System

Abstract

An object of the system according to the embodiment is to enable a hearing-impaired person to perform a carrying procedure without sign language or assistance.SOLUTION: A system according to an embodiment includes a generation AI and an explanation unit. The generation AI generates contract contents. The explanation unit explains the contract content generated by the generation AI by voice in cooperation with the transcription application. The explanation part explains by characters for the hearing-impaired person and explains by voice for the visually impaired person.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, hearing and visually impaired people needed specialized counters and assistance when applying for a mobile phone, making the process complicated.

[0005] The system according to the embodiment is intended to enable hearing and visually impaired people to carry out mobile procedures without sign language or assistance. [Means for solving the problem]

[0006] The system according to the embodiment includes a generation AI and an explanation unit. The generation AI generates contract content. The explanation unit transcribes the contract content generated by the generation AI and explains it audibly in cooperation with an app. The explanation unit provides explanations in text to those with hearing impairments and in audio to those with visual impairments. [Effects of the Invention]

[0007] The system according to the embodiment allows hearing and visually impaired people to carry out mobile procedures without sign language or assistance. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

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

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

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's 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 read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The contract support system according to an embodiment of the present invention allows hearing- and visually-impaired people to enter into contracts at shops nationwide without sign language or assistance. This system uses a generation AI to generate contract contents and explains them in text to hearing-impaired people and audibly to visually-impaired people. This allows hearing- and visually-impaired people to independently complete contract procedures.

[0029] A contract assistance system according to an embodiment includes a generation AI, a transcription app, and an explanation unit. The generation AI generates contract content. For example, the generation AI generates contract content using a text generation AI (e.g., LLM). The generation AI can also generate contract content using a multimodal generation AI. The generation AI can also generate contract content based on user instructions. For example, the text generation AI has learned large amounts of text data and has advanced natural language processing capabilities. The multimodal generation AI can handle multiple modalities, including not only text but also images and audio. The generation AI receives prompts containing instructions on what the user wants the generation AI to do, and generates contract content based on the prompts. The transcription app works in conjunction with the generation AI to provide audible explanations of the contract content. For example, the transcription app reads out the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content based on user instructions. For example, a transcription app can read out the contract contents aloud at a speed and tone specified by the user. The explanation unit explains the contract contents in text to the hearing impaired and aloud to the visually impaired. For example, the explanation unit displays the contract contents in text format and explains them step by step to make them easier for the user to understand. The explanation unit also reads the contract contents aloud to make them understandable to the visually impaired. The explanation unit can also operate based on user instructions when explaining the contract contents aloud. For example, the explanation unit can read the contract contents aloud at a speed and tone specified by the user. This allows hearing-impaired and visually impaired people to enter into contracts without sign language or assistance. For example, hearing-impaired people can easily understand the contract contents by receiving text explanations, and visually impaired people can proceed with the procedures more smoothly by receiving audio explanations. Furthermore, applying this technology to other disabilities will enable more people to complete procedures independently.

[0030] The explanation unit can refer to the user's past contract history or usage status and provide an individually customized explanation. For example, the generation AI refers to the user's past contract history and customizes and explains the current contract details based on the plans and options previously subscribed to. For example, for a user who has used a lot of data in the past, the explanation will focus on plans with high data usage. The explanation unit also refers to the user's usage status and customizes and explains the current contract details based on usage frequency and usage patterns. For example, the explanation will focus on services that are used frequently. This makes it possible to provide the user with an optimal explanation and help them understand.

[0031] The explanation unit can evaluate the user's level of understanding in real time and adjust the level of detail of the explanation depending on the level of understanding. For example, the explanation unit has the generation AI evaluate the user's level of understanding in real time, and if the level of understanding is low, provide a more detailed explanation. For example, if a user does not understand the basic contract contents, the explanation unit begins with the basic concepts of the contract. Also, the explanation unit has the generation AI evaluate the user's level of understanding in real time, and if the level of understanding is high, provide a concise explanation. For example, if a user already understands the contract contents, only the main points are explained. This makes it possible to provide an explanation that suits the user's level of understanding and help them understand.

