System

Abstract

An object of a system according to an embodiment is to quickly and efficiently understand the content of a sentence.SOLUTION: A system includes an imaging part, an analysis part, a feature extraction part, a symbolization part, and a display part. The photographing unit photographs a sentence using a camera of a smartphone. The analysis part analyzes the image data photographed by the photographing part. The feature extraction unit extracts an important feature from the content of the sentence analyzed by the analysis unit. The symbolization unit symbolizes the feature extracted by the feature extraction unit. The display unit displays the information encoded by the encoding unit.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 techniques have had the problem of making it difficult to quickly and efficiently understand the content of a text.

[0005] The system according to the embodiment aims to quickly and efficiently understand the content of a text. [Means for solving the problem]

[0006] The system according to the embodiment includes a photographing unit, an analysis unit, a feature extraction unit, a symbolization unit, and a display unit. The photographing unit photographs text using a smartphone camera. The analysis unit analyzes the image data photographed by the photographing unit. The feature extraction unit extracts important features from the content of the text analyzed by the analysis unit. The symbolization unit symbolizes the features extracted by the feature extraction unit. The display unit displays the information symbolized by the symbolization unit. [Effects of the Invention]

[0007] The system according to the embodiment can quickly and efficiently understand the content of a text. [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 system according to the embodiment of the present invention uses a smartphone camera to read text such as product descriptions, advertisements, and signage, extracts features from the text, and displays them as symbols, allowing users to easily grasp the main points of the text.

[0029] The system according to the embodiment includes a photographing unit, an analysis unit, a feature extraction unit, a symbolization unit, and a display unit. The photographing unit photographs text using a smartphone camera. For example, the camera photographs a store poster or a description on a product package. The photographing unit can also photograph the text at high resolution and save it as image data. The analysis unit analyzes the image data photographed by the photographing unit. For example, the analysis unit can extract text from the image data using OCR (optical character recognition) technology. The analysis unit can also analyze the image data using an image processing algorithm. The feature extraction unit extracts important features from the content of the text analyzed by the analysis unit. For example, the feature extraction unit extracts product features, advertising slogans, important messages on signage, etc. The feature extraction unit can also extract keywords and analyze grammatical features. The symbolization unit symbolizes the features extracted by the feature extraction unit. For example, the symbolization unit generates an icon indicating a product feature or a symbol indicating an advertising slogan. The symbolization unit can also express the main points of a sentence with simple symbols or icons. The display unit displays the information symbolized by the symbolization unit. For example, the display unit displays the symbolized information on a smartphone screen. The display unit also allows the user to check the symbolized information. This allows the system according to the embodiment to easily grasp the main points of the sentence. For example, by displaying an icon indicating the features of a product, the user can understand at a glance what features the product has.

[0030] The imaging unit adds an AR (augmented reality) function to the smartphone camera, and highlights the main points of the text in real time when the image is captured. For example, the imaging unit is equipped with an AR function in the smartphone camera, and automatically detects and highlights the main points of the text when the image is captured. For example, important keywords or phrases are surrounded by a colored frame. The imaging unit also uses AR technology to display the main points of the text as a pop-up while the image is being captured. For example, the main points appear on the screen the moment the camera captures the text. The imaging unit also adds an AR function to the smartphone camera, and highlights the main points of the text with animation when the image is captured. For example, important parts may blink or be enlarged. This allows the user to instantly grasp the main points of the text when the image is being captured.

[0031] The imaging unit automatically adjusts the optimal focus and exposure when capturing a photograph, improving the accuracy of reading text. For example, the imaging unit adds an autofocus adjustment function to a smartphone camera, automatically setting the optimal focus when capturing a photograph of text. For example, it detects the outlines of characters and adjusts the focus. The imaging unit also enhances the camera's exposure adjustment function, automatically setting the optimal brightness when capturing a photograph. For example, it adjusts the exposure according to the amount of ambient light to make the text easier to read. The imaging unit also combines the autofocus and exposure adjustment functions to achieve optimal image quality when capturing a photograph of text. For example, it adjusts the focus and exposure simultaneously to increase the contrast of the characters. This improves the accuracy of reading text.

