System

Abstract

To provide a system for protecting craftsmanship and skills and sharing them by converting them into language or multimedia.SOLUTION: A system includes a recording unit, a protection unit and a generation unit. The recording unit records techniques or skills. The protection unit protects information recorded by the recording unit by blockchain technology. The generation unit converts the information protected by the protection unit into language or multimedia with generative AI.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional technology does not adequately protect the techniques and skills of artisans and share that knowledge, so there is room for improvement.

[0005] The system according to the embodiment aims to protect the techniques and skills of artisans and share them through verbalization or multimedia. [Means for solving the problem]

[0006] The system according to the embodiment includes a recording unit, a protection unit, and a generation unit. The recording unit records technology or skills. The protection unit protects the information recorded by the recording unit using blockchain technology. The generation unit verbalizes or multimedializes the information protected by the protection unit using a generation AI. Effect of the Invention

[0007] The system according to the embodiment protects the techniques and skills of craftsmen and enables them to be shared through verbalization or multimedia. [Brief description 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. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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 PREFERRED EMBODIMENTS

[0009] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one 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 signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs and 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 code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "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, the RAM 30, and the 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 (e.g., 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., voice and / or text). Display 40A displays visible information such as text and images according to instructions from processor 46. Speaker 40B outputs voice according to 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 Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the 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. Also, the data processing device 12 may be a server device, or may be a terminal device (e.g., a mobile phone, a robot, a home appliance, etc.) owned by a user. Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The craftsmanship transmission support system according to the embodiment of the present invention is a system that records the techniques and skills of craftsmen when selecting a guitar, protects them with blockchain technology, and verbalizes and multimedializes them using a generation AI. This system records in detail the techniques and skills of craftsmen when selecting a guitar, and protects them with blockchain technology. Furthermore, the recorded techniques and skills are verbalized and multimedialized using a generation AI. For example, the steps and points when a craftsman selects a guitar are expressed in text and video. The generation AI analyzes the words and actions of the craftsman and provides information in an easy-to-understand form. This mechanism makes it easier to transmit craftsmanship, and high-level skills can be conveyed to the next generation of craftsmen. In addition, building a knowledge database promotes learning and research of craftsmanship, contributing to the improvement of technology in the entire musical instrument industry. For example, when selecting a guitar, a video is shown of how a craftsman evaluates the vibration system, and the steps are explained in text. In addition, the selection criteria are also described in detail and provided in a form that is easy for the next generation of craftsmen to learn. This makes it possible to efficiently transmit craftsmanship and improve the quality of musical instruments. In this way, the craftsmanship transmission support system can protect the techniques and skills of craftsmen and pass them on to the next generation.

[0029] The craftsmanship tradition support system according to the embodiment includes a recording unit, a protection unit, and a generation unit. The recording unit records the techniques and skills of a craftsman when selecting a guitar. The recording unit records, for example, a video of the procedure when the craftsman selects a guitar. The video recording includes, for example, standards such as resolution, frame rate, and recording time. The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes, for example, public blockchain and private blockchain. The protection unit includes a mechanism for ensuring that the recorded information is not tampered with. For example, a technology such as a hash function or a digital signature is used. The generation unit uses a generation AI to verbalize or multimedialize the recorded techniques and skills. The generation AI uses, for example, a technology such as natural language generation, image generation, and video generation. The generation unit analyzes the words and actions of a craftsman and provides information in an easy-to-understand form. For example, the generation AI analyzes the words of the craftsman and expresses them in text or video. This makes it easier to pass on the craftsmanship, and high skills can be conveyed to the next generation of craftsmen. Furthermore, a knowledge database is constructed so that the next generation of craftsmen can use it for learning and research. The knowledge database includes, for example, detailed records of techniques and skills, selection criteria, evaluation methods, and the like. This will advance learning and research of craftsmanship, and contribute to technological improvement in the entire musical instrument industry. As a result, the craftsmanship transmission support system according to the embodiment can protect the techniques and skills of craftsmen and pass them on to the next generation.

[0030] The recording unit records in detail the techniques and skills of the craftsman when selecting a guitar. Specifically, the steps taken by the craftsman when selecting a guitar are recorded in high-resolution video. This video recording includes standards such as resolution, frame rate, and recording time, and can accurately capture the craftsman's detailed actions and selection criteria. For example, the craftsman's hand movements and ear usage when checking the material and tone of the guitar, as well as the judgment process based on the selection criteria, are recorded in detail. This allows the craftsman's techniques and skills to be visually captured, making it easier for the next generation of craftsmen to learn the techniques. In addition, the recording unit can also convey the theory and experience behind the techniques and skills by recording the craftsman's comments and explanations in audio and synchronizing them with the video. Furthermore, the recording unit can capture the craftsman's movements from multiple angles using multiple camera angles. This makes it possible to understand the craftsman's techniques in a more three-dimensional way. For example, by capturing not only the movements of the hands but also the overall posture and flow of the movements, the overall picture of the technique can be grasped. This allows the recording unit to record the craftsman's techniques and skills in detail and from multiple angles, and provide a foundation for conveying high techniques to the next generation of craftsmen.

[0031] The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes public blockchains and private blockchains, which ensure that the recorded information is not tampered with. Specifically, the integrity and reliability of the recorded information is ensured using technologies such as hash functions and digital signatures. For example, recorded video and audio data generates a unique hash value using a hash function, and this hash value is recorded in the blockchain. As a result, if the data is tampered with, the hash values ​​will not match, making it easier to detect the tampering. In addition, by using a digital signature, it is possible to confirm the creator of the data and whether it has been tampered with. Furthermore, the protection unit has an access control function and manages access rights to the recorded information. This allows only authorized users to access the information, preventing information leaks and unauthorized access. For example, when the next generation of craftsmen or researchers access the information, they are granted access rights through an authentication process. In addition, the protection unit regularly backs up the data to prepare for data loss or damage. This ensures that the recorded information is safely protected for a long period of time. This allows the conservation department to ensure the integrity and reliability of the recorded information and provide a robust foundation to support the transmission of craftsmanship.

[0032] The generation unit uses the generation AI to verbalize and multimediate the recorded techniques and skills. The generation AI uses technologies such as natural language generation, image generation, and video generation to provide information on the craftsman's techniques and skills in an easy-to-understand form. Specifically, the generation AI analyzes the words and actions of the craftsman and expresses them in text and video. For example, the words used by the craftsman when explaining the criteria for selecting a guitar can be analyzed and generated as text including technical details. It is also possible to analyze the craftsman's movements and generate videos that emphasize the key points and points of attention of the movements. Furthermore, the generation unit can provide the craftsman's techniques and skills in multiple languages. The generation AI can be used to translate the recorded information into multiple languages, so that the techniques can be conveyed to international craftsmen and researchers. For example, techniques recorded in Japanese can be translated into English, French, etc., so that overseas craftsmen and researchers can learn them. The generation unit can also generate interactive learning content. For example, it can generate quizzes and simulations to learn the craftsman's techniques, so that the next generation of craftsmen can learn the techniques practically. This allows the Generation Unit to provide artisanal techniques and skills in a variety of forms, and provide an environment in which the next generation of artisans can learn efficiently and effectively. Furthermore, a knowledge database is constructed and made available for the next generation of artisans to use for learning and research. The knowledge database includes detailed records of techniques and skills, selection criteria, evaluation methods, etc., and will advance the learning and research of artisanal skills, contributing to technological improvement throughout the musical instrument industry. This allows the Generation Unit to support the transmission of artisanal skills and provide a powerful tool for conveying advanced skills to the next generation of artisans.

[0033] The recording unit can record the steps taken by the craftsman when selecting a guitar as a video. The video recording includes criteria such as resolution, frame rate, and recording time. For example, the recording unit can record the steps taken by the craftsman when selecting a guitar using a high-resolution camera and record them as a detailed video. The recording unit can also record the steps taken by the craftsman from multiple camera angles to record them in more detail. Furthermore, the recording unit can record the steps taken by the craftsman in real time, edit them later, and save them as a detailed video. This allows the craftsman's techniques and skills to be recorded in detail. Some or all of the above-mentioned processing in the recording unit can be performed using, for example, AI, or can be performed without using AI. For example, the recording unit can record the steps taken by the craftsman in real time, automatically edit them using AI, and save them as a detailed video.

[0034] The protection unit can include a mechanism for ensuring that the recorded information is not tampered with. The protection unit prevents tampering of the recorded information using, for example, a hash function. The hash function is used to generate a one-way hash value for input data and verify the integrity of the data. The protection unit can also ensure the reliability of the recorded information using a digital signature. The digital signature uses a public key cryptosystem to authenticate the sender of the data and prevent tampering of the data. Furthermore, the protection unit can also prevent tampering of the recorded information using blockchain technology. The blockchain technology uses a distributed database to prevent tampering of data and ensure reliability. This makes it possible to ensure the reliability of the recorded information. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can automate the generation of hash values ​​and the creation of digital signatures using AI to prevent tampering of the recorded information.