[0032] The explanation unit can provide the contract contents in multiple languages ​​simultaneously, making it possible to accommodate foreign users as well. For example, the generation AI can provide the contract contents in multiple languages ​​simultaneously, making it possible to accommodate foreign users as well. For example, the contract contents are explained in a language selected by the user, such as Japanese, English, or Chinese. Furthermore, the explanation unit can provide the contract contents in multiple languages ​​simultaneously, making it possible to display the contract contents in a language selected by the user, such as Japanese, English, or Chinese. This makes it possible to accommodate foreign users as well as make it easier for them to understand the contract contents.

[0033] The explanation unit can use visual aids to make the contract contents easier to understand visually. For example, when the generation AI explains the contract contents, the explanation unit uses diagrams and illustrations to make them easier to understand visually. For example, it displays a comparison table of contract plans and a graph of data communication volume. Furthermore, when the generation AI explains the contract contents, the explanation unit uses visual aids to make them easier to understand visually. For example, it explains the contract contents using diagrams and illustrations. This provides a visually easy-to-understand explanation, helping the user understand.

[0034] The generation AI can use the user's voice recognition data to explain the contract details in the optimal voice tone or speed. For example, the generation AI analyzes the user's voice recognition data and explains the contract details in the optimal voice tone and speed. For example, if the user prefers a calm tone, the explanation will be given in a calm tone. The generation AI also analyzes the user's voice recognition data and explains the contract details in the optimal voice tone and speed. For example, if the user prefers explanations at a fast speed, the explanation will be given at a fast speed. This makes it possible to provide explanations at the optimal voice tone and speed for the user, helping them understand.

[0035] The generation AI can collect user feedback in real time and instantly revise the explanation content. The generation AI can, for example, collect user feedback in real time and instantly revise the explanation content. For example, if the user points out something that is difficult to understand, the generation AI can explain that point in detail. The generation AI can also collect user feedback in real time and instantly revise the explanation content. For example, if the user requests additional information, the generation AI can provide that information. This makes it possible to instantly revise the explanation content based on user feedback and help understanding.

[0036] The generation AI can explain the contract contents in different accents or dialects to meet the needs of each region. For example, the generation AI can explain the contract contents in different accents or dialects to meet the needs of each region. For example, it can explain in a dialect that the user is familiar with, such as Kansai dialect or Tohoku dialect. The generation AI can also explain the contract contents in different accents or dialects to meet the needs of each region. For example, it can explain in an accent or dialect specified by the user. This makes it possible to meet the needs of each region and provide explanations that are easy for the user to understand.

[0037] When the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, when the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, the user can ask questions by voice about points they are unsure about, and the generation AI will immediately answer. Furthermore, when the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, if the user requests additional information, that information will be provided. This allows the user to input questions by voice, and an interactive explanation can be provided.

[0038] The generating AI can optimize the progress of a procedure by referring to the user's past procedure history. The generating AI can, for example, optimize the progress of a procedure by referring to the user's past procedure history. For example, it can smoothly proceed with the current procedure based on the content of the procedures that were performed in the past. The generating AI can also optimize the progress of a procedure by referring to the user's past procedure history. For example, it can smoothly proceed with the current procedure based on the content of the procedures that were performed in the past. This allows the progress of a procedure to be optimized and smoothly proceeded based on the user's past procedure history.

[0039] The generation AI can evaluate the user's level of understanding in real time and provide additional explanations as needed. For example, if the user points out a point that is difficult to understand, the generation AI will explain that point in detail. The generation AI can also evaluate the user's level of understanding in real time and provide additional explanations as needed. For example, if the user requests additional information, the generation AI will provide that information. This makes it possible to provide additional explanations according to the user's level of understanding and help with understanding.

