system

Abstract

The system according to the embodiment aims to continuously support an individual's career growth and development. [Solution] A system according to an embodiment includes a reception unit, a generation unit, a session unit, and another generation unit. The reception unit receives input of a user's career-related questions or goals. The generation unit provides advice or questions based on the information received by the reception unit. The session unit conducts periodic sessions. The generation unit automatically generates a career plan sheet based on the content of the dialogue.

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] Existing technologies lack ongoing support to support individuals' career growth and development, leaving room for improvement.

[0005] The system according to the embodiment aims to continuously support an individual's career growth and development. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a generation unit, a session unit, and another generation unit. The reception unit receives input of a user's career-related questions or goals. The generation unit provides advice or questions based on the information received by the reception unit. The session unit conducts periodic sessions. The generation unit automatically generates a career plan sheet based on the content of the dialogue. [Effects of the Invention]

[0007] The system according to the embodiment can continuously support an individual's career growth and development. [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) A career coaching system according to an embodiment of the present invention utilizes a generative AI to support individual career growth and development. In this career coaching system, a user inputs career-related questions and goals. The generative AI provides advice and questions based on the input, engaging in dialogue from goal setting to action planning. Furthermore, the system provides ongoing support through periodic sessions, automatically generating and constantly updating a career plan sheet based on the content of the dialogue. For example, when a user inputs career-related questions and goals, the user may enter a question such as, "What skills should I acquire as my next career step?" This information is input into the generative AI. The generative AI then analyzes the input information and provides advice and questions. The generative AI generates optimal advice based on the user's input and provides it to the user. For example, the system may provide advice such as, "As your next career step, I recommend acquiring project management skills." Furthermore, the generative AI engages in dialogue from goal setting to action planning. The system proposes specific action plans for the user's set goals and supports the user in following those plans. For example, the system may propose specific action plans such as, "I recommend you take an online course to acquire project management skills." The generative AI provides ongoing support through periodic sessions. Each time a user reports their progress, the generating AI uses that information to provide new advice and questions to support the user's career growth. For example, the generating AI can provide new advice in response to a question such as, "What steps should I take next after taking an online course?" Finally, the generating AI automatically generates and constantly updates a career plan sheet based on the content of the conversation. This allows users to understand their career plan at a glance and clarify their next steps. For example, the career plan sheet neatly displays goals, action plans, progress, and other information.In this way, the career coaching system utilizing generative AI supports individual career growth and development 24 hours a day, helping users clarify their own career plans and providing specific action plans for taking the next step. This allows the career coaching system to support users' career growth and provide continuous support.

[0029] A career coaching system according to an embodiment includes a reception unit, a generation unit, a session unit, and a generation unit. The reception unit receives input of questions and goals related to a user's career. The questions and goals related to a user's career include, but are not limited to, career selection, skill development, and career changes. The reception unit receives, for example, a question input by the user, such as, "What skills should I acquire as my next career step?" The generation unit uses a generation AI to provide advice and questions based on the information received by the reception unit. The generation unit generates optimal advice based on the user's input and provides it to the user. For example, the generation unit provides advice such as, "As your next career step, I recommend acquiring project management skills." The generation unit also conducts dialogue with the user from goal setting to action planning. The generation unit proposes, for example, a specific action plan for the user's set goals and supports the user in acting in accordance with the plan. For example, the generation unit proposes a specific action plan such as, "I recommend taking an online course to acquire project management skills." The session unit conducts periodic sessions. For example, each time the user reports their progress, the generation unit provides new advice and questions based on the information, supporting the user's career growth. For example, the session unit may provide new advice in response to a question such as, "What steps should I take next after taking the online course?" The generation unit automatically generates a career plan sheet based on the content of the dialogue. For example, the generation unit may automatically generate and constantly update a sheet summarizing the user's career plan. For example, the generation unit may organize and display goals, action plans, progress, and the like on the career plan sheet. This allows the career coaching system according to the embodiment to support the user's career growth and provide continuous support.

[0030] The generation unit can provide appropriate advice based on the user's input. The generation unit, for example, provides advice according to the user's skill level. For example, if the user is a beginner, the generation unit provides advice for acquiring basic skills. Furthermore, if the user is an intermediate user, the generation unit can provide advice for acquiring applied skills. Furthermore, if the user is an advanced user, the generation unit can provide advice for acquiring specialized skills. For example, if the user is a beginner, the generation unit can provide advice such as, "We recommend that you take an online course to acquire basic programming skills." Furthermore, if the user is an intermediate user, the generation unit can provide advice such as, "We recommend that you gain practical experience to acquire project management skills." Furthermore, if the user is an advanced user, the generation unit can provide advice such as, "We recommend that you read specialized books to acquire specialized skills." In this way, the generation unit can support the user's career growth by providing optimal advice based on the user's input.

[0031] The generation unit can perform processes from user goal setting to action planning. For example, the generation unit proposes a specific action plan for a goal set by the user. For example, if the user sets a goal of "acquiring project management skills," the generation unit can propose a specific action plan such as "we recommend taking an online course." Furthermore, if the user sets a goal of "improving leadership skills," the generation unit can also propose a specific action plan such as "we recommend participating in a leadership training program." Furthermore, if the user sets a goal of "improving communication skills," the generation unit can also propose a specific action plan such as "we recommend participating in a workshop to improve communication skills." For example, if the user sets a goal of "acquiring project management skills," the generation unit can propose a specific action plan such as "we recommend taking an online course." Furthermore, if the user sets a goal of "improving leadership skills," the generation unit can also propose a specific action plan such as "we recommend participating in a leadership training program." Furthermore, if the user sets a goal of "improving communication skills," the generation unit can also propose a specific action plan such as "we recommend participating in a workshop to improve communication skills." This allows the generation unit to provide a specific action plan by conducting a dialogue from the user's goal setting to the action plan.

[0032] The session unit may include a unit for recording the user's progress. The session unit, for example, records the progress toward goals set by the user. For example, if the user sets a goal of "acquiring project management skills," the session unit records the progress. Furthermore, if the user sets a goal of "improving leadership skills," the session unit can also record the progress. Furthermore, if the user sets a goal of "improving communication skills," the session unit can also record the progress. For example, if the user sets a goal of "acquiring project management skills," the session unit records the progress. Furthermore, if the user sets a goal of "improving leadership skills," the session unit can also record the progress. Furthermore, if the user sets a goal of "improving communication skills," the session unit can also record the progress. In this way, the session unit can provide continuous support by recording the user's progress.

[0033] The generation unit can provide new advice or questions based on the user's progress. For example, the generation unit can provide new advice based on the progress toward a goal set by the user. For example, the generation unit can provide new advice when the user sets a goal of "acquiring project management skills" and reports the progress toward that goal. The generation unit can also provide new advice when the user sets a goal of "improving leadership skills" and reports the progress toward that goal. The generation unit can also provide new advice when the user sets a goal of "improving communication skills" and reports the progress toward that goal. For example, when the user sets a goal of "acquiring project management skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you gain work experience." When the user sets a goal of "improving leadership skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you participate in a leadership training program." When the user sets a goal of "improving communication skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you participate in a workshop to improve communication skills." This allows the generator to support the user's career growth by providing new advice and questions based on the user's progress.

