The question response unit uses the generation AI to generate an answer to the customer's question. For example, the question response unit uses the generation AI to analyze a customer's question and generate an appropriate answer. The question response unit also uses the generation AI to generate an answer based on the customer's question. For example, if a customer asks, "What is the expiration date of this product?", the question response unit uses the generation AI to answer, "The expiration date of this product is December 31, 2023." The sales promotion department uses the generation AI to provide event information. For example, the sales promotion department uses the generation AI to provide appropriate information to customers based on the event schedule and content. The sales promotion department also uses the generation AI to generate information based on the event content. For example, the sales promotion department may provide information such as, "We are currently offering samples of new products in the tasting corner. Please stop by," and guide the customer to the tasting corner. As a result, the customer service support system according to the embodiment can provide product location information based on customer questions, generate answers to those questions, and provide event information, thereby improving customer satisfaction. For example, customers can be spared the trouble of searching for products and receive quick and accurate answers to their questions. Furthermore, information and guidance about in-store events make it easier for customers to participate in events. This is expected to improve the service quality of the supermarket as a whole and increase customer repeat business.

[0052] The sales floor guidance department can analyze a customer's purchase history and recommend the most suitable products for them. For example, the sales floor guidance department retrieves a customer's past purchase history from a database, and the generation AI analyzes that data to identify products that the customer may be interested in. For example, a new yogurt product can be recommended to a customer who has frequently purchased dairy products in the past. The generation AI can also recommend the most suitable products for a customer based on the customer's purchase history. For example, it can suggest new products related to products that the customer has previously purchased. In this way, customer satisfaction can be improved by analyzing a customer's purchase history and recommending the most suitable products.

[0053] The sales floor guidance unit can grasp the congestion situation in the store in real time and guide customers to a route that avoids crowds. For example, the sales floor guidance unit uses the generation AI to analyze data from cameras and sensors installed in the store and grasp the congestion situation in real time. For example, if a specific aisle is congested, the generation AI can guide customers to an alternative route based on that information. The sales floor guidance unit also guides customers to the optimal route based on the congestion situation. For example, it can suggest a route that avoids crowds. This can reduce stress for customers by guiding them to a route that avoids crowds.

[0054] The sales floor guidance unit uses an emotion estimation function to analyze the emotional state of the customer and can guide stressed customers to a relaxing route. For example, the sales floor guidance unit analyzes the customer's facial expressions and voice, and the generation AI estimates their emotional state. For example, a customer who is feeling stressed can be guided to a quiet area or a relaxing route. The sales floor guidance unit also uses the generation AI to suggest a relaxing route based on the customer's emotional state. For example, it can guide customers to a quiet route that avoids crowded areas. In this way, by analyzing the customer's emotional state and guiding them to a relaxing route, it is possible to reduce stress for customers.

[0055] The sales floor guidance unit can link the lighting and music in the store to create an atmosphere that lifts the customer's spirits while the guidance is being given. For example, the sales floor guidance unit can link with the lighting system in the store, and the generation AI can adjust the color and brightness of the lighting while the customer is being guided. For example, it can switch to warm lighting to create a relaxing atmosphere. The sales floor guidance unit can also link with the music system in the store, and the generation AI can adjust the music while the customer is being guided. For example, it can play relaxing music. In this way, by linking the lighting and music, it is possible to create an atmosphere that lifts the customer's spirits.

[0056] The sales floor guidance unit can work in conjunction with other robots in the store, allowing multiple robots to work together to guide customers. For example, the sales floor guidance unit may involve multiple robots placed in the store working together, with the generation AI giving instructions to each robot. For example, when a customer moves to a different area, the next robot takes over. The sales floor guidance unit may also involve the generation AI coordinating multiple robots to provide optimal guidance to customers. For example, the robots may work together to guide customers. This improves the efficiency of guidance by allowing multiple robots to work together to guide customers.

[0057] The sales floor guidance unit can use the emotion estimation function to predict products that are predicted to interest customers and introduce those products during the guidance. For example, the sales floor guidance unit analyzes the customer's facial expressions and voice, and the generation AI estimates their emotional state. For example, it identifies products that the customer is interested in and introduces those products during the guidance. The sales floor guidance unit also uses the generation AI to suggest products that the customer may be interested in based on the customer's emotional state. For example, it introduces products that the customer is interested in during the guidance. In this way, by predicting products that the customer may be interested in and introducing them during the guidance, it is possible to increase the customer's desire to purchase.