[0035] The generation unit can use the generation AI to analyze the craftsman's techniques and skills and provide information in a clear form. The generation unit can, for example, use the generation AI to analyze the craftsman's techniques and skills and provide information in text format. The generation AI can analyze the craftsman's words using natural language processing technology and output them as easy-to-understand sentences. The generation unit can also use the generation AI to provide information on the craftsman's techniques and skills in video format. The generation AI can analyze the craftsman's movements using image recognition technology and output them as easy-to-understand videos. The generation unit can also use the generation AI to provide information on the craftsman's techniques and skills in graphical format. The generation AI uses data visualization technology to visually represent the craftsman's techniques and skills as graphs and charts. This makes it possible to convey the craftsman's techniques and skills in an easy-to-understand manner. Some or all of the above-mentioned processing in the generation unit can be performed, for example, using AI, or can be performed without using AI. For example, the generation unit can analyze the craftsman's techniques and skills and automatically provide information in text, video, or graphical format using AI.

[0036] The generation unit can analyze the words or actions of the craftsman using the generation AI and express them in text or video. The generation unit can, for example, use the generation AI to analyze the words of the craftsman and express them in text. The generation AI can analyze the words of the craftsman using natural language processing technology and output them as easy-to-understand text. The generation unit can also analyze the actions of the craftsman using the generation AI and express them in video. The generation AI can analyze the actions of the craftsman using image recognition technology and output them as easy-to-understand video. The generation unit can also analyze the words and actions of the craftsman using the generation AI and express them in both text and video. The generation AI outputs the words of the craftsman as text and simultaneously outputs the actions of the craftsman as video. This makes it possible to express the techniques and skills of the craftsman in a variety of formats. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can analyze the words and actions of the craftsman and automatically express them in text or video using AI.

[0037] A knowledge database can be constructed so that the next generation of craftsmen can use it for learning and research. The knowledge database includes, for example, detailed records of techniques and skills, selection criteria, evaluation methods, and the like. The knowledge database is constructed so that the next generation of craftsmen can use it for learning and research. For example, the knowledge database provides the steps and points that craftsmen use when selecting a guitar in the form of videos and text. The knowledge database also provides detailed descriptions of selection criteria and evaluation methods in a form that is easy for the next generation of craftsmen to learn. Furthermore, the knowledge database is regularly updated so that learning and research of craftsmanship progresses. For example, every time a new technique or skill is recorded, it is added to the knowledge database. This allows the knowledge database to always provide the latest information, promoting the transmission of craftsmanship and the improvement of skills. Part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can automatically record and update the techniques and skills of craftsmen using AI.

[0038] The recording unit can analyze the past selection history of the craftsman and select the optimal recording method. For example, the recording unit can analyze the recording methods (video, audio, text, etc.) used by the craftsman in the past and propose the optimal method. The recording unit identifies parts that require detailed recording based on the past selection history and records them in a focused manner. For example, the recording unit analyzes the contents recorded by the craftsman in the past and records specific procedures and points with emphasis. The recording unit can also record specific procedures and points with emphasis from the craftsman's past selection history. This makes it possible to select the optimal recording method based on the past history. Some or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit can input the craftsman's past selection history into AI and cause AI to select the optimal recording method.

[0039] The recording unit can customize the recorded contents based on the type and model of the guitar when recording. The recording unit adjusts the recorded contents according to, for example, the type of guitar (acoustic, electric, etc.). The recording unit records a specific evaluation point based on the model of the guitar (manufacturer, series, etc.). For example, the recording unit customizes the recording procedure and method according to the material and structure of the guitar. The recording unit can also customize the recorded contents based on the type and model of the guitar. This makes it possible to record according to the type and model of the guitar. A part or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit can input information on the type and model of the guitar to AI and cause the AI ​​to customize the recorded contents.

[0040] The recording unit can preferentially record highly relevant information in consideration of the geographical location information of the craftsman when recording. For example, when the craftsman is active in a specific area, the recording unit preferentially records information related to the area. The recording unit preferentially records highly relevant information based on the geographical location information. For example, when the craftsman records while moving, the recording unit preferentially records information related to the current location. In addition, when the craftsman is active in a specific store or workshop, the recording unit can also preferentially record information related to the location. This makes it possible to record highly relevant information based on the geographical location information. Part or all of the above-mentioned processing in the recording unit may be performed, for example, using AI or may be performed without using AI. For example, the recording unit can input the geographical location information of the craftsman to AI and cause AI to execute recording of highly relevant information.

[0041] The recording unit can analyze the social media activity of the craftsman at the time of recording and record related information. The recording unit performs related recording based on, for example, information shared by the craftsman on social media. The recording unit records related information based on social media activity. For example, the recording unit records information related to a specific topic or theme from the social media activity of the craftsman. The recording unit can also adjust the recorded content with reference to feedback received by the craftsman on social media. This makes it possible to record related information based on social media activity. Some or all of the above-mentioned processing in the recording unit may be performed using, for example, AI, or may be performed without using AI. For example, the recording unit can input the social media activity of the craftsman into AI and cause AI to execute recording of related information.

[0042] The protection unit can select an optimal protection method by referring to the past tampering history at the time of protection. For example, the protection unit analyzes information that has been tampered with in the past and selects a protection method for preventing similar tampering. The protection unit adjusts the strength of protection for specific information based on the tampering history. For example, the protection unit analyzes the past tampering history and increases the strength of protection for specific information. The protection unit can also periodically review and optimize the protection method based on the tampering history. This makes it possible to select an optimal protection method based on the past tampering history. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the protection unit can input the past tampering history to the AI ​​and cause the AI ​​to select the optimal protection method.

[0043] The protection unit can adjust the level of detail of the protection based on the importance of the recorded information at the time of protection. The protection unit applies a detailed protection method to important information, for example. The protection unit adjusts the level of detail of the protection based on the importance of the recorded information. For example, the protection unit applies a strong protection method to highly confidential information. The protection unit can also apply a standard protection method to general information. Furthermore, the protection unit can adjust the level of detail of the protection according to the importance of the information. This makes it possible to adjust the level of detail of the protection according to the importance of the information. A part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can input the importance of the recorded information to AI and cause AI to adjust the level of detail of the protection.

[0044] The protection unit can protect information by taking into consideration the geographical distribution of the information during protection. For example, the protection unit preferentially protects information related to a specific region. The protection unit protects information based on the geographical distribution of the information. For example, the protection unit centrally protects geographically distributed information. The protection unit can also adjust the protection method according to geographical characteristics. This makes it possible to protect information based on the geographical distribution. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can input the geographical distribution of information to AI and cause AI to adjust the protection method.

[0045] The protection unit can improve the accuracy of protection by referring to related legal documents during protection. The protection unit, for example, refers to legal documents and adjusts the protection method based on the latest laws and regulations. The protection unit improves the accuracy of protection based on related legal documents. For example, the protection unit checks the protection requirements for specific information from the legal documents. The protection unit can also periodically review and optimize the protection method based on the legal documents. This makes it possible to improve the accuracy of protection based on the legal documents. Some or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can input related legal documents into the AI ​​and cause the AI ​​to adjust the protection method.

[0046] The generation unit can adjust the level of detail of the generation based on the importance of the technology or skill at the time of generation. For example, for important technology or skill, the generation unit selects a generation method including a detailed explanation. The generation unit adjusts the level of detail of the generation based on the importance of the technology or skill. For example, the generation unit selects a visually easy-to-understand generation method for a specific technology or skill. In addition, the generation unit can also select a standard generation method for general technology or skill. Furthermore, the generation unit can adjust the level of detail of the generation according to the importance of the technology or skill. This makes it possible to adjust the level of detail of the generation according to the importance of the technology or skill. A part or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can input the importance of the technology or skill to AI and cause the AI ​​to adjust the level of detail of the generation.

[0047] The generation unit can apply different generation algorithms depending on the category of the technique or skill at the time of generation. For example, the generation unit applies a specific algorithm to the technique of selecting a guitar. The generation unit applies different generation algorithms depending on the category of the technique or skill. For example, the generation unit applies a different algorithm to the evaluation method of the vibration system of a guitar. The generation unit can also apply yet another algorithm to the technique related to the material and structure of the guitar. This makes it possible to apply an optimal generation algorithm depending on the category. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the generation unit can input the category of the technique or skill to the AI ​​and cause the AI ​​to apply the generation algorithm.

