Necklace-type terminal and data processing system

Abstract

This disclosure aims to propose dynamic learning plans based on biometric data. [Solution] The data processing system includes a processing unit that, when the user state analyzed based on biometric data transmitted from a necklace-type terminal satisfies predetermined conditions, inputs a prompt including biometric data and user learning data into a data generation model, and uses the output of the data generation model to acquire a dynamic learning plan.

Description

Technical Field

[0001] The technology of the present disclosure relates to a necklace-type terminal and a data processing system.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventionally, wearable devices have been used for user health management and voice response functions. However, in learning support, the support functions for maximizing the user's learning efficiency have been insufficient. In addition, there has been room for improvement in the mechanism for directly linking the user's biological data to the learning process.

[0005] Therefore, an object of the present disclosure is to provide a data processing system capable of improving learning support suitable for the state of a wearer identified from the biological data of the wearer wearing a necklace-type terminal.

Means for Solving the Problems

[0006] A data processing system according to a first embodiment of the technology of this disclosure comprises a necklace-type terminal including a camera that photographs the area around the wearer, a sensor that detects the wearer's biometric data, a microphone, a collection unit that collects the outputs of the camera, the sensor, and the microphone, a communication unit that transmits the outputs of the camera, the sensor, and the microphone collected by the collection unit to a data processing device, and a speaker that outputs a response corresponding to user speech picked up by the microphone; an input unit that acquires the biometric data and user learning data, an analysis unit that analyzes the user state indicated by the biometric data, a processing unit that inputs prompts including the user state and the user learning data into a data generation model and uses the output of the data generation model to acquire a learning plan corresponding to the user state and the user learning data, and an output unit that outputs a proposal based on the learning plan to the necklace-type terminal.

[0007] A data processing system in a second embodiment of the technology of this disclosure includes: an analysis unit that analyzes the degree of concentration as the user state; a processing unit that adds an instruction statement to the prompt to suggest a learning task of a difficulty level corresponding to the degree of concentration of the user state; a learning plan including the suggested task of the difficulty level; and an output unit that outputs the suggested task of the difficulty level as the learning plan.

[0008] A data processing system in a third embodiment of the technology of the present disclosure includes: an analysis unit that analyzes the degree of fatigue and stress level as the user state; a processing unit that, if at least one of the degree of fatigue and stress level of the user state is high, adds an instruction to the prompt to suggest a break, obtains the learning plan including the break suggestion; and an output unit that outputs the break suggestion as the learning plan.

[0009] A data processing system according to a fourth aspect of the technology of this disclosure includes a processing unit which adds an instruction statement including the learning progress of the user learning data to the prompt, obtains the learning plan including review timing, and outputs a suggestion for review timing as the learning plan. [Brief explanation of the drawing]

[0010] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system. [Figure 2] This is a conceptual diagram showing an example of the main functions of a data processing device and a necklace-type terminal. [Figure 3] This is a side view showing the configuration of a necklace-type terminal. [Figure 4] This is a top view showing the configuration of a necklace-type terminal. [Figure 5] The functional configuration of the control unit of the necklace-type terminal is shown in general terms. [Figure 6] The functional configuration of the specific processing unit of the data processing device according to the first embodiment is schematically shown. [Figure 7] This diagram outlines an example of the operation flow of a specific process performed by a data processing device. [Figure 8] The functional configuration of the specific processing unit of the data processing device according to the second embodiment is schematically shown. [Figure 9] The storage configuration of the data processing unit is shown in general terms. [Figure 10] A schematic example of the operation flow of the learning plan proposal process by the data processing device is shown. [Modes for carrying out the invention]

[0011] Hereinafter, an example of an embodiment of the data processing device, data processing method, and program relating to the technology of this disclosure will be described with reference to the attached drawings.

[0012] First, let's explain the terminology used in the following explanation.

[0013] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), or an APU (Accelerated Processing Unit), etc.

[0014] In the following embodiments, the labeled RAM (Random Access Memory) is a memory where information is temporarily stored and is used as a work memory by the processor.

[0015] In the following embodiments, the labeled 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), or magnetic tapes, etc.

[0016] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0017] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. In this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0018] (First Embodiment) First, a first embodiment of the data processing system 10 according to the embodiment will be described.

[0019] FIG. 1 shows an example of the configuration of the data processing system 10 according to the embodiment.

[0020] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a necklace-type terminal 14. An example of the data processing device 12 is a server. In the present embodiment, the data processing device 12 is an example of the "data processing device" according to the technology of the present disclosure, and the necklace-type terminal 14 is an example of the "necklace-type terminal" according to the technology of the present disclosure.