[0032] The photographing unit adds a voice input function, allowing the user to take a photograph by issuing voice commands. For example, the photographing unit adds a voice input function to a smartphone camera, allowing the user to take a photograph by issuing a voice command such as "start photographing." For example, the voice command is analyzed using voice recognition technology. The photographing unit also uses the voice input function to allow the camera to automatically start photographing when the user utters a specific phrase. For example, it recognizes instructions such as "take a photograph of this sentence." The photographing unit also enhances the voice input function, allowing the user to specify photographing conditions by voice. For example, it can accept detailed instructions such as "adjust the brightness and take a photograph." This allows the user to easily take photographs by voice.

[0033] The photographing unit automatically uploads captured images to the cloud, making them accessible from other devices. The photographing unit adds a function to automatically upload images captured with, for example, a smartphone camera to the cloud. For example, the images are stored in the cloud using Wi-Fi or mobile data communication. The photographing unit also builds a system that makes image data uploaded to the cloud accessible from other devices. For example, the images can be viewed from a PC or tablet. The photographing unit also adds a function to share image data stored in the cloud, making it easy to share with other users. For example, a sharing link can be generated and sent via email or social media. This makes it easy to access captured images from other devices.

[0034] When analyzing image data, the analysis unit refers to relevant external data to understand the context of the text. For example, when the generation AI analyzes image data, the analysis unit automatically collects related news articles and specialized literature and refers to it to understand the context. For example, the latest news on a specific topic is used in the analysis. The analysis unit also retrieves relevant information from external databases and reflects it in the analysis so that the generation AI can understand the context of the text. For example, specialized literature is referred to to understand technical terms and concepts. The analysis unit also collects relevant external data in real time when the generation AI analyzes image data and uses it to understand the context. For example, publicly available data on the Internet is incorporated into the analysis. This allows for a deeper understanding of the context of the text.

[0035] The analysis unit generates multiple analysis results and selects the most appropriate one from among them before presenting the analysis results to the user. For example, when the generation AI analyzes image data, the analysis unit develops an algorithm that generates multiple analysis results and selects the most appropriate one from among them. For example, the selection is made based on the accuracy and reliability of the analysis results. The analysis unit also builds a system in which the generation AI generates multiple analysis results and selects the optimal result before presenting it to the user. For example, the analysis unit selects the optimal result based on the user's past selection history. The analysis unit also sets evaluation criteria for the generation AI to generate multiple analysis results and select the most appropriate one from among them. For example, the evaluation is made based on the degree of agreement and relevance of the analysis results. This makes it possible to provide the user with the optimal analysis result.

[0036] The analysis unit analyzes not only image data, but also audio and video data simultaneously. For example, the analysis unit will build a system in which, when the generation AI analyzes image data, it also analyzes audio and video data simultaneously. For example, it will use voice recognition technology to convert audio data into text and use it for analysis. The analysis unit will also enable the generation AI to analyze image data and audio data in an integrated manner to generate more accurate analysis results. For example, it will understand the context based on audio information extracted from video data. The analysis unit will also develop a system in which the generation AI will analyze image data, audio data, and video data simultaneously to generate comprehensive analysis results. For example, it will analyze the audio and video in a video in conjunction with each other. This will enable it to analyze a variety of data and provide more accurate results.

[0037] The analysis unit stores the analysis results in the cloud so that they can be shared with other users. For example, the analysis unit builds a system that automatically stores the analysis results generated by the generation AI in the cloud. For example, it uploads the analysis results to cloud storage. The analysis unit also adds a function that allows the analysis results stored in the cloud to be shared with other users. For example, it generates a sharing link and sends it to other users. The analysis unit also develops a system that stores the analysis results in the cloud so that other users can access them. For example, it provides an interface that allows the analysis results to be viewed and edited on the cloud. This makes it easy to share the analysis results with other users.

