System

Abstract

An object of the system according to the embodiment is to improve the efficiency of a job seeking activity of a refugee and an employment activity of a company.SOLUTION: A system according to an embodiment includes a profile generation part, a job seeking support part, and an employment support part. The profile generation unit generates an accurate and quick profile using the generation AI. A job hunting support part supports the job hunting activity of the refugee on the basis of the profile generated by the profile generation part. An employment support part supports the employment activity of the enterprise on the basis of the profile generated by the profile generation part.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, creating profiles for refugees seeking jobs and companies recruiting requires time and effort, making it difficult to do so efficiently.

[0005] The system according to the embodiment aims to improve the efficiency of refugees' job-seeking activities and companies' recruitment activities. [Means for solving the problem]

[0006] The system according to the embodiment includes a profile generation unit, a job search support unit, and a recruitment support unit. The profile generation unit generates accurate and prompt profiles using generation AI. The job search support unit supports refugees' job searches based on the profiles generated by the profile generation unit. The recruitment support unit supports companies' recruitment activities based on the profiles generated by the profile generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can improve the efficiency of refugees' job-seeking activities and companies' recruitment activities. [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 employment support system according to an embodiment of the present invention is a system aimed at expanding employment opportunities for refugees and enhancing corporate recruitment activities. This system uses generative AI to generate accurate and rapid profiles, streamlining refugee job searches and significantly improving corporate recruitment efficiency. As a result, the employment support system can streamline refugee job searches and enhance corporate recruitment activities.

[0029] An employment support system according to an embodiment includes a profile generation unit, a job search support unit, and a recruitment support unit. The profile generation unit generates accurate and rapid profiles using a generation AI. For example, the generation AI imports interviews with refugees and their shared experiences as text data and generates profiles in a short time. The generation AI analyzes the interview content and experiences and generates profiles based on appropriate prompts. The generation AI receives prompts including the interview content and experiences, and generates profiles based on the prompts. The job search support unit supports refugees' job searches based on the profiles generated by the profile generation unit. For example, posting the generated profiles on job sites increases the likelihood of receiving job offers from companies. The job search support unit can automatically match and notify refugees of job offers that are most suitable for them based on the profiles generated by the generation AI. The recruitment support unit supports companies' recruitment activities based on the profiles generated by the profile generation unit. For example, companies can quickly find refugees who match their desired skill sets and experience, allowing them to quickly proceed with interviews and hiring procedures. The recruitment support unit can also link the profiles generated by the generation AI with the company's recruitment system to instantly generate a list of interview candidates. As a result, the employment support system according to the embodiment can improve the efficiency of refugees' job-seeking activities and enhance companies' recruitment activities.

[0030] When analyzing interview content, the profile generation unit can convert it into text in real time using voice recognition technology and instantly reflect it in the profile. For example, during an interview, the profile generation unit uses voice recognition technology to convert what is spoken into text in real time using a generation AI, and instantly reflects that text in the profile. For example, work history and skills mentioned during the interview are added to the profile on the spot. The profile generation unit also analyzes interview audio data in real time, and builds a system in which the generation AI automatically converts it into text. For example, the interview audio is instantly converted into text and reflected in the profile. The profile generation unit also uses voice recognition technology to convert conversations during an interview into text in real time, and the generation AI analyzes that text and reflects it in the profile. For example, the interview content is instantly converted into text and added to the profile. This allows the interview content to be converted into text in real time and reflected in the profile.

[0031] When analyzing past work experience and skills, the profile generation unit can refer to the latest industry trends and technical information and add the latest information to the profile. For example, when the generation AI analyzes past work experience and skills, the profile generation unit automatically collects the latest trends and technical information in related industries and reflects it in the profile. For example, the latest technological trends and market needs are added to the profile. In addition, when the generation AI analyzes past work experience and skills, the profile generation unit refers to the latest industry news and trend information and adds the latest information to the profile. For example, the latest technology and market trends are reflected in the profile. In addition, when the generation AI analyzes past work experience and skills, the profile generation unit builds a system that refers to the latest trends and technical information in related industries and adds the latest information to the profile. For example, the latest technological trends and market needs are reflected in the profile. This makes it possible to reflect the latest industry information in the profile.