[0021] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. 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. Also, the database 24 and the communication I / F 26 are 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).

[0022] The necklace-type terminal 14 includes a computer 36, a microphone 38, a sensor 39, a speaker 40, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 38, speaker 40, and camera 42 are also connected to the bus 52.

[0023] The user 20 wearing the necklace-type terminal 14 may be, for example, a patient whose health condition is being diagnosed, or a regular user.

[0024] The microphone 38 picks up the voice emitted by the user 20, who is wearing the necklace-type terminal 14, as well as sounds around the user 20. The microphone 38 also receives instructions from the user 20 by receiving the voice emitted by the user 20. The microphone 38 captures the voice emitted by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 40 outputs audio according to the instructions from the processor 46. The speaker 40 is, for example, a directional speaker and outputs audio towards the user 20's ears.

[0025] Sensor 39 is a sensor that detects biometric data of the user 20, who is wearing the necklace-type terminal. For example, sensor 39 may be a heart rate sensor or a blood oxygen sensor.

[0026] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the necklace-type terminal 14.

[0029] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. The storage 32 stores a specific processing program 56. 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 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58. The data generation model 58 is used by the specific processing unit 290. The storage 32 also includes a data storage unit 54.

[0031] In the necklace-type terminal 14, data acquisition processing is performed by the processor 46. The storage 50 stores the data acquisition program 60. The processor 46 reads the data acquisition program 60 from the storage 50 and executes the read data acquisition program 60 on the RAM 48. The data acquisition processing is realized by the processor 46 operating as a control unit 46A according to the data acquisition program 60 executed on the RAM 48.

[0032] As shown in Figures 3 and 4, the necklace-type terminal 14 includes multiple microphones 38, multiple sensors 39, multiple speakers 40, and multiple cameras 42. Figures 3 and 4 show an example where two microphones 38 are positioned in front of the user 20 when the user 20 wears the necklace-type terminal 14. They also show an example where two sensors 39 are positioned to the right and left of the user 20 when the user 20 wears the necklace-type terminal 14. They also show an example where two speakers 40 are positioned to the right rear and left rear of the user 20 when the user 20 wears the necklace-type terminal 14. They also show an example where two cameras 42 are positioned to the right front and left front of the user 20 when the user 20 wears the necklace-type terminal 14. Finally, they show an example where two sensors 39 are positioned inside the necklace-type terminal 14 so as to contact the user 20's neck when the user 20 wears the necklace-type terminal 14.

[0033] Next, we will explain the processing of the control unit 46A when the necklace-type terminal 14 performs data collection processing to collect data.

[0034] In this embodiment, the data collection process collects the user's biometric data in real time. Furthermore, it collects not only biometric data but also all surrounding environment data. This makes it possible to detect early signs of conditions such as Alzheimer's disease and dementia. It also allows for monitoring of the user's health status (e.g., heart disease).

[0035] As shown in Figure 5, the control unit 46A includes a data acquisition unit 100 and a communication unit 102.

[0036] The data acquisition unit 100 collects the outputs of the microphone 38, sensor 39, and camera 42, respectively.

[0037] The communication unit 102 transmits the outputs of the microphone 38, sensor 39, and camera 42, which are collected by the data acquisition unit 100, to the data processing unit 12.

[0038] Next, we will describe the processing of the specific processing unit 290 when the data processing device 12 performs specific processing to obtain a response corresponding to a user utterance.

[0039] In the specific processing in this embodiment, a response corresponding to the user utterance picked up by the microphone 38 of the necklace-type terminal 14 is obtained using the data generation model 58.

[0040] As shown in Figure 6, the specific processing unit 290 includes an input unit 292, a processing unit 294, and an output unit 296.

[0041] The input unit 292 stores the outputs of the microphone 38, sensor 39, and camera 42, respectively, received from the necklace-type terminal 14, in the data storage unit 54.

[0042] The input unit 292 acquires user utterances received by the necklace-type terminal 14. Specifically, it acquires user utterances picked up by the microphone 38 of the necklace-type terminal 14.

[0043] The processing unit 294 performs specific processing using the data generation model 58. Specifically, it inputs a prompt including user utterances to the data generation model 58 and obtains a generation result. At this time, the outputs of the sensor 39 and camera 42 collected by the data acquisition unit 100 may also be included in the prompt.