[0040] The generation AI can make contract procedures possible on different devices. The generation AI can make procedures possible on different devices, such as smartphones and tablets. For example, it can provide a procedure method depending on the device the user has. The generation AI can also make procedures possible on different devices, such as smartphones and tablets. For example, it can provide a procedure method depending on the device the user has. This makes it possible for users to perform procedures on different devices.

[0041] The generative AI can provide guidelines or checklists to help the user go through a procedure. The generative AI can, for example, provide guidelines or checklists to help the user go through a procedure. For example, it can clearly show each step of the procedure so that the user can go through the procedure smoothly. The generative AI can also provide guidelines or checklists to help the user go through a procedure. For example, it can clearly show each step of the procedure so that the user can go through the procedure smoothly. This makes it possible to provide guidelines or checklists to help the user go through the procedure smoothly.

[0042] Generative AI can provide customized explanation methods tailored to each disability. For example, Generative AI can explain the contract details in simple language to people with intellectual disabilities. Generative AI can also provide audio and text explanations to people with physical disabilities. This provides explanation methods tailored to each disability, helping users understand.

[0043] The generative AI can collect user feedback and continuously improve its explanation methods. The generative AI, for example, collects user feedback and continuously improves its explanation methods. For example, if a user points out something that is difficult to understand, the generative AI will improve that point. The generative AI also collects user feedback and continuously improves its explanation methods. For example, if a user requests additional information, the generative AI will provide that information. This allows the generative AI to continuously improve its explanation methods based on user feedback and help with understanding.

[0044] The generation AI can provide the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI provides the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI explains the contract content in a language selected by the user, such as Japanese, English, or Chinese. The generation AI also provides the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI provides an explanation based on the language or culture specified by the user. This provides an explanation method that corresponds to different languages ​​and cultures, helping the user understand.

[0045] When explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, when explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, the user can input any questions they have, and the generation AI can immediately answer them. Furthermore, when explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, if the user requests additional information, that information can be provided. This allows the user to input questions and provide interactive explanations.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The contract assistance system can further include a customization unit that personalizes the contract contents based on the user's preferences and past behavioral history. For example, the system can propose optimal contract contents based on the plans and options the user has previously selected. The customization unit can also analyze the user's usage frequency and patterns to propose optimal plans. This allows the system to provide optimal contract contents for the user and improve satisfaction.

[0048] The contract assistance system can further include a comprehension assessment unit that assesses the user's level of understanding in real time and adjusts the level of detail of the explanation according to the level of understanding. For example, if the user does not understand the basic contents of the contract, a detailed explanation will be provided, starting with the basic concepts of the contract. Alternatively, if the user already understands the contents of the contract, a concise explanation of only the main points will be provided. This makes it possible to provide an explanation according to the user's level of understanding and help them understand.

[0049] The contract assistance system can also be equipped with a multilingual support section that can simultaneously provide the contract contents in multiple languages ​​and accommodate foreign users. For example, the contract contents can be explained in a language selected by the user, such as Japanese, English, or Chinese. The contract contents can also be simultaneously displayed in multiple languages. This makes it easier for foreign users to understand the contract contents.

[0050] The contract assistance system can also be equipped with a visual aid unit that uses visual aids to make the contract details easier to understand visually. For example, it can display a comparison table of contract plans or a graph of data traffic volume. It can also explain the contract details using diagrams and illustrations. This provides a visually easy-to-understand explanation, helping the user understand.

[0051] The contract assistance system can further include a feedback collection unit that collects user feedback in real time and instantly corrects the explanation content. For example, if the user points out something that is difficult to understand, the system will explain that point in detail. Also, if the user requests additional information, the system will provide that information. This allows the explanation content to be instantly corrected based on the user's feedback, helping to improve understanding.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The generation AI generates the contract content. For example, the generation AI can generate the contract content using a text generation AI (e.g., LLM) or a multimodal generation AI. The generation AI can also generate the contract content based on user instructions. Step 2: The contract contents generated by the generation AI are explained aloud in cooperation with a transcription app. The transcription app works in cooperation with the generation AI to read out the contract contents aloud. For example, when reading out the contract contents aloud, the transcription app can read them out at a speed and tone specified by the user. Step 3: The explanation section explains the contract contents in text to those with hearing impairments and audibly to those with visual impairments. For example, the explanation section displays the contract contents in text format and explains them step by step to make them easy for the user to understand. The explanation section also reads out the contract contents aloud to make them understandable to those with visual impairments.

