System

Abstract

An object of a system according to an embodiment is to efficiently manage and effectively utilize business card data.SOLUTION: A system includes a business card data registration part, a business card data exchange part, a position information registration part, and a data matching part. The business card data registration part registers business card data. The business card data exchange part exchanges the business card data registered by the business card data registration part. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. A data matching part analyzes the information of the home page of the working place registered by the business card data registration part and performs data matching.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, it is difficult to manage and effectively utilize business card data, and there is room for improvement in efficiently organizing and utilizing information.

[0005] The system according to the embodiment aims to efficiently manage and effectively utilize business card data. [Means for solving the problem]

[0006] The system according to the embodiment includes a business card data registration unit, a business card data exchange unit, a location information registration unit, and a data matching unit. The business card data registration unit registers business card data. The business card data exchange unit exchanges the business card data registered by the business card data registration unit. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. The data matching unit analyzes information on the workplace homepage registered by the business card data registration unit and performs data matching. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently manage and effectively utilize business card data. [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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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 business card management system according to the embodiment of the present invention is a system that improves the efficiency of management and utilization by using a tool app for exchanging business cards to remember the affiliations and names of business partners encountered during sales activities, etc. This enables the business card management system to eliminate paper media, simplify management, and make effective use of data.

[0029] A business card management system according to an embodiment includes a business card data registration unit, a business card data exchange unit, a location information registration unit, and a data matching unit. The business card data registration unit registers business card data. For example, a user registers "place of employment," "contact information," and "photograph" in a tool app to use the data as a business card. The business card data registration unit also stores the business card information as digital data. For example, when a sales representative meets a new client, the sales representative inputs the client's place of employment, contact information, and photo into the app. The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during meetings or face-to-face meetings. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered during the exchange, recording where the two parties met. The data matching unit analyzes information from the employer's website registered by the business card data registration unit and performs data matching. For example, the AI ​​generator can match data with business partners listed on a website and tell users who they are likely to have a relationship with on their business card data. This allows the business card management system to efficiently register, exchange, and match business card data, as well as register location information.

[0030] The business card data registration unit can analyze social media posts or public information and automatically tag interests. For example, when registering business card data, the business card data registration unit uses a generation AI to analyze the other person's social media posts and tag their interests. For example, it can automatically extract topics that the other person frequently posts about and register them as tags. The business card data registration unit also analyzes public information and tags the other person's field of expertise and hobbies. For example, it can extract work history and skills from the other person's LinkedIn profile and register them as tags. The business card data registration unit can also automatically tag the other person's interests based on social media posts and public information, and use this information as a reference for the next meeting. For example, it can suggest events or news that the other person is interested in. This allows the other person's interests to be automatically tagged.

[0031] The business card data exchange unit can analyze the tone of voice or speaking style and generate a customized message according to the communication style. For example, when exchanging business cards, the generation AI in the business card data exchange unit analyzes the tone of the other person's voice and generates a message according to the communication style. For example, it will suggest a polite message to someone who speaks in a calm tone. The business card data exchange unit also analyzes speaking characteristics and generates a message tailored to the other person. For example, it will suggest a concise message to someone who speaks quickly. The business card data exchange unit also generates a follow-up message that is optimal for the other person's communication style based on the tone of voice and speaking style. For example, it will suggest a casual message to someone who speaks in a friendly tone. This makes it possible to generate a message according to the other person's communication style.

[0032] The business card data registration unit automatically translates business card information, enabling information exchange between users of different languages. For example, when registering business card data, the generation AI automatically translates the other person's business card information. For example, Japanese business card information can be translated into English, enabling information exchange between users of different languages. The generation AI also provides an automatic translation function to make business card information multilingual. For example, French business card information can be translated into English or Chinese. The business card data registration unit also automatically translates business card information and displays it within the app to enable smooth information exchange between users of different languages. For example, Spanish business card information can be translated into English and displayed. This allows smooth information exchange between users of different languages.