[0044] The output unit 296 transmits the result of the specific processing to the necklace-type terminal 14. In the necklace-type terminal 14, the control unit 46A causes the speaker 40 to output the result of the specific processing. In this way, a response corresponding to the user utterance picked up by the microphone 38 is output to the user 20 by the speaker 40. The microphone 38 further acquires the user utterance in response to the result of the specific processing. The control unit 46A transmits the audio data indicating the user utterance acquired by the microphone 38 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the user utterance.

[0045] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include those described above. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0046] The outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 are used, for example, to diagnose the health status of user 20. In this case, the outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 may be transmitted to a terminal on the medical institution's side. Alternatively, the data processing device 12 may analyze the outputs of the microphone 38, sensor 39, and camera 42 stored in the data storage unit 54 to diagnose the health status of user 20.

[0047] Next, the operation of the data processing system 10 will be explained.

[0048] First, let's explain an example of the data collection process flow.

[0049] When user 20 is wearing the necklace-type terminal 14, the data acquisition unit 100 sequentially collects the outputs of the microphone 38, sensor 39, and camera 42. The communication unit 102 sequentially transmits the outputs of the microphone 38, sensor 39, and camera 42 collected by the data acquisition unit 100 to the data processing unit 12.

[0050] Next, an example of the flow of a specific process will be explained with reference to Figure 7. Here, the input unit 292 of the data processing device 12 sequentially acquires the outputs of the microphone 38, sensor 39, and camera 42 received from the necklace-type terminal 14 and stores them in the data storage unit 54.

[0051] In step S300, the processing unit 294 determines whether a predetermined trigger condition is met. Specifically, the trigger condition may be that the user utterance picked up by the microphone 38 contains a specific word (for example, the name of the agent installed in the necklace-type terminal 14) or a phrase (for example, "Hi! XX" (where XX is the name of the agent)).

[0052] If the trigger condition is met in step S300 (step S300; Yes), the data processing system 10 proceeds to step S301. On the other hand, if the trigger condition is not met in step S300 (step S300; No), the data processing system 10 terminates the specific processing.

[0053] In step S301, the processing unit 294 generates a prompt by adding an instruction to obtain the result of a specific process to the text representing the user utterance picked up by the microphone 38.

[0054] For example, a prompt such as "The user is speaking as follows: XXX. Please respond as the agent." (XXX is the user's speech) can be generated. Alternatively, the outputs of sensor 39 and camera 42 can be added to the prompt to generate a prompt such as "This is biometric data representing the user's heart rate and video data representing the user's surroundings. The user is also speaking as follows: XXX. Please respond as the agent." (XXX is the user's speech)

[0055] In step S303, the processing unit 294 inputs the generated prompt to the data generation model 58 and obtains the result of a specific process based on the output of the data generation model 58.

[0056] In step S304, the output unit 296 outputs the result of the specific processing to the necklace-type terminal 14 and terminates the specific processing.

[0057] (Second embodiment) Next, a second embodiment of the data processing system 10 according to the embodiment will be described, omitting or simplifying parts that overlap with the above embodiment.

[0058] In the data processing system 10 according to the second embodiment, the data processing device 12 generates a learning plan for the user 20 based on the biometric data transmitted from the necklace-type terminal 14 and the input user learning data, and executes suggestion processing according to the learning plan. The necklace-type terminal 14 outputs the result of the suggestion processing transmitted from the data processing device 12 through the speaker 40.

[0059] Next, we will describe the processing of the specific processing unit 290 when the data processing device 12 performs the proposed processing.

[0060] As shown in Figure 8, the identification processing unit 390 according to the second embodiment includes an input unit 392, an analysis unit 394, a processing unit 396, and an output unit 398.

[0061] The configuration of the storage 32 of the data processing device 12 will now be described. Figure 9 is a block diagram showing the configuration of the storage 32 of the data processing device 12 according to the second embodiment.

[0062] As shown in Figure 9, the storage 32 stores a specific processing program 56, a data storage unit 57, a data generation model 58, a user learning database 70, and a user state database 72. Regarding the user learning data and user state described below, the learning data is stored in the user learning database 70 and retrieved from the user learning database 70. The user state is stored in the user state database 72 and retrieved from the user state database 72.

[0063] The proposal process is realized by the processor 28 operating as a specific processing unit 290 shown in Figure 8, according to a specific processing program 56 executed on the RAM 30. The data generation model 58 and the data storage unit 57 are used by the specific processing unit 290 when the learning plan proposal process is executed.

[0064] The input unit 392 stores the outputs of the microphone 38, sensor 39, and camera 42, respectively, received from the necklace-type terminal 14, in the data storage unit 57.