[0058] The question response unit uses a generation AI to provide answers to customer questions in multiple languages, making it possible to accommodate foreign customers as well. For example, the generation AI in the question response unit analyzes customer questions and generates answers in multiple languages. For example, answers are provided in major languages ​​such as English, Chinese, and Spanish. The question response unit also uses a generation AI to generate answers in multiple languages, making it possible to accommodate foreign customers as well. For example, answers are provided in multiple languages ​​to customer questions. This makes it possible to accommodate foreign customers by providing answers in multiple languages.

[0059] The question response unit can provide detailed information and reviews of related products depending on the content of the question. For example, the generation AI in the question response unit analyzes the customer's question and provides detailed information about related products. For example, it provides detailed explanations of the product's ingredients, usage, price, etc. The generation AI in the question response unit also provides reviews of related products based on the content of the customer's question. For example, it introduces ratings and comments from other customers. This makes it possible to increase the customer's desire to purchase by providing detailed information and reviews depending on the content of the question.

[0060] The question response unit uses an emotion estimation function to analyze the emotional response of customers to questions, and can make follow-up suggestions if there is a negative response. For example, the question response unit analyzes the emotional response of customers to questions in real time, and if the generation AI detects a negative response, it makes follow-up suggestions, such as providing additional information or alternatives. The question response unit also makes follow-up suggestions based on the customer's emotional response, such as providing additional information or a special offer if there is a negative response. In this way, customer satisfaction can be improved by analyzing emotional responses and following up if there is a negative response.

[0061] When answering a question, the question response unit can provide relevant coupons and special offer information to increase purchasing motivation. For example, the generation AI in the question response unit analyzes the content of a customer's question and provides relevant coupons and special offer information. For example, in response to a question about a specific product, it will provide information on coupons that can be used for that product. In addition, the question response unit can provide special offer information based on the content of the customer's question through the generation AI. For example, in response to a question about a specific product, it will provide information on special offers. In this way, by providing coupons and special offer information, it is possible to increase the customer's purchasing motivation.

[0062] The question response unit can record the content of the question and send a personalized follow-up email to the customer at a later date. In the question response unit, for example, the generation AI records the content of the customer's question and sends a personalized follow-up email based on that information. For example, it provides additional information in response to the question or guidance on related products. In addition, the question response unit can send a follow-up email based on the content of the customer's question using the generation AI. For example, it makes a personalized suggestion in response to the customer's question. In this way, by recording the content of the question and sending a personalized follow-up email, customer satisfaction can be improved.

[0063] The question response unit uses the emotion estimation function to analyze the emotional state of the customer when asking a question, and can adjust the environment so that the customer can ask the question in a relaxed state. For example, the question response unit analyzes the customer's facial expressions and voice, and the generation AI estimates the emotional state. For example, relaxing music can be played for a nervous customer. The question response unit also adjusts the environment based on the customer's emotional state using the generation AI. For example, the color and brightness of the lighting can be adjusted to provide a relaxing environment. This allows the environment to be adjusted so that customers can ask questions in a relaxed state, thereby improving customer satisfaction.

[0064] The sales promotion department can use the generation AI to analyze customers' purchasing history and preferences, and provide the most suitable promotional information to each individual customer. For example, the sales promotion department retrieves a customer's purchasing history from a database, and the generation AI analyzes that data to provide the customer with the most suitable promotional information. For example, it may provide coupons related to products previously purchased. The sales promotion department also uses the generation AI to provide the most suitable promotional information based on the customer's preferences. For example, it may introduce new products that the customer may be interested in. In this way, by analyzing a customer's purchasing history and preferences and providing the most suitable promotional information, it is possible to increase the customer's desire to purchase.

[0065] The sales promotion department can update the in-store event schedule in real time and provide customers with the latest information. For example, the sales promotion department updates the in-store event schedule in real time, and the generation AI provides customers with the latest event information based on that information. For example, it notifies them of the start times of limited-time special offers and tasting events. The sales promotion department also provides customers with the latest information based on the event schedule using the generation AI. For example, it notifies them of changes and additional information about events in real time. In this way, by updating the event schedule in real time and providing the latest information, it is possible to increase customers' motivation to participate.

[0066] The sales promotion department can use the emotion estimation function to analyze the emotional state of the customer and carry out promotional activities that elicit positive emotions. For example, the sales promotion department analyzes the customer's facial expressions and voice, and the generation AI estimates the emotional state. For example, to elicit positive emotions, the sales promotion department provides the customer with a special offer. The generation AI also performs promotional activities that elicit positive emotions based on the customer's emotional state. For example, it provides positive messages to the customer. In this way, by analyzing the customer's emotional state and carrying out promotional activities that elicit positive emotions, the customer's desire to purchase can be increased.

