System

Abstract

An object of the system according to the embodiment is to convert an official document into a format that can be easily understood by anyone.SOLUTION: A system includes a digitization part, an analysis part, and a conversion part. The digitizing section captures the official document as digital data. The analysis unit analyzes the digital data captured by the digitization unit. The conversion unit converts the content analyzed by the analysis unit into a cartoon format.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] Conventional technology has had the problem that it is difficult for citizens to understand paper-based official documents or official documents written in difficult language.

[0005] The system according to the embodiment aims to convert official documents into a format that is easy for anyone to understand. [Means for solving the problem]

[0006] The system according to the embodiment includes a digitizing unit, an analyzing unit, and a converting unit. The digitizing unit captures official documents as digital data. The analyzing unit analyzes the digital data captured by the digitizing unit. The converting unit converts the content analyzed by the analyzing unit into a manga format. [Effects of the Invention]

[0007] The system according to the embodiment can convert official documents into a format that is easy for anyone to understand. [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 manga conversion system according to an embodiment of the present invention converts paper-based official documents or official documents written in complex sentences into manga format using generative AI technology. As a result, the manga conversion system provides manga that is easy for anyone to understand and read, contributing to improving the transparency of government information and increasing convenience for citizens.

[0029] A manga conversion system according to an embodiment includes a digitization unit, an analysis unit, and a conversion unit. The digitization unit imports official documents as digital data. For example, a paper-based official document can be scanned using a scanner and imported as digital data. Furthermore, official documents written in complex language can be input as text data. The analysis unit analyzes the digital data imported by the digitization unit. For example, a generation AI analyzes each paragraph and sentence of the official document to extract important information and keywords. The generation AI performs the analysis using natural language processing technology. The conversion unit converts the content analyzed by the analysis unit into a manga format. For example, the generation AI creates characters and scenes to visually represent important information in the official document and places them in manga frames. The generation AI generates specific manga pages based on a storyboard. Thus, the manga conversion system according to an embodiment imports official documents as digital data, analyzes them, and converts them into a manga format, thereby improving the transparency of government information and convenience for citizens. For example, the generated manga-format official documents can be provided digitally and viewed by citizens using devices such as smartphones, tablets, and PCs.

[0030] The digitization department can use a scanner to scan official documents and import them as digital data. For example, the digitization department inputs the image data of the official document imported by the scanner into the generation AI for character recognition. The generation AI recognizes characters using OCR technology and automatically corrects misrecognized characters. For example, this improves the recognition accuracy of handwritten characters and old fonts. This enables efficient digitization by importing paper-based official documents as digital data with a scanner.

[0031] The analysis unit can analyze each paragraph and sentence of an official document and extract important information and keywords. For example, the analysis unit automatically recognizes the layout and format of an official document scanned by the generation AI and converts it into a digital format. For example, it digitizes the document while preserving its structure, such as paragraphs, headings, and bullet points. The generation AI also analyzes each paragraph and sentence of the official document and extracts important information and keywords. For example, it extracts frequently occurring keywords and information related to a specific theme. This enables efficient content analysis by extracting important information and keywords from official documents.

[0032] The conversion unit can create characters and scenes to visually express important information from official documents and place them in manga panels. For example, the conversion unit uses a generation AI to analyze the content of digitized official documents and evaluate the emotional impact on citizens using an emotion estimation function. For example, it makes suggestions to replace negative expressions with positive ones. The generation AI also creates characters and scenes to visually express important information from official documents and places them in manga panels. For example, it designs characters and sets scenes, and generates specific manga pages based on a storyboard. This allows important information from official documents to be visually expressed and converted into an easy-to-understand manga format.

[0033] The system can provide the generated comic-formatted official documents so that they can be viewed on devices such as smartphones, tablets, and PCs. For example, the system can provide the generated comic-formatted official documents in digital format, which citizens can view on devices such as smartphones, tablets, and PCs. For example, they can be viewed through a web application or a mobile application. Furthermore, if citizens wish to provide feedback in paper form, they can print the results using a printer. This improves convenience for citizens by making the generated comic-formatted official documents viewable on a variety of devices.

[0034] The system can automatically translate the generated comic-format official documents into different languages ​​to generate multilingual digital data. For example, the system inputs digitized official documents into the generation AI, which then automatically translates them into different languages. For example, it generates digital data in multiple languages, such as English, Japanese, and French. The generation AI then uses machine translation technology to translate the contents of the official documents into different languages, generating multilingual digital data. This makes the generated comic-format official documents multilingual, allowing information to be provided to citizens who speak different languages.

