Information processing system, information processing device, information processing method, and program

Abstract

This involves registering a person's skills using AI that generates data from natural language input, such as speech. [Solution] The information processing system includes: an acquisition unit that acquires speech data including the content of speech spoken by a person to be identified as a skill; a generation unit that generates first instruction information that instructs the identification of a skill related to the content of speech included in the speech data based on the speech data; a transmission unit that transmits the speech data and the first instruction information to a generation AI; a receiving unit that receives a first response from the generation AI that transmitted the first instruction information; an identification unit that identifies a skill to be registered as a skill of the person based on information related to the content of speech identified by the generation AI, which is included in the first response; and a registration unit that associates the person and the identified skill and registers them in a storage unit.

Description

Technical Field

[0001] The present invention relates to an information processing system, an information processing apparatus, an information processing method, and a program.

Background Art

[0002] Understanding what skills each individual belonging to an organization such as a company has is also important for realizing the placement of personnel in the right positions. It is conceivable to grasp skills by referring to resumes or conducting interviews, etc., but both impose a large burden on the parties and are not economical.

[0003] On the other hand, conventionally, a technique for analyzing an input natural language and registering an individual's skills based on a skill mapping rule has been disclosed (for example, Patent Document 1).

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, it was not possible to register the skills of a target person using a generative AI from a natural language input by speech or the like.

[0005] The present invention has been made in view of the above points, and an object thereof is to register the skills of a target person using a generative AI from a natural language input by speech or the like.

Means for Solving the Problems

[0006] To solve the above problems, the information processing system includes: an acquisition unit that acquires speech data including the content of speech spoken by a person to be identified as a skill; a generation unit that generates first instruction information that instructs the identification of skills related to the content of speech included in the speech data based on the speech data; a transmission unit that transmits the speech data and the first instruction information to a generation AI; a receiving unit that receives a first response from the generation AI that transmitted the first instruction information; an identification unit that identifies skills to be registered as the skills of the person based on information related to the content of speech identified by the generation AI, which is included in the first response; and a registration unit that associates the person and the identified skills and registers them in a storage unit. [Effects of the Invention]

[0007] The system can register a person's skills using AI that generates data from natural language input, such as speech. [Brief explanation of the drawing]

[0008] [Figure 1] This figure shows an example of the configuration of the information processing system in the first embodiment. [Figure 2] This figure shows an example of the hardware configuration of the information processing device 10 in the first embodiment. [Figure 3] This figure shows an example of the functional configuration of the information processing system in the first embodiment. [Figure 4] This is a flowchart illustrating an example of the processing procedure for identifying the skills of a target person in the first embodiment. [Figure 5] This figure shows an example of the configuration of the personnel master storage unit 21 in the first embodiment. [Figure 6] This figure shows an example of the functional configuration of the information processing system in the third embodiment. [Figure 7] This is a flowchart illustrating an example of the processing procedure for the personnel search process in the third embodiment. [Figure 8] This figure shows an example of the display of the search criteria input screen. [Figure 9] This figure shows an example of how the search results screen is displayed. [Figure 10] This figure shows an example of the configuration of the information processing system in the fourth embodiment. [Figure 11] This figure shows an example of the functional configuration of the information processing system in the fourth embodiment. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will be described below with reference to the drawings. Figure 1 is a diagram showing an example configuration of an information processing system in the first embodiment. In Figure 1, the information processing system includes a personnel server 20, an information processing device 10, an AI server 30, and one or more terminals 40. The terminals 40 are connected to the personnel server 20 and the information processing device 10 via the Internet or a LAN or other network. The information processing device 10 is connected to the personnel server 20 and the AI ​​server 30 via the Internet or a LAN or other network.

[0010] The personnel server 20 is one or more computers that manage information (hereinafter referred to as "skill information") indicating what skills each individual belonging to a certain organization such as a company (hereinafter referred to as "organization X") possesses.

[0011] Terminal 40 is a device that uploads (transmits) data to the information processing device 10, which will be used as the source for extracting skill information. In this embodiment, audio data containing the speech of a subject (hereinafter simply referred to as "subject") whose skills are to be evaluated becomes the source for extracting skill information about that subject.

[0012] The information processing device 10 is one or more computers that register skill information about the subject in the personnel server 20 based on voice data received from the terminal 40. The information processing device 10 converts the voice data into text data that shows the content of the utterances contained in the voice data (hereinafter referred to as "utterance data"), and identifies the subject's skills related to the voice data from the utterance data.