[0033] The business card data exchange unit can use AR technology to enable visual confirmation of business card information in real time. For example, when exchanging business cards, the business card data exchange unit uses AR technology to have the generation AI display the other party's business card information in real time. For example, the business card information is visually confirmed through a smartphone camera. The business card data exchange unit also uses AR technology to display the business card information in real time, allowing the other party's information to be visually confirmed. For example, the business card information is displayed as a hologram. The business card data exchange unit also uses AR technology to display the other party's business card information in real time when exchanging business cards, allowing the other party's information to be visually confirmed. For example, the business card information is displayed on smart glasses. This allows the business card information to be visually confirmed in real time using AR technology.

[0034] The data matching unit can use the generation AI to analyze a client's past projects or success stories and propose similar projects. For example, during data matching, the data matching unit uses the generation AI to analyze a client's past projects and propose similar projects. For example, it can propose new projects based on past success stories. The data matching unit can also use the generation AI to analyze a client's success stories and propose similar projects. For example, it can propose new business opportunities based on success stories in the same industry. The data matching unit can also use the generation AI to analyze a client's past projects and propose similar projects. For example, it can make new proposals based on the results of past projects. This makes it possible to propose similar projects.

[0035] The data matching unit uses the generation AI to analyze the client's industry news and trends and can provide matching results based on the latest information. For example, during data matching, the generation AI analyzes the client's industry news and provides matching results based on the latest information. For example, it makes proposals that reflect the latest technological trends. The data matching unit also uses the generation AI to analyze the client's industry trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. The data matching unit also uses the generation AI to analyze the client's industry news and trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. This makes it possible to provide matching results based on the latest information.

[0036] The data matching unit can use the generation AI to analyze the design and layout of a workplace homepage and evaluate the visual brand match. For example, when a workplace homepage is registered, the data matching unit has the generation AI analyze the design and layout of the homepage and evaluate the visual brand match. For example, it evaluates the brand match based on the colors and fonts used on the homepage. The data matching unit also adds a function whereby the generation AI analyzes the design and layout of the homepage and evaluates the visual brand match. For example, it evaluates the brand match based on the layout and images of the homepage. The data matching unit also adds a function whereby the generation AI analyzes the design and layout of the homepage when a workplace homepage is registered and evaluates the visual brand match. For example, it evaluates the brand match based on the design elements of the homepage. This makes it possible to evaluate the visual brand match.

[0037] The data matching unit can use the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, when matching data, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are engaged in environmental protection activities. Furthermore, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are engaged in social contribution activities. Furthermore, when matching data, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are working on the Sustainable Development Goals (SDGs). This allows for preferential matching with companies that share common social values.

[0038] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0039] The business card data registration unit registers business card data. For example, it registers "company name," "contact information," and "photo" in a tool app so that users can use the data as a business card. The business card data registration unit also stores business card information as digital data. For example, when a sales representative meets a new client, they enter the client's company name, contact information, and photo into the app. The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during meetings or face-to-face meetings. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered during the exchange, recording where the meeting took place. The data matching unit analyzes information from the company's website registered by the business card data registration unit and performs data matching. For example, the generation AI matches data with client names listed on the website and identifies potential relationships with the business card data on hand. This allows the business card management system to efficiently register and exchange business card data, register location information, and match data.

[0040] The business card data registration unit can analyze social media posts or public information and automatically tag interests. For example, when registering business card data, the generation AI analyzes the other person's social media posts and tags their interests. For example, it can automatically extract topics that the other person frequently posts about and register them as tags. The business card data registration unit also analyzes public information and tags the other person's area of ​​expertise and hobbies. For example, it can extract work history and skills from the other person's LinkedIn profile and register them as tags. The business card data registration unit can also automatically tag the other person's interests based on social media posts and public information, and use this information as reference for the next meeting. For example, it can suggest events or news that the other person is interested in. This allows the other person's interests to be automatically tagged.

[0041] The business card data exchange unit can analyze the tone of voice or speaking style and generate a customized message according to the communication style. For example, when exchanging business cards, the generation AI analyzes the other person's tone of voice and generates a message that suits their communication style. For example, it will suggest a polite message to someone who speaks in a calm tone. The business card data exchange unit also analyzes speaking characteristics and generates a message that suits the other person. For example, it will suggest a concise message to someone who speaks quickly. The business card data exchange unit also generates a follow-up message that is optimal for the other person's communication style based on the tone of voice and speaking style. For example, it will suggest a casual message to someone who speaks in a friendly tone. This makes it possible to generate a message that suits the other person's communication style.