[0054] (Example 2) The contract support system according to an embodiment of the present invention allows hearing- and visually-impaired people to enter into contracts at shops nationwide without sign language or assistance. This system uses a generation AI to generate contract contents and explains them in text to hearing-impaired people and audibly to visually-impaired people. This allows hearing- and visually-impaired people to independently complete contract procedures.

[0055] A contract assistance system according to an embodiment includes a generation AI, a transcription app, and an explanation unit. The generation AI generates contract content. For example, the generation AI generates contract content using a text generation AI (e.g., LLM). The generation AI can also generate contract content using a multimodal generation AI. The generation AI can also generate contract content based on user instructions. For example, the text generation AI has learned large amounts of text data and has advanced natural language processing capabilities. The multimodal generation AI can handle multiple modalities, including not only text but also images and audio. The generation AI receives prompts containing instructions on what the user wants the generation AI to do, and generates contract content based on the prompts. The transcription app works in conjunction with the generation AI to provide audible explanations of the contract content. For example, the transcription app reads out the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content. The transcription app can also work in conjunction with the generation AI to provide audible explanations of the contract content based on user instructions. For example, a transcription app can read out the contract contents aloud at a speed and tone specified by the user. The explanation unit explains the contract contents in text to the hearing impaired and aloud to the visually impaired. For example, the explanation unit displays the contract contents in text format and explains them step by step to make them easier for the user to understand. The explanation unit also reads the contract contents aloud to make them understandable to the visually impaired. The explanation unit can also operate based on user instructions when explaining the contract contents aloud. For example, the explanation unit can read the contract contents aloud at a speed and tone specified by the user. This allows hearing-impaired and visually impaired people to enter into contracts without sign language or assistance. For example, hearing-impaired people can easily understand the contract contents by receiving text explanations, and visually impaired people can proceed with the procedures more smoothly by receiving audio explanations. Furthermore, applying this technology to other disabilities will enable more people to complete procedures independently.

[0056] The explanation unit can refer to the user's past contract history or usage status and provide an individually customized explanation. For example, the generation AI refers to the user's past contract history and customizes and explains the current contract details based on the plans and options previously subscribed to. For example, for a user who has used a lot of data in the past, the explanation will focus on plans with high data usage. The explanation unit also refers to the user's usage status and customizes and explains the current contract details based on usage frequency and usage patterns. For example, the explanation will focus on services that are used frequently. This makes it possible to provide the user with an optimal explanation and help them understand.

[0057] The explanation unit can evaluate the user's level of understanding in real time and adjust the level of detail of the explanation depending on the level of understanding. For example, the explanation unit has the generation AI evaluate the user's level of understanding in real time, and if the level of understanding is low, provide a more detailed explanation. For example, if a user does not understand the basic contract contents, the explanation unit begins with the basic concepts of the contract. Also, the explanation unit has the generation AI evaluate the user's level of understanding in real time, and if the level of understanding is high, provide a concise explanation. For example, if a user already understands the contract contents, only the main points are explained. This makes it possible to provide an explanation that suits the user's level of understanding and help them understand.

[0058] The explanation unit can use the emotion estimation function to analyze the user's emotional state and select an explanation method to reduce stress or anxiety. For example, if the user is feeling stressed, the explanation unit can use the emotion estimation function to select an explanation method that will help the user relax. For example, the explanation can be given in a calm tone to reduce the user's anxiety. Furthermore, if the user is relaxed, the explanation unit can use the emotion estimation function to select a normal explanation method. For example, the explanation can be given in a normal tone. This makes it possible to provide an explanation that is appropriate for the user's emotional state and reduce stress and anxiety.