[0013] This embodiment describes an example where the target is an employee of organization X. The speech data is text data that shows the content of speech recorded from audio data, for example, when an employee explains an organization X's products or services during customer service or during an internal meeting. Any method can be used to record the audio data. By automatically registering each employee's skill information based on each employee's speech data, the information processing device 10 can efficiently collect skill information for each employee, even if organization X has thousands of employees nationwide.

[0014] The AI ​​server 30 is one or more computers that have a generating AI. The generating AI is used to identify the skills of a target person from speech data. Note that the AI ​​server 30 does not have to be a component specific to the information processing system. For example, the AI ​​server 30 may be a cloud server that makes the generating AI publicly available.

[0015] Figure 2 shows an example of the hardware configuration of the information processing device 10 in the first embodiment. As shown in Figure 2, the information processing device 10 is built by a computer and includes a CPU 101, ROM 102, RAM 103, HD 104, HDD (Hard Disk Drive) controller 105, display 106, external device connection I / F (Interface) 108, network I / F 109, data bus 110, keyboard 111, pointing device 112, DVD-RW (Digital Versatile Disk Rewritable) drive 114, and media I / F 116.

[0016] Among these, the CPU 101 controls the operation of the entire information processing apparatus 10. The ROM 102 stores programs used for driving the CPU 101 such as the IPL. The RAM 103 is used as a work area for the CPU 101. The HD 104 stores various data such as programs. The HDD controller 105 controls the reading or writing of various data to and from the HD 104 according to the control of the CPU 101. The display 106 displays various information such as a cursor, menu, window, characters, or images. The external device connection I / F 108 is an interface for connecting various external devices. The external devices in this case are, for example, a USB (Universal Serial Bus) memory, a printer, and the like. The network I / F 109 is an interface for performing data communication using the communication network 100. The data bus 110 is an address bus, a data bus, etc. for electrically connecting each component such as the CPU 101 shown in FIG. 2.

[0017] Also, the keyboard 111 is a type of input means having a plurality of keys for inputting characters, numerical values, various instructions, and the like. The pointing device 112 is a type of input means for selecting and executing various instructions, selecting a processing target, moving a cursor, and the like. The DVD-RW drive 114 controls the reading or writing of various data to and from the DVD-RW 113 as an example of a removable recording medium. Note that it is not limited to DVD-RW, and it may be DVD-R or the like. The media I / F 116 controls the reading or writing (storage) of data to and from the recording medium 115 such as a flash memory.

[0018] FIG. 3 is a diagram showing a functional configuration example of the information processing system in the first embodiment. In FIG. 3, the AI server 30 has a generation AI 31. The generation AI 31 is a generation AI. The generation AI refers to, for example, a machine learning model (e.g., a neural network, etc.) that has already acquired the ability to generate various contents through machine learning. In the present embodiment, a machine learning model that can input text and generate text according to the text may be used as the generation AI. As an example of such a machine learning model, a large language model (LLM: Large Language Models) may be used. The LLM is a machine learning model that has learned natural language processing using a large amount of text data. The LLM is used in many NLP tasks such as response generation to specific questions, automatic article generation, text summarization, translation, sentiment analysis, etc. Also, it can be utilized in various applications such as education, entertainment, customer service, product development, etc.

[0019] Note that machine learning is a technology for enabling a computer to acquire learning capabilities like those of humans. It refers to a technology in which a computer autonomously generates algorithms necessary for judgments such as data identification from learning data that is pre-loaded, and applies this to new data for prediction. The learning method for machine learning may be any one of supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, and deep learning, and furthermore, a learning method combining these learning methods may also be used. The learning method for machine learning is not limited.

[0020] The personnel server 20 has a personnel master storage unit 21. The personnel master storage unit 21 can be realized by using an auxiliary storage device of the personnel server 20 or a storage device that can be connected to the personnel server 20 via a network.

[0021] The personnel master storage unit 21 stores information indicating skills determined to be possessed by (specified for) each employee belonging to Organization X in association with the identification information of the employee (hereinafter referred to as "employee ID").

[0022] The information processing device 10 includes an acquisition unit 11, a generation unit 12, a transmission unit 13, a reception unit 14, an identification unit 15, and a registration unit 16. Each of these units is realized by processing that one or more programs installed in the information processing device 10 cause the CPU 101 to execute.