[0034] The generation unit can periodically update and automatically generate a career plan sheet according to the content of the dialogue. The generation unit updates the career plan sheet based on, for example, goals set by the user and progress. For example, the generation unit updates the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. The generation unit can also update the career plan sheet when the user sets a goal of "improving leadership skills" and reports progress toward that goal. The generation unit can also update the career plan sheet when the user sets a goal of "improving communication skills" and reports progress toward that goal. For example, the generation unit can add an action plan of "taking an online course" to the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. The generation unit can also add an action plan of "participating in a leadership training program" to the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. Furthermore, if the user sets a goal of "improving communication skills" and reports the progress, the generation unit can add an action plan to the career plan sheet, such as "participate in a workshop to improve communication skills." This allows the generation unit to keep the user's career plan up to date by constantly updating and automatically generating the career plan sheet according to the content of the conversation.

[0035] The reception unit can analyze the user's past input history of questions and goals and select an appropriate input method. For example, if the user has preferred text input in the past, the reception unit can preferentially suggest text input. For example, if the user has frequently used voice input in the past, the reception unit can also preferentially suggest voice input. Furthermore, if the user has previously input during a specific time period, the reception unit can also prompt the user to input during that time period. For example, if the user has previously preferred text input, the reception unit can display a message such as "Please give priority to text input." Furthermore, if the user has previously used voice input frequently, the reception unit can display a message such as "Please give priority to voice input." Furthermore, if the user has previously input during a specific time period, the reception unit can display a message such as "Please input during that time period." In this way, the reception unit can provide the optimal input method by analyzing the user's past input history.

[0036] When a question or a goal is input, the reception unit can filter the question or goal based on the user's current career status or area of ​​interest. For example, the reception unit can preferentially display questions and goals related to the user's current job. The reception unit can also suggest related questions and goals based on the user's area of ​​interest. The reception unit can also filter appropriate questions and goals according to the user's career stage. For example, the reception unit can preferentially display questions and goals related to the user's current job. The reception unit can also suggest related questions and goals based on the user's area of ​​interest. The reception unit can also filter appropriate questions and goals according to the user's career stage. In this way, the reception unit can provide highly relevant questions and goals by filtering based on the user's career status and area of ​​interest.

[0037] When inputting a question or goal, the reception unit can prioritize inputting highly relevant questions or goals based on the user's geographical location information. For example, if the user is in a specific area, the reception unit can prioritize providing career information related to that area. For example, if the user is on a business trip, the reception unit can also suggest career goals related to the business trip destination. Furthermore, if the user is considering changing jobs, the reception unit can also provide information related to the area where the user will be changing jobs. For example, if the user is in a specific area, the reception unit can display a message such as "Career information related to that area will be prioritized." Furthermore, if the user is on a business trip, the reception unit can display a message such as "Career goals related to the business trip destination will be suggested." Furthermore, if the user is considering changing jobs, the reception unit can display a message such as "Information related to the area where the user will be changing jobs will be provided." In this way, the reception unit can provide highly relevant questions and goals by taking the user's geographical location information into consideration.

[0038] When a question or goal is input, the reception unit can analyze the user's social media activity and input a related question or goal. For example, the reception unit can suggest questions or goals related to fields in which the user has shown interest on social media. For example, the reception unit can also input questions or goals based on industry trends that the user follows. The reception unit can also analyze the user's social media activity history and suggest related career goals. For example, the reception unit can suggest questions or goals related to fields in which the user has shown interest on social media. The reception unit can also input questions or goals based on industry trends that the user follows. The reception unit can also analyze the user's social media activity history and suggest related career goals. In this way, the reception unit can provide related questions and goals by analyzing the user's social media activity.

[0039] When generating advice or a question, the generation unit can set the level of detail based on the importance of the user's career goal. For example, the generation unit provides detailed advice for an important career goal. For example, the generation unit can provide brief advice for a low-priority goal. The generation unit can also provide in-depth advice for a goal in which the user is particularly interested. For example, the generation unit can display a message such as "We will provide detailed advice" for an important career goal. For example, the generation unit can display a message such as "We will provide brief advice" for a low-priority goal. For example, the generation unit can display a message such as "We will provide in-depth advice" for a goal in which the user is particularly interested. In this way, the generation unit can provide more appropriate advice or a question by adjusting the level of detail based on the importance of the user's career goal.

[0040] The generation unit can apply different algorithms depending on the user's career category when generating advice or questions. For example, the generation unit can apply an algorithm that provides technical advice to a user in a technical occupation. For example, the generation unit can apply an algorithm that provides leadership advice to a user in a managerial occupation. The generation unit can also apply an algorithm that provides creativity-boosting advice to a user in a creative occupation. For example, the generation unit can display a message such as "An algorithm that provides technical advice will be applied" to a user in a technical occupation. The generation unit can also display a message such as "An algorithm that provides leadership advice will be applied" to a user in a managerial occupation. The generation unit can also display a message such as "An algorithm that provides creativity-boosting advice will be applied" to a user in a creative occupation. In this way, the generation unit can provide more appropriate advice or questions by applying different generation algorithms depending on the user's career category.

[0041] When generating advice or questions, the generation unit can set priorities based on the time of submission of the user's career goals. For example, the generation unit can provide advice preferentially for urgent career goals. For example, the generation unit can also provide advice quickly for goals with an upcoming submission deadline. The generation unit can also provide step-by-step advice for long-term goals. For example, the generation unit can display a message such as "We will provide you with advice as a priority" for urgent career goals. For goals with an upcoming submission deadline, the generation unit can also display a message such as "We will provide you with advice quickly." For long-term goals, the generation unit can display a message such as "We will provide you with step-by-step advice." In this way, the generation unit can provide more appropriate advice or questions by determining priorities based on the time of submission of the user's career goals.

[0042] When generating advice or questions, the generation unit may set an order based on the user's career relevance. For example, the generation unit may preferentially provide advice related to the user's current job. For example, the generation unit may also provide advice related to the user's future career goals in stages. The generation unit may also preferentially provide advice related to the user's field of interest. For example, the generation unit may preferentially provide advice related to the user's current job. The generation unit may also provide advice related to the user's future career goals in stages. The generation unit may also preferentially provide advice related to the user's field of interest. In this way, the generation unit can provide more appropriate advice or questions by adjusting the order based on the user's career relevance.

[0043] During a session, the session unit can select an appropriate progress method by referring to the user's past session history. The session unit, for example, preferentially adopts a progress method that the user has previously preferred. The session unit can also select an effective progress method from the user's past session history, for example. The session unit can also analyze the user's past session history and suggest an optimal progress method. For example, the session unit preferentially adopts a progress method that the user has previously preferred. The session unit can also select an effective progress method from the user's past session history. The session unit can also analyze the user's past session history and suggest an optimal progress method. In this way, the session unit can provide an optimal progress method by referring to the user's past session history.

[0044] During a session, the session unit can set the content of the session based on the user's degree of achievement of his / her career goal. For example, if the user achieves his / her goal, the session unit can hold a session on setting a new goal. For example, if the user is approaching his / her goal, the session unit can hold a session on the next step. Furthermore, if the user is far from his / her goal, the session unit can hold a session on a specific action plan for achieving the goal. For example, if the user achieves his / her goal, the session unit can display a message such as "We will hold a session on setting a new goal." Furthermore, if the user is approaching his / her goal, the session unit can display a message such as "We will hold a session on the next step." Furthermore, if the user is far from his / her goal, the session unit can display a message such as "We will hold a session on a specific action plan for achieving the goal." In this way, the session unit can provide a more appropriate session by customizing the content of the session based on the user's degree of achievement of his / her career goal.