[0059] The explanation unit can provide the contract contents in multiple languages ​​simultaneously, making it possible to accommodate foreign users as well. For example, the generation AI can provide the contract contents in multiple languages ​​simultaneously, making it possible to accommodate foreign users as well. For example, the contract contents are explained in a language selected by the user, such as Japanese, English, or Chinese. Furthermore, the explanation unit can provide the contract contents in multiple languages ​​simultaneously, making it possible to display the contract contents in a language selected by the user, such as Japanese, English, or Chinese. This makes it possible to accommodate foreign users as well as make it easier for them to understand the contract contents.

[0060] The explanation unit can use visual aids to make the contract contents easier to understand visually. For example, when the generation AI explains the contract contents, the explanation unit uses diagrams and illustrations to make them easier to understand visually. For example, it displays a comparison table of contract plans and a graph of data communication volume. Furthermore, when the generation AI explains the contract contents, the explanation unit uses visual aids to make them easier to understand visually. For example, it explains the contract contents using diagrams and illustrations. This provides a visually easy-to-understand explanation, helping the user understand.

[0061] The explanation unit can use the emotion estimation function to provide an environment in which the user can be most relaxed while providing the explanation. The explanation unit, for example, uses the emotion estimation function to provide an environment in which the user can be most relaxed while explaining the contract details. For example, the explanation is given while playing relaxing music. The explanation unit also uses the emotion estimation function to provide an environment in which the user can be most relaxed while explaining the contract details. For example, the explanation is given while setting a relaxing background color. This allows the user to receive the explanation in a relaxing environment.

[0062] The generation AI can use the user's voice recognition data to explain the contract details in the optimal voice tone or speed. For example, the generation AI analyzes the user's voice recognition data and explains the contract details in the optimal voice tone and speed. For example, if the user prefers a calm tone, the explanation will be given in a calm tone. The generation AI also analyzes the user's voice recognition data and explains the contract details in the optimal voice tone and speed. For example, if the user prefers explanations at a fast speed, the explanation will be given at a fast speed. This makes it possible to provide explanations at the optimal voice tone and speed for the user, helping them understand.

[0063] The generation AI can collect user feedback in real time and instantly revise the explanation content. The generation AI can, for example, collect user feedback in real time and instantly revise the explanation content. For example, if the user points out something that is difficult to understand, the generation AI can explain that point in detail. The generation AI can also collect user feedback in real time and instantly revise the explanation content. For example, if the user requests additional information, the generation AI can provide that information. This makes it possible to instantly revise the explanation content based on user feedback and help understanding.

[0064] The generation AI can use the emotion estimation function to analyze the user's emotional state and adjust the voice tone so that the user can receive the explanation in a relaxed state. For example, the generation AI uses the emotion estimation function to adjust the voice tone so that the user can receive the explanation in a relaxed state. For example, if the user is feeling stressed, the explanation will be given in a calm tone. The generation AI also uses the emotion estimation function to adjust the voice tone so that the user can receive the explanation in a relaxed state. For example, if the user is relaxed, the explanation will be given in a normal tone. This allows the user to receive the explanation in a relaxed state.

[0065] The generation AI can explain the contract contents in different accents or dialects to meet the needs of each region. For example, the generation AI can explain the contract contents in different accents or dialects to meet the needs of each region. For example, it can explain in a dialect that the user is familiar with, such as Kansai dialect or Tohoku dialect. The generation AI can also explain the contract contents in different accents or dialects to meet the needs of each region. For example, it can explain in an accent or dialect specified by the user. This makes it possible to meet the needs of each region and provide explanations that are easy for the user to understand.

[0066] When the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, when the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, the user can ask questions by voice about points they are unsure about, and the generation AI will immediately answer. Furthermore, when the contract contents are explained aloud, the generation AI can add an interactive function that allows the user to input questions by voice. For example, if the user requests additional information, that information will be provided. This allows the user to input questions by voice, and an interactive explanation can be provided.