[0032] The profile generation unit can link video interviews to profiles and provide visual information as well. For example, the profile generation unit builds a system that links video interviews of refugees to profiles generated by the generation AI and provides visual information as well. For example, it adds links to video interviews to profiles. The profile generation unit also provides visual information by embedding video interviews of refugees in profiles generated by the generation AI. For example, it displays thumbnails of video interviews in profiles. The profile generation unit also develops a system that links video interviews of refugees to profiles generated by the generation AI and provides visual information as well. For example, it adds links to video interviews to profiles. This makes it possible to provide visual information.

[0033] The profile generation unit can attach a portfolio of past projects and deliverables to the profile to show specific achievements. For example, the profile generation unit builds a system that attaches a portfolio of a refugee's past projects and deliverables to a profile generated by the generation AI to show specific achievements. For example, it adds project details and links to the deliverables to the profile. The profile generation unit also attaches a portfolio of a refugee's past projects and deliverables to the profile generated by the generation AI to show specific achievements. For example, it displays project details and images of the deliverables on the profile. The profile generation unit also develops a system that attaches a portfolio of a refugee's past projects and deliverables to a profile generated by the generation AI to show specific achievements. For example, it adds project details and links to the deliverables to the profile. This makes it possible to show specific achievements.

[0034] The Job Search Support Department will automatically post the profiles generated by the generation AI to job sites and social media, allowing them to approach a wide range of companies. For example, the Job Search Support Department will build a system that automatically posts the profiles generated by the generation AI to job sites and social media. For example, the profiles will be automatically posted to multiple job sites. The Job Search Support Department will also automatically post the profiles generated by the generation AI to job sites and social media, allowing them to approach a wide range of companies. For example, the profiles will be automatically posted to multiple social media. The Job Search Support Department will also develop a system that automatically posts the profiles generated by the generation AI to job sites and social media. For example, the profiles will be automatically posted to multiple job sites. This will allow them to approach a wide range of companies.

[0035] The job search support department can automatically match and notify refugees of job information that is most suitable for them based on the profile generated by the generation AI. The job search support department, for example, builds a system that automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. The job search support department also automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. The job search support department also develops a system that automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. This makes it possible to automatically match and notify the most suitable job information.

[0036] The job search support department can automatically translate the profiles generated by the generation AI into different languages ​​to support international job searches. The job search support department, for example, builds a system that automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. The job search support department also automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. The job search support department also develops a system that automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. This can support international job searches.

[0037] The Job Search Support Department can convert the profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, the Job Search Support Department builds a system that converts profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. The Job Search Support Department can also convert profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. The Job Search Support Department can also develop a system that converts profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. This makes it easier to understand visually.

[0038] The recruitment support department can link the profiles generated by the generation AI with a company's recruitment system and instantly generate a list of interview candidates. For example, the recruitment support department builds a system that links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. The recruitment support department also links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. The recruitment support department also develops a system that links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. This makes it possible to instantly generate a list of interview candidates.

[0039] The recruitment support department can automatically generate detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. The recruitment support department, for example, builds a system that automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. The recruitment support department also automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. The recruitment support department also develops a system that automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. This makes it possible to automatically generate detailed reports.

[0040] The recruitment support department can compare the profile generated by the generation AI with the company's internal database and identify the most suitable candidate by comparing it with past recruitment data. For example, the recruitment support department builds a system that compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. The recruitment support department also compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. The recruitment support department also develops a system that compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. This makes it possible to identify the most suitable candidate.

[0041] The recruitment support department can automatically upload the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department builds a system that automatically uploads the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. The recruitment support department can also automatically upload the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. The recruitment support department can also develop a system that automatically uploads the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. This can streamline the recruitment process.

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

[0043] Employment support systems can also be equipped with matching functions that take into account refugees' cultural backgrounds and language skills. For example, they can recommend suitable companies and job types based on refugees' native language and cultural background. They can also provide cultural training and support to help refugees adapt to their new environment. They can also prioritize introductions to jobs that utilize specific language skills that refugees possess. This will make it easier for refugees to find jobs that make the most of their skills and backgrounds.

[0044] The profile generation unit can generate a profile that takes into account the refugee's health condition and physical limitations. For example, it can reflect the refugee's specific health issues and physical limitations in the profile and recommend companies that offer suitable working environments. It can also suggest adjusting job content and working hours based on the refugee's health condition. It can also provide health management advice and support so that refugees can work while maintaining their health. This makes it easier for refugees to find a workplace where they can work while maintaining their health.