[0048] The generation unit can determine the priority of generation based on the recording time of the technology or skill at the time of generation. The generation unit, for example, generates the most recently recorded technology or skill with priority. The generation unit determines the priority of generation based on the recording time of the technology or skill. For example, the generation unit generates important information with priority based on the technology or skill recorded in the past. The generation unit can also adjust the priority of generation according to the recording time. This makes it possible to adjust the priority of generation according to the recording time. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input the recording time of the technology or skill to AI and cause the AI ​​to execute the determination of the priority of generation.

[0049] The generation unit can adjust the order of generation based on the relevance of the technologies and skills at the time of generation. For example, the generation unit generates technologies and skills with high relevance preferentially. The generation unit adjusts the order of generation based on the relevance of the technologies and skills. For example, the generation unit generates technologies and skills with low relevance later. The generation unit can also adjust the order of generation according to the relevance of the technologies and skills. This makes it possible to adjust the order of generation according to the relevance of the technologies and skills. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input the relevance of the technologies and skills to AI and cause the AI ​​to adjust the order of generation.

[0050] When constructing a database, the knowledge database can select an optimal construction method by referring to past database construction history. For example, the knowledge database analyzes databases constructed in the past and selects an optimal construction method. The knowledge database is constructed by referring to a specific procedure or method based on the database construction history. For example, the knowledge database analyzes past database construction history and constructs the knowledge database by referring to a specific procedure or method. The knowledge database can also periodically review and optimize the construction method based on the database construction history. This makes it possible to select an optimal construction method based on the past database construction history. A part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input past database construction history into AI and have the AI ​​select an optimal construction method.

[0051] The knowledge database can adjust the level of detail of the database based on the importance of the technology or skill when constructing the database. For example, the knowledge database constructs a detailed database for important technology or skill. The knowledge database adjusts the level of detail of the database based on the importance of the technology or skill. For example, the knowledge database constructs a visually easy-to-understand database for specific technology or skill. In addition, the knowledge database can also construct a standard database for general technology or skill. Furthermore, the knowledge database can adjust the level of detail of the database according to the importance of the technology or skill. This makes it possible to adjust the level of detail of the database according to the importance of the technology or skill. Part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input the importance of the technology or skill into AI and cause AI to adjust the level of detail of the database.

[0052] The knowledge database can construct the database taking into consideration the geographical distribution of technologies and skills when constructing the database. For example, the knowledge database preferentially registers technologies and skills related to a specific region in the database. The knowledge database constructs the database based on the geographical distribution of technologies and skills. For example, the knowledge database centrally registers geographically distributed technologies and skills in the database. The knowledge database can also adjust the database construction method according to geographical characteristics. This makes it possible to construct the database based on the geographical distribution. Some or all of the above-mentioned processing in the knowledge database may be performed using, for example, AI, or may be performed without using AI. For example, the knowledge database can input the geographical distribution of technologies and skills into AI and have the AI ​​adjust the database construction method.

[0053] The knowledge database can improve the accuracy of the database by referring to related academic literature when constructing the database. The knowledge database, for example, refers to academic literature and constructs the database based on the latest research results. The knowledge database improves the accuracy of the database based on related academic literature. For example, the knowledge database registers information on specific technologies and skills from academic literature in the database. The knowledge database can also periodically review and optimize the database construction method based on academic literature. This makes it possible to improve the accuracy of the database based on academic literature. Some or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input related academic literature into AI and have the AI ​​improve the accuracy of the database.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The recording unit can measure the craftsman's hand movements and the amount of force used by the sensor and record them as detailed data. For example, the hand movements of the craftsman when selecting a guitar can be recorded using motion capture technology, and the trajectory and speed of the hand movements can be saved as data. It can also use a force sensor to measure the amount of force used by the craftsman when touching the guitar and record that data. Furthermore, the recording unit can analyze this data, extract characteristics of the craftsman's techniques and skills, and save them in a database. This allows the craftsman's subtle techniques and skills to be recorded in detail and passed on to the next generation of craftsmen.

[0056] The recording unit can record the environmental sounds during the craftsman's selection process and record the acoustic environment at the time of selection. For example, the recording unit can use a high-precision microphone to record the surrounding sounds and the sound of the guitar when the craftsman is selecting a guitar, and store the acoustic data. The recording unit can also analyze the recorded acoustic data and extract the characteristics of the sounds during the selection process. Furthermore, the recording unit can visualize the acoustic data and display the waveforms and spectra of the sounds. This allows the acoustic environment during the craftsman's selection process to be recorded in detail and passed on to the next generation of craftsmen.

[0057] The generation unit can use generative AI to reproduce the craftsman's techniques and skills as a 3D model and provide it visually. For example, the hand movements and postures of a craftsman when selecting a guitar can be recorded using 3D scanning technology, and a 3D model can be generated based on that data. The generation unit can also provide the generated 3D model in an interactive format, allowing users to freely change the viewpoint to observe it. Furthermore, the generation unit can add annotations to the 3D model to visually indicate key points of the techniques and skills. This makes it possible to convey the craftsman's techniques and skills in an easy-to-understand visual manner.

[0058] The knowledge database can provide learning content in the form of quizzes about the techniques and skills of craftsmen. For example, a quiz can be created about the steps and key points a craftsman should take when selecting a guitar, and the user can progress in their learning by answering the quiz. The knowledge database can also evaluate the user's level of understanding based on the results of the quiz and provide appropriate feedback. Furthermore, the knowledge database can regularly update the content of the quiz and add questions about new techniques and skills. This allows the user to enjoy learning about the techniques and skills of craftsmen.

[0059] The recording unit can evaluate the craftsman's performance in the selection task based on the craftsman's past selection history. For example, the recording unit can analyze the evaluation results of guitars selected by the craftsman in the past and evaluate the accuracy and efficiency of the selection task. The recording unit can also evaluate the degree of improvement in the craftsman's techniques and skills based on the past selection history. Furthermore, the recording unit can provide the craftsman with the evaluation results as feedback to support the improvement of techniques and skills. This makes it possible to objectively evaluate the craftsman's performance in the selection task and promote the improvement of techniques and skills.

[0060] The recording unit can measure the acoustic characteristics of the guitar when recording and reflect them in the recorded content. For example, it can measure the acoustic characteristics of the guitar (frequency characteristics, sound pressure level, etc.) and record the data. The recording unit can also analyze the acoustic characteristic data and evaluate the quality and characteristics of the guitar. Furthermore, the recording unit can visualize the acoustic characteristic data and display it as a graph or chart. This allows the acoustic characteristics of the guitar to be recorded in detail and used as a reference for the selection process.

[0061] The process flow of the first embodiment will be briefly described below.

[0062] Step 1: The recording unit records the techniques and skills used by the craftsman when selecting a guitar. For example, the steps taken by the craftsman when selecting a guitar are recorded on video. The video recording includes criteria such as resolution, frame rate, and recording time. Step 2: The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes public blockchains and private blockchains. The protection unit has a mechanism to ensure that the recorded information is not tampered with. For example, it uses technologies such as hash functions and digital signatures. Step 3: The generation unit uses a generative AI to verbalize and convert the recorded techniques and skills into multimedia. The generative AI uses technologies such as natural language generation, image generation, and video generation. The generation unit analyzes the words and actions of the craftsman and provides information in an easy-to-understand format. For example, the generative AI analyzes the words of the craftsman and expresses them in text or video. This makes it easier to pass on craftsmanship and allows advanced techniques to be passed on to the next generation of craftsmen.

[0063] (Example 2) The craftsmanship transmission support system according to the embodiment of the present invention is a system that records the techniques and skills of craftsmen when selecting a guitar, protects them with blockchain technology, and verbalizes and multimedializes them using a generation AI. This system records in detail the techniques and skills of craftsmen when selecting a guitar, and protects them with blockchain technology. Furthermore, the recorded techniques and skills are verbalized and multimedialized using a generation AI. For example, the steps and points when a craftsman selects a guitar are expressed in text and video. The generation AI analyzes the words and actions of the craftsman and provides information in an easy-to-understand form. This mechanism makes it easier to transmit craftsmanship, and high-level skills can be conveyed to the next generation of craftsmen. In addition, building a knowledge database promotes learning and research of craftsmanship, contributing to the improvement of technology in the entire musical instrument industry. For example, when selecting a guitar, a video is shown of how a craftsman evaluates the vibration system, and the steps are explained in text. In addition, the selection criteria are also described in detail and provided in a form that is easy for the next generation of craftsmen to learn. This makes it possible to efficiently transmit craftsmanship and improve the quality of musical instruments. In this way, the craftsmanship transmission support system can protect the techniques and skills of craftsmen and pass them on to the next generation.