[0067] The generation AI can use the emotion estimation function to analyze the time period when the user can concentrate best and adjust the schedule so that the explanation will be given during that time period. The generation AI can, for example, use the emotion estimation function to analyze the time period when the user can concentrate best and explain the contract details during that time period. For example, it can schedule the explanation for a time period when the user can concentrate best. The generation AI can also use the emotion estimation function to analyze the time period when the user can concentrate best and adjust the schedule so that the explanation will be given during that time period. For example, it can schedule the explanation for a time period when the user can concentrate best. This allows the user to receive the explanation during a time period when they can concentrate best.

[0068] The generating AI can optimize the progress of a procedure by referring to the user's past procedure history. The generating AI can, for example, optimize the progress of a procedure by referring to the user's past procedure history. For example, it can smoothly proceed with the current procedure based on the content of the procedures that were performed in the past. The generating AI can also optimize the progress of a procedure by referring to the user's past procedure history. For example, it can smoothly proceed with the current procedure based on the content of the procedures that were performed in the past. This allows the progress of a procedure to be optimized and smoothly proceeded based on the user's past procedure history.

[0069] The generation AI can evaluate the user's level of understanding in real time and provide additional explanations as needed. For example, if the user points out a point that is difficult to understand, the generation AI will explain that point in detail. The generation AI can also evaluate the user's level of understanding in real time and provide additional explanations as needed. For example, if the user requests additional information, the generation AI will provide that information. This makes it possible to provide additional explanations according to the user's level of understanding and help with understanding.

[0070] The generation AI can use the emotion estimation function to analyze the user's emotional state and provide support to reduce stress or anxiety. For example, if the user is feeling stressed, the generation AI can use the emotion estimation function to provide support that helps the user relax. For example, it can explain things in a calm tone to reduce the user's anxiety. Furthermore, the generation AI can use the emotion estimation function to provide normal support if the user is relaxed. For example, it can explain things in a normal tone. This allows the generation AI to provide support that is appropriate for the user's emotional state and reduce stress and anxiety.

[0071] The generation AI can make contract procedures possible on different devices. The generation AI can make procedures possible on different devices, such as smartphones and tablets. For example, it can provide a procedure method depending on the device the user has. The generation AI can also make procedures possible on different devices, such as smartphones and tablets. For example, it can provide a procedure method depending on the device the user has. This makes it possible for users to perform procedures on different devices.

[0072] The generative AI can provide guidelines or checklists to help the user go through a procedure. The generative AI can, for example, provide guidelines or checklists to help the user go through a procedure. For example, it can clearly show each step of the procedure so that the user can go through the procedure smoothly. The generative AI can also provide guidelines or checklists to help the user go through a procedure. For example, it can clearly show each step of the procedure so that the user can go through the procedure smoothly. This makes it possible to provide guidelines or checklists to help the user go through the procedure smoothly.

[0073] The generation AI can use the emotion estimation function to provide a user with the most relaxing environment while proceeding with the procedure. The generation AI can, for example, use the emotion estimation function to provide a user with the most relaxing environment while proceeding with the procedure. For example, the procedure can be performed while playing relaxing music. The generation AI can also use the emotion estimation function to provide a user with the most relaxing environment while proceeding with the procedure. For example, the procedure can be performed while setting a relaxing background color. This allows the user to proceed with the procedure in a relaxing environment.

[0074] Generative AI can provide customized explanation methods tailored to each disability. For example, Generative AI can explain the contract details in simple language to people with intellectual disabilities. Generative AI can also provide audio and text explanations to people with physical disabilities. This provides explanation methods tailored to each disability, helping users understand.

[0075] The generative AI can collect user feedback and continuously improve its explanation methods. The generative AI, for example, collects user feedback and continuously improves its explanation methods. For example, if a user points out something that is difficult to understand, the generative AI will improve that point. The generative AI also collects user feedback and continuously improves its explanation methods. For example, if a user requests additional information, the generative AI will provide that information. This allows the generative AI to continuously improve its explanation methods based on user feedback and help with understanding.