[0023] The acquisition unit 11 acquires speech data from the audio data uploaded from the terminal 40. Acquisition of speech data from the audio data can be performed using known speech recognition technology. Furthermore, if the audio data contains speech from multiple speakers, the acquisition unit 11 may use known speaker separation technology to acquire only the speech data of the target speaker. When collecting the target speaker's speech, a bone conduction microphone or the like may be used to prevent ambient sounds (i.e., speech from speakers other than the target speaker) from being mixed into the same audio data.

[0024] The generation unit 12 generates a first prompt that instructs the generation AI 31 to identify skills related to the utterance content contained in the utterance data, based on the utterance data acquired by the acquisition unit 11. The first prompt includes the utterance content and information instructing the identification of skills related to the utterance content. In other words, the generation unit 12 generates the utterance content and information instructing the identification of skills related to the utterance content.

[0025] The transmitting unit 13 transmits the prompt (such as the first prompt) generated by the generating unit 12 to the generating AI 31, thereby transmitting the utterance content and information instructing the generation AI 31 to identify the skills related to the utterance content.

[0026] The receiving unit 14 receives a response from the generating AI that sent the prompt. The response to the first prompt is hereinafter referred to as the "first response". The identification unit 15 identifies skills to be registered as the subject's skills based on information about skills related to the utterance content, which has been identified by the generating AI and is included in the first response.

[0027] The registration unit 16 associates the identified skills with the target individuals and registers them in the storage unit. More specifically, the registration unit 16 associates skill identification information (skill ID, described later) that identifies the identified skills with target individuals (target individual ID, described later) and registers them in the storage unit. In this embodiment, the personnel master storage unit 21 is an example of such storage unit.

[0028] The following describes the processing procedures performed in the information processing system. Figure 4 is a flowchart illustrating an example of the processing procedure for identifying the skills of a target person in the first embodiment.

[0029] In step S101, the acquisition unit 11 receives the voice data transmitted from the terminal 40 and the employee ID of the subject (hereinafter referred to as "subject ID"). The transmission of the voice data and subject ID from the terminal 40 may be at any time after the recording of the voice data, or it may be while the subject is speaking (in real time).

[0030] Next, the acquisition unit 11 acquires speech data in text format from the received audio data (S102). For example, speech data may be acquired by applying speech recognition to the audio data.

[0031] Next, the generation unit 12 generates a first prompt that instructs the system to identify the subject's skills based on the speech data. For example, the content of the first prompt may be as follows:

[0032] <Example of the first prompt starts here> The following is the speech data.

[0033] {Speech data} Identify the skills that the person who made the above utterance is presumed to possess, and output the details of those skills.

[0034] <This is an example of the first prompt.> In the above, {speech data} is the entire text of the speech data. That is, the first prompt contains the entire text of the speech data.

[0035] Next, the transmission unit 13 sends the first prompt generated by the generation unit 12 to the generation AI 31 (S104). When the generation AI 31 receives the first prompt, it outputs text corresponding to the first prompt based on the learned parameters and sends the first response containing the text to the information processing device 10.

[0036] Next, the receiving unit 14 receives the first response (S106). Next, the identification unit 15 identifies the skills to be registered as the subject's skills based on the first response. For example, if the first response is a skill of about 50 characters and its description, such as "This person has presentation skills because of ~", the identification unit 15 identifies the skill name "Presentation Skills" as the skill to be registered. Alternatively, if the first prompt includes the instruction "Please list your skills in bullet points", and the first response includes a bullet point such as "•Presentation Skills•Industry Knowledge", the identification unit 15 extracts the bullet point portion and identifies the skill. Alternatively, if the first response describes the skills in the form of a sentence, the identification unit 15 may identify the entire sentence as the skill to be registered.

[0037] Next, the registration unit 16 performs a registration process to associate the target individuals with the set of skill IDs to be registered (S107). Specifically, the registration unit 16 updates the personnel master storage unit 21.

[0038] Figure 5 shows an example of the configuration of the personnel master memory unit 21 in the first embodiment. As shown in Figure 5, the personnel master memory unit 21 stores skill information indicating the content of each skill that has been determined to be possessed by each employee (individual) belonging to organization X.

[0039] The registration unit 16 associates the string representing the skill identified by the identification unit 15 with the target person and registers it in the personnel master storage unit 21.