[0045] The job search support department can provide job information that takes into account the refugee's family structure and living environment. For example, if a refugee lives with his or her family, the department will prioritize job information in areas where the whole family can live comfortably. Also, if the refugee has children, the department can provide job information in areas with good educational environments for the children. Furthermore, it is possible to provide information on the living environment and security in the area where the refugee lives, and support the refugee in finding a workplace where they can work safely. This will make it easier for refugees to find a workplace where they can live safely with their families.

[0046] The recruitment support department can provide training to company recruiters on refugees' cultural backgrounds and language skills. For example, they can provide information on the culture and customs of refugees' home countries to deepen companies' understanding when accepting refugees. They can also provide language training to facilitate communication with refugees. They can also introduce specific methods and resources that companies can use to support refugees. This will make it easier for companies to accept refugees and smoothen their recruitment efforts.

[0047] The employment support system can provide skill-up training to refugees to help them advance their careers in the workplace. For example, it can provide training programs to help refugees acquire the skills and qualifications necessary for their desired jobs. It can also provide career counseling to help refugees advance their careers in the workplace. It can also introduce refugees to online courses and workshops to improve their skills in the workplace. This makes it easier for refugees to aim for career advancement in the workplace.

[0048] The employment support system can provide training to refugees to improve their communication skills in the workplace. For example, it can provide language training to help refugees communicate better in the workplace. It can also hold workshops to help refugees improve their teamwork and leadership skills in the workplace. It can also plan activities and events to help refugees communicate better in the workplace. This will make it easier for refugees to improve their communication skills in the workplace.

[0049] The employment support system can provide a feedback system to help refugees improve their performance at work. For example, it can provide regular feedback to help refugees improve their performance at work. It can also support refugees in setting goals and managing their progress to improve their performance at work. It can also provide training and coaching to help refugees improve their performance at work. This makes it easier for refugees to improve their performance at work.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The profile generation unit uses generation AI to generate accurate and rapid profiles. The generation AI takes in interviews with refugees and their shared experiences as text data and generates a profile in a short amount of time. The generation AI analyzes the interview content and experiences and generates a profile based on appropriate prompts. The input to the generation AI is prompts that include the interview content and experiences, and the generation AI generates a profile based on those prompts. Step 2: The Job Search Support Department supports refugees in their job search activities based on the profile generated by the Profile Generation Department. By posting the generated profile on a job site, refugees are more likely to receive job offers from companies. The Job Search Support Department can also automatically match and notify refugees of the most suitable job information based on the profile generated by the AI. Step 3: The Recruitment Support Department supports companies' recruitment activities based on the profiles generated by the Profile Generation Department. They can quickly find refugees who match the skills and experience that companies are looking for, and expedite interview and recruitment procedures. The Recruitment Support Department can also link the profiles generated by the AI ​​with the company's recruitment system to instantly generate a list of interview candidates.

[0052] (Example 2) The employment support system according to an embodiment of the present invention is a system aimed at expanding employment opportunities for refugees and enhancing corporate recruitment activities. This system uses generative AI to generate accurate and rapid profiles, streamlining refugee job searches and significantly improving corporate recruitment efficiency. As a result, the employment support system can streamline refugee job searches and enhance corporate recruitment activities.

[0053] An employment support system according to an embodiment includes a profile generation unit, a job search support unit, and a recruitment support unit. The profile generation unit generates accurate and rapid profiles using a generation AI. For example, the generation AI imports interviews with refugees and their shared experiences as text data and generates profiles in a short time. The generation AI analyzes the interview content and experiences and generates profiles based on appropriate prompts. The generation AI receives prompts including the interview content and experiences, and generates profiles based on the prompts. The job search support unit supports refugees' job searches based on the profiles generated by the profile generation unit. For example, posting the generated profiles on job sites increases the likelihood of receiving job offers from companies. The job search support unit can automatically match and notify refugees of job offers that are most suitable for them based on the profiles generated by the generation AI. The recruitment support unit supports companies' recruitment activities based on the profiles generated by the profile generation unit. For example, companies can quickly find refugees who match their desired skill sets and experience, allowing them to quickly proceed with interviews and hiring procedures. The recruitment support unit can also link the profiles generated by the generation AI with the company's recruitment system to instantly generate a list of interview candidates. As a result, the employment support system according to the embodiment can improve the efficiency of refugees' job-seeking activities and enhance companies' recruitment activities.