[0067] The sales promotion department can provide visually appealing promotional information by linking with in-store displays and digital signage. For example, the sales promotion department can link with in-store displays and digital signage, and the generation AI can provide visually appealing promotional information. For example, it can play a promotional video for a new product. The sales promotion department can also use the generation AI to provide visually appealing information by using displays and digital signage. For example, it can display information about special offers and discounts. In this way, by linking with displays and digital signage, it can provide visually appealing promotional information.

[0068] The sales promotion department can work in conjunction with other robots in the store, allowing multiple robots to cooperate in sales promotion activities. For example, the sales promotion department allows multiple robots placed in the store to work together, with the generation AI giving instructions to each robot. For example, the robots work together to provide information about a tasting event. In addition, the sales promotion department allows the generation AI to cooperate with multiple robots to provide optimal sales promotion activities to customers. For example, the robots work together to provide information about special offers to customers. In this way, the efficiency of sales promotion activities is improved by having multiple robots cooperate in sales promotion activities.

[0069] The sales promotion department can use the emotion estimation function to predict events and tastings that customers might be interested in and provide individual information about them. For example, the sales promotion department analyzes the customer's facial expressions and voice, and the generation AI estimates their emotional state. For example, it identifies events and tastings that the customer is interested in and provides information about them. The sales promotion department also uses the generation AI to predict events and tastings that the customer might be interested in based on the customer's emotional state and provides individual information about them. For example, it provides information about events and tastings that the customer is interested in. This makes it possible to predict events and tastings that the customer might be interested in and provide individual information about them, thereby increasing the customer's motivation to participate.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The customer service support system can further include a health management unit that monitors the customer's health condition. For example, the health management unit analyzes the customer's walking speed and posture to estimate their health condition. If it determines that the customer is tired, it guides the customer to a rest area. The health management unit can also suggest healthy products based on the customer's health condition. For example, it can suggest foods rich in vitamins or low-calorie snacks. This makes it possible to provide services that take the customer's health condition into consideration, thereby improving customer satisfaction.

[0072] Customer service support systems can also incorporate game elements to further increase customer motivation to purchase. For example, customers can earn points by purchasing specific products and use those points to exchange for prizes. They can also earn bonus points by following specific routes within the store. Furthermore, a ranking system can be introduced in which customers compete with other customers, and special benefits can be offered to customers who rank highly. In this way, incorporating game elements can increase customer motivation to purchase.

[0073] The customer service support system can further include a music providing unit that estimates the emotional state of the customer and provides appropriate music based on the estimated emotion. For example, if the customer feels like relaxing, relaxing music can be played. On the other hand, if the customer feels like cheering up, upbeat music can be provided. Furthermore, the music providing unit can adjust the genre and volume of the music according to the customer's emotional state. This can improve customer satisfaction by providing music that matches the customer's emotional state.

[0074] The customer service support system can further include a scent providing unit that estimates the emotional state of the customer and provides an appropriate scent based on the estimated emotion. For example, if the customer wants to relax, a lavender scent can be provided. Alternatively, if the customer wants to feel energized, a citrus scent can be provided. Furthermore, the scent providing unit can adjust the strength and type of scent depending on the customer's emotional state. This can improve customer satisfaction by providing a scent that matches the customer's emotional state.

[0075] The customer service support system may further include a lighting unit that estimates the emotional state of the customer and provides appropriate lighting based on the estimated emotion. For example, if the customer feels like relaxing, warm lighting may be provided. Alternatively, if the customer feels like cheering up, bright white lighting may be provided. Furthermore, the lighting unit may adjust the color and brightness of the lighting according to the customer's emotional state. This allows for improved customer satisfaction by providing lighting that matches the customer's emotional state.

[0076] The customer service support system can also be equipped with a recipe suggestion unit that suggests optimal recipes to customers based on their purchasing history. For example, a generation AI can generate recipes based on ingredients purchased in the past by the customer and suggest them to the customer. The recipe suggestion unit can also suggest optimal recipes taking into account the customer's preferences and allergy information. Furthermore, the recipe suggestion unit can also provide information about ingredients needed for the suggested recipes in the store. This makes it possible to improve customer satisfaction by utilizing the customer's purchasing history to suggest optimal recipes to customers.

[0077] The customer service support system can further include a tasting suggestion unit that estimates the emotional state of the customer and suggests appropriate products to sample based on the estimated emotion. For example, the system can identify products that the customer is interested in and offer those products for tasting. The tasting suggestion unit can also adjust the type and amount of samples to be offered depending on the customer's emotional state. Furthermore, the tasting suggestion unit can collect feedback on products that the customer has sampled and use it to suggest products for the next time. This can improve customer satisfaction by suggesting samples that match the customer's emotional state.