[0035] The system can automatically convert the generated official document in manga format into animation format and provide it as a video. For example, the system automatically converts official documents converted into manga format by the generation AI into animation format. For example, character movements and scene changes are expressed through animation and provided as a video. The generation AI uses animation technology to convert official documents in manga format into video format, providing information that is visually easy to understand. In this way, by converting the generated official document in manga format into animation format and providing it as a video, it becomes possible to provide information that is visually easy to understand.

[0036] The system can automatically generate characters and scenes adapted to different cultures and regions from the generated manga-style official documents, creating manga from an international perspective. For example, the system uses a generation AI to automatically generate characters and scenes adapted to different cultures and regions based on the content of the official document. For example, it creates characters that take cultural background and regional characteristics into consideration. The generation AI also analyzes the content of the official document and automatically generates characters and scenes adapted to different cultures and regions, creating manga from an international perspective. For example, it provides information from an international perspective by using characters and scenes adapted to different cultures and regions. This makes it possible to provide information from an international perspective by automatically generating characters and scenes adapted to different cultures and regions.

[0037] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0038] The system can be equipped with a function to read out loud the generated manga-style official documents to the visually impaired. For example, the generating AI can analyze the content of each manga panel and use speech synthesis technology to provide the characters' lines and narration. The system can also adjust the tone and speed of the voice to emphasize important information and keywords, making it easier for the visually impaired to understand the contents of official documents.

[0039] The system can customize the manga-style official documents it generates for educational institutions and provide them as educational materials. For example, the generating AI can analyze the contents of official documents and add educational elements. It can also adjust the difficulty level according to grade level and subject, converting them into a format that is easy for students to understand. This allows official documents to be used effectively in the educational field.

[0040] The system can be equipped with a function to automatically update the generated comic-style official document based on user feedback. For example, if a user requests additional explanation for specific information, the system can add supplementary content to that information. Also, if a user points out a part that is easily misunderstood, the system can correct that part and provide it again. This makes it possible to update official documents to reflect user feedback.

[0041] The system can seamlessly synchronize the generated manga-style official documents across different devices. For example, a user can start viewing an official document on a smartphone and continue viewing it on a tablet or PC. The system can also store the user's browsing history and bookmarks in the cloud and synchronize them across different devices. This allows users to enjoy a consistent experience across all devices.

[0042] The system can customize the generated comic-style official documents based on the user's interests. For example, if the user shows interest in a particular topic, information related to that topic will be highlighted. Related topics can also be suggested based on the user's browsing and search history. This allows for personalized information provision based on the user's interests.

[0043] The processing flow of the first embodiment will be briefly explained below.

[0044] Step 1: The digitization department captures official documents as digital data. For example, paper-based official documents can be scanned using a scanner and converted into digital data. Official documents written in complex language can also be input as text data. Step 2: The analysis unit analyzes the digital data captured by the digitization unit. For example, the generation AI analyzes each paragraph and sentence of an official document and extracts important information and keywords. The generation AI performs its analysis using natural language processing technology. Step 3: The conversion unit converts the content analyzed by the analysis unit into a manga format. For example, the generation AI creates characters and scenes to visually represent important information from official documents and places them in manga panels. The generation AI generates specific manga pages based on the storyboard.

[0045] (Example 2) The manga conversion system according to an embodiment of the present invention converts paper-based official documents or official documents written in complex sentences into manga format using generative AI technology. As a result, the manga conversion system provides manga that is easy for anyone to understand and read, contributing to improving the transparency of government information and increasing convenience for citizens.

[0046] A manga conversion system according to an embodiment includes a digitization unit, an analysis unit, and a conversion unit. The digitization unit imports official documents as digital data. For example, a paper-based official document can be scanned using a scanner and imported as digital data. Furthermore, official documents written in complex language can be input as text data. The analysis unit analyzes the digital data imported by the digitization unit. For example, a generation AI analyzes each paragraph and sentence of the official document to extract important information and keywords. The generation AI performs the analysis using natural language processing technology. The conversion unit converts the content analyzed by the analysis unit into a manga format. For example, the generation AI creates characters and scenes to visually represent important information in the official document and places them in manga frames. The generation AI generates specific manga pages based on a storyboard. Thus, the manga conversion system according to an embodiment imports official documents as digital data, analyzes them, and converts them into a manga format, thereby improving the transparency of government information and convenience for citizens. For example, the generated manga-format official documents can be provided digitally and viewed by citizens using devices such as smartphones, tablets, and PCs.

[0047] The digitization department can use a scanner to scan official documents and import them as digital data. For example, the digitization department inputs the image data of the official document imported by the scanner into the generation AI for character recognition. The generation AI recognizes characters using OCR technology and automatically corrects misrecognized characters. For example, this improves the recognition accuracy of handwritten characters and old fonts. This enables efficient digitization by importing paper-based official documents as digital data with a scanner.