[0054] When analyzing interview content, the profile generation unit can convert it into text in real time using voice recognition technology and instantly reflect it in the profile. For example, during an interview, the profile generation unit uses voice recognition technology to convert what is spoken into text in real time using a generation AI, and instantly reflects that text in the profile. For example, work history and skills mentioned during the interview are added to the profile on the spot. The profile generation unit also analyzes interview audio data in real time, and builds a system in which the generation AI automatically converts it into text. For example, the interview audio is instantly converted into text and reflected in the profile. The profile generation unit also uses voice recognition technology to convert conversations during an interview into text in real time, and the generation AI analyzes that text and reflects it in the profile. For example, the interview content is instantly converted into text and added to the profile. This allows the interview content to be converted into text in real time and reflected in the profile.

[0055] When analyzing past work experience and skills, the profile generation unit can refer to the latest industry trends and technical information and add the latest information to the profile. For example, when the generation AI analyzes past work experience and skills, the profile generation unit automatically collects the latest trends and technical information in related industries and reflects it in the profile. For example, the latest technological trends and market needs are added to the profile. In addition, when the generation AI analyzes past work experience and skills, the profile generation unit refers to the latest industry news and trend information and adds the latest information to the profile. For example, the latest technology and market trends are reflected in the profile. In addition, when the generation AI analyzes past work experience and skills, the profile generation unit builds a system that refers to the latest trends and technical information in related industries and adds the latest information to the profile. For example, the latest technological trends and market needs are reflected in the profile. This makes it possible to reflect the latest industry information in the profile.

[0056] The profile generation unit can use the emotion estimation function to analyze the emotions of refugees during interviews and generate a profile that elicits positive emotions. The profile generation unit, for example, uses the emotion estimation function to analyze the emotions of refugees during interviews in real time and generate a profile that elicits positive emotions. For example, it emphasizes the content that the refugee spoke with confidence. The profile generation unit also builds a system that analyzes the emotions of refugees during interviews and provides feedback to elicit positive emotions. For example, it displays words of encouragement in response to the content that the refugee spoke. The profile generation unit also uses the emotion estimation function to develop a system that analyzes the emotions of refugees during interviews and generates a profile that elicits positive emotions. For example, it expresses the content that the refugee spoke in a positive manner. This makes it possible to generate a profile that elicits positive emotions.

[0057] The profile generation unit can link video interviews to profiles and provide visual information as well. For example, the profile generation unit builds a system that links video interviews of refugees to profiles generated by the generation AI and provides visual information as well. For example, it adds links to video interviews to profiles. The profile generation unit also provides visual information by embedding video interviews of refugees in profiles generated by the generation AI. For example, it displays thumbnails of video interviews in profiles. The profile generation unit also develops a system that links video interviews of refugees to profiles generated by the generation AI and provides visual information as well. For example, it adds links to video interviews to profiles. This makes it possible to provide visual information.

[0058] The profile generation unit can attach a portfolio of past projects and deliverables to the profile to show specific achievements. For example, the profile generation unit builds a system that attaches a portfolio of a refugee's past projects and deliverables to a profile generated by the generation AI to show specific achievements. For example, it adds project details and links to the deliverables to the profile. The profile generation unit also attaches a portfolio of a refugee's past projects and deliverables to the profile generated by the generation AI to show specific achievements. For example, it displays project details and images of the deliverables on the profile. The profile generation unit also develops a system that attaches a portfolio of a refugee's past projects and deliverables to a profile generated by the generation AI to show specific achievements. For example, it adds project details and links to the deliverables to the profile. This makes it possible to show specific achievements.

[0059] The profile generation unit uses the emotion estimation function to monitor the emotions of refugees when they create their profiles in real time and can provide advice to reduce stress. The profile generation unit, for example, uses the emotion estimation function to build a system that monitors the emotions of refugees when they create their profiles in real time and provides advice to reduce stress. For example, it makes suggestions to help refugees relax when they feel stressed. The profile generation unit also analyzes the emotions of refugees when they are creating their profiles in real time and provides advice to reduce stress. For example, it makes suggestions to help refugees relax when they feel stressed. The profile generation unit also uses the emotion estimation function to develop a system that monitors the emotions of refugees when they create their profiles in real time and provides advice to reduce stress. For example, it makes suggestions to help refugees relax when they feel stressed. This makes it possible to provide advice to reduce stress.