[0045] The session unit can select an appropriate session method based on the user's geographical location information during a session. For example, when the user is on a business trip, the session unit can conduct a session that provides information related to the business trip destination. For example, when the user is at home, the session unit can conduct a session in a relaxing environment. Furthermore, when the user is in the office, the session unit can conduct a session that provides information related to work. For example, when the user is on a business trip, the session unit can display a message such as "A session that provides information related to the business trip destination will be conducted." Furthermore, when the user is at home, the session unit can display a message such as "A session that provides information related to work will be conducted." Furthermore, when the user is in the office, the session unit can display a message such as "A session that provides information related to work will be conducted." In this way, the session unit can provide an optimal session method by taking the user's geographical location information into consideration.

[0046] During a session, the session unit can analyze the user's social media activity and suggest session content. For example, the session unit can suggest sessions related to areas in which the user has shown interest on social media. For example, the session unit can also suggest session content based on industry trends followed by the user. The session unit can also analyze the user's social media activity history and suggest sessions related to related career goals. For example, the session unit can suggest sessions related to areas in which the user has shown interest on social media. For example, the session unit can suggest session content based on industry trends followed by the user. For example, the session unit can suggest sessions related to related career goals by analyzing the user's social media activity history.

[0047] When recording progress, the recording unit can select an appropriate recording method by referring to the user's past recording history. For example, the recording unit preferentially adopts a recording method that the user has previously preferred. For example, the recording unit can also select an effective recording method from the user's past recording history. The recording unit can also analyze the user's past recording history and suggest an optimal recording method. For example, the recording unit preferentially adopts a recording method that the user has previously preferred. The recording unit can also select an effective recording method from the user's past recording history. The recording unit can also analyze the user's past recording history and suggest an optimal recording method. In this way, the recording unit can provide an optimal recording method by referring to the user's past recording history.

[0048] When recording progress, the recording unit can set the level of detail of the recording based on the degree of achievement of the user's career goal. For example, when the user achieves the goal, the recording unit performs detailed recording. For example, when the user is approaching the goal, the recording unit can also perform detailed recording of the progress. Furthermore, when the user is far from the goal, the recording unit can also perform brief recording. For example, when the user achieves the goal, the recording unit can display a message such as "A detailed record will be made." Furthermore, when the user is approaching the goal, the recording unit can display a message such as "A detailed record will be made of the progress." Furthermore, when the user is far from the goal, the recording unit can display a message such as "A brief record will be made." In this way, the recording unit can provide a more appropriate recording method by adjusting the level of detail of the recording based on the degree of achievement of the user's career goal.

[0049] When recording progress, the recording unit can select an appropriate recording method based on the user's geographical location information. For example, when the user is on a business trip, the recording unit records progress related to the business trip destination. For example, when the user is at home, the recording unit can also record progress in a relaxing environment. Furthermore, when the user is in the office, the recording unit can also record work-related progress. For example, when the user is on a business trip, the recording unit can display a message such as "Recording progress related to the business trip destination." Furthermore, when the user is at home, the recording unit can display a message such as "Recording progress in a relaxing environment." Furthermore, when the user is in the office, the recording unit can display a message such as "Recording work-related progress." In this way, the recording unit can provide an optimal recording method by taking the user's geographical location information into consideration.

[0050] When recording progress, the recording unit can analyze the user's social media activity and suggest content for the record. For example, the recording unit records progress related to areas in which the user has shown interest on social media. For example, the recording unit can also record progress based on industry trends that the user follows. The recording unit can also analyze the user's social media activity history and record progress related to related career goals. For example, the recording unit records progress related to areas in which the user has shown interest on social media. For example, the recording unit can also record progress based on industry trends that the user follows. For example, the recording unit can analyze the user's social media activity history and record progress related to related career goals. In this way, the recording unit can provide related content for the record by analyzing the user's social media activity.

[0051] When generating a career plan sheet, the career plan sheet generation unit can select an appropriate generation method by referring to the user's past career plan history. The career plan sheet generation unit, for example, preferentially adopts a career plan sheet format that the user has previously preferred. The career plan sheet generation unit can also select an effective generation method from the user's past career plan history. The career plan sheet generation unit can also analyze the user's past career plan history and suggest an optimal generation method. For example, the career plan sheet generation unit preferentially adopts a career plan sheet format that the user has previously preferred. The career plan sheet generation unit can also select an effective generation method from the user's past career plan history. The career plan sheet generation unit can also analyze the user's past career plan history and suggest an optimal generation method. In this way, the career plan sheet generation unit can provide an optimal generation method by referring to the user's past career plan history.

[0052] When generating a career plan sheet, the career plan sheet generation unit can set the level of detail of the sheet based on the user's degree of achievement of their career goals. For example, if the user has achieved their goal, the career plan sheet generation unit generates a detailed career plan sheet. For example, if the user is approaching their goal, the career plan sheet generation unit can generate a career plan sheet that details their progress. Furthermore, if the user is far from their goal, the career plan sheet generation unit can generate a concise career plan sheet. For example, if the user has achieved their goal, the career plan sheet generation unit can display a message such as "A detailed career plan sheet will be generated." Furthermore, if the user is approaching their goal, the career plan sheet generation unit can display a message such as "A career plan sheet that details their progress will be generated." Furthermore, if the user is far from their goal, the career plan sheet generation unit can display a message such as "A concise career plan sheet will be generated." In this way, the career plan sheet generation unit can provide a more appropriate career plan sheet by adjusting the level of detail of the sheet based on the user's degree of achievement of their career goals.

[0053] When generating a career plan sheet, the career plan sheet generation unit can select an appropriate generation method based on the user's geographical location information. For example, when the user is on a business trip, the career plan sheet generation unit generates a career plan sheet that includes information related to the business trip destination. For example, when the user is at home, the career plan sheet generation unit can generate a career plan sheet in a relaxing environment. Also, when the user is in the office, the career plan sheet generation unit can generate a career plan sheet that includes information related to work. For example, when the user is on a business trip, the career plan sheet generation unit can display a message such as "A career plan sheet including information related to the business trip destination will be generated." Also, when the user is at home, the career plan sheet generation unit can display a message such as "A career plan sheet in a relaxing environment will be generated." Also, when the user is in the office, the career plan sheet generation unit can display a message such as "A career plan sheet including information related to work will be generated." In this way, the career plan sheet generation unit can provide an optimal career plan sheet by taking the user's geographical location information into consideration.

[0054] The career plan sheet generation unit can analyze the user's social media activities and suggest the content of the career plan sheet when generating the career plan sheet. The career plan sheet generation unit, for example, generates a career plan sheet including information related to fields in which the user has shown interest on social media. The career plan sheet generation unit can also suggest the content of the career plan sheet based on industry trends followed by the user. The career plan sheet generation unit can also analyze the user's social media activity history and generate a career plan sheet including information on related career goals. For example, the career plan sheet generation unit generates a career plan sheet including information related to fields in which the user has shown interest on social media. The career plan sheet generation unit can also suggest the content of the career plan sheet based on industry trends followed by the user. The career plan sheet generation unit can also analyze the user's social media activity history and generate a career plan sheet including information on related career goals. In this way, the career plan sheet generation unit can provide the content of a related career plan sheet by analyzing the user's social media activity.