[0038] The feature extraction unit represents the extracted features with multiple symbols or icons, allowing the user to select from them. For example, the feature extraction unit may represent the features extracted by the generation AI with multiple symbols or icons, providing an interface from which the user can select. For example, it may display icons with different designs, allowing the user to select their preferred one. The feature extraction unit may also represent the extracted features with multiple symbols or icons, creating a system that can be customized by the user. For example, it may provide an option to change the color or shape of the icon. The feature extraction unit may also represent the features extracted by the generation AI with multiple symbols or icons, allowing the user to select from them. For example, it may provide an icon set with different themes or styles, allowing the user to select their preferred symbol or icon.

[0039] The feature extraction unit displays features using symbols that correspond to different languages ​​and cultures. For example, the feature extraction unit builds a system that displays features extracted by the generation AI using symbols that correspond to different languages ​​and cultures. For example, it provides an icon set that matches the culture of each country. The feature extraction unit also translates the extracted features into different languages ​​and displays them using symbols that correspond to those languages. For example, it uses symbols that correspond to languages ​​such as English, Japanese, and Chinese. The feature extraction unit also displays the features extracted by the generation AI using symbols that correspond to different cultures. For example, it expresses features using cultural symbols and icons. This makes it possible to display symbols that correspond to different languages ​​and cultures.

[0040] The feature extraction unit expresses the extracted features using audio or video, providing information in ways other than visual. For example, the feature extraction unit constructs a system that expresses the features extracted by the generative AI using audio, providing information in ways other than visual. For example, it uses speech synthesis technology to explain the features through audio. The feature extraction unit also expresses the extracted features using video, providing information in ways other than visual. For example, it explains the features using animations or video clips. The feature extraction unit also develops a system that expresses the features extracted by the generative AI using audio or video, providing information in ways other than visual. For example, it provides audio guides or video tutorials. This makes it possible to provide information in ways other than visual.

[0041] The display unit provides an interface that allows the user to customize the symbolized information according to their preferences. The display unit, for example, provides an interface that allows the user to customize the symbolized information according to their preferences. For example, an option to change the color or shape of an icon is added. The display unit also builds a system that allows the user to customize the symbolized information. For example, icon sets with different themes or styles are provided so that the user can select. The display unit also develops an interface that allows the user to customize the symbolized information according to their preferences. For example, a function to adjust the size and arrangement of icons is added. This allows the user to customize the symbolized information according to their preferences.

[0042] The display unit uses AR (augmented reality) technology to display the symbolized information superimposed on the real world. The display unit, for example, builds a system that uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon superimposed on the real world through a smartphone camera. The display unit also uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon on product packaging to visually show the product's features. The display unit also develops a system that uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon superimposed on an advertisement in the city to emphasize the main points of the advertisement. This makes it possible to display information superimposed on the real world.

[0043] The display unit also displays the encoded information on other devices such as a smartwatch or smart glasses. The display unit, for example, builds a system that displays the encoded information on a smartwatch. For example, information captured with a smartphone is transferred to the smartwatch and displayed there. The display unit also develops a system that displays the encoded information on smart glasses. For example, information captured with a smartphone is transferred to the smartglasses and displayed overlaid on the field of view. The display unit also builds a system that enables the encoded information to be displayed on other devices. For example, information captured with a smartphone is also displayed on a tablet or PC. This allows the information to be displayed on other devices.

[0044] The display unit provides the coded information by voice through a voice assistant. The display unit, for example, builds a system that provides coded information by voice through a voice assistant. For example, a voice assistant on a smartphone reads out the coded information. The display unit also provides the coded information by voice using the voice assistant. For example, a smart speaker explains the coded information. The display unit also develops a system that provides the coded information by voice through a voice assistant. For example, the voice assistant answers a user's question with coded information by voice. This makes it possible to provide information by voice.

[0045] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0046] The camera unit can also add a night mode function to the smartphone camera, enabling it to capture high-quality images even in dark places. For example, when taking a photo at night or in a dimly lit area, the night mode is automatically activated, adjusting brightness and contrast to produce a clear image. The camera unit can also use the night mode function to correct images so that text is easier to read even in low-light environments. For example, it can emphasize the outlines of text and reduce background noise. Furthermore, the camera unit can enhance the night mode function by automatically extending the exposure time when taking a photo in dark places to capture more light. This allows it to capture high-quality images even in dark places.