[0065] The input unit 392 acquires biometric data received by the necklace-type terminal 14. Specifically, it acquires biometric data collected by the sensor 39 of the necklace-type terminal 14. The input unit 392 also acquires user learning data through input from the user 20 or collection by the data collection unit 100. This biometric data and user learning data are used to generate a learning plan. In addition to biometric data acquired by the sensor 39, the sensor 39 or camera 42 may also be used to acquire the user's sitting time, standing time, behavior, and posture during learning. From this, it is also possible to evaluate the user's approach to learning and attitude.

[0066] In the data processing system 10 of this embodiment, the learning plan is adjusted to change dynamically according to the user's state, and suggestions are made based on a dynamic learning plan. Therefore, the system is set to acquire biometric data and user learning data at predetermined intervals, triggered by the start of the user's study. In addition, data is acquired not only during study, but also, for example, at times when the user's study is scheduled or close to that time, to generate and propose a dynamic learning plan in real time.

[0067] Biometric data includes the user's heart rate, blood oxygen saturation, and electroencephalogram (EEG) collected from sensor 39. User learning data includes learning progress, comprehension level, learning time, previously studied problems, and problem answer time. User learning data can be used to understand the user's comprehension level and progress in learning.

[0068] The analysis unit 394 analyzes the user state of user 20, which is indicated by the biometric data received by the necklace-type terminal 14. Specifically, it analyzes the user state, including the degree of concentration, the degree of fatigue, and the stress level, from the biometric data. The biometric data collected in this way is transmitted to the data processing system 10, where the user state is analyzed in real time by the analysis unit 398.

[0069] The processing unit 396 generates a prompt containing the user state and user learning data, and inputs it to the data generation model. The processing unit 396 uses the output of the data generation model to obtain a dynamic learning plan corresponding to the user state.

[0070] Specifically, the processing unit 396 adds an instruction to the prompt to suggest a learning task of a difficulty level corresponding to the user's level of concentration, and obtains a learning plan that includes the suggestion of a task of that difficulty level. In this way, it generates a prompt with an instruction to adjust the difficulty level of the learning content in the learning plan according to the level of concentration. If the level of concentration is high, the instruction will be to increase the difficulty level of the learning. If the level of concentration is low, the instruction may be to decrease the difficulty level of the learning, or to suggest a relaxation method such as meditation to relax, or to suggest a break. The threshold for high and low levels of concentration may be determined based on the average level of concentration of the user 20 themselves, or the average level of concentration collected from all users or users by attribute. Criteria for fatigue levels and stress levels may be determined similarly.

[0071] Furthermore, if at least one of the degree of fatigue or stress level is high, the processing unit 396 adds an instruction to the prompt to suggest a break and obtains a learning plan that includes the suggestion to take a break. In addition to suggesting a break, it also adjusts the difficulty level of the learning content in the learning plan according to the degree of fatigue and stress level. If the stress level is high, the instruction may also suggest relaxation methods to help the user relax, similar to when the degree of concentration is low. Furthermore, the processing unit 396 adds an instruction to the prompt that includes the learning progress of the user's learning data and obtains a learning plan that includes review timings.

[0072] For example, if the prompt is for suggesting tasks based on difficulty level, the prompt will be generated with the added instruction, "This is the user's level of concentration. As the agent, suggest a learning plan that includes tasks appropriate to the user's level of concentration." Similarly, if the prompt is for suggesting breaks based on fatigue level or stress level, the prompt will be generated with the added instruction, "This is the user's level of fatigue and stress level. As the agent, suggest a learning plan that includes when the user needs to take a break." Furthermore, if the prompt is for suggesting review timing, the prompt will be generated with the added instruction, "This is the user's learning progress. As the agent, suggest a learning plan that includes the optimal timing for reviewing previously learned problems."

[0073] Furthermore, the learning plan dynamically generated in the processing unit 396 may be configured to suggest the most suitable study method for each individual user based on past user learning data and the current user status. For example, it may include adjusting the learning pace, creating an efficient review plan, and automatically generating comprehension tests.

[0074] The output unit 398 outputs suggestions based on the dynamic learning plan acquired by the processing unit 396 to the necklace-type terminal 14. The suggestions are output as voice from the speaker 40 of the necklace-type terminal 14, for example. Alternatively, the user 20 may be notified via text message or other means to any terminal he uses. For example, the output unit 398 may output suggestions for tasks of varying difficulty levels according to the user's concentration level as part of the learning plan, suggestions for breaks as part of the learning plan, and suggestions for review timing as part of the learning plan. The learning plan suggestions include suggestions for review timing of the learned content and suggestions for additional problems. The learning plan suggestions also include encouraging messages and suggestions for relaxation methods as needed, depending on the user's fatigue level and stress level. As a suggestion for relaxation methods, the system may also suggest playing music for relaxation and output the music. In this way, by integrating biometric data and learning data and proposing complex and dynamic learning plans, the retention of the user 20's learned memories is promoted, and an improvement in learning effectiveness can be expected.