[0055] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0056] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0057] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0058] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0059] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0060] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0061] The processing flow of the first embodiment will be briefly explained below.

[0062] Step 1: The reception unit receives input of the user's career-related questions and goals. For example, the reception unit receives input of a question such as, "What skills should I acquire as my next career step?" Step 2: The generator provides advice and questions based on the information received by the receiver. For example, the generator may provide advice such as, "As your next career step, we recommend that you acquire project management skills." The generator also conducts a dialogue with the user, from goal setting to action planning, and proposes a specific action plan. For example, it may propose a specific action plan such as, "We recommend that you take an online course to acquire project management skills." Step 3: The session unit conducts regular sessions. For example, each time the user reports their progress, the generator unit uses that information to provide new advice and questions to support the user's career growth. For example, the generator unit provides new advice in response to a question such as, "What steps should I take next after taking the online course?" Step 4: The generation unit automatically generates a career plan sheet based on the content of the conversation. For example, it automatically generates a sheet summarizing the user's career plan, constantly updating it, and organizes and displays goals, action plans, progress, etc.

[0063] (Example 2) A career coaching system according to an embodiment of the present invention utilizes a generative AI to support individual career growth and development. In this career coaching system, a user inputs career-related questions and goals. The generative AI provides advice and questions based on the input, engaging in dialogue from goal setting to action planning. Furthermore, the system provides ongoing support through periodic sessions, automatically generating and constantly updating a career plan sheet based on the content of the dialogue. For example, when a user inputs career-related questions and goals, the user may enter a question such as, "What skills should I acquire as my next career step?" This information is input into the generative AI. The generative AI then analyzes the input information and provides advice and questions. The generative AI generates optimal advice based on the user's input and provides it to the user. For example, the system may provide advice such as, "As your next career step, I recommend acquiring project management skills." Furthermore, the generative AI engages in dialogue from goal setting to action planning. The system proposes specific action plans for the user's set goals and supports the user in following those plans. For example, the system may propose specific action plans such as, "I recommend you take an online course to acquire project management skills." The generative AI provides ongoing support through periodic sessions. Each time a user reports their progress, the generating AI uses that information to provide new advice and questions to support the user's career growth. For example, the generating AI can provide new advice in response to a question such as, "What steps should I take next after taking an online course?" Finally, the generating AI automatically generates and constantly updates a career plan sheet based on the content of the conversation. This allows users to understand their career plan at a glance and clarify their next steps. For example, the career plan sheet neatly displays goals, action plans, progress, and other information.In this way, the career coaching system utilizing generative AI supports individual career growth and development 24 hours a day, helping users clarify their own career plans and providing specific action plans for taking the next step. This allows the career coaching system to support users' career growth and provide continuous support.

[0064] A career coaching system according to an embodiment includes a reception unit, a generation unit, a session unit, and a generation unit. The reception unit receives input of questions and goals related to a user's career. The questions and goals related to a user's career include, but are not limited to, career selection, skill development, and career changes. The reception unit receives, for example, a question input by the user, such as, "What skills should I acquire as my next career step?" The generation unit uses a generation AI to provide advice and questions based on the information received by the reception unit. The generation unit generates optimal advice based on the user's input and provides it to the user. For example, the generation unit provides advice such as, "As your next career step, I recommend acquiring project management skills." The generation unit also conducts dialogue with the user from goal setting to action planning. The generation unit proposes, for example, a specific action plan for the user's set goals and supports the user in acting in accordance with the plan. For example, the generation unit proposes a specific action plan such as, "I recommend taking an online course to acquire project management skills." The session unit conducts periodic sessions. For example, each time the user reports their progress, the generation unit provides new advice and questions based on the information, supporting the user's career growth. For example, the session unit may provide new advice in response to a question such as, "What steps should I take next after taking the online course?" The generation unit automatically generates a career plan sheet based on the content of the dialogue. For example, the generation unit may automatically generate and constantly update a sheet summarizing the user's career plan. For example, the generation unit may organize and display goals, action plans, progress, and the like on the career plan sheet. This allows the career coaching system according to the embodiment to support the user's career growth and provide continuous support.

[0065] The generation unit can provide appropriate advice based on the user's input. The generation unit, for example, provides advice according to the user's skill level. For example, if the user is a beginner, the generation unit provides advice for acquiring basic skills. Furthermore, if the user is an intermediate user, the generation unit can provide advice for acquiring applied skills. Furthermore, if the user is an advanced user, the generation unit can provide advice for acquiring specialized skills. For example, if the user is a beginner, the generation unit can provide advice such as, "We recommend that you take an online course to acquire basic programming skills." Furthermore, if the user is an intermediate user, the generation unit can provide advice such as, "We recommend that you gain practical experience to acquire project management skills." Furthermore, if the user is an advanced user, the generation unit can provide advice such as, "We recommend that you read specialized books to acquire specialized skills." In this way, the generation unit can support the user's career growth by providing optimal advice based on the user's input.

[0066] The generation unit can perform processes from user goal setting to action planning. For example, the generation unit proposes a specific action plan for a goal set by the user. For example, if the user sets a goal of "acquiring project management skills," the generation unit can propose a specific action plan such as "we recommend taking an online course." Furthermore, if the user sets a goal of "improving leadership skills," the generation unit can also propose a specific action plan such as "we recommend participating in a leadership training program." Furthermore, if the user sets a goal of "improving communication skills," the generation unit can also propose a specific action plan such as "we recommend participating in a workshop to improve communication skills." For example, if the user sets a goal of "acquiring project management skills," the generation unit can propose a specific action plan such as "we recommend taking an online course." Furthermore, if the user sets a goal of "improving leadership skills," the generation unit can also propose a specific action plan such as "we recommend participating in a leadership training program." Furthermore, if the user sets a goal of "improving communication skills," the generation unit can also propose a specific action plan such as "we recommend participating in a workshop to improve communication skills." This allows the generation unit to provide a specific action plan by conducting a dialogue from the user's goal setting to the action plan.

[0067] The session unit may include a unit for recording the user's progress. The session unit, for example, records the progress toward goals set by the user. For example, if the user sets a goal of "acquiring project management skills," the session unit records the progress. Furthermore, if the user sets a goal of "improving leadership skills," the session unit can also record the progress. Furthermore, if the user sets a goal of "improving communication skills," the session unit can also record the progress. For example, if the user sets a goal of "acquiring project management skills," the session unit records the progress. Furthermore, if the user sets a goal of "improving leadership skills," the session unit can also record the progress. Furthermore, if the user sets a goal of "improving communication skills," the session unit can also record the progress. In this way, the session unit can provide continuous support by recording the user's progress.

[0068] The generation unit can provide new advice or questions based on the user's progress. For example, the generation unit can provide new advice based on the progress toward a goal set by the user. For example, the generation unit can provide new advice when the user sets a goal of "acquiring project management skills" and reports the progress toward that goal. The generation unit can also provide new advice when the user sets a goal of "improving leadership skills" and reports the progress toward that goal. The generation unit can also provide new advice when the user sets a goal of "improving communication skills" and reports the progress toward that goal. For example, when the user sets a goal of "acquiring project management skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you gain work experience." When the user sets a goal of "improving leadership skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you participate in a leadership training program." When the user sets a goal of "improving communication skills" and reports the progress toward that goal, the generation unit can provide new advice such as "Next, we recommend that you participate in a workshop to improve communication skills." This allows the generator to support the user's career growth by providing new advice and questions based on the user's progress.