[0042] The business card data registration unit automatically translates business card information, enabling information exchange between users of different languages. For example, when registering business card data, the generation AI automatically translates the other person's business card information. For example, Japanese business card information can be translated into English, enabling information exchange between users of different languages. The business card data registration unit also provides an automatic translation function to make business card information multilingual. For example, French business card information can be translated into English or Chinese. The business card data registration unit also automatically translates business card information and displays it within the app to enable smooth information exchange between users of different languages. For example, Spanish business card information can be translated into English and displayed. This allows smooth information exchange between users of different languages.

[0043] The business card data exchange unit can use AR technology to enable visual confirmation of business card information in real time. For example, when exchanging business cards, the generation AI displays the other party's business card information in real time using AR technology. For example, the business card information is visually confirmed through a smartphone camera. The business card data exchange unit can also use AR technology to display the business card information in real time, allowing the other party's information to be visually confirmed. For example, the business card information is displayed as a hologram. The business card data exchange unit can also use AR technology to display the other party's business card information in real time when exchanging business cards, allowing the other party's information to be visually confirmed. For example, the business card information is displayed on smart glasses. This allows the business card information to be visually confirmed in real time using AR technology.

[0044] The data matching department can use the generation AI to analyze a client's past projects or success stories and propose similar projects. For example, during data matching, the generation AI can analyze a client's past projects and propose similar projects. For example, it can propose new projects based on past success stories. The data matching department can also use the generation AI to analyze a client's success stories and propose similar projects. For example, it can propose new business opportunities based on success stories in the same industry. The data matching department can also use the generation AI to analyze a client's past projects and propose similar projects. For example, it can make new proposals based on the results of past projects. This makes it possible to propose similar projects.

[0045] The data matching unit uses the generation AI to analyze the client's industry news and trends and provide matching results based on the latest information. For example, when matching data, the generation AI analyzes the client's industry news and provides matching results based on the latest information. For example, it makes proposals that reflect the latest technological trends. The data matching unit also uses the generation AI to analyze the client's industry trends and provide matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. The data matching unit also uses the generation AI to analyze the client's industry news and trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. This makes it possible to provide matching results based on the latest information.

[0046] The processing flow of the first embodiment will be briefly explained below.

[0047] Step 1: The business card data registration unit registers business card data. For example, a user registers "place of employment," "contact information," and "photo" in the tool app to use the card as a business card. The business card data registration unit also saves business card information as digital data. For example, when a sales representative meets a new client, they enter the client's place of employment, contact information, and photo into the app. Step 2: The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during a meeting or face-to-face meeting. Step 3: The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered at the time of exchange, and the location where the person met is recorded. Step 4: The data matching unit analyzes the information on the company's website registered by the business card data registration unit and performs data matching. For example, the generation AI matches the data with business partners listed on the website and tells you who on your business card data you are likely to be related to.

[0048] (Example 2) The business card management system according to the embodiment of the present invention is a system that improves the efficiency of management and utilization by using a tool app for exchanging business cards to remember the affiliations and names of business partners encountered during sales activities, etc. This enables the business card management system to eliminate paper media, simplify management, and make effective use of data.

[0049] A business card management system according to an embodiment includes a business card data registration unit, a business card data exchange unit, a location information registration unit, and a data matching unit. The business card data registration unit registers business card data. For example, a user registers "place of employment," "contact information," and "photograph" in a tool app to use the data as a business card. The business card data registration unit also stores the business card information as digital data. For example, when a sales representative meets a new client, the sales representative inputs the client's place of employment, contact information, and photo into the app. The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during meetings or face-to-face meetings. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered during the exchange, recording where the two parties met. The data matching unit analyzes information from the employer's website registered by the business card data registration unit and performs data matching. For example, the AI ​​generator can match data with business partners listed on a website and tell users who they are likely to have a relationship with on their business card data. This allows the business card management system to efficiently register, exchange, and match business card data, as well as register location information.

