System

Abstract

An object of a system according to an embodiment is to improve the efficiency of a funeral consultation or procedure and reduce the burden on a consultant and an employee of a funeral company.SOLUTION: A system includes a generation AI, an information addition unit, and a company information addition unit. The generation AI automatically generates an answer to the question of the requester. The information addition part adds detailed information on the funeral. The company information adding unit adds information of a company to be introduced.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, funeral consultations and procedures had the problem of placing a burden on both the person seeking advice and the funeral company's employees.

[0005] The system according to the embodiment aims to streamline funeral consultations and procedures, and reduce the burden on those seeking advice and funeral company employees. [Means for solving the problem]

[0006] The system according to the embodiment includes a generation AI, an information adding unit, and a company information adding unit. The generation AI automatically generates answers to questions from clients. The information adding unit adds detailed information about funerals. The company information adding unit adds information about the company that will be implementing the system. [Effects of the Invention]

[0007] The system according to the embodiment can streamline funeral consultations and procedures, reducing the burden on those seeking advice and funeral company employees. [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 funeral consultation system according to an embodiment of the present invention is a system for efficiently and accurately providing consultations and procedures for funerals. This system uses a generation AI to automatically generate answers to questions from clients, add detailed information about the funeral, and add information about the company that will be implementing the system. This allows the funeral consultation system to efficiently and accurately provide consultations and procedures for funerals.

[0029] The funeral consultation system according to the embodiment includes a generation AI, an information adding unit, and a company information adding unit. The generation AI automatically generates answers to questions from clients. For example, in response to a client's question, "How much does a funeral cost?", the generation AI generates an answer such as, "A typical funeral costs between XXX yen and XXX yen." In response to a client's question, "What is the difference between a family funeral and a general funeral?", the generation AI generates an answer such as, "A family funeral is a small funeral attended only by close family and friends, while a general funeral is a large funeral attended by many people." In response to a client's question, "Which funeral company serves this area?", the generation AI generates an answer such as, "XXX Funeral Company serves this area." The information adding unit adds detailed information about the funeral. For example, the information adding unit adds information such as the type of funeral, the procedure, necessary documents, and a breakdown of costs. This allows the generation AI to provide accurate answers to specific client questions. The company information adding unit adds information about the funeral company to be implemented. For example, the company information addition unit adds information such as the services provided by the company, pricing plans, and service areas. This allows the generation AI to provide specific company information to the person seeking advice. This allows the funeral consultation system according to the embodiment to efficiently and accurately handle funeral consultations and procedures. For example, the generation AI automatically answers basic questions, allowing funeral company employees to focus on more specialized consultations and procedures. Furthermore, the information provided by the generation AI is always up-to-date, allowing accurate information to be provided to the person seeking advice.

[0030] The generation AI can refer to the client's past consultation history and provide an answer that is individually customized. For example, the generation AI can retrieve the client's past consultation history from a database and generate an answer that is customized based on the content of the past consultation. For example, if a client has previously consulted about a family funeral, the latest information on family funerals will be provided. The generation AI can also provide an answer that is tailored to the client's preferences and needs based on the client's past consultation history. For example, if a client has previously consulted about a specific funeral plan, detailed information about that plan will be provided. This allows the client to receive a more appropriate answer.

[0031] The generative AI can interact with the person seeking advice via video call and utilize visual information to provide answers. The generative AI can interact with the person seeking advice via video call and utilize visual information to provide answers. For example, the generative AI can explain funeral procedures while displaying documents on a shared screen. The generative AI can also analyze the person seeking advice's facial expressions and gestures via video call and provide answers that correspond to their emotional state. For example, if the person seeking advice is confused, it can provide a more detailed explanation. The generative AI can also provide the person seeking advice with information that is visually easy to understand via video call. This allows the use of visual information to provide more specific answers.

[0032] The generation AI can support multiple languages ​​and respond to consultations in different languages. The generation AI can, for example, support multiple languages ​​and respond to consultations in different languages. For example, it can respond to consultations in multiple languages ​​such as Japanese, English, and Chinese. The generation AI can also automatically provide answers in the appropriate language based on the language setting of the person seeking advice. For example, if the person seeking advice selects English, it will provide answers in English. The generation AI can also use translation technology for multilingual support to translate the person's question into the appropriate language and generate an answer. This makes it possible to respond to consultations in different languages.