[0040] As described above, according to the first embodiment, the subject's skills can be registered using the generating AI 31 based on the subject's speech data. Here, the speech data is data that represents the content of the subject's natural language utterances. Therefore, the subject's skills can be registered using the generating AI from natural language input such as speech.

[0041] While it is possible to have subjects self-report their skills through resumes or other means, the basis for such self-reporting is ambiguous. As in this embodiment, by identifying a subject's skills based on their actual spoken content, the reliability of the skills they possess can be increased, and the workload of the individuals involved can be reduced.

[0042] Next, a second embodiment will be described. The differences between the second embodiment and the above embodiments will be described. Therefore, points that are not specifically mentioned may be the same as in the above embodiments.

[0043] In the second embodiment, in step S103 of Figure 4, the generation unit 12 generates a first prompt that includes information about the subject's attributes by including text indicating the subject's attributes in response to the first prompt, and instructs the identification of the skills of the subject having the said attributes. Attributes may be classified (distinguished) by, for example, job type or role (role, position), or by other criteria that may require different skills. When attributes are classified by job type or rules, examples of attributes include sales staff, sales managers, researchers, and researchers.

[0044] In the second embodiment, the prompt generated by the generation unit 12 may be, for example, as follows:

[0045] <Example of the first prompt starts here> The following is the speech data.

[0046] {Speech data} The attributes of the person who made the above statement are as follows:

[0047] {attribute} Identify the skills this person is presumed to possess and output the details of those skills.

[0048] <This is an example of the first prompt.> Other aspects may be the same as in the first embodiment.

[0049] According to the second embodiment, the generating AI 31 can be made to identify skills that also take into account the attributes of the target person. As a result, the likelihood of identifying skills related to the target person's attributes (such as occupation or role) can be increased.

[0050] Next, a third embodiment will be described. The differences between the third embodiment and the first embodiment will be described. Therefore, points not specifically mentioned may be the same as in the first embodiment.

[0051] Figure 6 shows an example of the functional configuration of the information processing system in the third embodiment. In Figure 6, the same reference numerals are used for parts that are the same as those in Figure 3, and their descriptions are omitted.

[0052] In Figure 6, the information processing device 10 further includes a receiving unit 17 and an output unit 18. Each of these units is realized by processing that one or more programs installed in the information processing device 10 cause the CPU 101 to execute.

[0053] The reception unit 17 accepts search conditions written in natural language.

[0054] The output unit 18 outputs a list of employees that match the search criteria. Hereinafter, the process of searching for employees that match the search criteria will be referred to as the "personnel search process".

[0055] Figure 7 is a flowchart illustrating an example of the processing procedure for the personnel search process in the third embodiment.

[0056] In step S301, the reception unit 17 receives the search conditions entered in the terminal 40 from the terminal 40. The reception unit 17 requests the generation unit 12 to generate a second prompt for the generation AI 31 to execute a search based on the search conditions.

[0057] On terminal 40, for example, search conditions written in natural language may be entered via a search condition input screen 510 as shown in Figure 8. Figure 8 shows an example where the search condition "Who has high communication skills?" is entered.

[0058] Next, the generation unit 12 executes a process to generate a second prompt in response to a request from the reception unit 17. First, the generation unit 12 obtains skill information for each employee from the personnel master storage unit 21 (Figure 5) (S302). Next, the generation unit 12 generates a second prompt, based on the search conditions received by the reception unit 17 and the skill information of multiple employees, which instructs the system to search for individuals (employees) associated with skills that match the search conditions (S303). For example, the content of the second prompt may be as follows.

[0059] <Example of the second prompt starts here> Currently, each employee possesses the following skills:

[0060] {Employee-specific skill information} Based on the above, please extract and output the employees who possess the skills that match the following search criteria.

[0061] {search criteria} <This is an example of the second prompt.> In the above, {Employee-Specific Skill Information} is text that shows the skill information (Employee ID, Skill ID, Skill Name) obtained in step S302 for each employee. {Search Criteria} is text that shows the search criteria.

[0062] Next, the transmission unit 13 sends the second prompt generated by the generation unit 12 to the generation AI 31 (S304). When the generation AI 31 receives the second prompt, it outputs text corresponding to the second prompt based on the learned parameters and sends the second response containing the text to the information processing device 10.

[0063] Next, the receiving unit 14 receives the second response (S305).