[0069] The generation unit can periodically update and automatically generate a career plan sheet according to the content of the dialogue. The generation unit updates the career plan sheet based on, for example, goals set by the user and progress. For example, the generation unit updates the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. The generation unit can also update the career plan sheet when the user sets a goal of "improving leadership skills" and reports progress toward that goal. The generation unit can also update the career plan sheet when the user sets a goal of "improving communication skills" and reports progress toward that goal. For example, the generation unit can add an action plan of "taking an online course" to the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. The generation unit can also add an action plan of "participating in a leadership training program" to the career plan sheet when the user sets a goal of "acquiring project management skills" and reports progress toward that goal. Furthermore, if the user sets a goal of "improving communication skills" and reports the progress, the generation unit can add an action plan to the career plan sheet, such as "participate in a workshop to improve communication skills." This allows the generation unit to keep the user's career plan up to date by constantly updating and automatically generating the career plan sheet according to the content of the conversation.

[0070] The reception unit can estimate the user's emotions and adjust the timing of inputting a question or a goal based on the estimated user's emotions. For example, if the user is feeling stressed, the reception unit prompts the user to input a question or a goal at a time when the user can relax. For example, if the user is concentrating, the reception unit can prompt the user to input a question or a goal repeatedly. Furthermore, if the user is tired, the reception unit can prompt the user to input a question or a goal after taking a break. For example, if the user is feeling stressed, the reception unit can display a message such as "Please input a question or a goal at a time when the user can relax." Furthermore, if the user is concentrating, the reception unit can display a message such as "Please input a question or a goal continuously." Furthermore, if the user is tired, the reception unit can display a message such as "Please input a question or a goal after taking a break." In this way, the reception unit can adjust the input timing according to the user's emotions, thereby allowing the user to input a question or a goal at a more appropriate time.

[0071] The reception unit can analyze the user's past input history of questions and goals and select an appropriate input method. For example, if the user has preferred text input in the past, the reception unit can preferentially suggest text input. For example, if the user has frequently used voice input in the past, the reception unit can also preferentially suggest voice input. Furthermore, if the user has previously input during a specific time period, the reception unit can also prompt the user to input during that time period. For example, if the user has previously preferred text input, the reception unit can display a message such as "Please give priority to text input." Furthermore, if the user has previously used voice input frequently, the reception unit can display a message such as "Please give priority to voice input." Furthermore, if the user has previously input during a specific time period, the reception unit can display a message such as "Please input during that time period." In this way, the reception unit can provide the optimal input method by analyzing the user's past input history.

[0072] When a question or a goal is input, the reception unit can filter the question or goal based on the user's current career status or area of ​​interest. For example, the reception unit can preferentially display questions and goals related to the user's current job. The reception unit can also suggest related questions and goals based on the user's area of ​​interest. The reception unit can also filter appropriate questions and goals according to the user's career stage. For example, the reception unit can preferentially display questions and goals related to the user's current job. The reception unit can also suggest related questions and goals based on the user's area of ​​interest. The reception unit can also filter appropriate questions and goals according to the user's career stage. In this way, the reception unit can provide highly relevant questions and goals by filtering based on the user's career status and area of ​​interest.

[0073] The reception unit can estimate the user's emotions and determine the priority of questions and goals to be input based on the estimated user's emotions. For example, when the user is impatient, the reception unit prioritizes input of important questions and goals. For example, when the user is relaxed, the reception unit can also input detailed questions and goals. Furthermore, when the user is tired, the reception unit can also prioritize input of simple questions and goals. For example, when the user is impatient, the reception unit can display a message such as "Please input important questions and goals first." Furthermore, when the user is relaxed, the reception unit can display a message such as "Please input detailed questions and goals first." Furthermore, when the user is tired, the reception unit can display a message such as "Please input simple questions and goals first." In this way, the reception unit can provide more appropriate questions and goals by determining the priority of questions and goals according to the user's emotions.

[0074] When inputting a question or goal, the reception unit can prioritize inputting highly relevant questions or goals based on the user's geographical location information. For example, if the user is in a specific area, the reception unit can prioritize providing career information related to that area. For example, if the user is on a business trip, the reception unit can also suggest career goals related to the business trip destination. Furthermore, if the user is considering changing jobs, the reception unit can also provide information related to the area where the user will be changing jobs. For example, if the user is in a specific area, the reception unit can display a message such as "Career information related to that area will be prioritized." Furthermore, if the user is on a business trip, the reception unit can display a message such as "Career goals related to the business trip destination will be suggested." Furthermore, if the user is considering changing jobs, the reception unit can display a message such as "Information related to the area where the user will be changing jobs will be provided." In this way, the reception unit can provide highly relevant questions and goals by taking the user's geographical location information into consideration.

[0075] When a question or goal is input, the reception unit can analyze the user's social media activity and input a related question or goal. For example, the reception unit can suggest questions or goals related to fields in which the user has shown interest on social media. For example, the reception unit can also input questions or goals based on industry trends that the user follows. The reception unit can also analyze the user's social media activity history and suggest related career goals. For example, the reception unit can suggest questions or goals related to fields in which the user has shown interest on social media. The reception unit can also input questions or goals based on industry trends that the user follows. The reception unit can also analyze the user's social media activity history and suggest related career goals. In this way, the reception unit can provide related questions and goals by analyzing the user's social media activity.

[0076] The generation unit can estimate the user's emotions and adjust the way advice and questions are expressed based on the estimated user's emotions. For example, if the user is nervous, the generation unit provides advice in gentle language. For example, if the user is relaxed, the generation unit can provide advice including detailed explanations. Furthermore, if the user is in a hurry, the generation unit can provide advice that is concise and to the point. For example, if the user is nervous, the generation unit can display a message such as "We will provide advice in gentle language." Furthermore, if the user is relaxed, the generation unit can display a message such as "We will provide advice including detailed explanations." Furthermore, if the user is in a hurry, the generation unit can display a message such as "We will provide advice that is concise and to the point." In this way, the generation unit can provide more appropriate advice and questions by adjusting the way advice and questions are expressed based on the user's emotions.

[0077] When generating advice or a question, the generation unit can set the level of detail based on the importance of the user's career goal. For example, the generation unit provides detailed advice for an important career goal. For example, the generation unit can provide brief advice for a low-priority goal. The generation unit can also provide in-depth advice for a goal in which the user is particularly interested. For example, the generation unit can display a message such as "We will provide detailed advice" for an important career goal. For example, the generation unit can display a message such as "We will provide brief advice" for a low-priority goal. For example, the generation unit can display a message such as "We will provide in-depth advice" for a goal in which the user is particularly interested. In this way, the generation unit can provide more appropriate advice or a question by adjusting the level of detail based on the importance of the user's career goal.

[0078] The generation unit can apply different algorithms depending on the user's career category when generating advice or questions. For example, the generation unit can apply an algorithm that provides technical advice to a user in a technical occupation. For example, the generation unit can apply an algorithm that provides leadership advice to a user in a managerial occupation. The generation unit can also apply an algorithm that provides creativity-boosting advice to a user in a creative occupation. For example, the generation unit can display a message such as "An algorithm that provides technical advice will be applied" to a user in a technical occupation. The generation unit can also display a message such as "An algorithm that provides leadership advice will be applied" to a user in a managerial occupation. The generation unit can also display a message such as "An algorithm that provides creativity-boosting advice will be applied" to a user in a creative occupation. In this way, the generation unit can provide more appropriate advice or questions by applying different generation algorithms depending on the user's career category.