[0033] Generative AI can automatically collect the latest funeral industry news and legal reform information and provide it to the client. Generative AI can, for example, automatically collect the latest funeral industry news and provide it to the client. For example, it can provide information on new funeral plans and services in real time. Generative AI can also automatically collect legal reform information and provide it to the client. For example, it can provide information on new laws and regulations related to funerals. Generative AI can also provide appropriate advice to the client based on the latest funeral industry news and legal reform information. This allows the client to receive the latest information.

[0034] Generative AI can provide information that takes into account regional funeral customs and cultural backgrounds. For example, generative AI can retrieve regional funeral customs from a database and provide them to the client. For example, it can explain the traditional funeral procedures that are performed in a particular region. Generative AI can also provide information that takes cultural backgrounds into account. For example, it can explain funeral customs and rituals based on a particular religion or culture. Generative AI can also provide appropriate advice to the client based on regional funeral customs and cultural backgrounds. This makes it possible to provide information that is appropriate for regional funeral customs and cultural backgrounds.

[0035] The generative AI can provide visually easy-to-understand information using videos and images related to funerals. The generative AI can provide visually easy-to-understand information using videos related to funerals. For example, the procedure for funerals and the flow of ceremonies can be explained using videos. The generative AI can also provide visually easy-to-understand information using images related to funerals. For example, it can display photos of the funeral venue and facilities. The generative AI can also provide visually easy-to-understand information to the client using videos and images. This makes it possible to provide information that is visually easy to understand.

[0036] The generation AI can automatically generate FAQs about funerals, allowing the person seeking advice to resolve their own problem. The generation AI can, for example, automatically generate FAQs about funerals, allowing the person seeking advice to resolve their own problem. For example, it can display a list of frequently asked questions and their answers. The generation AI can also automatically display related FAQs based on the person seeking advice. For example, if the person seeking advice asks, "How much does a funeral cost?", it will display related FAQs. The generation AI can also support the person seeking advice to resolve their own problem by automatically generating FAQs. This helps the person seeking advice to resolve their own problem.

[0037] The generation AI can analyze the past performance and evaluations of each funeral company and recommend the most suitable company. For example, the generation AI can retrieve the past performance of each funeral company from a database and recommend the most suitable company based on that performance. For example, it can make recommendations based on the number of funerals held in the past and customer satisfaction. The generation AI can also analyze the evaluations of each funeral company and recommend the most suitable company. For example, it can make recommendations based on customer feedback and industry evaluations. The generation AI can also recommend the most suitable funeral company to the client based on past performance and evaluations. This makes it possible to recommend the most suitable funeral company.

[0038] The generation AI can compare the service content of each funeral company in detail and propose the most suitable plan to the client. For example, the generation AI retrieves the service content of each funeral company from a database and compares them in detail. For example, it compares the types and content of services provided and proposes the most suitable plan. The generation AI also proposes the most suitable plan based on the client's needs. For example, it proposes the most suitable plan based on the client's budget and desired service content. The generation AI can also propose the most suitable plan to the client by comparing the service content in detail. This makes it possible to propose the most suitable funeral plan.

[0039] The generating AI can provide promotional videos and interviews of each funeral company to provide visual information to the person seeking advice. For example, the generating AI can retrieve promotional videos of each funeral company from a database and provide them to the person seeking advice. For example, the generating AI can explain while showing an introductory video of the company. The generating AI can also provide interviews of each funeral company to provide visual information to the person seeking advice. For example, the generating AI can explain while showing interviews with the company's representative or staff. The generating AI can also use promotional videos and interviews to provide information that is easy to understand visually to the person seeking advice. By providing visual information, the person seeking advice can understand more specifically.

[0040] The generation AI can automatically compare the pricing plans of each funeral company and propose the most suitable plan. For example, the generation AI retrieves the pricing plans of each funeral company from a database and automatically compares them. For example, it proposes the most suitable pricing plan according to the budget. The generation AI also compares the breakdown of pricing plans in detail and proposes the most suitable plan for the client. For example, it compares the service content and fee breakdown and proposes the most suitable plan. The generation AI also automatically compares pricing plans and can propose the most suitable plan for the client. This makes it possible to propose the most suitable pricing plan.