[0064] Next, the output unit 18 outputs (sends) the search results included in the second response (i.e., a list of employee IDs that match the search criteria) to the terminal 40 that sent the search criteria (S306). For example, the output unit 18 may display a search results screen 520 on the terminal 40, as shown in Figure 9.

[0065] As described above, according to the third embodiment, the user can identify personnel with specific skills by inputting them in natural language. As a result, for example, when allocating personnel (assigning employees to each sales office) or transferring personnel, it is possible to distribute employees with specific skills to each sales office.

[0066] Furthermore, the third embodiment may be combined with the second embodiment.

[0067] Next, a fourth embodiment will be described. The differences between the fourth embodiment and the first embodiment will be described. Therefore, points not specifically mentioned may be the same as in the first embodiment.

[0068] Figure 10 shows an example of the configuration of the information processing system in the fourth embodiment. In Figure 10, the same reference numerals are used for parts that are the same as or corresponding to parts in Figure 1, and their descriptions are omitted.

[0069] As shown in Figure 10, the information processing system in the fourth embodiment does not necessarily have an AI server 30.

[0070] Figure 11 shows an example of the functional configuration of the information processing system in the fourth embodiment. In Figure 11, the same reference numerals are used for parts that are the same as those in Figure 3, and their descriptions are omitted as appropriate.

[0071] In Figure 11, the information processing device 10 further includes a generating AI 31. That is, in the fourth embodiment, the generating AI 31 is located inside the information processing device 10, not outside of it. Therefore, in the fourth embodiment, an external AI server 30 does not need to exist.

[0072] The processing procedure performed in the fourth embodiment may be the same as in the first embodiment.

[0073] The fourth embodiment may be combined with one or more of the second and third embodiments.

[0074] Next, a fifth embodiment will be described. The differences between the fifth embodiment and the first embodiment will be described. Therefore, points not specifically mentioned may be the same as in the first embodiment.

[0075] In the fifth embodiment, an example in which the generating AI 31 is a multimodal AI will be described. For example, in each of the embodiments described above, an example in which the speech data is text data was described, but voice data may be used directly as speech data and input to the generating AI 31. Alternatively, instead of voice data, video data (including audio) of the subject speaking may be used as speech data and input to the generating AI 31. Furthermore, the speech data from the subject does not necessarily have to be data based on the voice spoken by the subject. For example, presentation materials (projected materials) used by the subject in explanations at meetings, the name of the meeting, the date and time of the meeting, the subject's work chat history, invitation information, etc., may be input to the generating AI 31. By inputting multimodal information into the generating AI 31, it is possible to expect an improvement in the accuracy of skill identification.

[0076] Furthermore, when inputting audio or video data to the generating AI 31, the prompt to the generating AI 31 may also include instructions for outputting numerical values ​​indicating the degree of certainty (likelihood) for each skill included in the output text, depending on the speaker's manner of speaking (volume, speed, etc.). Specifically, skills extracted from the speech data corresponding to a speaking style that suggests confidence in the content of the utterance may be assigned a relatively high degree of certainty, while skills extracted from other parts may be assigned a relatively low degree of certainty. In this case, the personnel master memory unit 21 (Figure 5) may register the degree of certainty for each skill determined to be possessed by that employee. The user may specify a threshold for the degree of certainty to identify employees who possess a particular skill.

[0077] Furthermore, the technology of this embodiment can be applied to various fields as long as skills can be estimated from conversation. In other words, the technology of this embodiment can be applied to any field as long as the subject's skills can be identified based on the content of their speech when they communicate something to others.

[0078] For example, if organization X is a company that sells products such as cosmetics, the skills of each salesperson may be identified. Alternatively, the skills of a business designer (presentation skills, facilitation skills, planning ability, proficiency with AI, etc.) may be identified based on the content of the business designer's utterances. Similarly, the skills of a teacher (whether they can recite the open lesson scenario, whether they can teach the teaching materials and units, etc.) may be identified based on the content of the teacher's utterances during a lesson. Furthermore, the skills of a construction site supervisor may be identified based on the content of their utterances at the construction site. In fields where the skills required may change depending on the site, such as for a site supervisor, the site identification information may be included in the first prompt. In this case, it can be expected that the skills corresponding to the site in which the subject (site supervisor) made their utterances will be identified by the generating AI 31.

[0079] In any field, the skills identified for each target group may be used in their respective training programs. For example, a certification system based on the skills possessed may be established.