[0076] The generation AI can use the emotion estimation function to analyze the user's emotional state and select the optimal explanation method. For example, if the user is feeling stressed, the generation AI can use the emotion estimation function to select an explanation method that will help them relax. For example, it can explain in a calm tone to reduce the user's anxiety. Also, if the user is relaxed, the generation AI can use the emotion estimation function to select a normal explanation method. For example, it can explain in a normal tone. This makes it possible to provide the optimal explanation method according to the user's emotional state and aid understanding.

[0077] The generation AI can provide the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI provides the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI explains the contract content in a language selected by the user, such as Japanese, English, or Chinese. The generation AI also provides the contract content in an explanation method that corresponds to different languages ​​or cultures. For example, the generation AI provides an explanation based on the language or culture specified by the user. This provides an explanation method that corresponds to different languages ​​and cultures, helping the user understand.

[0078] When explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, when explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, the user can input any questions they have, and the generation AI can immediately answer them. Furthermore, when explaining the contents of a contract, the generation AI can add an interactive function that allows the user to input questions. For example, if the user requests additional information, that information can be provided. This allows the user to input questions and provide interactive explanations.

[0079] The generative AI can use the emotion estimation function to analyze the user's emotional reactions and continuously search for the optimal explanation method. For example, the generative AI can use the emotion estimation function to collect the user's emotional reactions in real time and search for the optimal explanation method based on that data. For example, it can prioritize the adoption of explanation methods that result in a lot of positive emotional reactions. The generative AI can also use the emotion estimation function to collect the user's emotional reactions in real time and search for the optimal explanation method based on that data. For example, it can prioritize the adoption of explanation methods that result in a lot of positive emotional reactions. This allows the generative AI to continuously search for the optimal explanation method based on the user's emotional reactions and help them understand.

[0080] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0081] The contract assistance system can further include a customization unit that personalizes the contract contents based on the user's preferences and past behavioral history. For example, the system can propose optimal contract contents based on the plans and options the user has previously selected. The customization unit can also analyze the user's usage frequency and patterns to propose optimal plans. This allows the system to provide optimal contract contents for the user and improve satisfaction.

[0082] The contract assistance system can further include an emotion adjustment unit that estimates the user's emotion and adjusts the explanation method for the contract contents based on the estimated emotion. For example, if the user is feeling anxious, the explanation can be given in a calm tone so that the user can receive the explanation in a relaxed state. On the other hand, if the user is relaxed, the explanation can be given in a normal tone. This makes it possible to provide the optimal explanation method according to the user's emotional state and help them understand.

[0083] The contract assistance system can further include a comprehension assessment unit that assesses the user's level of understanding in real time and adjusts the level of detail of the explanation according to the level of understanding. For example, if the user does not understand the basic contents of the contract, a detailed explanation will be provided, starting with the basic concepts of the contract. Alternatively, if the user already understands the contents of the contract, a concise explanation of only the main points will be provided. This makes it possible to provide an explanation according to the user's level of understanding and help them understand.

[0084] The contract assistance system may further include an environment adjustment unit that estimates the user's emotions and provides a relaxing environment based on the estimated emotions. For example, if the user is feeling stressed, the explanation may be given while playing relaxing music. If the user is relaxed, the explanation may be given in a normal environment. This allows the user to receive the explanation in a relaxing environment.

[0085] The contract assistance system can also be equipped with a multilingual support section that can simultaneously provide the contract contents in multiple languages ​​and accommodate foreign users. For example, the contract contents can be explained in a language selected by the user, such as Japanese, English, or Chinese. The contract contents can also be simultaneously displayed in multiple languages. This makes it easier for foreign users to understand the contract contents.