[0041] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0042] The funeral consultation system can refer to the consultation history of the client and provide an answer that is individually customized. For example, if a client has previously consulted about a family funeral, the latest information on family funerals can be provided. Also, if a client has previously consulted about a specific funeral plan, detailed information on that plan can be provided. Furthermore, it is possible to provide answers that are tailored to the client's preferences and needs. This allows the client to receive a more appropriate answer.

[0043] The funeral consultation system can automatically collect the latest funeral industry news and legal reform information and provide it to the client. For example, it can provide information on new funeral plans and services in real time. It can also provide information on new laws and regulations related to funerals. Furthermore, it can provide appropriate advice to the client based on the latest funeral industry news and legal reform information. This allows the client to receive the latest information.

[0044] The funeral consultation system analyzes the past performance and evaluations of each funeral company and can recommend the most suitable company. For example, recommendations can be made based on the number of funerals held in the past and customer satisfaction. Recommendations can also be made based on customer feedback and industry evaluations. Furthermore, based on past performance and evaluations, it can recommend the most suitable funeral company for the client. This makes it possible to recommend the most suitable funeral company.

[0045] The funeral consultation system can compare the service content of each funeral company in detail and propose the most suitable plan to the client. For example, it can compare the types and contents of services offered and propose the most suitable plan. It can also propose the most suitable plan based on the client's needs. Furthermore, by comparing the service content in detail, it can propose the most suitable plan to the client. This makes it possible to propose the most suitable funeral plan.

[0046] The funeral consultation system can provide promotional videos and interviews of each funeral company to provide visual information to the client. For example, explanations can be given while showing an introductory video of the company. It can also provide explanations while showing interviews with company representatives and staff. Furthermore, promotional videos and interviews can be used to provide information that is visually easy to understand to the client. Providing visual information allows the client to understand more specifically.

[0047] The funeral consultation system can automatically compare the pricing plans of each funeral company and propose the most suitable plan. For example, it can propose the most suitable pricing plan according to the budget. It can also compare the breakdown of pricing plans in detail and propose the most suitable plan for the client. Furthermore, by automatically comparing pricing plans, it can propose the most suitable plan for the client. This makes it possible to propose the most suitable pricing plan.

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

[0049] Step 1: The generation AI automatically generates answers to the client's questions. For example, in response to a client's question, "How much does a funeral cost?", the generation AI generates an answer such as, "A typical funeral costs between XXX yen and XXX yen." In response to a client's question, "What is the difference between a family funeral and a general funeral?", the generation AI generates an answer such as, "A family funeral is a small funeral attended only by close family and friends, while a general funeral is a large funeral attended by many people." In response to a client's question, "Which funeral companies serve this area?", the generation AI generates an answer such as, "XXX Funeral Home serves this area." Step 2: The information addition unit adds detailed information about the funeral. For example, the information addition unit adds information such as the type of funeral, the procedure, necessary documents, and a breakdown of costs. This allows the generation AI to provide accurate answers to even the most specific questions from the client. Step 3: The company information addition unit adds information about the funeral company being introduced. For example, the company information addition unit adds information such as the services provided by the company, pricing plans, and service areas. This allows the generation AI to provide specific company information to the person seeking advice.

[0050] (Example 2) The funeral consultation system according to an embodiment of the present invention is a system for efficiently and accurately providing consultations and procedures for funerals. This system uses a generation AI to automatically generate answers to questions from clients, add detailed information about the funeral, and add information about the company that will be implementing the system. This allows the funeral consultation system to efficiently and accurately provide consultations and procedures for funerals.