[0079] The generation unit can estimate the user's emotions and adjust the length of advice or questions based on the estimated user's emotions. For example, if the user is in a hurry, the generation unit can provide short, to-the-point advice. For example, if the user is relaxed, the generation unit can provide longer advice with detailed explanations. Furthermore, if the user is excited, the generation unit can provide advice with visually stimulating effects. For example, if the user is in a hurry, the generation unit can display a message such as "We will provide you with short, to-the-point advice." Furthermore, if the user is relaxed, the generation unit can display a message such as "We will provide you with longer advice with detailed explanations." Furthermore, if the user is excited, the generation unit can display a message such as "We will provide you with advice with visually stimulating effects." In this way, the generation unit can adjust the length of advice or questions according to the user's emotions, thereby providing more appropriate advice or questions.

[0080] When generating advice or questions, the generation unit can set priorities based on the time of submission of the user's career goals. For example, the generation unit can provide advice preferentially for urgent career goals. For example, the generation unit can also provide advice quickly for goals with an upcoming submission deadline. The generation unit can also provide step-by-step advice for long-term goals. For example, the generation unit can display a message such as "We will provide you with advice as a priority" for urgent career goals. For goals with an upcoming submission deadline, the generation unit can also display a message such as "We will provide you with advice quickly." For long-term goals, the generation unit can display a message such as "We will provide you with step-by-step advice." In this way, the generation unit can provide more appropriate advice or questions by determining priorities based on the time of submission of the user's career goals.

[0081] When generating advice or questions, the generation unit may set an order based on the user's career relevance. For example, the generation unit may preferentially provide advice related to the user's current job. For example, the generation unit may also provide advice related to the user's future career goals in stages. The generation unit may also preferentially provide advice related to the user's field of interest. For example, the generation unit may preferentially provide advice related to the user's current job. The generation unit may also provide advice related to the user's future career goals in stages. The generation unit may also preferentially provide advice related to the user's field of interest. In this way, the generation unit can provide more appropriate advice or questions by adjusting the order based on the user's career relevance.

[0082] The session unit can estimate the user's emotions and adjust the way the session proceeds based on the estimated user's emotions. For example, if the user is nervous, the session unit can proceed with the session in a way that allows the user to relax. For example, if the user is relaxed, the session unit can proceed with the session while providing detailed information. Furthermore, if the user is in a hurry, the session unit can proceed with the session while focusing on the main points. For example, if the user is nervous, the session unit can display a message such as "The session will proceed with the session in a way that allows the user to relax." Furthermore, if the user is relaxed, the session unit can display a message such as "The session will proceed with the session while providing detailed information." Furthermore, if the user is in a hurry, the session unit can display a message such as "The session will proceed with the session while focusing on the main points." In this way, the session unit can provide a more appropriate session by adjusting the way the session proceeds based on the user's emotions.

[0083] During a session, the session unit can select an appropriate progress method by referring to the user's past session history. The session unit, for example, preferentially adopts a progress method that the user has previously preferred. The session unit can also select an effective progress method from the user's past session history, for example. The session unit can also analyze the user's past session history and suggest an optimal progress method. For example, the session unit preferentially adopts a progress method that the user has previously preferred. The session unit can also select an effective progress method from the user's past session history. The session unit can also analyze the user's past session history and suggest an optimal progress method. In this way, the session unit can provide an optimal progress method by referring to the user's past session history.

[0084] During a session, the session unit can set the content of the session based on the user's degree of achievement of his / her career goal. For example, if the user achieves his / her goal, the session unit can hold a session on setting a new goal. For example, if the user is approaching his / her goal, the session unit can hold a session on the next step. Furthermore, if the user is far from his / her goal, the session unit can hold a session on a specific action plan for achieving the goal. For example, if the user achieves his / her goal, the session unit can display a message such as "We will hold a session on setting a new goal." Furthermore, if the user is approaching his / her goal, the session unit can display a message such as "We will hold a session on the next step." Furthermore, if the user is far from his / her goal, the session unit can display a message such as "We will hold a session on a specific action plan for achieving the goal." In this way, the session unit can provide a more appropriate session by customizing the content of the session based on the user's degree of achievement of his / her career goal.

[0085] The session unit can estimate the user's emotions and determine the priority of sessions based on the estimated user's emotions. For example, if the user is nervous, the session unit can prioritize a session that allows the user to relax. For example, if the user is relaxed, the session unit can prioritize a session that provides detailed information. Furthermore, if the user is in a hurry, the session unit can prioritize a session that covers the main points. For example, if the user is nervous, the session unit can display a message such as "A session that allows the user to relax will be prioritized." Furthermore, if the user is relaxed, the session unit can display a message such as "A session that provides detailed information will be prioritized." Furthermore, if the user is in a hurry, the session unit can display a message such as "A session that covers the main points will be prioritized." In this way, the session unit can provide more appropriate sessions by determining the priority of sessions according to the user's emotions.

[0086] The session unit can select an appropriate session method based on the user's geographical location information during a session. For example, when the user is on a business trip, the session unit can conduct a session that provides information related to the business trip destination. For example, when the user is at home, the session unit can conduct a session in a relaxing environment. Furthermore, when the user is in the office, the session unit can conduct a session that provides information related to work. For example, when the user is on a business trip, the session unit can display a message such as "A session that provides information related to the business trip destination will be conducted." Furthermore, when the user is at home, the session unit can display a message such as "A session that provides information related to work will be conducted." Furthermore, when the user is in the office, the session unit can display a message such as "A session that provides information related to work will be conducted." In this way, the session unit can provide an optimal session method by taking the user's geographical location information into consideration.

[0087] During a session, the session unit can analyze the user's social media activity and suggest session content. For example, the session unit can suggest sessions related to areas in which the user has shown interest on social media. For example, the session unit can also suggest session content based on industry trends followed by the user. The session unit can also analyze the user's social media activity history and suggest sessions related to related career goals. For example, the session unit can suggest sessions related to areas in which the user has shown interest on social media. For example, the session unit can suggest session content based on industry trends followed by the user. For example, the session unit can suggest sessions related to related career goals by analyzing the user's social media activity history.

[0088] The recording unit can estimate the user's emotions and adjust the progress recording method based on the estimated user's emotions. For example, if the user is nervous, the recording unit can provide a concise and highly visible recording method. For example, if the user is relaxed, the recording unit can provide a detailed recording method. Furthermore, if the user is in a hurry, the recording unit can provide a recording method that focuses on the main points. For example, if the user is nervous, the recording unit can display a message such as "We provide a concise and highly visible recording method." Furthermore, if the user is relaxed, the recording unit can display a message such as "We provide a detailed recording method." Furthermore, if the user is in a hurry, the recording unit can display a message such as "We provide a recording method that focuses on the main points." In this way, the recording unit can adjust the progress recording method according to the user's emotions, thereby providing a more appropriate recording method.