[0048] The analysis unit can analyze each paragraph and sentence of an official document and extract important information and keywords. For example, the analysis unit automatically recognizes the layout and format of an official document scanned by the generation AI and converts it into a digital format. For example, it digitizes the document while preserving its structure, such as paragraphs, headings, and bullet points. The generation AI also analyzes each paragraph and sentence of the official document and extracts important information and keywords. For example, it extracts frequently occurring keywords and information related to a specific theme. This enables efficient content analysis by extracting important information and keywords from official documents.

[0049] The conversion unit can create characters and scenes to visually express important information from official documents and place them in manga panels. For example, the conversion unit uses a generation AI to analyze the content of digitized official documents and evaluate the emotional impact on citizens using an emotion estimation function. For example, it makes suggestions to replace negative expressions with positive ones. The generation AI also creates characters and scenes to visually express important information from official documents and places them in manga panels. For example, it designs characters and sets scenes, and generates specific manga pages based on a storyboard. This allows important information from official documents to be visually expressed and converted into an easy-to-understand manga format.

[0050] The system can provide the generated comic-formatted official documents so that they can be viewed on devices such as smartphones, tablets, and PCs. For example, the system can provide the generated comic-formatted official documents in digital format, which citizens can view on devices such as smartphones, tablets, and PCs. For example, they can be viewed through a web application or a mobile application. Furthermore, if citizens wish to provide feedback in paper form, they can print the results using a printer. This improves convenience for citizens by making the generated comic-formatted official documents viewable on a variety of devices.

[0051] The system can automatically translate the generated comic-format official documents into different languages ​​to generate multilingual digital data. For example, the system inputs digitized official documents into the generation AI, which then automatically translates them into different languages. For example, it generates digital data in multiple languages, such as English, Japanese, and French. The generation AI then uses machine translation technology to translate the contents of the official documents into different languages, generating multilingual digital data. This makes the generated comic-format official documents multilingual, allowing information to be provided to citizens who speak different languages.

[0052] The system can use an emotion estimation function to evaluate the emotional impact of the generated comic-style official document on citizens and suggest modifications to elicit positive emotions. For example, the system uses a generation AI to analyze the content of a digitized official document and use the emotion estimation function to evaluate the emotional impact on citizens. For example, if the emotion score is low, the system will suggest improvement suggestions. The generation AI can also analyze the content of the official document and use the emotion estimation function to evaluate the emotional impact on citizens and suggest modifications to elicit positive emotions. For example, it can suggest replacing negative expressions with positive ones. In this way, using the emotion estimation function to evaluate the emotional impact on citizens and suggest modifications to elicit positive emotions makes it easier to gain their understanding and sympathy.

[0053] The system can automatically convert the generated official document in manga format into animation format and provide it as a video. For example, the system automatically converts official documents converted into manga format by the generation AI into animation format. For example, character movements and scene changes are expressed through animation and provided as a video. The generation AI uses animation technology to convert official documents in manga format into video format, providing information that is visually easy to understand. In this way, by converting the generated official document in manga format into animation format and providing it as a video, it becomes possible to provide information that is visually easy to understand.

[0054] The system can automatically generate characters and scenes adapted to different cultures and regions from the generated manga-style official documents, creating manga from an international perspective. For example, the system uses a generation AI to automatically generate characters and scenes adapted to different cultures and regions based on the content of the official document. For example, it creates characters that take cultural background and regional characteristics into consideration. The generation AI also analyzes the content of the official document and automatically generates characters and scenes adapted to different cultures and regions, creating manga from an international perspective. For example, it provides information from an international perspective by using characters and scenes adapted to different cultures and regions. This makes it possible to provide information from an international perspective by automatically generating characters and scenes adapted to different cultures and regions.

[0055] The system can use an emotion estimation function to monitor the emotional impact of generated comic-style official documents on citizens in real time and provide appropriate feedback. For example, the system analyzes the content of the comics generated by the generation AI and uses the emotion estimation function to monitor the emotional impact on citizens in real time. For example, if the emotion score is low, it will suggest improvement suggestions. The generation AI can also analyze the content of the generated comics and use the emotion estimation function to monitor the emotional impact on citizens in real time and provide appropriate feedback. For example, if the emotion score is low, it will suggest improvement suggestions. In this way, by using the emotion estimation function to monitor the emotional impact on citizens in real time and providing appropriate feedback, it becomes easier to gain public understanding and sympathy.

[0056] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0057] The system can be equipped with a function to read out loud the generated manga-style official documents to the visually impaired. For example, the generating AI can analyze the content of each manga panel and use speech synthesis technology to provide the characters' lines and narration. The system can also adjust the tone and speed of the voice to emphasize important information and keywords, making it easier for the visually impaired to understand the contents of official documents.