[0064] The craftsmanship tradition support system according to the embodiment includes a recording unit, a protection unit, and a generation unit. The recording unit records the techniques and skills of a craftsman when selecting a guitar. The recording unit records, for example, a video of the procedure when the craftsman selects a guitar. The video recording includes, for example, standards such as resolution, frame rate, and recording time. The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes, for example, public blockchain and private blockchain. The protection unit includes a mechanism for ensuring that the recorded information is not tampered with. For example, a technology such as a hash function or a digital signature is used. The generation unit uses a generation AI to verbalize or multimedialize the recorded techniques and skills. The generation AI uses, for example, a technology such as natural language generation, image generation, and video generation. The generation unit analyzes the words and actions of a craftsman and provides information in an easy-to-understand form. For example, the generation AI analyzes the words of the craftsman and expresses them in text or video. This makes it easier to pass on the craftsmanship, and high skills can be conveyed to the next generation of craftsmen. Furthermore, a knowledge database is constructed so that the next generation of craftsmen can use it for learning and research. The knowledge database includes, for example, detailed records of techniques and skills, selection criteria, evaluation methods, and the like. This will advance learning and research of craftsmanship, and contribute to technological improvement in the entire musical instrument industry. As a result, the craftsmanship transmission support system according to the embodiment can protect the techniques and skills of craftsmen and pass them on to the next generation.

[0065] The recording unit records in detail the techniques and skills of the craftsman when selecting a guitar. Specifically, the steps taken by the craftsman when selecting a guitar are recorded in high-resolution video. This video recording includes standards such as resolution, frame rate, and recording time, and can accurately capture the craftsman's detailed actions and selection criteria. For example, the craftsman's hand movements and ear usage when checking the material and tone of the guitar, as well as the judgment process based on the selection criteria, are recorded in detail. This allows the craftsman's techniques and skills to be visually captured, making it easier for the next generation of craftsmen to learn the techniques. In addition, the recording unit can also convey the theory and experience behind the techniques and skills by recording the craftsman's comments and explanations in audio and synchronizing them with the video. Furthermore, the recording unit can capture the craftsman's movements from multiple angles using multiple camera angles. This makes it possible to understand the craftsman's techniques in a more three-dimensional way. For example, by capturing not only the movements of the hands but also the overall posture and flow of the movements, the overall picture of the technique can be grasped. This allows the recording unit to record the craftsman's techniques and skills in detail and from multiple angles, and provide a foundation for conveying high techniques to the next generation of craftsmen.

[0066] The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes public blockchains and private blockchains, which ensure that the recorded information is not tampered with. Specifically, the integrity and reliability of the recorded information is ensured using technologies such as hash functions and digital signatures. For example, recorded video and audio data generates a unique hash value using a hash function, and this hash value is recorded in the blockchain. As a result, if the data is tampered with, the hash values ​​will not match, making it easier to detect the tampering. In addition, by using a digital signature, it is possible to confirm the creator of the data and whether it has been tampered with. Furthermore, the protection unit has an access control function and manages access rights to the recorded information. This allows only authorized users to access the information, preventing information leaks and unauthorized access. For example, when the next generation of craftsmen or researchers access the information, they are granted access rights through an authentication process. In addition, the protection unit regularly backs up the data to prepare for data loss or damage. This ensures that the recorded information is safely protected for a long period of time. This allows the conservation department to ensure the integrity and reliability of the recorded information and provide a robust foundation to support the transmission of craftsmanship.

[0067] The generation unit uses the generation AI to verbalize and multimediate the recorded techniques and skills. The generation AI uses technologies such as natural language generation, image generation, and video generation to provide information on the craftsman's techniques and skills in an easy-to-understand form. Specifically, the generation AI analyzes the words and actions of the craftsman and expresses them in text and video. For example, the words used by the craftsman when explaining the criteria for selecting a guitar can be analyzed and generated as text including technical details. It is also possible to analyze the craftsman's movements and generate videos that emphasize the key points and points of attention of the movements. Furthermore, the generation unit can provide the craftsman's techniques and skills in multiple languages. The generation AI can be used to translate the recorded information into multiple languages, so that the techniques can be conveyed to international craftsmen and researchers. For example, techniques recorded in Japanese can be translated into English, French, etc., so that overseas craftsmen and researchers can learn them. The generation unit can also generate interactive learning content. For example, it can generate quizzes and simulations to learn the craftsman's techniques, so that the next generation of craftsmen can learn the techniques practically. This allows the Generation Unit to provide artisanal techniques and skills in a variety of forms, and provide an environment in which the next generation of artisans can learn efficiently and effectively. Furthermore, a knowledge database is constructed and made available for the next generation of artisans to use for learning and research. The knowledge database includes detailed records of techniques and skills, selection criteria, evaluation methods, etc., and will advance the learning and research of artisanal skills, contributing to technological improvement throughout the musical instrument industry. This allows the Generation Unit to support the transmission of artisanal skills and provide a powerful tool for conveying advanced skills to the next generation of artisans.

[0068] The recording unit can record the steps taken by the craftsman when selecting a guitar as a video. The video recording includes criteria such as resolution, frame rate, and recording time. For example, the recording unit can record the steps taken by the craftsman when selecting a guitar using a high-resolution camera and record them as a detailed video. The recording unit can also record the steps taken by the craftsman from multiple camera angles to record them in more detail. Furthermore, the recording unit can record the steps taken by the craftsman in real time, edit them later, and save them as a detailed video. This allows the craftsman's techniques and skills to be recorded in detail. Some or all of the above-mentioned processing in the recording unit can be performed using, for example, AI, or can be performed without using AI. For example, the recording unit can record the steps taken by the craftsman in real time, automatically edit them using AI, and save them as a detailed video.

[0069] The protection unit can include a mechanism for ensuring that the recorded information is not tampered with. The protection unit prevents tampering of the recorded information using, for example, a hash function. The hash function is used to generate a one-way hash value for input data and verify the integrity of the data. The protection unit can also ensure the reliability of the recorded information using a digital signature. The digital signature uses a public key cryptosystem to authenticate the sender of the data and prevent tampering of the data. Furthermore, the protection unit can also prevent tampering of the recorded information using blockchain technology. The blockchain technology uses a distributed database to prevent tampering of data and ensure reliability. This makes it possible to ensure the reliability of the recorded information. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can automate the generation of hash values ​​and the creation of digital signatures using AI to prevent tampering of the recorded information.

[0070] The generation unit can use the generation AI to analyze the craftsman's techniques and skills and provide information in a clear form. The generation unit can, for example, use the generation AI to analyze the craftsman's techniques and skills and provide information in text format. The generation AI can analyze the craftsman's words using natural language processing technology and output them as easy-to-understand sentences. The generation unit can also use the generation AI to provide information on the craftsman's techniques and skills in video format. The generation AI can analyze the craftsman's movements using image recognition technology and output them as easy-to-understand videos. The generation unit can also use the generation AI to provide information on the craftsman's techniques and skills in graphical format. The generation AI uses data visualization technology to visually represent the craftsman's techniques and skills as graphs and charts. This makes it possible to convey the craftsman's techniques and skills in an easy-to-understand manner. Some or all of the above-mentioned processing in the generation unit can be performed, for example, using AI, or can be performed without using AI. For example, the generation unit can analyze the craftsman's techniques and skills and automatically provide information in text, video, or graphical format using AI.

[0071] The generation unit can analyze the words or actions of the craftsman using the generation AI and express them in text or video. The generation unit can, for example, use the generation AI to analyze the words of the craftsman and express them in text. The generation AI can analyze the words of the craftsman using natural language processing technology and output them as easy-to-understand text. The generation unit can also analyze the actions of the craftsman using the generation AI and express them in video. The generation AI can analyze the actions of the craftsman using image recognition technology and output them as easy-to-understand video. The generation unit can also analyze the words and actions of the craftsman using the generation AI and express them in both text and video. The generation AI outputs the words of the craftsman as text and simultaneously outputs the actions of the craftsman as video. This makes it possible to express the techniques and skills of the craftsman in a variety of formats. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can analyze the words and actions of the craftsman and automatically express them in text or video using AI.

[0072] A knowledge database can be constructed so that the next generation of craftsmen can use it for learning and research. The knowledge database includes, for example, detailed records of techniques and skills, selection criteria, evaluation methods, and the like. The knowledge database is constructed so that the next generation of craftsmen can use it for learning and research. For example, the knowledge database provides the steps and points that craftsmen use when selecting a guitar in the form of videos and text. The knowledge database also provides detailed descriptions of selection criteria and evaluation methods in a form that is easy for the next generation of craftsmen to learn. Furthermore, the knowledge database is regularly updated so that learning and research of craftsmanship progresses. For example, every time a new technique or skill is recorded, it is added to the knowledge database. This allows the knowledge database to always provide the latest information, promoting the transmission of craftsmanship and the improvement of skills. Part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can automatically record and update the techniques and skills of craftsmen using AI.