[0060] The Job Search Support Department will automatically post the profiles generated by the generation AI to job sites and social media, allowing them to approach a wide range of companies. For example, the Job Search Support Department will build a system that automatically posts the profiles generated by the generation AI to job sites and social media. For example, the profiles will be automatically posted to multiple job sites. The Job Search Support Department will also automatically post the profiles generated by the generation AI to job sites and social media, allowing them to approach a wide range of companies. For example, the profiles will be automatically posted to multiple social media. The Job Search Support Department will also develop a system that automatically posts the profiles generated by the generation AI to job sites and social media. For example, the profiles will be automatically posted to multiple job sites. This will allow them to approach a wide range of companies.

[0061] The job search support department can automatically match and notify refugees of job information that is most suitable for them based on the profile generated by the generation AI. The job search support department, for example, builds a system that automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. The job search support department also automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. The job search support department also develops a system that automatically matches and notifies refugees of job information that is most suitable for them based on the profile generated by the generation AI. For example, it automatically matches and notifies job information based on the profile. This makes it possible to automatically match and notify the most suitable job information.

[0062] The job search support department can use the emotion estimation function to analyze the anxiety and stress that refugees feel while job searching and provide them with advice to relax. The job search support department, for example, uses the emotion estimation function to build a system that analyzes the anxiety and stress that refugees feel while job searching in real time and provides them with advice to relax. For example, when a refugee feels anxious, the system makes suggestions to help them relax. The job search support department also analyzes the emotions of refugees while job searching in real time and provides them with advice to reduce their anxiety and stress. For example, when a refugee feels anxious, the system makes suggestions to help them relax. The job search support department also uses the emotion estimation function to develop a system that analyzes the anxiety and stress that refugees feel while job searching in real time and provides them with advice to help them relax. For example, when a refugee feels anxious, the system makes suggestions to help them relax. This makes it possible to provide them with advice to reduce their anxiety and stress.

[0063] The job search support department can automatically translate the profiles generated by the generation AI into different languages ​​to support international job searches. The job search support department, for example, builds a system that automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. The job search support department also automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. The job search support department also develops a system that automatically translates profiles generated by the generation AI into different languages ​​to support international job searches. For example, it automatically translates profiles into multiple languages. This can support international job searches.

[0064] The Job Search Support Department can convert the profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, the Job Search Support Department builds a system that converts profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. The Job Search Support Department can also convert profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. The Job Search Support Department can also develop a system that converts profiles generated by the generation AI into visual notes or infographics to make them easier to understand visually. For example, it converts profiles into visual notes or infographics. This makes it easier to understand visually.

[0065] The job search support unit can use the emotion estimation function to provide feedback to reinforce the positive emotions felt by refugees while they are job searching. For example, the job search support unit uses the emotion estimation function to build a system that analyzes the positive emotions felt by refugees while job searching in real time and provides feedback to reinforce the emotions. For example, it displays words of encouragement when a refugee feels positive emotions. The job search support unit also analyzes the emotions of refugees while job searching in real time and provides feedback to reinforce the positive emotions. For example, it displays words of encouragement when a refugee feels positive emotions. The job search support unit also uses the emotion estimation function to develop a system that analyzes the positive emotions felt by refugees while job searching in real time and provides feedback to reinforce the emotions. For example, it displays words of encouragement when a refugee feels positive emotions. This makes it possible to provide feedback to reinforce the positive emotions.

[0066] The recruitment support department can link the profiles generated by the generation AI with a company's recruitment system and instantly generate a list of interview candidates. For example, the recruitment support department builds a system that links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. The recruitment support department also links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. The recruitment support department also develops a system that links the profiles generated by the generation AI with a company's recruitment system and instantly generates a list of interview candidates. For example, the profiles are automatically imported into the recruitment system and a list of interview candidates is generated. This makes it possible to instantly generate a list of interview candidates.