[0058] The system can estimate the user's emotions and customize the generated comic-style official document based on the estimated emotions. For example, it can highlight information related to topics the user expressed interest in. If the user expressed negative emotions, it can adjust the content by adding positive elements. This makes it possible to provide personalized information according to the user's emotions.

[0059] The system can customize the manga-style official documents it generates for educational institutions and provide them as educational materials. For example, the generating AI can analyze the contents of official documents and add educational elements. It can also adjust the difficulty level according to grade level and subject, converting them into a format that is easy for students to understand. This allows official documents to be used effectively in the educational field.

[0060] The system can estimate the user's emotions in the generated comic-style official document and add interactive elements based on the estimated emotions. For example, it can provide additional information or stories for characters that the user shows interest in. Also, if the user expresses negative emotions, it can provide interactive content that emphasizes positive elements. This enables an interactive experience that responds to the user's emotions.

[0061] The system can estimate the user's emotions from the generated comic-style official document and provide feedback based on the estimated emotions. For example, if the user expresses positive emotions, the system can provide more detailed information or related topics. On the other hand, if the user expresses negative emotions, the system can provide supplementary information or explanations to help with understanding. This makes it possible to provide appropriate feedback according to the user's emotions.

[0062] The system can estimate the user's emotions from the generated comic-style official document and adjust the story development based on the estimated emotions. For example, it can add episodes related to themes that the user has shown interest in. Also, if the user expresses negative emotions, it can provide a story development that emphasizes positive elements. This makes it possible to develop a story in accordance with the user's emotions.

[0063] The system can estimate the user's emotions in the generated comic-style official document and adjust the character's facial expression and dialogue based on the estimated emotions. For example, if the user expresses positive emotions, the system can brighten the character's facial expression and change the dialogue to more positive content. On the other hand, if the user expresses negative emotions, the system can soften the character's facial expression and change the dialogue to more encouraging content. This makes it possible for the character to express emotions according to the user's emotions.

[0064] The system can be equipped with a function to automatically update the generated comic-style official document based on user feedback. For example, if a user requests additional explanation for specific information, the system can add supplementary content to that information. Also, if a user points out a part that is easily misunderstood, the system can correct that part and provide it again. This makes it possible to update official documents to reflect user feedback.

[0065] The system can seamlessly synchronize the generated manga-style official documents across different devices. For example, a user can start viewing an official document on a smartphone and continue viewing it on a tablet or PC. The system can also store the user's browsing history and bookmarks in the cloud and synchronize them across different devices. This allows users to enjoy a consistent experience across all devices.

[0066] The system can customize the generated comic-style official documents based on the user's interests. For example, if the user shows interest in a particular topic, information related to that topic will be highlighted. Related topics can also be suggested based on the user's browsing and search history. This allows for personalized information provision based on the user's interests.

[0067] The processing flow of the second embodiment will be briefly explained below.

[0068] Step 1: The digitization department captures official documents as digital data. For example, paper-based official documents can be scanned using a scanner and converted into digital data. Official documents written in complex language can also be input as text data. Step 2: The analysis unit analyzes the digital data captured by the digitization unit. For example, the generation AI analyzes each paragraph and sentence of an official document and extracts important information and keywords. The generation AI performs its analysis using natural language processing technology. Step 3: The conversion unit converts the content analyzed by the analysis unit into a manga format. For example, the generation AI creates characters and scenes to visually represent important information from official documents and places them in manga panels. The generation AI generates specific manga pages based on the storyboard.

[0069] 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.

[0070] 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.

[0071] 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.

[0072] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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.

[0077] 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).

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] 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.

[0087] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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).

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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).

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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."

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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]

[0136] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A digitization department that captures official documents as digital data; an analysis unit that analyzes the digital data captured by the digitization unit; a conversion unit that converts the content analyzed by the analysis unit into a comic format. A system characterized by:

2. The digitizing unit Scan the official document using a scanner and capture it as digital data.

2. The system of claim 1.

3. The analysis unit Analyze each paragraph and sentence of the official document to extract important information and keywords.

2. The system of claim 1.

4. The system comprises: The generated official documents in comic format will be made available for viewing on devices such as smartphones, tablets, and PCs.

2. The system of claim 1.

5. The system comprises: The generated comic-style official document is evaluated for its emotional impact on citizens using an emotion estimation function, and revisions are proposed to elicit positive emotions.

2. The system of claim 1.

6. The system comprises: The generated official document in comic format is automatically converted into animation format and provided as a video.

2. The system of claim 1.

7. The system comprises: The generated official documents in manga format are automatically adapted to different cultures and regions to create manga from an international perspective.

2. The system of claim 1.

8. The system comprises: The generated comic-style official document is monitored in real time to determine the emotional impact it has on citizens using an emotion estimation function, and appropriate feedback is provided.

2. The system of claim 1.

Images