[0078] The customer service support system can also be equipped with a gift suggestion unit that suggests the most suitable gift to a customer based on the customer's purchase history. For example, the generation AI suggests gifts based on the customer's past purchases and preferences. The gift suggestion unit can also suggest the most suitable gift by taking into account the customer's budget and information about the recipient. Furthermore, the gift suggestion unit can provide detailed information about the suggested gift and instructions on how to purchase it. This makes it possible to improve customer satisfaction by utilizing the customer's purchase history to suggest the most suitable gift to the customer.

[0079] The customer service support system can further include a travel suggestion unit that proposes optimal travel plans to customers based on their purchasing history. For example, the generation AI proposes travel plans based on the customer's past purchases and preferences. The travel suggestion unit can also propose optimal travel plans taking into account the customer's budget and travel destination information. Furthermore, the travel suggestion unit can provide detailed information about the proposed travel plan and instructions on how to make reservations. This makes it possible to improve customer satisfaction by utilizing the customer's purchasing history to propose optimal travel plans to customers.

[0080] The customer service support system may further include a feedback providing unit that estimates the emotional state of the customer and provides appropriate feedback based on the estimated emotion. For example, if a customer is dissatisfied, the system identifies the cause and proposes a remedy. The feedback providing unit may also adjust the content and method of feedback depending on the customer's emotional state. Furthermore, the feedback providing unit may collect feedback from customers and use it to improve the next service. In this way, customer satisfaction can be improved by providing feedback that matches the customer's emotional state.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The sales floor guidance department uses generation AI to guide the customer to the location of the product based on the customer's question. For example, the sales floor guidance department uses generation AI to guide the customer to the location of the product they are looking for based on in-store map information and product layout information. The sales floor guidance department also uses generation AI to analyze the customer's question and generate appropriate guidance. For example, if a customer asks, "Where is the milk?", the sales floor guidance department uses generation AI to answer, "The milk is in the refrigerated section. We will show you there," and actually guide the customer to the refrigerated section. Step 2: The question response unit uses the generation AI to generate an answer to the customer's question. For example, the generation AI in the question response unit analyzes the question from the customer and generates an appropriate answer. The generation AI in the question response unit also generates an answer based on the content of the customer's question. For example, if a customer asks, "When is the expiration date of this product?", the question response unit uses the generation AI to answer, "The expiration date of this product is December 31, 2023." Step 3: The sales promotion department uses the generation AI to provide information about the event. For example, the generation AI in the sales promotion department provides appropriate information to customers based on the event schedule and content. The generation AI in the sales promotion department also generates information based on the content of the event. For example, the sales promotion department may provide information such as, "We are currently offering samples of our new products in the tasting corner. Please stop by," and guide customers to the tasting corner.

[0083] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0084] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0085] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0088] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0089] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0090] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0091] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0092] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0093] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0096] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0097] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0098] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0099] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0100] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0103] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0104] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0105] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0106] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0107] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0108] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0109] 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.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0111] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0112] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0113] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0114] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 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.

[0118] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0119] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0120] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0121] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0122] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0123] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0124] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0125] 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.

[0126] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0127] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0128] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0129] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0130] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0131] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0132] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0133] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0134] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0135] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0136] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0137] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0138] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0139] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0140] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0141] 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.

[0142] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0143] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0144] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0145] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0146] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0147] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0148] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0149] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0150] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A sales floor guidance department that uses generative AI to guide customers to the location of products based on their questions; a question response unit that generates an answer to the customer's question using the generation AI; A sales promotion activity department that uses the generation AI to guide events. A system characterized by:

2. The sales floor guide unit Analyze the customer's purchase history and recommend the most suitable products for the customer.

2. The system of claim 1.

3. The sales floor guide unit By linking the lighting and music in the store, the customer's mood is enhanced during the guidance.

2. The system of claim 1.

4. The question response unit The generative AI is used to provide answers to customer questions in multiple languages, and to accommodate foreign customers.

2. The system of claim 1.

5. The sales promotion department The generation AI is used to analyze the customer's purchasing history and preferences, and provide the optimal sales promotion information to each individual customer.

2. The system of claim 1.

6. The sales floor guide unit Analyze the emotional state of the customer and guide stressed customers to a relaxing route 2. The system of claim 1.

7. The question response unit Analyze the customer's emotional response to the question and provide follow-up suggestions if there is a negative response 2. The system of claim 1.

8. The sales promotion department Analyze the emotional state of the customer and carry out promotional activities that elicit positive emotions 2. The system of claim 1.

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