[0089] When recording progress, the recording unit can select an appropriate recording method by referring to the user's past recording history. For example, the recording unit preferentially adopts a recording method that the user has previously preferred. For example, the recording unit can also select an effective recording method from the user's past recording history. The recording unit can also analyze the user's past recording history and suggest an optimal recording method. For example, the recording unit preferentially adopts a recording method that the user has previously preferred. The recording unit can also select an effective recording method from the user's past recording history. The recording unit can also analyze the user's past recording history and suggest an optimal recording method. In this way, the recording unit can provide an optimal recording method by referring to the user's past recording history.

[0090] When recording progress, the recording unit can set the level of detail of the recording based on the degree of achievement of the user's career goal. For example, when the user achieves the goal, the recording unit performs detailed recording. For example, when the user is approaching the goal, the recording unit can also perform detailed recording of the progress. Furthermore, when the user is far from the goal, the recording unit can also perform brief recording. For example, when the user achieves the goal, the recording unit can display a message such as "A detailed record will be made." Furthermore, when the user is approaching the goal, the recording unit can display a message such as "A detailed record will be made of the progress." Furthermore, when the user is far from the goal, the recording unit can display a message such as "A brief record will be made." In this way, the recording unit can provide a more appropriate recording method by adjusting the level of detail of the recording based on the degree of achievement of the user's career goal.

[0091] The recording unit can estimate the user's emotions and determine the priority of recording progress status based on the estimated user's emotions. For example, if the user is nervous, the recording unit prioritizes recording important progress status. For example, if the user is relaxed, the recording unit can also record detailed progress status. Furthermore, if the user is in a hurry, the recording unit can also record progress status that focuses on the main points. For example, if the user is nervous, the recording unit can display a message such as "Important progress status will be recorded first." Furthermore, if the user is relaxed, the recording unit can display a message such as "Detailed progress status will be recorded." Furthermore, if the user is in a hurry, the recording unit can display a message such as "Progress status that focuses on the main points." In this way, the recording unit can determine the priority of recording progress status according to the user's emotions, thereby providing a more appropriate recording method.

[0092] When recording progress, the recording unit can select an appropriate recording method based on the user's geographical location information. For example, when the user is on a business trip, the recording unit records progress related to the business trip destination. For example, when the user is at home, the recording unit can also record progress in a relaxing environment. Furthermore, when the user is in the office, the recording unit can also record work-related progress. For example, when the user is on a business trip, the recording unit can display a message such as "Recording progress related to the business trip destination." Furthermore, when the user is at home, the recording unit can display a message such as "Recording progress in a relaxing environment." Furthermore, when the user is in the office, the recording unit can display a message such as "Recording work-related progress." In this way, the recording unit can provide an optimal recording method by taking the user's geographical location information into consideration.

[0093] When recording progress, the recording unit can analyze the user's social media activity and suggest content for the record. For example, the recording unit records progress related to areas in which the user has shown interest on social media. For example, the recording unit can also record progress based on industry trends that the user follows. The recording unit can also analyze the user's social media activity history and record progress related to related career goals. For example, the recording unit records progress related to areas in which the user has shown interest on social media. For example, the recording unit can also record progress based on industry trends that the user follows. For example, the recording unit can analyze the user's social media activity history and record progress related to related career goals. In this way, the recording unit can provide related content for the record by analyzing the user's social media activity.

[0094] The career plan sheet generation unit can estimate the user's emotions and adjust the generation method of the career plan sheet based on the estimated user emotions. For example, when the user is nervous, the career plan sheet generation unit generates a simple and highly visible career plan sheet. For example, when the user is relaxed, the career plan sheet generation unit can generate a career plan sheet that includes detailed information. Furthermore, when the user is in a hurry, the career plan sheet generation unit can generate a career plan sheet that focuses on the main points. For example, when the user is nervous, the career plan sheet generation unit can display a message such as "A simple and highly visible career plan sheet will be generated." Furthermore, when the user is relaxed, the career plan sheet generation unit can display a message such as "A career plan sheet that includes detailed information will be generated." Furthermore, when the user is in a hurry, the career plan sheet generation unit can display a message such as "A career plan sheet that focuses on the main points will be generated." In this way, the career plan sheet generation unit can provide a more appropriate career plan sheet by adjusting the generation method of the career plan sheet according to the user's emotions.

[0095] When generating a career plan sheet, the career plan sheet generation unit can select an appropriate generation method by referring to the user's past career plan history. The career plan sheet generation unit, for example, preferentially adopts a career plan sheet format that the user has previously preferred. The career plan sheet generation unit can also select an effective generation method from the user's past career plan history. The career plan sheet generation unit can also analyze the user's past career plan history and suggest an optimal generation method. For example, the career plan sheet generation unit preferentially adopts a career plan sheet format that the user has previously preferred. The career plan sheet generation unit can also select an effective generation method from the user's past career plan history. The career plan sheet generation unit can also analyze the user's past career plan history and suggest an optimal generation method. In this way, the career plan sheet generation unit can provide an optimal generation method by referring to the user's past career plan history.

[0096] When generating a career plan sheet, the career plan sheet generation unit can set the level of detail of the sheet based on the user's degree of achievement of their career goals. For example, if the user has achieved their goal, the career plan sheet generation unit generates a detailed career plan sheet. For example, if the user is approaching their goal, the career plan sheet generation unit can generate a career plan sheet that details their progress. Furthermore, if the user is far from their goal, the career plan sheet generation unit can generate a concise career plan sheet. For example, if the user has achieved their goal, the career plan sheet generation unit can display a message such as "A detailed career plan sheet will be generated." Furthermore, if the user is approaching their goal, the career plan sheet generation unit can display a message such as "A career plan sheet that details their progress will be generated." Furthermore, if the user is far from their goal, the career plan sheet generation unit can display a message such as "A concise career plan sheet will be generated." In this way, the career plan sheet generation unit can provide a more appropriate career plan sheet by adjusting the level of detail of the sheet based on the user's degree of achievement of their career goals.

[0097] The career plan sheet generation unit can estimate the user's emotions and determine the priority of career plan sheets based on the estimated user's emotions. For example, when the user is nervous, the career plan sheet generation unit generates a career plan sheet that prioritizes important information. For example, when the user is relaxed, the career plan sheet generation unit can generate a career plan sheet that includes detailed information. Furthermore, when the user is in a hurry, the career plan sheet generation unit can generate a career plan sheet that focuses on the main points. For example, when the user is nervous, the career plan sheet generation unit can display a message such as "A career plan sheet will be generated that prioritizes important information." Furthermore, when the user is relaxed, the career plan sheet generation unit can display a message such as "A career plan sheet will be generated that includes detailed information." Furthermore, when the user is in a hurry, the career plan sheet generation unit can display a message such as "A career plan sheet will be generated that focuses on the main points." In this way, the career plan sheet generation unit can provide a more appropriate career plan sheet by determining the priority of career plan sheets according to the user's emotions.

[0098] When generating a career plan sheet, the career plan sheet generation unit can select an appropriate generation method based on the user's geographical location information. For example, when the user is on a business trip, the career plan sheet generation unit generates a career plan sheet that includes information related to the business trip destination. For example, when the user is at home, the career plan sheet generation unit can generate a career plan sheet in a relaxing environment. Also, when the user is in the office, the career plan sheet generation unit can generate a career plan sheet that includes information related to work. For example, when the user is on a business trip, the career plan sheet generation unit can display a message such as "A career plan sheet including information related to the business trip destination will be generated." Also, when the user is at home, the career plan sheet generation unit can display a message such as "A career plan sheet in a relaxing environment will be generated." Also, when the user is in the office, the career plan sheet generation unit can display a message such as "A career plan sheet including information related to work will be generated." In this way, the career plan sheet generation unit can provide an optimal career plan sheet by taking the user's geographical location information into consideration.