[0051] The funeral consultation system according to the embodiment includes a generation AI, an information adding unit, and a company information adding unit. The generation AI automatically generates answers to questions from clients. For example, in response to a client's question, "How much does a funeral cost?", the generation AI generates an answer such as, "A typical funeral costs between XXX yen and XXX yen." In response to a client's question, "What is the difference between a family funeral and a general funeral?", the generation AI generates an answer such as, "A family funeral is a small funeral attended only by close family and friends, while a general funeral is a large funeral attended by many people." In response to a client's question, "Which funeral company serves this area?", the generation AI generates an answer such as, "XXX Funeral Company serves this area." The information adding unit adds detailed information about the funeral. For example, the information adding unit adds information such as the type of funeral, the procedure, necessary documents, and a breakdown of costs. This allows the generation AI to provide accurate answers to specific client questions. The company information adding unit adds information about the funeral company to be implemented. For example, the company information addition unit adds information such as the services provided by the company, pricing plans, and service areas. This allows the generation AI to provide specific company information to the person seeking advice. This allows the funeral consultation system according to the embodiment to efficiently and accurately handle funeral consultations and procedures. For example, the generation AI automatically answers basic questions, allowing funeral company employees to focus on more specialized consultations and procedures. Furthermore, the information provided by the generation AI is always up-to-date, allowing accurate information to be provided to the person seeking advice.

[0052] The generation AI can refer to the client's past consultation history and provide an answer that is individually customized. For example, the generation AI can retrieve the client's past consultation history from a database and generate an answer that is customized based on the content of the past consultation. For example, if a client has previously consulted about a family funeral, the latest information on family funerals will be provided. The generation AI can also provide an answer that is tailored to the client's preferences and needs based on the client's past consultation history. For example, if a client has previously consulted about a specific funeral plan, detailed information about that plan will be provided. This allows the client to receive a more appropriate answer.

[0053] The generation AI can analyze the caller's tone of voice and language and generate an answer that corresponds to their emotional state. For example, the generation AI can analyze the caller's tone of voice in real time to estimate their emotional state. For example, if there is a strong tone of sadness, the generation AI can generate an answer using gentle language. The generation AI can also analyze the caller's language and generate an answer that corresponds to their emotional state. For example, if there is a strong tone of anger, the generation AI can generate an answer using calm language. The generation AI can also analyze both the caller's tone of voice and language and generate the optimal answer according to their emotional state. This makes it possible to provide an answer that takes into consideration the caller's emotions.

[0054] The generation AI can use the emotion estimation function to estimate the emotions of the person seeking advice in real time and provide an answer that takes those emotions into consideration. For example, the generation AI can use the emotion estimation function to estimate the emotions of the person seeking advice in real time from their facial expressions and voice, and generate an answer that takes those emotions into consideration. For example, if the person feels strong sadness, it will provide an answer that includes comforting words. The generation AI can also use the emotion estimation function to analyze the person's emotional state and provide an answer that takes those emotions into consideration. For example, if the person feels strong anger, it will provide an answer using calm language. The generation AI can also use the emotion estimation function to provide the optimal answer based on the person's emotions. This makes it possible to provide an appropriate answer based on the person's emotions.

[0055] The generative AI can interact with the person seeking advice via video call and utilize visual information to provide answers. The generative AI can interact with the person seeking advice via video call and utilize visual information to provide answers. For example, the generative AI can explain funeral procedures while displaying documents on a shared screen. The generative AI can also analyze the person seeking advice's facial expressions and gestures via video call and provide answers that correspond to their emotional state. For example, if the person seeking advice is confused, it can provide a more detailed explanation. The generative AI can also provide the person seeking advice with information that is visually easy to understand via video call. This allows the use of visual information to provide more specific answers.

[0056] The generation AI can support multiple languages ​​and respond to consultations in different languages. The generation AI can, for example, support multiple languages ​​and respond to consultations in different languages. For example, it can respond to consultations in multiple languages ​​such as Japanese, English, and Chinese. The generation AI can also automatically provide answers in the appropriate language based on the language setting of the person seeking advice. For example, if the person seeking advice selects English, it will provide answers in English. The generation AI can also use translation technology for multilingual support to translate the person's question into the appropriate language and generate an answer. This makes it possible to respond to consultations in different languages.