[0047] When analyzing image data, the analysis unit can refer to the user's past search history and browsing history to provide more relevant information. For example, the analysis results can be customized based on keywords the user has previously searched for and the content of web pages they have viewed. The analysis unit can also prioritize the analysis results based on the user's interests. For example, it can prioritize information related to topics the user frequently searches for. Furthermore, the analysis unit can learn the user's behavioral history and improve the accuracy of the analysis results. This allows the system to provide more useful information to the user.

[0048] The feature extraction unit can extract features not only by considering the content of the text, but also by considering the intention and purpose of the writer. For example, if it is a product description, it can extract key points to promote product sales. Similarly, if it is an advertising slogan, it can extract elements to attract consumers' attention. Furthermore, the feature extraction unit can analyze the structure and context of the text to understand the writer's intention. For example, it can focus on the beginning or conclusion of the text to extract important messages. This makes it possible to extract features according to the intention and purpose of the text.

[0049] The display unit may also provide an interface that allows the user to customize the symbolized information according to the user's visual preferences. For example, an option may be added that allows the user to select a preferred color or font. The display unit may also build a system that allows the user to customize the symbolized information. For example, icon sets with different themes or styles may be provided and the user may select from them. The display unit may also develop an interface that allows the user to customize the symbolized information according to the user's visual preferences. For example, a function may be added that allows the size and placement of icons to be adjusted. This allows the user to customize the symbolized information according to their preferences.

[0050] The photographing unit can add a voice input function to the smartphone camera, allowing the user to take a photograph by giving voice instructions. For example, the user can take a photograph by issuing a voice command such as "start shooting." The photographing unit can also use the voice input function to have the camera automatically start taking a photograph when the user utters a specific phrase. For example, it can recognize instructions such as "take a photograph of this sentence." Furthermore, the photographing unit can enhance the voice input function to allow the user to specify the photographing conditions by voice. For example, it can accept detailed instructions such as "adjust the brightness and take a photograph." This allows the user to easily take photographs by voice.

[0051] The analysis unit can simultaneously analyze not only image data, but also audio data and video data. For example, it can use voice recognition technology to convert audio data into text and use it for analysis. The analysis unit can also perform an integrated analysis of image data and audio data to generate more accurate analysis results. For example, it can understand the context based on audio information extracted from video data. Furthermore, the analysis unit can develop a system that simultaneously analyzes image data, audio data, and video data to generate comprehensive analysis results. For example, it can analyze the audio and video in a video in conjunction with each other. This allows for the analysis of a variety of data and provides more accurate results.

[0052] The display unit can also display the encoded information on other devices such as smartwatches and smart glasses. For example, a system can be built to display encoded information on a smartwatch. The display unit can also develop a system to display encoded information on smart glasses. For example, information captured with a smartphone can be transferred to smart glasses and displayed overlaid on the field of view. Furthermore, the display unit can also build a system that allows encoded information to be displayed on other devices. For example, information captured with a smartphone can also be displayed on a tablet or PC. This allows information to be displayed on other devices.

[0053] The processing flow of the first embodiment will be briefly explained below.

[0054] Step 1: The camera uses the smartphone's camera to capture text. For example, the camera can capture a poster in a store or a description on a product package. The camera can also capture text at high resolution and save it as image data. Step 2: The analysis unit analyzes the image data captured by the image capture unit. For example, the analysis unit may extract text from the image data using OCR (optical character recognition) technology. The analysis unit may also analyze the image data using an image processing algorithm. Step 3: The feature extraction unit extracts important features from the content of the text analyzed by the analysis unit. For example, the feature extraction unit extracts product features, advertising slogans, important messages from signage, etc. The feature extraction unit can also extract keywords and analyze grammatical features. Step 4: The symbolization unit symbolizes the features extracted by the feature extraction unit. For example, the symbolization unit generates an icon that indicates the features of a product or a symbol that indicates a catchy slogan for an advertisement. The symbolization unit can also express the main points of a sentence with concise symbols or icons. Step 5: The display unit displays the information encoded by the encoding unit. For example, the display unit displays the encoded information on a smartphone screen. The display unit also allows the user to check the encoded information. This allows the system according to the embodiment to easily grasp the main points of the text. For example, the user can understand at a glance what features the product has by seeing an icon indicating the product's features.