[0073] The recording unit can estimate the emotion of the craftsman and adjust the timing of recording based on the estimated emotion of the craftsman. For example, the recording unit starts recording when the craftsman is concentrating and pauses when the concentration is broken. The recording unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the timing of recording. For example, the recording unit captures the facial expression of the craftsman with a camera and estimates the concentration level using an emotion estimation algorithm. The recording unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the recording unit analyzes the tone and speed of the voice to estimate the concentration level. Furthermore, the recording unit can collect the biometric data of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the recording unit estimates the concentration level based on the fluctuation of the heart rate. This makes it possible to record at the optimal timing according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit may input image data of a craftsman captured by a camera to the generation AI, and cause the generation AI to estimate the craftsman's emotions.

[0074] The recording unit can analyze the past selection history of the craftsman and select the optimal recording method. For example, the recording unit can analyze the recording methods (video, audio, text, etc.) used by the craftsman in the past and propose the optimal method. The recording unit identifies parts that require detailed recording based on the past selection history and records them in a focused manner. For example, the recording unit analyzes the contents recorded by the craftsman in the past and records specific procedures and points with emphasis. The recording unit can also record specific procedures and points with emphasis from the craftsman's past selection history. This makes it possible to select the optimal recording method based on the past history. Some or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit can input the craftsman's past selection history into AI and cause AI to select the optimal recording method.

[0075] The recording unit can customize the recorded contents based on the type and model of the guitar when recording. The recording unit adjusts the recorded contents according to, for example, the type of guitar (acoustic, electric, etc.). The recording unit records a specific evaluation point based on the model of the guitar (manufacturer, series, etc.). For example, the recording unit customizes the recording procedure and method according to the material and structure of the guitar. The recording unit can also customize the recorded contents based on the type and model of the guitar. This makes it possible to record according to the type and model of the guitar. A part or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit can input information on the type and model of the guitar to AI and cause the AI ​​to customize the recorded contents.

[0076] The recording unit can estimate the emotion of the craftsman and determine the priority of the procedures to be recorded based on the estimated emotion of the craftsman. For example, when the craftsman is relaxed, the recording unit preferentially records detailed procedures. The recording unit estimates the emotion of the craftsman using an emotion estimation algorithm and determines the priority of the procedures to be recorded. For example, the recording unit captures the facial expression of the craftsman with a camera and estimates the degree of relaxation using an emotion estimation algorithm. The recording unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the recording unit analyzes the tone and speed of the voice and estimates the degree of relaxation. Furthermore, the recording unit can collect the biodata of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the recording unit estimates the degree of relaxation based on the fluctuation of the heart rate. This makes it possible to adjust the priority of the recorded procedures according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the recording unit may be performed, for example, using AI, or may be performed without using AI. For example, the recording unit may input image data of a craftsman captured by a camera to the generation AI, and cause the generation AI to estimate the craftsman's emotions.

[0077] The recording unit can preferentially record highly relevant information in consideration of the geographical location information of the craftsman when recording. For example, when the craftsman is active in a specific area, the recording unit preferentially records information related to the area. The recording unit preferentially records highly relevant information based on the geographical location information. For example, when the craftsman records while moving, the recording unit preferentially records information related to the current location. In addition, when the craftsman is active in a specific store or workshop, the recording unit can also preferentially record information related to the location. This makes it possible to record highly relevant information based on the geographical location information. Part or all of the above-mentioned processing in the recording unit may be performed, for example, using AI or may be performed without using AI. For example, the recording unit can input the geographical location information of the craftsman to AI and cause AI to execute recording of highly relevant information.

[0078] The recording unit can analyze the social media activity of the craftsman at the time of recording and record related information. The recording unit performs related recording based on, for example, information shared by the craftsman on social media. The recording unit records related information based on social media activity. For example, the recording unit records information related to a specific topic or theme from the social media activity of the craftsman. The recording unit can also adjust the recorded content with reference to feedback received by the craftsman on social media. This makes it possible to record related information based on social media activity. Some or all of the above-mentioned processing in the recording unit may be performed using, for example, AI, or may be performed without using AI. For example, the recording unit can input the social media activity of the craftsman into AI and cause AI to execute recording of related information.

[0079] The protection unit can estimate the emotion of the craftsman and adjust the strength of protection based on the estimated emotion of the craftsman. For example, if the craftsman feels anxious, the protection unit increases the strength of protection. The protection unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the strength of protection. For example, the protection unit captures the facial expression of the craftsman with a camera and estimates the anxiety level using an emotion estimation algorithm. The protection unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the protection unit analyzes the tone and speed of the voice to estimate the anxiety level. Furthermore, the protection unit can collect the biometric data of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the protection unit estimates the anxiety level based on the fluctuation of the heart rate. This makes it possible to adjust the strength of protection according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is a text generation AI (for example, LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the protection unit may be performed using AI, or may be performed without using AI. For example, the protection unit may input image data of a craftsman taken by a camera to the generation AI and cause the generation AI to estimate the emotions of the craftsman.

[0080] The protection unit can select an optimal protection method by referring to the past tampering history at the time of protection. For example, the protection unit analyzes information that has been tampered with in the past and selects a protection method for preventing similar tampering. The protection unit adjusts the strength of protection for specific information based on the tampering history. For example, the protection unit analyzes the past tampering history and increases the strength of protection for specific information. The protection unit can also periodically review and optimize the protection method based on the tampering history. This makes it possible to select an optimal protection method based on the past tampering history. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the protection unit can input the past tampering history to the AI ​​and cause the AI ​​to select the optimal protection method.

[0081] The protection unit can adjust the level of detail of the protection based on the importance of the recorded information at the time of protection. The protection unit applies a detailed protection method to important information, for example. The protection unit adjusts the level of detail of the protection based on the importance of the recorded information. For example, the protection unit applies a strong protection method to highly confidential information. The protection unit can also apply a standard protection method to general information. Furthermore, the protection unit can adjust the level of detail of the protection according to the importance of the information. This makes it possible to adjust the level of detail of the protection according to the importance of the information. A part or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit can input the importance of the recorded information to AI and cause AI to adjust the level of detail of the protection.

[0082] The protection unit can estimate the emotion of the craftsman and determine the priority of the information to be protected based on the estimated emotion of the craftsman. For example, when the craftsman feels anxious, the protection unit prioritizes the protection of important information. The protection unit estimates the emotion of the craftsman using an emotion estimation algorithm and determines the priority of the information to be protected. For example, the protection unit captures the facial expression of the craftsman with a camera and estimates the anxiety level using an emotion estimation algorithm. The protection unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the protection unit analyzes the tone and speed of the voice to estimate the anxiety level. Furthermore, the protection unit can collect the biometric data of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the protection unit estimates the anxiety level based on the fluctuation of the heart rate. This makes it possible to adjust the protection priority of information according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the protection unit may be performed, for example, using AI, or may be performed without using AI. For example, the protection unit may input image data of a craftsman captured by a camera to the generation AI, and cause the generation AI to estimate the craftsman's emotions.

[0083] The protection unit can protect information by taking into consideration the geographical distribution of the information during protection. For example, the protection unit preferentially protects information related to a specific region. The protection unit protects information based on the geographical distribution of the information. For example, the protection unit centrally protects geographically distributed information. The protection unit can also adjust the protection method according to geographical characteristics. This makes it possible to protect information based on the geographical distribution. A part or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can input the geographical distribution of information to AI and cause AI to adjust the protection method.

[0084] The protection unit can improve the accuracy of protection by referring to related legal documents during protection. The protection unit, for example, refers to legal documents and adjusts the protection method based on the latest laws and regulations. The protection unit improves the accuracy of protection based on related legal documents. For example, the protection unit checks the protection requirements for specific information from the legal documents. The protection unit can also periodically review and optimize the protection method based on the legal documents. This makes it possible to improve the accuracy of protection based on the legal documents. Some or all of the above-mentioned processing in the protection unit may be performed using, for example, AI, or may be performed without using AI. For example, the protection unit can input related legal documents into the AI ​​and cause the AI ​​to adjust the protection method.

[0085] The generation unit can estimate the emotion of the craftsman and adjust the expression method of the information to be generated based on the estimated emotion of the craftsman. For example, when the craftsman is relaxed, the generation AI selects an expression method including a detailed description. The generation unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the expression method of the information to be generated. For example, the generation unit takes a picture of the expression of the craftsman with a camera and estimates the degree of relaxation using an emotion estimation algorithm. The generation unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the generation unit analyzes the tone and speed of the voice and estimates the degree of relaxation. Furthermore, the generation unit can collect the biodata of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the generation unit estimates the degree of relaxation based on the fluctuation of the heart rate. This makes it possible to adjust the expression method of the information according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit may input image data of a craftsman captured by a camera to the generation AI, and cause the generation AI to estimate the craftsman's emotions.