[0050] The business card data registration unit can use generation AI to infer emotions from facial photos and suggest follow-up actions based on those emotions. For example, when registering business card data, the business card data registration unit uses generation AI to analyze the other person's facial photo and infer emotions. For example, it can infer positive emotions from a smiling photo and suggest content for a follow-up email. The business card data registration unit also suggests topics to discuss at the next meeting based on the emotions inferred from the facial photo. For example, the generation AI automatically lists topics that the other person is likely to be interested in. The business card data registration unit also suggests follow-up actions based on the emotion estimation results, depending on the other person's emotions. For example, if the other person is nervous, it can suggest a message to help them relax. This makes it possible to suggest appropriate follow-up actions based on the other person's emotions.

[0051] The business card data registration unit can analyze social media posts or public information and automatically tag interests. For example, when registering business card data, the business card data registration unit uses a generation AI to analyze the other person's social media posts and tag their interests. For example, it can automatically extract topics that the other person frequently posts about and register them as tags. The business card data registration unit also analyzes public information and tags the other person's field of expertise and hobbies. For example, it can extract work history and skills from the other person's LinkedIn profile and register them as tags. The business card data registration unit can also automatically tag the other person's interests based on social media posts and public information, and use this information as a reference for the next meeting. For example, it can suggest events or news that the other person is interested in. This allows the other person's interests to be automatically tagged.

[0052] The business card data exchange unit can analyze the tone of voice or speaking style and generate a customized message according to the communication style. For example, when exchanging business cards, the generation AI in the business card data exchange unit analyzes the tone of the other person's voice and generates a message according to the communication style. For example, it will suggest a polite message to someone who speaks in a calm tone. The business card data exchange unit also analyzes speaking characteristics and generates a message tailored to the other person. For example, it will suggest a concise message to someone who speaks quickly. The business card data exchange unit also generates a follow-up message that is optimal for the other person's communication style based on the tone of voice and speaking style. For example, it will suggest a casual message to someone who speaks in a friendly tone. This makes it possible to generate a message according to the other person's communication style.

[0053] The business card data registration unit automatically translates business card information, enabling information exchange between users of different languages. For example, when registering business card data, the generation AI automatically translates the other person's business card information. For example, Japanese business card information can be translated into English, enabling information exchange between users of different languages. The generation AI also provides an automatic translation function to make business card information multilingual. For example, French business card information can be translated into English or Chinese. The business card data registration unit also automatically translates business card information and displays it within the app to enable smooth information exchange between users of different languages. For example, Spanish business card information can be translated into English and displayed. This allows smooth information exchange between users of different languages.

[0054] The business card data exchange unit can use AR technology to enable visual confirmation of business card information in real time. For example, when exchanging business cards, the business card data exchange unit uses AR technology to have the generation AI display the other party's business card information in real time. For example, the business card information is visually confirmed through a smartphone camera. The business card data exchange unit also uses AR technology to display the business card information in real time, allowing the other party's information to be visually confirmed. For example, the business card information is displayed as a hologram. The business card data exchange unit also uses AR technology to display the other party's business card information in real time when exchanging business cards, allowing the other party's information to be visually confirmed. For example, the business card information is displayed on smart glasses. This allows the business card information to be visually confirmed in real time using AR technology.

[0055] The business card data exchange unit can use the emotion estimation function to analyze emotions in real time and provide conversation hints to elicit positive emotions. For example, when exchanging business cards, the business card data exchange unit uses the generation AI to analyze the other person's emotions in real time and provide conversation hints to elicit positive emotions. For example, it suggests topics that the other person is likely to be interested in. The business card data exchange unit also uses the emotion estimation function to analyze the other person's emotions in real time and provide conversation hints to elicit positive emotions. For example, it suggests topics that will make the other person smile. The business card data exchange unit also uses the emotion estimation function to analyze the other person's emotions in real time when exchanging business cards and provide conversation hints to elicit positive emotions. For example, it suggests topics that will make the other person relax. In this way, it is possible to analyze the other person's emotions in real time and provide conversation hints to elicit positive emotions.