[0055] (Example 2) The system according to the embodiment of the present invention uses a smartphone camera to read text such as product descriptions, advertisements, and signage, extracts features from the text, and displays them as symbols, allowing users to easily grasp the main points of the text.

[0056] The system according to the embodiment includes a photographing unit, an analysis unit, a feature extraction unit, a symbolization unit, and a display unit. The photographing unit photographs text using a smartphone camera. For example, the camera photographs a store poster or a description on a product package. The photographing unit can also photograph the text at high resolution and save it as image data. The analysis unit analyzes the image data photographed by the photographing unit. For example, the analysis unit can extract text from the image data using OCR (optical character recognition) technology. The analysis unit can also analyze the image data using an image processing algorithm. The feature extraction unit extracts important features from the content of the text analyzed by the analysis unit. For example, the feature extraction unit extracts product features, advertising slogans, important messages on signage, etc. The feature extraction unit can also extract keywords and analyze grammatical features. The symbolization unit symbolizes the features extracted by the feature extraction unit. For example, the symbolization unit generates an icon indicating a product feature or a symbol indicating an advertising slogan. The symbolization unit can also express the main points of a sentence with simple symbols or icons. The display unit displays the information symbolized by the symbolization unit. For example, the display unit displays the symbolized information on a smartphone screen. The display unit also allows the user to check the symbolized information. This allows the system according to the embodiment to easily grasp the main points of the sentence. For example, by displaying an icon indicating the features of a product, the user can understand at a glance what features the product has.

[0057] The imaging unit adds an AR (augmented reality) function to the smartphone camera, and highlights the main points of the text in real time when the image is captured. For example, the imaging unit is equipped with an AR function in the smartphone camera, and automatically detects and highlights the main points of the text when the image is captured. For example, important keywords or phrases are surrounded by a colored frame. The imaging unit also uses AR technology to display the main points of the text as a pop-up while the image is being captured. For example, the main points appear on the screen the moment the camera captures the text. The imaging unit also adds an AR function to the smartphone camera, and highlights the main points of the text with animation when the image is captured. For example, important parts may blink or be enlarged. This allows the user to instantly grasp the main points of the text when the image is being captured.

[0058] The imaging unit automatically adjusts the optimal focus and exposure when capturing a photograph, improving the accuracy of reading text. For example, the imaging unit adds an autofocus adjustment function to a smartphone camera, automatically setting the optimal focus when capturing a photograph of text. For example, it detects the outlines of characters and adjusts the focus. The imaging unit also enhances the camera's exposure adjustment function, automatically setting the optimal brightness when capturing a photograph. For example, it adjusts the exposure according to the amount of ambient light to make the text easier to read. The imaging unit also combines the autofocus and exposure adjustment functions to achieve optimal image quality when capturing a photograph of text. For example, it adjusts the focus and exposure simultaneously to increase the contrast of the characters. This improves the accuracy of reading text.

[0059] The photographing unit uses the emotion estimation function to analyze the emotions of the user when taking a photograph and provides feedback to elicit positive emotions. The photographing unit, for example, is equipped with the emotion estimation function in a smartphone camera and analyzes the user's facial expressions when taking a photograph to estimate emotions. For example, it detects expressions of smile or surprise. The photographing unit also uses the emotion estimation function to analyze the emotions of the user when taking a photograph in real time and displays a message to elicit positive emotions. For example, it provides feedback such as "Great shot!". The photographing unit also provides advice to make the user's emotions positive based on the emotional data at the time of taking a photograph. For example, it displays a message such as "Please relax and take a photograph." This improves the user's photographing experience.