[0086] The generation unit can adjust the level of detail of the generation based on the importance of the technology or skill at the time of generation. For example, for important technology or skill, the generation unit selects a generation method including a detailed explanation. The generation unit adjusts the level of detail of the generation based on the importance of the technology or skill. For example, the generation unit selects a visually easy-to-understand generation method for a specific technology or skill. In addition, the generation unit can also select a standard generation method for general technology or skill. Furthermore, the generation unit can adjust the level of detail of the generation according to the importance of the technology or skill. This makes it possible to adjust the level of detail of the generation according to the importance of the technology or skill. A part or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit can input the importance of the technology or skill to AI and cause the AI ​​to adjust the level of detail of the generation.

[0087] The generation unit can apply different generation algorithms depending on the category of the technique or skill at the time of generation. For example, the generation unit applies a specific algorithm to the technique of selecting a guitar. The generation unit applies different generation algorithms depending on the category of the technique or skill. For example, the generation unit applies a different algorithm to the evaluation method of the vibration system of a guitar. The generation unit can also apply yet another algorithm to the technique related to the material and structure of the guitar. This makes it possible to apply an optimal generation algorithm depending on the category. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the generation unit can input the category of the technique or skill to the AI ​​and cause the AI ​​to apply the generation algorithm.

[0088] The generation unit can estimate the emotion of the craftsman and adjust the length of the information to be generated based on the estimated emotion of the craftsman. For example, when the craftsman is relaxed, the generation AI generates longer information including a detailed description. The generation unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the length of the information to be generated. For example, the generation unit takes a picture of the facial expression of the craftsman with a camera and estimates the degree of relaxation using an emotion estimation algorithm. The generation unit can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the generation unit analyzes the tone and speed of the voice and estimates the degree of relaxation. Furthermore, the generation unit can collect the biodata of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the generation unit estimates the degree of relaxation based on the fluctuation of the heart rate. This makes it possible to adjust the length of the information according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the generation unit may be performed, for example, using AI, or may be performed without using AI. For example, the generation unit may input image data of a craftsman captured by a camera to the generation AI, and cause the generation AI to estimate the craftsman's emotions.

[0089] The generation unit can determine the priority of generation based on the recording time of the technology or skill at the time of generation. The generation unit, for example, generates the most recently recorded technology or skill with priority. The generation unit determines the priority of generation based on the recording time of the technology or skill. For example, the generation unit generates important information with priority based on the technology or skill recorded in the past. The generation unit can also adjust the priority of generation according to the recording time. This makes it possible to adjust the priority of generation according to the recording time. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input the recording time of the technology or skill to AI and cause the AI ​​to execute the determination of the priority of generation.

[0090] The generation unit can adjust the order of generation based on the relevance of the technologies and skills at the time of generation. For example, the generation unit generates technologies and skills with high relevance preferentially. The generation unit adjusts the order of generation based on the relevance of the technologies and skills. For example, the generation unit generates technologies and skills with low relevance later. The generation unit can also adjust the order of generation according to the relevance of the technologies and skills. This makes it possible to adjust the order of generation according to the relevance of the technologies and skills. A part or all of the above-mentioned processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can input the relevance of the technologies and skills to AI and cause the AI ​​to adjust the order of generation.

[0091] The knowledge database can estimate the emotion of the craftsman and adjust the construction method of the database based on the estimated emotion of the craftsman. For example, when the craftsman is relaxed, the knowledge database constructs a detailed database. The knowledge database estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the construction method of the database. For example, the knowledge database captures the facial expression of the craftsman with a camera and estimates the degree of relaxation using an emotion estimation algorithm. The knowledge database can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the knowledge database analyzes the tone and speed of the voice and estimates the degree of relaxation. Furthermore, the knowledge database can collect the biometric data of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the knowledge database estimates the degree of relaxation based on the fluctuation of the heart rate. This makes it possible to adjust the construction method of the database according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, but is not limited to, a text generation AI (for example, LLM) or a multimodal generation AI. Some or all of the above-mentioned processes in the knowledge database may be performed using AI, or may be performed without using AI. For example, the knowledge database may input image data of a craftsman taken by a camera to the generation AI, and have the generation AI estimate the emotions of the craftsman.

[0092] When constructing a database, the knowledge database can select an optimal construction method by referring to past database construction history. For example, the knowledge database analyzes databases constructed in the past and selects an optimal construction method. The knowledge database is constructed by referring to a specific procedure or method based on the database construction history. For example, the knowledge database analyzes past database construction history and constructs the knowledge database by referring to a specific procedure or method. The knowledge database can also periodically review and optimize the construction method based on the database construction history. This makes it possible to select an optimal construction method based on the past database construction history. A part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input past database construction history into AI and have the AI ​​select an optimal construction method.

[0093] The knowledge database can adjust the level of detail of the database based on the importance of the technology or skill when constructing the database. For example, the knowledge database constructs a detailed database for important technology or skill. The knowledge database adjusts the level of detail of the database based on the importance of the technology or skill. For example, the knowledge database constructs a visually easy-to-understand database for specific technology or skill. In addition, the knowledge database can also construct a standard database for general technology or skill. Furthermore, the knowledge database can adjust the level of detail of the database according to the importance of the technology or skill. This makes it possible to adjust the level of detail of the database according to the importance of the technology or skill. Part or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input the importance of the technology or skill into AI and cause AI to adjust the level of detail of the database.

[0094] The knowledge database can estimate the emotion of the craftsman and determine the priority of the database based on the estimated emotion of the craftsman. For example, when the craftsman is relaxed, the knowledge database preferentially registers detailed information in the database. The knowledge database estimates the emotion of the craftsman using an emotion estimation algorithm and determines the priority of the database. For example, the knowledge database captures the facial expression of the craftsman with a camera and estimates the degree of relaxation using an emotion estimation algorithm. The knowledge database can also record the voice of the craftsman and estimate the emotion using a voice analysis technology. For example, the knowledge database analyzes the tone and speed of the voice and estimates the degree of relaxation. Furthermore, the knowledge database can collect the biometric data of the craftsman (heart rate and electrodermal activity) with a sensor and estimate the emotion using an emotion estimation algorithm. For example, the knowledge database estimates the degree of relaxation based on the fluctuation of the heart rate. This makes it possible to adjust the priority of the database according to the emotion of the craftsman. The emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI is, but is not limited to, a text generation AI (for example, LLM) or a multimodal generation AI. Some or all of the above-mentioned processes in the knowledge database may be performed using AI, or may be performed without using AI. For example, the knowledge database may input image data of a craftsman taken by a camera to the generation AI, and have the generation AI estimate the emotions of the craftsman.

[0095] The knowledge database can construct the database taking into consideration the geographical distribution of technologies and skills when constructing the database. For example, the knowledge database preferentially registers technologies and skills related to a specific region in the database. The knowledge database constructs the database based on the geographical distribution of technologies and skills. For example, the knowledge database centrally registers geographically distributed technologies and skills in the database. The knowledge database can also adjust the database construction method according to geographical characteristics. This makes it possible to construct the database based on the geographical distribution. Some or all of the above-mentioned processing in the knowledge database may be performed using, for example, AI, or may be performed without using AI. For example, the knowledge database can input the geographical distribution of technologies and skills into AI and have the AI ​​adjust the database construction method.

[0096] The knowledge database can improve the accuracy of the database by referring to related academic literature when constructing the database. The knowledge database, for example, refers to academic literature and constructs the database based on the latest research results. The knowledge database improves the accuracy of the database based on related academic literature. For example, the knowledge database registers information on specific technologies and skills from academic literature in the database. The knowledge database can also periodically review and optimize the database construction method based on academic literature. This makes it possible to improve the accuracy of the database based on academic literature. Some or all of the above-mentioned processing in the knowledge database may be performed, for example, using AI, or may be performed without using AI. For example, the knowledge database can input related academic literature into AI and have the AI ​​improve the accuracy of the database.

[0097] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0098] The recording unit can measure the craftsman's hand movements and the amount of force used by the sensor and record them as detailed data. For example, the hand movements of the craftsman when selecting a guitar can be recorded using motion capture technology, and the trajectory and speed of the hand movements can be saved as data. It can also use a force sensor to measure the amount of force used by the craftsman when touching the guitar and record that data. Furthermore, the recording unit can analyze this data, extract characteristics of the craftsman's techniques and skills, and save them in a database. This allows the craftsman's subtle techniques and skills to be recorded in detail and passed on to the next generation of craftsmen.