[0086] The contract assistance system can further include a voice adjustment unit that estimates the user's emotions and explains the contract details in an optimal voice tone and speed based on the estimated emotions. For example, if the user prefers a calm tone, the explanation will be given in a calm tone. On the other hand, if the user prefers explanations at a fast speed, the explanation will be given at a fast speed. This makes it possible to provide explanations at an optimal voice tone and speed to the user, helping them understand.

[0087] The contract assistance system can also be equipped with a visual aid unit that uses visual aids to make the contract details easier to understand visually. For example, it can display a comparison table of contract plans or a graph of data traffic volume. It can also explain the contract details using diagrams and illustrations. This provides a visually easy-to-understand explanation, helping the user understand.

[0088] The contract assistance system can further include an emotion feedback unit that estimates the user's emotions and continuously searches for the optimal explanation method based on the estimated emotions. For example, the system can collect the user's emotional reactions in real time and search for the optimal explanation method based on that data. By prioritizing explanation methods that generate a high number of positive emotional reactions, it can help the user understand.

[0089] The contract assistance system can further include a feedback collection unit that collects user feedback in real time and instantly corrects the explanation content. For example, if the user points out something that is difficult to understand, the system will explain that point in detail. Also, if the user requests additional information, the system will provide that information. This allows the explanation content to be instantly corrected based on the user's feedback, helping to improve understanding.

[0090] The contract assistance system can further include an emotion optimization unit that estimates the user's emotion and selects the optimal explanation method based on the estimated emotion. For example, if the user is feeling stressed, an explanation method that helps the user relax is selected. On the other hand, if the user is relaxed, a normal explanation method is selected. This makes it possible to provide the optimal explanation method according to the user's emotional state and aid understanding.

[0091] The processing flow of the second embodiment will be briefly explained below.

[0092] Step 1: The generation AI generates the contract content. For example, the generation AI can generate the contract content using a text generation AI (e.g., LLM) or a multimodal generation AI. The generation AI can also generate the contract content based on user instructions. Step 2: The contract contents generated by the generation AI are explained aloud in cooperation with a transcription app. The transcription app works in cooperation with the generation AI to read out the contract contents aloud. For example, when reading out the contract contents aloud, the transcription app can read them out at a speed and tone specified by the user. Step 3: The explanation section explains the contract contents in text to those with hearing impairments and audibly to those with visual impairments. For example, the explanation section displays the contract contents in text format and explains them step by step to make them easy for the user to understand. The explanation section also reads out the contract contents aloud to make them understandable to those with visual impairments.

[0093] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0094] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0095] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0096] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0097] 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.

[0098] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0099] 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.

[0100] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0101] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0102] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0103] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0104] 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.

[0105] 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 user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0106] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0107] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0108] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0109] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0110] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0111] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0112] 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.

[0113] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0114] 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.

[0115] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0116] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0117] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0118] 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.

[0119] 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.

[0120] 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 user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0121] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0122] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0123] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0124] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0126] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0127] 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.

[0128] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0129] 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.

[0130] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0131] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0132] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0133] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0134] 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.

[0135] 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.

[0136] 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 user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0137] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0138] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0139] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0140] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0141] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0142] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0143] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0144] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0145] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0146] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0147] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0148] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0149] 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.

[0150] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0151] 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.

[0152] 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.

[0153] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0154] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0155] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0156] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0157] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0158] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0159] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0160] 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. Equipped with generative AI, The generation AI generates the contract content, An explanation unit that transcribes the contract contents generated by the generation AI and explains them by voice in cooperation with an app; The explanation section provides explanations in text to those with hearing impairments and in audio to those with visual impairments. A system characterized by.

2. The explanation section Evaluate the user's level of understanding in real time and adjust the level of detail of the explanation according to the level of understanding.

2. The system of claim 1.

3. The explanation section The above contract contents are provided simultaneously in multiple languages ​​to accommodate foreign users.

2. The system of claim 1.

4. The generated AI is Gather user feedback in real time and instantly revise instructions The system of claim 1 .

5. The generated AI is Analyze the user's emotional state and provide support to reduce stress or anxiety 2. The system of claim 1.

Images