[0057] The generation AI can use the emotion estimation function to provide music and videos with a relaxing effect based on the client's emotions. For example, the generation AI can use the emotion estimation function to analyze the client's emotional state and provide music with a relaxing effect. For example, if the client feels a strong sense of sadness, soothing music can be played. The generation AI can also use the emotion estimation function to provide videos with a relaxing effect based on the client's emotional state. For example, videos of natural landscapes or a calm ocean can be played. The generation AI can also use the emotion estimation function to provide music and videos with the optimal relaxing effect according to the client's emotions. This makes it possible to provide music and videos with a relaxing effect according to the client's emotions.

[0058] Generative AI can automatically collect the latest funeral industry news and legal reform information and provide it to the client. Generative AI can, for example, automatically collect the latest funeral industry news and provide it to the client. For example, it can provide information on new funeral plans and services in real time. Generative AI can also automatically collect legal reform information and provide it to the client. For example, it can provide information on new laws and regulations related to funerals. Generative AI can also provide appropriate advice to the client based on the latest funeral industry news and legal reform information. This allows the client to receive the latest information.

[0059] Generative AI can provide information that takes into account regional funeral customs and cultural backgrounds. For example, generative AI can retrieve regional funeral customs from a database and provide them to the client. For example, it can explain the traditional funeral procedures that are performed in a particular region. Generative AI can also provide information that takes cultural backgrounds into account. For example, it can explain funeral customs and rituals based on a particular religion or culture. Generative AI can also provide appropriate advice to the client based on regional funeral customs and cultural backgrounds. This makes it possible to provide information that is appropriate for regional funeral customs and cultural backgrounds.

[0060] The generation AI can use the emotion estimation function to optimize the order in which information is presented according to the client's emotions. For example, the generation AI uses the emotion estimation function to analyze the client's emotional state and optimize the order in which information is presented according to the emotion. For example, if the client feels strong sadness, it will first provide words of comfort, and then present specific information. The generation AI also uses the emotion estimation function to determine the optimal order in which information is presented according to the client's emotions. For example, if the client feels strong anger, it will provide information using calm language. The generation AI can also use the emotion estimation function to automatically adjust the optimal order in which information is presented according to the client's emotions. This makes it possible to present information optimally according to the client's emotions.

[0061] The generative AI can provide visually easy-to-understand information using videos and images related to funerals. The generative AI can provide visually easy-to-understand information using videos related to funerals. For example, the procedure for funerals and the flow of ceremonies can be explained using videos. The generative AI can also provide visually easy-to-understand information using images related to funerals. For example, it can display photos of the funeral venue and facilities. The generative AI can also provide visually easy-to-understand information to the client using videos and images. This makes it possible to provide information that is visually easy to understand.

[0062] The generation AI can automatically generate FAQs about funerals, allowing the person seeking advice to resolve their own problem. The generation AI can, for example, automatically generate FAQs about funerals, allowing the person seeking advice to resolve their own problem. For example, it can display a list of frequently asked questions and their answers. The generation AI can also automatically display related FAQs based on the person seeking advice. For example, if the person seeking advice asks, "How much does a funeral cost?", it will display related FAQs. The generation AI can also support the person seeking advice to resolve their own problem by automatically generating FAQs. This helps the person seeking advice to resolve their own problem.

[0063] The generation AI can use the emotion estimation function to provide music and videos with a relaxing effect based on the client's emotions. For example, the generation AI can use the emotion estimation function to analyze the client's emotional state and provide music with a relaxing effect. For example, if the client feels a strong sense of sadness, soothing music can be played. The generation AI can also use the emotion estimation function to provide videos with a relaxing effect based on the client's emotional state. For example, videos of natural landscapes or a calm ocean can be played. The generation AI can also use the emotion estimation function to provide music and videos with the optimal relaxing effect according to the client's emotions. This makes it possible to provide music and videos with a relaxing effect according to the client's emotions.

[0064] The generation AI can analyze the past performance and evaluations of each funeral company and recommend the most suitable company. For example, the generation AI can retrieve the past performance of each funeral company from a database and recommend the most suitable company based on that performance. For example, it can make recommendations based on the number of funerals held in the past and customer satisfaction. The generation AI can also analyze the evaluations of each funeral company and recommend the most suitable company. For example, it can make recommendations based on customer feedback and industry evaluations. The generation AI can also recommend the most suitable funeral company to the client based on past performance and evaluations. This makes it possible to recommend the most suitable funeral company.