[0060] The photographing unit adds a voice input function, allowing the user to take a photograph by issuing voice commands. For example, the photographing unit adds a voice input function to a smartphone camera, allowing the user to take a photograph by issuing a voice command such as "start photographing." For example, the voice command is analyzed using voice recognition technology. The photographing unit also uses the voice input function to allow the camera to automatically start photographing when the user utters a specific phrase. For example, it recognizes instructions such as "take a photograph of this sentence." The photographing unit also enhances the voice input function, allowing the user to specify photographing conditions by voice. For example, it can accept detailed instructions such as "adjust the brightness and take a photograph." This allows the user to easily take photographs by voice.

[0061] The photographing unit automatically uploads captured images to the cloud, making them accessible from other devices. The photographing unit adds a function to automatically upload images captured with, for example, a smartphone camera to the cloud. For example, the images are stored in the cloud using Wi-Fi or mobile data communication. The photographing unit also builds a system that makes image data uploaded to the cloud accessible from other devices. For example, the images can be viewed from a PC or tablet. The photographing unit also adds a function to share image data stored in the cloud, making it easy to share with other users. For example, a sharing link can be generated and sent via email or social media. This makes it easy to access captured images from other devices.

[0062] When analyzing image data, the analysis unit refers to relevant external data to understand the context of the text. For example, when the generation AI analyzes image data, the analysis unit automatically collects related news articles and specialized literature and refers to it to understand the context. For example, the latest news on a specific topic is used in the analysis. The analysis unit also retrieves relevant information from external databases and reflects it in the analysis so that the generation AI can understand the context of the text. For example, specialized literature is referred to to understand technical terms and concepts. The analysis unit also collects relevant external data in real time when the generation AI analyzes image data and uses it to understand the context. For example, publicly available data on the Internet is incorporated into the analysis. This allows for a deeper understanding of the context of the text.

[0063] The analysis unit generates multiple analysis results and selects the most appropriate one from among them before presenting the analysis results to the user. For example, when the generation AI analyzes image data, the analysis unit develops an algorithm that generates multiple analysis results and selects the most appropriate one from among them. For example, the selection is made based on the accuracy and reliability of the analysis results. The analysis unit also builds a system in which the generation AI generates multiple analysis results and selects the optimal result before presenting it to the user. For example, the analysis unit selects the optimal result based on the user's past selection history. The analysis unit also sets evaluation criteria for the generation AI to generate multiple analysis results and select the most appropriate one from among them. For example, the evaluation is made based on the degree of agreement and relevance of the analysis results. This makes it possible to provide the user with the optimal analysis result.

[0064] The analysis unit uses the emotion estimation function to analyze the user's emotions regarding the analysis results and makes adjustments to elicit positive emotions. For example, when the generation AI presents the analysis results, the analysis unit uses the emotion estimation function to analyze the user's emotions and makes adjustments to elicit positive emotions. For example, it makes the expression of the analysis results more positive. The analysis unit also uses the emotion estimation function to monitor the user's emotions regarding the analysis results in real time and provides feedback to elicit positive emotions. For example, it displays a message such as "These results are very useful." The analysis unit also builds a system that makes adjustments to elicit positive emotions based on the user's emotional data regarding the analysis results. For example, it adjusts the analysis results based on the user's emotion score. This makes it possible to provide analysis results that correspond to the user's emotions.

[0065] The analysis unit analyzes not only image data, but also audio and video data simultaneously. For example, the analysis unit will build a system in which, when the generation AI analyzes image data, it also analyzes audio and video data simultaneously. For example, it will use voice recognition technology to convert audio data into text and use it for analysis. The analysis unit will also enable the generation AI to analyze image data and audio data in an integrated manner to generate more accurate analysis results. For example, it will understand the context based on audio information extracted from video data. The analysis unit will also develop a system in which the generation AI will analyze image data, audio data, and video data simultaneously to generate comprehensive analysis results. For example, it will analyze the audio and video in a video in conjunction with each other. This will enable it to analyze a variety of data and provide more accurate results.