[0056] The data matching unit uses the generation AI to analyze the emotional tone on a company's homepage and infer the corporate culture and values ​​of a business partner. For example, when a company's homepage is registered, the data matching unit uses the generation AI to analyze the emotional tone on the homepage and infer the corporate culture and values. For example, it detects a positive tone from the text on the homepage and infers the company's values. The data matching unit also uses the generation AI to analyze the emotional tone on the homepage and infer the corporate culture and values ​​of a business partner. For example, it infers the company's atmosphere from the homepage's design and color usage. The data matching unit also uses the generation AI to analyze the emotional tone on the homepage when a company's homepage is registered and infers the corporate culture and values ​​of a business partner. For example, it infers the company's mission and vision from the homepage content. This makes it possible to infer the corporate culture and values ​​of a business partner.

[0057] The data matching unit can use the generation AI to analyze a client's past projects or success stories and propose similar projects. For example, during data matching, the data matching unit uses the generation AI to analyze a client's past projects and propose similar projects. For example, it can propose new projects based on past success stories. The data matching unit can also use the generation AI to analyze a client's success stories and propose similar projects. For example, it can propose new business opportunities based on success stories in the same industry. The data matching unit can also use the generation AI to analyze a client's past projects and propose similar projects. For example, it can make new proposals based on the results of past projects. This makes it possible to propose similar projects.

[0058] The data matching unit uses the generation AI to analyze the client's industry news and trends and can provide matching results based on the latest information. For example, during data matching, the generation AI analyzes the client's industry news and provides matching results based on the latest information. For example, it makes proposals that reflect the latest technological trends. The data matching unit also uses the generation AI to analyze the client's industry trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. The data matching unit also uses the generation AI to analyze the client's industry news and trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. This makes it possible to provide matching results based on the latest information.

[0059] The data matching unit can use the generation AI to analyze the design and layout of a workplace homepage and evaluate the visual brand match. For example, when a workplace homepage is registered, the data matching unit has the generation AI analyze the design and layout of the homepage and evaluate the visual brand match. For example, it evaluates the brand match based on the colors and fonts used on the homepage. The data matching unit also adds a function whereby the generation AI analyzes the design and layout of the homepage and evaluates the visual brand match. For example, it evaluates the brand match based on the layout and images of the homepage. The data matching unit also adds a function whereby the generation AI analyzes the design and layout of the homepage when a workplace homepage is registered and evaluates the visual brand match. For example, it evaluates the brand match based on the design elements of the homepage. This makes it possible to evaluate the visual brand match.

[0060] The data matching unit can use the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, when matching data, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are engaged in environmental protection activities. Furthermore, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are engaged in social contribution activities. Furthermore, when matching data, the data matching unit uses the generation AI to analyze the CSR activities of business partners and prioritize matching with companies that share common social values. For example, it can match companies that are working on the Sustainable Development Goals (SDGs). This allows for preferential matching with companies that share common social values.

[0061] The data matching unit can use the emotion estimation function to analyze the emotional tone on a business partner's website and identify business partners who are easy to empathize with emotionally. For example, during data matching, the data matching unit uses a generation AI to analyze the emotional tone on a business partner's website and identify business partners who are easy to empathize with emotionally. For example, it identifies companies with websites that have a positive tone. The data matching unit also uses the emotion estimation function to analyze the emotional tone on a business partner's website and identify business partners who are easy to empathize with emotionally. For example, it identifies companies with websites that have a warm tone. The data matching unit also uses the emotion estimation function to analyze the emotional tone on a business partner's website during data matching and identify business partners who are easy to empathize with emotionally. For example, it identifies companies with websites that have a friendly tone. This makes it possible to identify business partners who are easy to empathize with emotionally.

[0062] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0063] The business card data registration unit registers business card data. For example, it registers "company name," "contact information," and "photo" in a tool app so that users can use the data as a business card. The business card data registration unit also stores business card information as digital data. For example, when a sales representative meets a new client, they enter the client's company name, contact information, and photo into the app. The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during meetings or face-to-face meetings. The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered during the exchange, recording where the meeting took place. The data matching unit analyzes information from the company's website registered by the business card data registration unit and performs data matching. For example, the generation AI matches data with client names listed on the website and identifies potential relationships with the business card data on hand. This allows the business card management system to efficiently register and exchange business card data, register location information, and match data.