[0099] The recording unit can record the environmental sounds during the craftsman's selection process and record the acoustic environment at the time of selection. For example, the recording unit can use a high-precision microphone to record the surrounding sounds and the sound of the guitar when the craftsman is selecting a guitar, and store the acoustic data. The recording unit can also analyze the recorded acoustic data and extract the characteristics of the sounds during the selection process. Furthermore, the recording unit can visualize the acoustic data and display the waveforms and spectra of the sounds. This allows the acoustic environment during the craftsman's selection process to be recorded in detail and passed on to the next generation of craftsmen.

[0100] The protection unit can dynamically adjust the access rights to the recorded information based on the emotions of the craftsman. For example, if the craftsman is relaxed, the access rights are expanded to allow many people to access the information. Conversely, if the craftsman is feeling anxious, the access rights are restricted to allow only specific people to access the information. The protection unit estimates the emotions of the craftsman using an emotion estimation algorithm and adjusts the access rights. For example, the emotions can be estimated by analyzing the facial expressions, voice, and biometric data of the craftsman. This makes it possible to dynamically adjust the access rights to the information according to the emotions of the craftsman and strengthen the protection of the information.

[0101] The generation unit can use generative AI to reproduce the craftsman's techniques and skills as a 3D model and provide it visually. For example, the hand movements and postures of a craftsman when selecting a guitar can be recorded using 3D scanning technology, and a 3D model can be generated based on that data. The generation unit can also provide the generated 3D model in an interactive format, allowing users to freely change the viewpoint to observe it. Furthermore, the generation unit can add annotations to the 3D model to visually indicate key points of the techniques and skills. This makes it possible to convey the craftsman's techniques and skills in an easy-to-understand visual manner.

[0102] The generation unit can use the generation AI to provide an audio guide that describes the craftsman's techniques and skills. For example, it can generate an audio guide that explains the steps and key points for a craftsman to select a guitar. The generation unit can also add interactive functions to the audio guide, and respond to questions from the user in real time. Furthermore, the generation unit can incorporate an emotion estimation function into the audio guide, and adjust the content and tone of the guide according to the user's emotions. This makes it possible to easily convey the craftsman's techniques and skills through audio.

[0103] The knowledge database can provide learning content in the form of quizzes about the techniques and skills of craftsmen. For example, a quiz can be created about the steps and key points a craftsman should take when selecting a guitar, and the user can progress in their learning by answering the quiz. The knowledge database can also evaluate the user's level of understanding based on the results of the quiz and provide appropriate feedback. Furthermore, the knowledge database can regularly update the content of the quiz and add questions about new techniques and skills. This allows the user to enjoy learning about the techniques and skills of craftsmen.

[0104] The recording unit can estimate the emotion of the craftsman and adjust the level of detail of the recorded content based on the estimated emotion of the craftsman. For example, when the craftsman is concentrating, detailed steps and points are recorded. Conversely, when the craftsman is tired, simplified content is recorded. The recording unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the level of detail of the recorded content. For example, the emotion can be estimated by analyzing the facial expression, voice, and biometric data of the craftsman. This makes it possible to record with the optimal level of detail according to the emotion of the craftsman.

[0105] The recording unit can evaluate the craftsman's performance in the selection task based on the craftsman's past selection history. For example, the recording unit can analyze the evaluation results of guitars selected by the craftsman in the past and evaluate the accuracy and efficiency of the selection task. The recording unit can also evaluate the degree of improvement in the craftsman's techniques and skills based on the past selection history. Furthermore, the recording unit can provide the craftsman with the evaluation results as feedback to support the improvement of techniques and skills. This makes it possible to objectively evaluate the craftsman's performance in the selection task and promote the improvement of techniques and skills.

[0106] The recording unit can measure the acoustic characteristics of the guitar when recording and reflect them in the recorded content. For example, it can measure the acoustic characteristics of the guitar (frequency characteristics, sound pressure level, etc.) and record the data. The recording unit can also analyze the acoustic characteristic data and evaluate the quality and characteristics of the guitar. Furthermore, the recording unit can visualize the acoustic characteristic data and display it as a graph or chart. This allows the acoustic characteristics of the guitar to be recorded in detail and used as a reference for the selection process.

[0107] The recording unit can estimate the emotion of the craftsman and adjust the order of the steps to be recorded based on the estimated emotion of the craftsman. For example, if the craftsman is relaxed, complex steps are preferentially recorded. Conversely, if the craftsman is nervous, simple steps are preferentially recorded. The recording unit estimates the emotion of the craftsman using an emotion estimation algorithm and adjusts the order of the steps to be recorded. For example, the emotion can be estimated by analyzing the facial expression, voice, and biometric data of the craftsman. This makes it possible to record in the optimal order according to the emotion of the craftsman.

[0108] The process flow of the second embodiment will be briefly described below.

[0109] Step 1: The recording unit records the techniques and skills used by the craftsman when selecting a guitar. For example, the steps taken by the craftsman when selecting a guitar are recorded on video. The video recording includes criteria such as resolution, frame rate, and recording time. Step 2: The protection unit protects the information recorded by the recording unit using blockchain technology. Blockchain technology includes public blockchains and private blockchains. The protection unit has a mechanism to ensure that the recorded information is not tampered with. For example, it uses technologies such as hash functions and digital signatures. Step 3: The generation unit uses a generative AI to verbalize and convert the recorded techniques and skills into multimedia. The generative AI uses technologies such as natural language generation, image generation, and video generation. The generation unit analyzes the words and actions of the craftsman and provides information in an easy-to-understand format. For example, the generative AI analyzes the words of the craftsman and expresses them in text or video. This makes it easier to pass on craftsmanship and allows advanced techniques to be passed on to the next generation of craftsmen.

[0110] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0111] 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<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) are input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may also be an AI agent. In addition, when the processes of each of the above-mentioned parts are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0112] Furthermore, the above-described processing by the data processing system 10 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 required for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information required for processing from the data processing device 12 or an external device.

[0113] Each of the multiple elements including the recording unit, protection unit, and generation unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the recording unit uses the camera 42 of the smart device 14 to record a video of the craftsman's techniques and skills when selecting a guitar. The protection unit protects the information recorded by the specific processing unit 290 of the data processing device 12 using blockchain technology. The generation unit verbalizes or multimedializes the techniques and skills recorded by the specific processing unit 290 of the data processing device 12 using a generation AI. The correspondence between each unit and the device or control unit is not limited to the above example, and various changes are possible.

[0114] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0115] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0116] 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, the RAM 30, and the 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.

[0117] 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.

[0118] 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 the voice according to instructions from the processor 46.

[0119] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0120] 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 performed in a secure state.

[0121] Fig. 4 shows an example of 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.

[0122] 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.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0124] In the smart glasses 214, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 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 also perform processing similar to that of the specific processing unit 290 using these models.

[0125] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0126] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[0127] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0128] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, 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, and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device.

[0129] Each of the multiple elements including the recording unit, protection unit, and 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 recording unit uses the camera 42 of the smart glasses 214 to record a video of the craftsman's techniques and skills when selecting a guitar. The protection unit protects the information recorded by the specific processing unit 290 of the data processing device 12 using blockchain technology. The generation unit verbalizes or multimedializes the techniques and skills recorded by the specific processing unit 290 of the data processing device 12 using a generation AI. The correspondence between each unit and the device or control unit is not limited to the above example, and various changes are possible.

[0130] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0131] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0132] 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, the RAM 30, and the 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.

[0133] 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.

[0134] 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 the voice according to instructions from the processor 46.

[0135] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0136] 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 performed in a secure state.

[0137] 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.

[0138] 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.

[0139] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0140] In the headset type terminal 314, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50, and executes the read specific 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 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.

[0141] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0142] 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 voice indicating a user input for 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.

[0143] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0144] 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 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. In addition, 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, and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device.

[0145] Each of the multiple elements including the recording unit, protection unit, and generation unit described above is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the recording unit uses the camera 42 of the headset type terminal 314 to record a video of the craftsman's techniques and skills when selecting a guitar. The protection unit protects the information recorded by the specific processing unit 290 of the data processing device 12 with blockchain technology. The generation unit verbalizes or multimedializes the techniques and skills recorded by the specific processing unit 290 of the data processing device 12 using a generation AI. The correspondence between each unit and the device or control unit is not limited to the above example, and various changes are possible.

[0146] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0147] 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.

[0148] 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, the RAM 30, and the 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.

[0149] 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.

[0150] 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 the voice according to instructions from the processor 46.

[0151] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of a typical healthy person).

[0152] 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 performed in a secure state.

[0153] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and legs. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, and legs. 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.

[0154] 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.

[0155] 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.

[0156] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the emotion of the user using the emotion identification model 59 and perform identification processing using the user's emotion. In the emotion estimation function (emotion identification function) using the emotion identification model 59, various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, are performed, but are not limited to such examples. In addition, the estimation and prediction of the emotion also include, for example, analysis of the emotion.