[0066] The analysis unit stores the analysis results in the cloud so that they can be shared with other users. For example, the analysis unit builds a system that automatically stores the analysis results generated by the generation AI in the cloud. For example, it uploads the analysis results to cloud storage. The analysis unit also adds a function that allows the analysis results stored in the cloud to be shared with other users. For example, it generates a sharing link and sends it to other users. The analysis unit also develops a system that stores the analysis results in the cloud so that other users can access them. For example, it provides an interface that allows the analysis results to be viewed and edited on the cloud. This makes it easy to share the analysis results with other users.

[0067] The feature extraction unit also takes into account the emotional nuances of the text and generates symbols based on emotions. For example, when the generative AI extracts the features of a text, the feature extraction unit performs an emotion analysis and generates symbols taking into account the emotional nuances. For example, it uses an icon that indicates a positive emotion. The feature extraction unit also uses an emotion estimation function to analyze the emotional nuances of the text and generates symbols based on that. For example, it displays a warning icon for parts that indicate negative emotions. The feature extraction unit also builds a system that generates symbols based on emotions, taking into account the emotional nuances of the text. For example, it uses symbols of different colors and shapes depending on the emotion score. This makes it possible to generate symbols that reflect the emotional nuances of the text.

[0068] The feature extraction unit represents the extracted features with multiple symbols or icons, allowing the user to select from them. For example, the feature extraction unit may represent the features extracted by the generation AI with multiple symbols or icons, providing an interface from which the user can select. For example, it may display icons with different designs, allowing the user to select their preferred one. The feature extraction unit may also represent the extracted features with multiple symbols or icons, creating a system that can be customized by the user. For example, it may provide an option to change the color or shape of the icon. The feature extraction unit may also represent the features extracted by the generation AI with multiple symbols or icons, allowing the user to select from them. For example, it may provide an icon set with different themes or styles, allowing the user to select their preferred symbol or icon.

[0069] The feature extraction unit displays features using symbols that correspond to different languages ​​and cultures. For example, the feature extraction unit builds a system that displays features extracted by the generation AI using symbols that correspond to different languages ​​and cultures. For example, it provides an icon set that matches the culture of each country. The feature extraction unit also translates the extracted features into different languages ​​and displays them using symbols that correspond to those languages. For example, it uses symbols that correspond to languages ​​such as English, Japanese, and Chinese. The feature extraction unit also displays the features extracted by the generation AI using symbols that correspond to different cultures. For example, it expresses features using cultural symbols and icons. This makes it possible to display symbols that correspond to different languages ​​and cultures.

[0070] The feature extraction unit expresses the extracted features using audio or video, providing information in ways other than visual. For example, the feature extraction unit constructs a system that expresses the features extracted by the generative AI using audio, providing information in ways other than visual. For example, it uses speech synthesis technology to explain the features through audio. The feature extraction unit also expresses the extracted features using video, providing information in ways other than visual. For example, it explains the features using animations or video clips. The feature extraction unit also develops a system that expresses the features extracted by the generative AI using audio or video, providing information in ways other than visual. For example, it provides audio guides or video tutorials. This makes it possible to provide information in ways other than visual.

[0071] The display unit provides an interface that allows the user to customize the symbolized information according to their preferences. The display unit, for example, provides an interface that allows the user to customize the symbolized information according to their preferences. For example, an option to change the color or shape of an icon is added. The display unit also builds a system that allows the user to customize the symbolized information. For example, icon sets with different themes or styles are provided so that the user can select. The display unit also develops an interface that allows the user to customize the symbolized information according to their preferences. For example, a function to adjust the size and arrangement of icons is added. This allows the user to customize the symbolized information according to their preferences.

[0072] The display unit uses AR (augmented reality) technology to display the symbolized information superimposed on the real world. The display unit, for example, builds a system that uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon superimposed on the real world through a smartphone camera. The display unit also uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon on product packaging to visually show the product's features. The display unit also develops a system that uses AR technology to display the symbolized information superimposed on the real world. For example, it displays an icon superimposed on an advertisement in the city to emphasize the main points of the advertisement. This makes it possible to display information superimposed on the real world.