[0080] Furthermore, skills are not limited to those required for specific tasks, but may also be defined in terms of personality, character, and general job performance abilities (such as time management skills). Time management skills may be estimated from the length of the audio data.

[0081] Furthermore, speech data, which records the content of utterances, may be used for purposes other than skill identification. For example, it may be used as evidence that a certain matter was spoken.

[0082] Furthermore, the information processing device 10 is not limited to a general-purpose server computer, as long as it is a device equipped with information processing functions. The information processing device 10 may be, for example, an output device such as a PJ (Projector), IWB (Interactive White Board: an electronic whiteboard with the ability to communicate with each other), or digital signage, a HUD (Head Up Display) device, industrial machinery, imaging devices, sound collection devices, medical equipment, networked home appliances, a notebook PC (Personal Computer), a mobile phone, a smartphone, a tablet device, a game console, a PDA (Personal Digital Assistant), a digital camera, a wearable PC, or a desktop PC.

[0083] Furthermore, each function of each embodiment can be realized by one or more processing circuits. Hereinafter, "processing circuit" as used herein includes processors programmed to execute each function by software, such as processors implemented by electronic circuits, as well as devices such as ASICs (Application Specific Integrated Circuits), DSPs (digital signal processors), FPGAs (field programmable gate arrays), and conventional circuit modules designed to execute the functions described above.

[0084] Furthermore, the apparatus of each embodiment represents only one of several computing environments for carrying out the embodiments disclosed herein.

[0085] In one embodiment, the information processing device 10 includes a plurality of computing devices, such as a server cluster. The plurality of computing devices are configured to communicate with each other via any type of communication link, including a network or shared memory, and perform the processing disclosed herein. Similarly, the personnel server 20 may include a plurality of computing devices configured to communicate with each other.

[0086] Although embodiments of the present invention have been described in detail above, the present invention is not limited to these specific embodiments, and various modifications and changes are possible within the scope of the gist of the present invention as described in the claims.

[0087] Examples of the present invention are as follows:

[0088] <1> An acquisition unit that acquires speech data including the content of the speech of the person whose skill is to be identified, A generation unit generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data. A transmission unit that transmits the aforementioned speech data and the first instruction information to a generating AI, A receiving unit that receives a first response from the generating AI that transmitted the first instruction information, An identification unit identifies a skill to be registered as the subject's skill based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration unit that associates the identified subject with the identified skill and registers it in the memory unit, An information processing system characterized by having the following features. <2> The generation unit generates the first instruction information which includes information about the attributes of the subject and instructs the identification of the skills of the subject having the attributes. Characterized by <1> The information processing system described above. <3> It has a reception section that accepts search conditions written in natural language, The generation unit further generates a second prompt that instructs the search to search for individuals associated with skills that match the search conditions, based on the search conditions and the skills of a plurality of individuals stored in the storage unit. The transmitting unit further transmits the second prompt to the generating AI, The receiving unit further receives a second response from the generating AI that has input the second prompt, The device has an output unit that outputs the search results indicated by the second response, Characterized by <1> or <2> The information processing system described above. <4> The registration unit registers in the storage unit skill identification information that identifies the identified skill and subject identification information that identifies the subject, in association with each other. Characterized by <1> ~ <3> The information processing system described in any of the following. <5> The generation unit generates a first prompt which includes the first instruction information, which is information that instructs the identification of a skill related to the speech content contained in the speech data, and the speech data. The transmitting unit transmits the first instruction information and the speech data to the generating AI by transmitting the generated first prompt to the generating AI. Characterized by <1> ~ <4> The information processing system described in any of the following. <6> An acquisition unit that acquires speech data including the content of the speech of the person whose skill is to be identified, A generation unit generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data. A transmission unit that transmits the aforementioned speech data and the first instruction information to a generating AI, A receiving unit that receives a first response from the generating AI that transmitted the first instruction information, An identification unit identifies a skill to be registered as the subject's skill based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration unit that associates the identified subject with the identified skill and registers it in the memory unit, An information processing device characterized by having the following features. <7> A procedure for acquiring speech data that includes the content of the speech of the person whose skills are to be identified, A generation procedure that generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data, A transmission procedure for sending the aforementioned speech data and the first instruction information to the generating AI, A receiving procedure for receiving a first response from the generating AI that transmitted the first instruction information, An identification procedure to identify skills to be registered as the subject's skills, based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration procedure for associating the identified subject with the identified skills and registering them in the memory unit, An information processing method characterized by a computer executing the following. <8> A procedure for acquiring speech data that includes the content of the speech of the person whose skills are to be identified, A generation procedure that generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data, A transmission procedure for sending the aforementioned speech data and the first instruction information to the generating AI, A receiving procedure for receiving a first response from the generating AI that transmitted the first instruction information, An identification procedure to identify skills to be registered as the subject's skills, based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration procedure for associating the identified subject with the identified skills and registering them in the memory unit, A program that causes a computer to execute something. [Explanation of Symbols]