[0067] The recruitment support department can automatically generate detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. The recruitment support department, for example, builds a system that automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. The recruitment support department also automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. The recruitment support department also develops a system that automatically generates detailed reports on the skills and experience of candidates for company recruiters based on the profiles generated by the generation AI. For example, it automatically generates a detailed report based on the profile. This makes it possible to automatically generate detailed reports.

[0068] The recruitment support department can use the emotion estimation function to analyze the emotions that a company's recruiters feel toward candidates and support hiring decisions. The recruitment support department, for example, uses the emotion estimation function to analyze the emotions that a company's recruiters feel toward candidates in real time and build a system to support hiring decisions. For example, the recruitment support department analyzes the emotions of recruiters and uses the information to help with hiring decisions. The recruitment support department also analyzes the emotions that recruiters feel toward candidates in real time and supports hiring decisions. For example, the recruitment support department analyzes the emotions of recruiters and uses the information to help with hiring decisions. The recruitment support department also uses the emotion estimation function to develop a system to analyze the emotions that a company's recruiters feel toward candidates in real time and support hiring decisions. For example, the recruitment support department analyzes the emotions of recruiters and uses the information to help with hiring decisions. This can support hiring decisions.

[0069] The recruitment support department can compare the profile generated by the generation AI with the company's internal database and identify the most suitable candidate by comparing it with past recruitment data. For example, the recruitment support department builds a system that compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. The recruitment support department also compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. The recruitment support department also develops a system that compares the profile generated by the generation AI with the company's internal database and identifies the most suitable candidate by comparing it with past recruitment data. For example, the profile is compared with past recruitment data to identify the most suitable candidate. This makes it possible to identify the most suitable candidate.

[0070] The recruitment support department can automatically upload the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department builds a system that automatically uploads the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. The recruitment support department can also automatically upload the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. The recruitment support department can also develop a system that automatically uploads the profiles generated by the generation AI to a company's recruitment portal, thereby streamlining the recruitment process. For example, the recruitment support department automatically uploads the profiles to a recruitment portal. This can streamline the recruitment process.

[0071] The recruitment support department can use the emotion estimation function to provide feedback to reinforce the positive emotions felt by company recruiters toward candidates. The recruitment support department, for example, uses the emotion estimation function to build a system that analyzes the positive emotions felt by company recruiters toward candidates in real time and provides feedback to reinforce the emotions. For example, the recruiter displays encouraging words when he or she feels positive emotions. The recruitment support department also analyzes the positive emotions felt by recruiters toward candidates in real time and provides feedback to reinforce the emotions. For example, the recruiter displays encouraging words when he or she feels positive emotions. The recruitment support department also uses the emotion estimation function to develop a system that analyzes the positive emotions felt by company recruiters toward candidates in real time and provides feedback to reinforce the emotions. For example, the recruiter displays encouraging words when he or she feels positive emotions. This makes it possible to provide feedback to reinforce the positive emotions.

[0072] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0073] Employment support systems can also be equipped with matching functions that take into account refugees' cultural backgrounds and language skills. For example, they can recommend suitable companies and job types based on refugees' native language and cultural background. They can also provide cultural training and support to help refugees adapt to their new environment. They can also prioritize introductions to jobs that utilize specific language skills that refugees possess. This will make it easier for refugees to find jobs that make the most of their skills and backgrounds.

[0074] The profile generation unit can generate a profile that takes into account the refugee's health condition and physical limitations. For example, it can reflect the refugee's specific health issues and physical limitations in the profile and recommend companies that offer suitable working environments. It can also suggest adjusting job content and working hours based on the refugee's health condition. It can also provide health management advice and support so that refugees can work while maintaining their health. This makes it easier for refugees to find a workplace where they can work while maintaining their health.

[0075] The job search support department can provide job information that takes into account the refugee's family structure and living environment. For example, if a refugee lives with his or her family, the department will prioritize job information in areas where the whole family can live comfortably. Also, if the refugee has children, the department can provide job information in areas with good educational environments for the children. Furthermore, it is possible to provide information on the living environment and security in the area where the refugee lives, and support the refugee in finding a workplace where they can work safely. This will make it easier for refugees to find a workplace where they can live safely with their families.