[0099] The career plan sheet generation unit can analyze the user's social media activities and suggest the content of the career plan sheet when generating the career plan sheet. The career plan sheet generation unit, for example, generates a career plan sheet including information related to fields in which the user has shown interest on social media. The career plan sheet generation unit can also suggest the content of the career plan sheet based on industry trends followed by the user. The career plan sheet generation unit can also analyze the user's social media activity history and generate a career plan sheet including information on related career goals. For example, the career plan sheet generation unit generates a career plan sheet including information related to fields in which the user has shown interest on social media. The career plan sheet generation unit can also suggest the content of the career plan sheet based on industry trends followed by the user. The career plan sheet generation unit can also analyze the user's social media activity history and generate a career plan sheet including information on related career goals. In this way, the career plan sheet generation unit can provide the content of a related career plan sheet by analyzing the user's social media activity. === Hard Collateral 1-1 === Each of the multiple elements including the above-mentioned reception unit, generation unit, session unit, and career plan sheet generation unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14 and receives input of the user's career-related questions and goals. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides advice and questions using a generation AI. The session unit is realized, for example, by the control unit 46A of the smart device 14 and conducts periodic sessions. The career plan sheet generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and automatically generates a career plan sheet according to the content of the dialogue. === Hard Collateral 1-2 === Each of the multiple elements, including the reception unit, generation unit, session unit, and career plan sheet generation unit, described above, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214 and receives input of questions and goals related to the user's career. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides advice and questions using a generation AI. The session unit is realized, for example, by the control unit 46A of the smart glasses 214 and conducts periodic sessions. The career plan sheet generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and automatically generates a career plan sheet according to the content of the dialogue. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, generation unit, session unit, and career plan sheet generation unit is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset-type terminal 314 and receives input of questions and goals related to the user's career. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides advice and questions using a generation AI. The session unit is realized, for example, by the control unit 46A of the headset-type terminal 314 and conducts periodic sessions. The career plan sheet generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and automatically generates a career plan sheet according to the content of the dialogue. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, generation unit, session unit, and career plan sheet generation unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414 and receives input of questions and goals related to the user's career. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and provides advice and questions using a generation AI. The session unit is realized, for example, by the control unit 46A of the robot 414 and conducts periodic sessions. The career plan sheet generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and automatically generates a career plan sheet according to the content of the dialogue.

[0100] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0101] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0102] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0103] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0104] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0105] The generation unit can evaluate the user's degree of achievement toward their career goals and adjust the content of the advice based on the evaluation results. For example, if the user has achieved a high level of achievement toward their set goals, the generation unit can provide advanced advice for moving on to the next step. If the user has achieved a low level of achievement, the generation unit can provide advice for reviewing and strengthening basic skills. Furthermore, if the user has achieved an intermediate level of achievement, the generation unit can provide intermediate advice for applying current skills. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's degree of achievement toward their career goals.

[0106] The generation unit can estimate the user's emotions and adjust the content of the advice based on the estimated emotions. For example, if the user is feeling stressed, it can provide advice that helps the user to relax. If the user is feeling motivated, it can provide challenging advice. Furthermore, if the user is feeling anxious, it can provide advice that gives the user a sense of security. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's emotions.

[0107] The generation unit can estimate the user's emotions and adjust the content of the advice based on the estimated emotions. For example, if the user is feeling stressed, it can provide advice that helps the user to relax. If the user is feeling motivated, it can provide challenging advice. Furthermore, if the user is feeling anxious, it can provide advice that gives the user a sense of security. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's emotions.

[0108] The generation unit can estimate the user's emotions and adjust the content of the advice based on the estimated emotions. For example, if the user is feeling stressed, it can provide advice that helps the user to relax. If the user is feeling motivated, it can provide challenging advice. Furthermore, if the user is feeling anxious, it can provide advice that gives the user a sense of security. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's emotions.

[0109] The generation unit can estimate the user's emotions and adjust the content of the advice based on the estimated emotions. For example, if the user is feeling stressed, it can provide advice that helps the user to relax. If the user is feeling motivated, it can provide challenging advice. Furthermore, if the user is feeling anxious, it can provide advice that gives the user a sense of security. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's emotions.

[0110] The generation unit can estimate the user's emotions and adjust the content of the advice based on the estimated emotions. For example, if the user is feeling stressed, it can provide advice that helps the user to relax. If the user is feeling motivated, it can provide challenging advice. Furthermore, if the user is feeling anxious, it can provide advice that gives the user a sense of security. In this way, the generation unit can effectively support the user's career growth by providing appropriate advice according to the user's emotions.

[0111] The processing flow of the second embodiment will be briefly explained below.

[0112] Step 1: The reception unit receives input of the user's career-related questions and goals. For example, the reception unit receives input of a question such as, "What skills should I acquire as my next career step?" Step 2: The generator provides advice and questions based on the information received by the receiver. For example, the generator may provide advice such as, "As your next career step, we recommend that you acquire project management skills." The generator also conducts a dialogue with the user, from goal setting to action planning, and proposes a specific action plan. For example, it may propose a specific action plan such as, "We recommend that you take an online course to acquire project management skills." Step 3: The session unit conducts regular sessions. For example, each time the user reports their progress, the generator unit uses that information to provide new advice and questions to support the user's career growth. For example, the generator unit provides new advice in response to a question such as, "What steps should I take next after taking the online course?" Step 4: The generation unit automatically generates a career plan sheet based on the content of the conversation. For example, it automatically generates a sheet summarizing the user's career plan, constantly updating it, and organizes and displays goals, action plans, progress, etc.

[0113] 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.

[0114] 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 the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0115] 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.

[0116] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0117] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0118] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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).

[0123] 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.

[0124] 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.

[0125] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0127] 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.

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

[0129] The specific processing unit 290 transmits the result of the specific processing to the 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.

[0130] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0131] 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.

[0132] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0133] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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).

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 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 identification processing unit 290 using these models.

[0144] 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.

[0145] 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.

[0146] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0147] 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.

[0148] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0149] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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).

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification 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 the same process as the identification processing unit 290 using these models.

[0161] 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.

[0162] 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.

[0163] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0164] 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.

[0165] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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).

[0170] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0171] 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."

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] [Explanation of symbols]

[0185] 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 reception unit that receives input of questions or goals about a user's career; a generating unit that provides advice or questions based on the information received by the receiving unit; A department that holds regular sessions, A generation unit that automatically generates a career plan sheet according to the content of the dialogue. A system characterized by:

2. The generation unit Providing appropriate advice based on user input 2. The system of claim 1.

3. The generation unit Go through the process from user goal setting to action planning 2. The system of claim 1.

4. The session unit Equipped with a section for recording the user's progress 2. The system of claim 1.

5. The generation unit Providing new advice or questions based on the user's progress 2. The system of claim 1.

6. The generation unit Regularly update and automatically generate a career plan sheet based on the content of the conversation 2. The system of claim 1.

7. The reception unit Estimate the user's emotions and adjust the timing of questions and goal input based on the estimated user emotions.

2. The system of claim 1.

8. The reception unit Analyze the user's past question and goal input history and select the appropriate input method.

2. The system of claim 1.

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