[0157] In the robot 414, the specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads out the specific program 60 from the storage 50, and executes the specific 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 program 60 executed on the RAM 48. The robot 414 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.

[0158] 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 obtains a processing result (such as a prediction result) using the data generation model 58 by communicating with the server device having the data generation model 58. In addition, the data processing device 12 may be a server device, or may be a terminal device (such as a mobile phone, a robot, or a home appliance) owned by a user.

[0159] 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 a voice indicating a user input for 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.

[0160] 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. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image (e.g., still image data or video data) is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing while 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, and in this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. In the data processing device 12 and the like, the data generation model 58 includes a plurality of types, and the data generation model 58 includes an AI other than the generation AI. The AI ​​other than the generation AI is, for example, a linear regression, a logistic regression, a decision tree, a random forest, a support vector machine (SVM), a k-means clustering, a convolutional neural network (CNN), a recurrent neural network (RNN), a generative adversarial network (GAN), or a naive Bayes, and can perform various processes, but is not limited to such examples. The AI ​​may be an AI agent. In addition, when the processes of each part described above are performed by an AI, the processes are performed in part or in whole by the AI, but are not limited to such examples. In addition, the processes performed by the AI ​​including the generation AI may be replaced with rule-based processes, and the rule-based processes may be replaced with processes performed by the AI ​​including the generation AI.

[0161] 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 be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, 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.

[0162] Each of the multiple elements including the recording unit, protection unit, and generation unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the recording unit uses the camera 42 of the robot 414 to record a video of the craftsman's techniques and skills when selecting a guitar. The protection unit protects the information recorded by the specific processing unit 290 of the data processing device 12 using blockchain technology. The generation unit verbalizes or multimedializes the techniques and skills recorded by the specific processing unit 290 of the data processing device 12 using a generation AI. The correspondence between each unit and the device or control unit is not limited to the above example, and various changes are possible.

[0163] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[0164] FIG. 9 is a diagram showing 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. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0165] These emotions are distributed in the 3 o'clock direction of emotion map 400 and usually 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.

[0166] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0167] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[0168] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is 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 the positive emotion around "desire" on the response side. In other words, this is when the robot has positive feelings such as "I want more" or "I want to know more."

[0169] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the 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, "relief," "calm," and "encouraging," have similar emotion values.

[0170] 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.

[0171] 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 Universal Serial Bus (USB) 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.

[0172] In addition, 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 upon request from the data processing device 12.

[0173] 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.

[0174] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing a specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[0175] The hardware resource that executes the specific process may be one of these various processors, or may be 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.

[0176] As an example of a configuration using one 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 configuration using a processor that realizes the functions of the 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.

[0177] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[0178] In the above example, the first to fourth embodiments are described separately, but some or all of these embodiments may be combined. The smart device 14, the smart glasses 214, the headset terminal 314, and the robot 414 are only examples, and they may be combined with each other, or may be other devices. In the above example, the first and second embodiments are described separately, but they may be combined.

[0179] The above description and illustrations are detailed descriptions 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, function, action, and effect is an example of the configuration, function, action, and effect 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 replaced with respect to the description and illustrations shown above, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the description and illustrations shown above omit explanations of technical common sense that do not require particular explanation in enabling the implementation of the technology of the present disclosure.

[0180] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, and standard was specifically and individually indicated to be incorporated by reference.

[0181] (Appendix 1) A record section for recording techniques or skills; A protection unit that protects the information recorded by the recording unit using blockchain technology; A generation unit that verbalizes or multimediaizes the information protected by the protection unit using a generation AI. A system characterized by: (Appendix 2) The recording unit is Record a video of the steps a craftsman takes when selecting a guitar 2. The system of claim 1, (Appendix 3) The protective part is Equipping the system with mechanisms to ensure that recorded information is not tampered with 2. The system of claim 1, (Appendix 4) The system described in appendix 1 is characterized by using generative AI to analyze the techniques and skills of craftsmen and provide information in a clear form. (Appendix 5) The system described in appendix 1 is characterized in that it uses a generative AI to analyze the words or actions of a craftsman and express them in text or video. (Appendix 6) Build a knowledge database Making it accessible for the next generation of craftsmen to study and research 2. The system of claim 1, (Appendix 7) The recording unit is Estimate the emotions of the craftsman and adjust the timing of recording based on the estimated emotions of the craftsman 2. The system of claim 1, (Appendix 8) The recording unit is Analyze the past selection history of craftsmen and select the most appropriate recording method 2. The system of claim 1, (Appendix 9) The recording unit is When recording, customize what you record based on guitar type and model 2. The system of claim 1, (Appendix 10) The recording unit is Estimate the emotions of the craftsmen and prioritize the steps to be recorded based on the estimated emotions of the craftsmen. 2. The system of claim 1, (Appendix 11) The recording unit is When recording, the most relevant information is recorded based on the geographic location of the craftsman. 2. The system of claim 1, (Appendix 12) The recording unit is During recording, analyze the artisan's social media activity and record relevant information 2. The system of claim 1, (Appendix 13) The protective part is Estimate the emotions of the craftsmen and adjust the strength of the protection based on the estimated emotions of the craftsmen. 2. The system of claim 1, (Appendix 14) The protective part is When protecting data, the system refers to past tamper history to select the optimal protection method. 2. The system of claim 1, (Appendix 15) The protective part is During protection, the granularity of protection is adjusted based on the importance of the recorded information 2. The system of claim 1, (Appendix 16) The protective part is Estimate the emotions of craftsmen and prioritize the information to be protected based on the estimated emotions of craftsmen. 2. The system of claim 1, (Appendix 17) The protective part is When protecting information, the geographical distribution of the information should be taken into consideration. 2. The system of claim 1, (Appendix 18) The protective part is When protecting, refer to relevant legal documents to improve the accuracy of protection 2. The system of claim 1, (Appendix 19) The generation unit is Estimate the emotions of the craftsman and adjust the way the information is presented based on the estimated emotions of the craftsman 2. The system of claim 1, (Appendix 20) The generation unit is At generation time, adjust the level of detail of generation based on the importance of technology and skills. 2. The system of claim 1, (Appendix 21) The generation unit is During generation, different generation algorithms are applied depending on the technology or skill category. 2. The system of claim 1, (Appendix 22) The generation unit is The system estimates the emotions of the craftsman and adjusts the length of the generated information based on the estimated emotions of the craftsman. 2. The system of claim 1, (Appendix 23) The generation unit is During generation, generation priorities are determined based on when technologies and skills were recorded. 2. The system of claim 1, (Appendix 24) The generation unit is During generation, adjust the order of generation based on the relevance of technologies and skills 2. The system of claim 1, (Appendix 25) The knowledge database includes: Estimate the emotions of craftsmen and adjust the database construction method based on the estimated emotions of craftsmen. 2. The system of claim 1, (Appendix 26) The knowledge database includes: When building a database, refer to past database construction history to select the optimal construction method 2. The system of claim 1, (Appendix 27) The knowledge database includes: When building a database, adjust the level of detail based on the importance of technologies and skills. 2. The system of claim 1, (Appendix 28) The knowledge database includes: Estimate the emotions of craftsmen and prioritize the database based on the estimated emotions of craftsmen. 2. The system of claim 1, (Appendix 29) The knowledge database includes: When building a database, consider the geographical distribution of technologies and skills. 2. The system of claim 1, (Appendix 30) The knowledge database includes: When building a database, we refer to relevant academic literature to improve the accuracy of the database. 2. The system of claim 1, [Explanation of symbols]

[0182] 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 record section for recording techniques or skills; A protection unit that protects the information recorded by the recording unit using blockchain technology; A generation unit that verbalizes or multimediaizes the information protected by the protection unit using a generation AI. A system characterized by:

2. The recording unit is Record a video of the steps a craftsman takes when selecting a guitar 2. The system of claim 1 .

3. The protective part is Equipping the system with mechanisms to ensure that recorded information is not tampered with 2. The system of claim 1 .

4. The generation unit is Using generative AI to analyze the skills and techniques of craftsmen and provide information in a clear format 2. The system of claim 1 .

5. The generation unit is Using generative AI to analyze the words or actions of craftsmen and express them in text or video 2. The system of claim 1 .

6. Build a knowledge database, Making it accessible for the next generation of craftsmen to study and research 2. The system of claim 1 .

7. The recording unit is Estimate the emotions of the craftsman and adjust the timing of recording based on the estimated emotions of the craftsman 2. The system of claim 1 .

8. The recording unit is Analyze the past selection history of craftsmen and select the most appropriate recording method 2. The system of claim 1 .

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