[0065] The generation AI can compare the service content of each funeral company in detail and propose the most suitable plan to the client. For example, the generation AI retrieves the service content of each funeral company from a database and compares them in detail. For example, it compares the types and content of services provided and proposes the most suitable plan. The generation AI also proposes the most suitable plan based on the client's needs. For example, it proposes the most suitable plan based on the client's budget and desired service content. The generation AI can also propose the most suitable plan to the client by comparing the service content in detail. This makes it possible to propose the most suitable funeral plan.

[0066] The generation AI can use the emotion estimation function to select a company based on the emotions of the person seeking advice. For example, the generation AI uses the emotion estimation function to analyze the emotional state of the person seeking advice and select a company based on the emotions. For example, it will prioritize selecting a company that gives a sense of security. The generation AI also uses the emotion estimation function to select the most suitable company based on the emotions of the person seeking advice. For example, it will select a company that is highly reliable. The generation AI can also use the emotion estimation function to select the most suitable company based on the emotions of the person seeking advice. This makes it possible to select the most suitable company based on the emotions of the person seeking advice.

[0067] The generating AI can provide promotional videos and interviews of each funeral company to provide visual information to the person seeking advice. For example, the generating AI can retrieve promotional videos of each funeral company from a database and provide them to the person seeking advice. For example, the generating AI can explain while showing an introductory video of the company. The generating AI can also provide interviews of each funeral company to provide visual information to the person seeking advice. For example, the generating AI can explain while showing interviews with the company's representative or staff. The generating AI can also use promotional videos and interviews to provide information that is easy to understand visually to the person seeking advice. By providing visual information, the person seeking advice can understand more specifically.

[0068] The generation AI can automatically compare the pricing plans of each funeral company and propose the most suitable plan. For example, the generation AI retrieves the pricing plans of each funeral company from a database and automatically compares them. For example, it proposes the most suitable pricing plan according to the budget. The generation AI also compares the breakdown of pricing plans in detail and proposes the most suitable plan for the client. For example, it compares the service content and fee breakdown and proposes the most suitable plan. The generation AI also automatically compares pricing plans and can propose the most suitable plan for the client. This makes it possible to propose the most suitable pricing plan.

[0069] The generation AI can use the emotion estimation function to provide music and videos with a relaxing effect based on the client's emotions. For example, the generation AI can use the emotion estimation function to analyze the client's emotional state and provide music with a relaxing effect. For example, if the client feels a strong sense of sadness, soothing music can be played. The generation AI can also use the emotion estimation function to provide videos with a relaxing effect based on the client's emotional state. For example, videos of natural landscapes or a calm ocean can be played. The generation AI can also use the emotion estimation function to provide music and videos with the optimal relaxing effect according to the client's emotions. This makes it possible to provide music and videos with a relaxing effect according to the client's emotions.

[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 funeral consultation system can estimate the emotions of the person seeking advice and provide appropriate advice to the person based on the estimated emotions. For example, if the person seeking advice expresses sadness, the system can provide advice that includes comforting words. If the person seeking advice expresses anxiety, the system can provide information that gives the person a sense of security. Furthermore, if the person seeking advice expresses anger, the system can respond using calm language and provide advice to calm the person. This makes it possible to provide appropriate advice that takes into consideration the person seeking advice.

[0072] The funeral consultation system can refer to the consultation history of the client and provide an answer that is individually customized. For example, if a client has previously consulted about a family funeral, the latest information on family funerals can be provided. Also, if a client has previously consulted about a specific funeral plan, detailed information on that plan can be provided. Furthermore, it is possible to provide answers that are tailored to the client's preferences and needs. This allows the client to receive a more appropriate answer.

[0073] The funeral consultation system can use the emotion estimation function to provide music and images with a relaxing effect based on the client's emotions. For example, if the client feels a strong sense of sadness, soothing music can be played. If the client feels anxious, images of tranquil natural scenery or the sea can be provided. Furthermore, if the client shows anger, music and images with a relaxing effect can be provided to calm the client's emotions. In this way, it is possible to provide music and images with a relaxing effect that correspond to the client's emotions.