[0064] The business card data registration unit can use generation AI to infer emotions from facial photos and suggest follow-up actions based on those emotions. For example, when registering business card data, the generation AI analyzes the other person's facial photo to infer emotions. For example, it can infer positive emotions from a smiling photo and suggest the content of a follow-up email. The business card data registration unit also suggests topics to discuss at the next meeting based on the emotions inferred from the facial photo. For example, the generation AI automatically lists topics that the other person is likely to be interested in. The business card data registration unit also suggests follow-up actions based on the emotion estimation results, depending on the other person's emotions. For example, if the other person is nervous, it can suggest a message to help them relax. This makes it possible to suggest appropriate follow-up actions based on the other person's emotions.

[0065] The business card data registration unit can analyze social media posts or public information and automatically tag interests. For example, when registering business card data, the generation AI analyzes the other person's social media posts and tags their interests. For example, it can automatically extract topics that the other person frequently posts about and register them as tags. The business card data registration unit also analyzes public information and tags the other person's area of ​​expertise and hobbies. For example, it can extract work history and skills from the other person's LinkedIn profile and register them as tags. The business card data registration unit can also automatically tag the other person's interests based on social media posts and public information, and use this information as reference for the next meeting. For example, it can suggest events or news that the other person is interested in. This allows the other person's interests to be automatically tagged.

[0066] The business card data exchange unit can analyze the tone of voice or speaking style and generate a customized message according to the communication style. For example, when exchanging business cards, the generation AI analyzes the other person's tone of voice and generates a message that suits their communication style. For example, it will suggest a polite message to someone who speaks in a calm tone. The business card data exchange unit also analyzes speaking characteristics and generates a message that suits the other person. For example, it will suggest a concise message to someone who speaks quickly. The business card data exchange unit also generates a follow-up message that is optimal for the other person's communication style based on the tone of voice and speaking style. For example, it will suggest a casual message to someone who speaks in a friendly tone. This makes it possible to generate a message that suits the other person's communication style.

[0067] The business card data registration unit automatically translates business card information, enabling information exchange between users of different languages. For example, when registering business card data, the generation AI automatically translates the other person's business card information. For example, Japanese business card information can be translated into English, enabling information exchange between users of different languages. The business card data registration unit also provides an automatic translation function to make business card information multilingual. For example, French business card information can be translated into English or Chinese. The business card data registration unit also automatically translates business card information and displays it within the app to enable smooth information exchange between users of different languages. For example, Spanish business card information can be translated into English and displayed. This allows smooth information exchange between users of different languages.

[0068] The business card data exchange unit can use AR technology to enable visual confirmation of business card information in real time. For example, when exchanging business cards, the generation AI displays the other party's business card information in real time using AR technology. For example, the business card information is visually confirmed through a smartphone camera. The business card data exchange unit can also use AR technology to display the business card information in real time, allowing the other party's information to be visually confirmed. For example, the business card information is displayed as a hologram. The business card data exchange unit can also use AR technology to display the other party's business card information in real time when exchanging business cards, allowing the other party's information to be visually confirmed. For example, the business card information is displayed on smart glasses. This allows the business card information to be visually confirmed in real time using AR technology.

[0069] The business card data exchange unit can use the emotion estimation function to analyze emotions in real time and provide conversation hints to elicit positive emotions. For example, when exchanging business cards, the generation AI analyzes the other person's emotions in real time and provides conversation hints to elicit positive emotions. For example, it suggests topics that the other person is likely to be interested in. The business card data exchange unit can also use the emotion estimation function to analyze the other person's emotions in real time and provide conversation hints to elicit positive emotions. For example, it suggests topics that will make the other person smile. The business card data exchange unit can also use the emotion estimation function to analyze the other person's emotions in real time when exchanging business cards and provide conversation hints to elicit positive emotions. For example, it suggests topics that will make the other person relax. In this way, it is possible to analyze the other person's emotions in real time and provide conversation hints to elicit positive emotions.