[0075] Next, an example of the learning plan proposal process flow will be explained with reference to Figure 10. Here, the input unit 392 of the data processing device 12 sequentially acquires the outputs of the microphone 38, sensor 39, and camera 42 received from the necklace-type terminal 14 and stores them in the data storage unit 57. This process is triggered when the user 20 starts studying and is executed at predetermined intervals until the user 20 finishes studying.

[0076] In step S310, the input unit 392 acquires biometric data and user learning data received by the necklace-type terminal 14.

[0077] In step S311, the analysis unit 394 analyzes the user state of user 20, which is indicated by the biometric data acquired in step S310.

[0078] In step S312, the processing unit 396 determines whether the user state satisfies predetermined conditions. If the conditions are met, the process proceeds to step S313; otherwise, the process terminates. The predetermined conditions may be, for example, when at least one of the following values—the degree of concentration, the degree of fatigue, and the stress level—exceeds (or falls below) a predetermined threshold for each value. Note that if the timing for reviewing the learning plan is to be suggested, this step can be omitted and the process proceeds to step S313. The frequency of suggesting review timings can be predetermined.

[0079] In step S313, the processing unit 396 generates a prompt that includes the user state and user learning data. As an example, it generates a prompt by adding an instruction to suggest a learning task of a difficulty level corresponding to the user's level of concentration. As another example, it generates a prompt by adding an instruction to suggest a break if at least one of the user's fatigue level and stress level is high. As yet another example, it generates a prompt by adding an instruction to suggest a review timing according to the user's learning progress in the learning data.

[0080] In step S313, the processing unit 396 inputs the generated prompt into the data generation model and obtains a dynamic learning plan corresponding to the user state and user learning data.

[0081] In step S314, the output unit 398 outputs the suggestions based on the dynamic learning plan acquired by the processing unit 396 to the necklace-type terminal 14.

[0082] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0083] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0084] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0085] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0086] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0087] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0088] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0089] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0090] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0091] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0092] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. [Explanation of Symbols]

[0093] 10 Data Processing Systems 12 Data Processing Devices 14 Necklace-type terminal 38 Microphones 39 Sensors 40 speakers 42 cameras 46A Control Unit 100 Data Acquisition Unit 102 Communications Department 290 Specific Processing Unit 292 Input section 294 Processing Unit 296 Output section 392 Input section 394 Analysis Department 396 Processing Unit 398 Output section< / url:>

Claims

1. A camera that takes pictures of the area around the wearer. A sensor that detects the wearer's biometric data, microphone, A collection unit that collects the outputs of the camera, the sensor, and the microphone, A communication unit transmits the outputs of the camera, the sensor, and the microphone, respectively, collected by the collection unit, to a data processing unit. A necklace-type terminal including a speaker that outputs a response corresponding to user speech picked up by the aforementioned microphone, An input unit for acquiring the aforementioned biometric data and user learning data, An analysis unit that analyzes the user state indicated by the aforementioned biometric data, A processing unit inputs a prompt containing the user state and the user learning data into a data generation model, and uses the output of the model to obtain a learning plan corresponding to the user state and the user learning data. The data processing device includes an output unit that outputs a proposal based on the learning plan to the necklace-type terminal, A data processing system equipped with the following features.

2. The analysis unit analyzes the degree of concentration as the user state, The processing unit adds an instruction to the prompt to suggest a learning task of a difficulty level corresponding to the user's level of concentration, and obtains the learning plan including the suggested task of the difficulty level. The data processing system according to claim 1, wherein the output unit outputs a suggestion of tasks of the difficulty level as the learning plan.

3. The analysis unit analyzes the degree of fatigue and stress level as the user state, The processing unit adds an instruction to the prompt to suggest a break if at least one of the user's fatigue level and stress level is high, and retrieves the learning plan including the suggestion to take a break. The data processing system according to claim 1, wherein the output unit outputs a suggestion for a break as the learning plan.

4. The processing unit adds an instruction statement including the learning progress of the user learning data to the prompt, and obtains the learning plan including the review timing. The data processing system according to claim 1, wherein the output unit outputs a suggestion of review timing as the learning plan.

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