[0074] The funeral consultation system can automatically collect the latest funeral industry news and legal reform information and provide it to the client. For example, it can provide information on new funeral plans and services in real time. It can also provide information on new laws and regulations related to funerals. Furthermore, it can provide appropriate advice to the client based on the latest funeral industry news and legal reform information. This allows the client to receive the latest information.

[0075] The funeral consultation system can use the emotion estimation function to optimize the order in which information is presented according to the emotions of the client. For example, if the client is feeling strong sadness, comforting words can be provided first, followed by specific information. If the client is feeling anxious, information that provides a sense of security can be provided first. Furthermore, if the client is feeling angry, information can be provided in calm language, and information to calm the client's emotions can be provided first. This makes it possible to present optimal information according to the client's emotions.

[0076] The funeral consultation system analyzes the past performance and evaluations of each funeral company and can recommend the most suitable company. For example, recommendations can be made based on the number of funerals held in the past and customer satisfaction. Recommendations can also be made based on customer feedback and industry evaluations. Furthermore, based on past performance and evaluations, it can recommend the most suitable funeral company for the client. This makes it possible to recommend the most suitable funeral company.

[0077] The funeral consultation system can compare the service content of each funeral company in detail and propose the most suitable plan to the client. For example, it can compare the types and contents of services offered and propose the most suitable plan. It can also propose the most suitable plan based on the client's needs. Furthermore, by comparing the service content in detail, it can propose the most suitable plan to the client. This makes it possible to propose the most suitable funeral plan.

[0078] The funeral consultation system can use the emotion estimation function to select a company according to the emotion of the person seeking consultation. For example, it can prioritize the selection of a company that gives a sense of security. It can also select a company with high reliability. Furthermore, it can select the most suitable company according to the emotion of the person seeking consultation. This makes it possible to select the most suitable company according to the emotion of the person seeking consultation.

[0079] The funeral consultation system can provide promotional videos and interviews of each funeral company to provide visual information to the client. For example, explanations can be given while showing an introductory video of the company. It can also provide explanations while showing interviews with company representatives and staff. Furthermore, promotional videos and interviews can be used to provide information that is visually easy to understand to the client. Providing visual information allows the client to understand more specifically.

[0080] The funeral consultation system can automatically compare the pricing plans of each funeral company and propose the most suitable plan. For example, it can propose the most suitable pricing plan according to the budget. It can also compare the breakdown of pricing plans in detail and propose the most suitable plan for the client. Furthermore, by automatically comparing pricing plans, it can propose the most suitable plan for the client. This makes it possible to propose the most suitable pricing plan.

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

[0082] Step 1: The generation AI automatically generates answers to the client's questions. For example, in response to a client's question, "How much does a funeral cost?", the generation AI generates an answer such as, "A typical funeral costs between XXX yen and XXX yen." In response to a client's question, "What is the difference between a family funeral and a general funeral?", the generation AI generates an answer such as, "A family funeral is a small funeral attended only by close family and friends, while a general funeral is a large funeral attended by many people." In response to a client's question, "Which funeral companies serve this area?", the generation AI generates an answer such as, "XXX Funeral Home serves this area." Step 2: The information addition unit adds detailed information about the funeral. For example, the information addition unit adds information such as the type of funeral, the procedure, necessary documents, and a breakdown of costs. This allows the generation AI to provide accurate answers to even the most specific questions from the client. Step 3: The company information addition unit adds information about the funeral company being introduced. For example, the company information addition unit adds information such as the services provided by the company, pricing plans, and service areas. This allows the generation AI to provide specific company information to the person seeking advice.

[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, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[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. Equipped with generative AI, The generated AI is Automatically generate answers to the client's questions, an information addition section for adding detailed information about the funeral; a company information adding unit for adding information about the company that will introduce the system; A system characterized by:

2. The generated AI is Refer to the consultation history of the person seeking advice and provide an individually customized answer 2. The system of claim 1.

3. The generated AI is Interact with the client through a video call and provide answers using visual information 2. The system of claim 1.

4. The generated AI is Automatically collect the latest funeral industry news and legal reform information and provide it to the client.

2. The system of claim 1.

5. The generated AI is Select a company based on the client's feelings 2. The system of claim 1.

Images