[0070] The data matching unit uses the generation AI to analyze the emotional tone on a company's homepage and infer the corporate culture and values ​​of a client. For example, when a company's homepage is registered, the generation AI analyzes the emotional tone on the homepage and infers the corporate culture and values. For example, it detects a positive tone from the text on the homepage and infers the company's values. The data matching unit also analyzes the emotional tone on the homepage and infers the corporate culture and values ​​of a client. For example, it infers the company's atmosphere from the homepage's design and color usage. The data matching unit also analyzes the emotional tone on the homepage when a company's homepage is registered and infers the corporate culture and values ​​of a client. For example, it infers the company's mission and vision from the homepage content. This makes it possible to infer the corporate culture and values ​​of a client.

[0071] The data matching department can use the generation AI to analyze a client's past projects or success stories and propose similar projects. For example, during data matching, the generation AI can analyze a client's past projects and propose similar projects. For example, it can propose new projects based on past success stories. The data matching department can also use the generation AI to analyze a client's success stories and propose similar projects. For example, it can propose new business opportunities based on success stories in the same industry. The data matching department can also use the generation AI to analyze a client's past projects and propose similar projects. For example, it can make new proposals based on the results of past projects. This makes it possible to propose similar projects.

[0072] The data matching unit uses the generation AI to analyze the client's industry news and trends and provide matching results based on the latest information. For example, when matching data, the generation AI analyzes the client's industry news and provides matching results based on the latest information. For example, it makes proposals that reflect the latest technological trends. The data matching unit also uses the generation AI to analyze the client's industry trends and provide matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. The data matching unit also uses the generation AI to analyze the client's industry news and trends and provides matching results based on the latest information. For example, it makes proposals that reflect the latest market trends. This makes it possible to provide matching results based on the latest information.

[0073] The processing flow of the second embodiment will be briefly explained below.

[0074] Step 1: The business card data registration unit registers business card data. For example, a user registers "place of employment," "contact information," and "photo" in the tool app to use the card as a business card. The business card data registration unit also saves business card information as digital data. For example, when a sales representative meets a new client, they enter the client's place of employment, contact information, and photo into the app. Step 2: The business card data exchange unit exchanges the business card data registered by the business card data registration unit. For example, business card data can be exchanged through the app during a meeting or face-to-face meeting. Step 3: The location information registration unit registers location information based on the business card data exchanged by the business card data exchange unit. For example, location information is automatically registered at the time of exchange, and the location where the person met is recorded. Step 4: The data matching unit analyzes the information on the company's website registered by the business card data registration unit and performs data matching. For example, the generation AI matches the data with business partners listed on the website and tells you who on your business card data you are likely to be related to.

[0075] 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.

[0076] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<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.

[0077] 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.

[0078] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0079] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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).

[0084] 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.

[0085] 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.

[0086] 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.

[0087] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0088] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0089] 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.

[0090] 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.

[0091] 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 AI 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.

[0092] 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.

[0093] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0094] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0101] 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.

[0102] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0103] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0104] 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.

[0105] 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.

[0106] 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 AI 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.

[0107] 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.

[0108] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0119] In the robot 414, 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. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0120] 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.

[0121] 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.

[0122] 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 AI 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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).

[0128] 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.

[0129] 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."

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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, in order to avoid confusion and to 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.

[0141] 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]

[0142] 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 business card data registration unit for registering business card data; a business card data exchange unit that exchanges the business card data registered by the business card data registration unit; a location information registration unit that registers location information based on the business card data exchanged by the business card data exchange unit; a data matching unit that analyzes the information on the home page of the workplace registered by the business card data registration unit and performs data matching. A system characterized by:

2. The business card data registration unit Uses generative AI to infer emotions from facial photos and suggests follow-up actions based on those emotions 2. The system of claim 1.

3. The business card data registration unit Analyze the social media posts or public information and automatically tag your interests 2. The system of claim 1.

4. The business card data exchange unit Analyzing the tone of voice or the manner of speaking to generate a customized message according to the communication style 2. The system of claim 1.

5. The business card data registration unit Automatically translates business card information, enabling information exchange between users of different languages 2. The system of claim 1.

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