[0089] 10 Information Processing Devices 11 Acquisition Department 12 Generation part 13 Transmitter 14 Receiving Unit 15 Identification unit 16 Registration Department 17 Reception Department 18 Output section 20 HR Server 21. Human Resources Master Memory Unit 30 AI Servers 31 Generation AI 40 devices [Prior art documents] [Patent Documents]

[0090] [Patent Document 1] International Publication No. 2005 / 010789

Claims

1. An acquisition unit that acquires speech data including the content of the speech of the person whose skill is to be identified, A generation unit generates first instruction information that instructs the identification of skills related to the utterance content included in the utterance data, based on the utterance data. A transmission unit that transmits the aforementioned speech data and the first instruction information to the generating AI, A receiving unit that receives a first response from the generating AI that transmitted the first instruction information, An identification unit identifies a skill to be registered as the subject's skill based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration unit that associates the identified subject with the identified skill and registers it in the memory unit, An information processing system characterized by having the following features.

2. The generation unit generates the first instruction information which includes information about the attributes of the subject and instructs the identification of the skills of the subject having the attributes. The information processing system according to feature 1.

3. It has a reception section that accepts search conditions written in natural language, The generation unit further generates a second prompt that instructs the search to search for individuals associated with skills that match the search conditions, based on the search conditions and the skills of a plurality of individuals stored in the storage unit. The transmitting unit further transmits the second prompt to the generating AI. The receiving unit further receives a second response from the generating AI that has input the second prompt, The device has an output unit that outputs the search result indicated by the second response, The information processing system according to claim 1 or 2, characterized in that it is the same as described in claim 1 or 2.

4. The registration unit registers in the storage unit skill identification information that identifies the identified skill and subject identification information that identifies the subject, in association with each other. The information processing system according to feature 1.

5. The generation unit generates a first prompt which includes the first instruction information, which is information that instructs the identification of a skill related to the speech content included in the speech data, and the speech data. The transmitting unit transmits the first instruction information and the speech data to the generating AI by transmitting the generated first prompt to the generating AI. The information processing system according to feature 1.

6. An acquisition unit that acquires speech data including the content of the speech of the person whose skill is to be identified, A generation unit generates first instruction information that instructs the identification of skills related to the utterance content included in the utterance data, based on the utterance data. A transmission unit that transmits the aforementioned speech data and the first instruction information to the generating AI, A receiving unit that receives a first response from the generating AI that transmitted the first instruction information, An identification unit identifies a skill to be registered as the subject's skill based on information relating to the utterance content, which is included in the first response and identified by the generating AI; A registration unit that associates the identified subject with the identified skill and registers it in the memory unit, An information processing device characterized by having the following features.

7. A procedure for acquiring speech data that includes the content of the speech of the person whose skills are to be identified, A generation procedure that generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data, A transmission procedure for transmitting the aforementioned speech data and the first instruction information to the generating AI, A receiving procedure for receiving a first response from the generating AI that transmitted the first instruction information, An identification procedure for identifying skills to be registered as the subject's skills, based on information relating to the utterance content identified by the generating AI in the first response, A registration procedure for associating the identified subject with the identified skills and registering them in the memory unit, An information processing method characterized by a computer executing the following.

8. A procedure for acquiring speech data that includes the content of the speech of the person whose skills are to be identified, A generation procedure that generates first instruction information that instructs the identification of skills related to the utterance content contained in the utterance data, based on the utterance data, A transmission procedure for transmitting the aforementioned speech data and the first instruction information to the generating AI, A receiving procedure for receiving a first response from the generating AI that transmitted the first instruction information, An identification procedure for identifying skills to be registered as the subject's skills, based on information relating to the utterance content identified by the generating AI in the first response, A registration procedure for associating the identified subject with the identified skills and registering them in the memory unit, A program that causes a computer to execute something.

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