[0076] The recruitment support department can provide training to company recruiters on refugees' cultural backgrounds and language skills. For example, they can provide information on the culture and customs of refugees' home countries to deepen companies' understanding when accepting refugees. They can also provide language training to facilitate communication with refugees. They can also introduce specific methods and resources that companies can use to support refugees. This will make it easier for companies to accept refugees and smoothen their recruitment efforts.

[0077] The employment support system can provide mental health support to help refugees adapt to their new workplace. For example, it can provide counseling services to reduce the stress and anxiety refugees feel at work. It can also provide advice on interpersonal relationships and communication in the workplace. It can also introduce relaxation techniques and stress management methods to help refugees reduce stress at work. This can help refugees adapt more smoothly to their new workplace.

[0078] The employment support system can provide skill-up training to refugees to help them advance their careers in the workplace. For example, it can provide training programs to help refugees acquire the skills and qualifications necessary for their desired jobs. It can also provide career counseling to help refugees advance their careers in the workplace. It can also introduce refugees to online courses and workshops to improve their skills in the workplace. This makes it easier for refugees to aim for career advancement in the workplace.

[0079] The employment support system can provide training to refugees to improve their communication skills in the workplace. For example, it can provide language training to help refugees communicate better in the workplace. It can also hold workshops to help refugees improve their teamwork and leadership skills in the workplace. It can also plan activities and events to help refugees communicate better in the workplace. This will make it easier for refugees to improve their communication skills in the workplace.

[0080] The employment support system can provide relaxation techniques to help refugees reduce stress at work. For example, it can provide yoga and meditation classes to help refugees reduce stress at work. It can also introduce relaxation music and aromatherapy to help refugees reduce stress at work. It can also provide massage and reflexology services to help refugees reduce stress at work. This can make it easier for refugees to reduce stress at work.

[0081] The employment support system can provide a feedback system to help refugees improve their performance at work. For example, it can provide regular feedback to help refugees improve their performance at work. It can also support refugees in setting goals and managing their progress to improve their performance at work. It can also provide training and coaching to help refugees improve their performance at work. This makes it easier for refugees to improve their performance at work.

[0082] The employment support system can provide incentive programs to help refugees maintain their motivation at work. For example, it can provide rewards and perks when refugees achieve their goals at work. It can also hold challenges and competitions to help refugees maintain their motivation at work. It can also provide mentorship programs to help refugees maintain their motivation at work. This can make it easier for refugees to maintain their motivation at work.

[0083] The processing flow of the second embodiment will be briefly explained below.

[0084] Step 1: The profile generation unit uses generation AI to generate accurate and rapid profiles. The generation AI takes in interviews with refugees and their shared experiences as text data and generates a profile in a short amount of time. The generation AI analyzes the interview content and experiences and generates a profile based on appropriate prompts. The input to the generation AI is prompts that include the interview content and experiences, and the generation AI generates a profile based on those prompts. Step 2: The Job Search Support Department supports refugees in their job search activities based on the profile generated by the Profile Generation Department. By posting the generated profile on a job site, refugees are more likely to receive job offers from companies. The Job Search Support Department can also automatically match and notify refugees of the most suitable job information based on the profile generated by the AI. Step 3: The Recruitment Support Department supports companies' recruitment activities based on the profiles generated by the Profile Generation Department. They can quickly find refugees who match the skills and experience that companies are looking for, and expedite interview and recruitment procedures. The Recruitment Support Department can also link the profiles generated by the AI ​​with the company's recruitment system to instantly generate a list of interview candidates.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0089] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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).

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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).

[0109] 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.

[0110] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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).

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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).

[0138] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0139] 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."

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0151] 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]

[0152] 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 profile generation unit that generates accurate and fast profiles using generation AI; a job-seeking support unit that supports job-seeking activities of refugees based on the profile generated by the profile generation unit; a recruitment support unit that supports the recruitment activities of companies based on the profile generated by the profile generation unit. A system characterized by:

2. The profile generation unit When analyzing the interview content, voice recognition technology is used to convert it into text in real time and instantly reflect it in the profile. The system of claim 1 .

3. The profile generation unit When analyzing past work experience and skills, we refer to the latest industry trends and technical information to update the profile. The system of claim 1 .

4. The profile generation unit Analyzing the refugee's emotions during the interview and generating the profile that elicits positive emotions. The system of claim 1 .

5. The profile generation unit Link video interviews to the profile to provide visual information The system of claim 1 .

Images