[0073] The display unit uses the emotion estimation function to analyze the user's emotion toward the displayed symbols and provides a display method for eliciting positive emotions. The display unit, for example, uses the emotion estimation function to analyze the user's emotion toward the displayed symbols in real time and provides a display method for eliciting positive emotions. For example, the display unit displays symbols with a design that the user prefers. The display unit also builds a system that analyzes the user's emotion toward the displayed symbols and provides a display method for eliciting positive emotions. For example, the design of the symbols is changed according to the emotion score. The display unit also uses the emotion estimation function to analyze the user's emotion toward the displayed symbols in real time and provides a display method for eliciting positive emotions. For example, the color or shape of the symbols is adjusted according to the user's emotions. This makes it possible to provide a display method that corresponds to the user's emotions.

[0074] The display unit also displays the encoded information on other devices such as a smartwatch or smart glasses. The display unit, for example, builds a system that displays the encoded information on a smartwatch. For example, information captured with a smartphone is transferred to the smartwatch and displayed there. The display unit also develops a system that displays the encoded information on smart glasses. For example, information captured with a smartphone is transferred to the smartglasses and displayed overlaid on the field of view. The display unit also builds a system that enables the encoded information to be displayed on other devices. For example, information captured with a smartphone is also displayed on a tablet or PC. This allows the information to be displayed on other devices.

[0075] The display unit provides the coded information by voice through a voice assistant. The display unit, for example, builds a system that provides coded information by voice through a voice assistant. For example, a voice assistant on a smartphone reads out the coded information. The display unit also provides the coded information by voice using the voice assistant. For example, a smart speaker explains the coded information. The display unit also develops a system that provides the coded information by voice through a voice assistant. For example, the voice assistant answers a user's question with coded information by voice. This makes it possible to provide information by voice.

[0076] The display unit uses an emotion estimation function to monitor the user's emotion toward the displayed symbols in real time, and provides a display method based on the emotion. The display unit, for example, uses the emotion estimation function to build a system that monitors the user's emotion toward the displayed symbols in real time. For example, the display unit calculates an emotion score by analyzing the user's facial expressions and voice. The display unit also analyzes the user's emotion toward the displayed symbols in real time, and provides a display method based on the emotion. For example, the design of the symbols is adjusted to elicit positive emotions. The display unit also uses the emotion estimation function to monitor the user's emotion toward the displayed symbols in real time, and develops a system that provides a display method based on the emotion. For example, the display method is customized based on the user's emotion score. This makes it possible to provide a display method that corresponds to the user's emotion.

[0077] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0078] The camera unit can also add a night mode function to the smartphone camera, enabling it to capture high-quality images even in dark places. For example, when taking a photo at night or in a dimly lit area, the night mode is automatically activated, adjusting brightness and contrast to produce a clear image. The camera unit can also use the night mode function to correct images so that text is easier to read even in low-light environments. For example, it can emphasize the outlines of text and reduce background noise. Furthermore, the camera unit can enhance the night mode function by automatically extending the exposure time when taking a photo in dark places to capture more light. This allows it to capture high-quality images even in dark places.

[0079] When analyzing image data, the analysis unit can refer to the user's past search history and browsing history to provide more relevant information. For example, the analysis results can be customized based on keywords the user has previously searched for and the content of web pages they have viewed. The analysis unit can also prioritize the analysis results based on the user's interests. For example, it can prioritize information related to topics the user frequently searches for. Furthermore, the analysis unit can learn the user's behavioral history and improve the accuracy of the analysis results. This allows the system to provide more useful information to the user.

[0080] The feature extraction unit can extract features not only by considering the content of the text, but also by considering the intention and purpose of the writer. For example, if it is a product description, it can extract key points to promote product sales. Similarly, if it is an advertising slogan, it can extract elements to attract consumers' attention. Furthermore, the feature extraction unit can analyze the structure and context of the text to understand the writer's intention. For example, it can focus on the beginning or conclusion of the text to extract important messages. This makes it possible to extract features according to the intention and purpose of the text.

[0081] The display unit may also provide an interface that allows the user to customize the symbolized information according to the user's visual preferences. For example, an option may be added that allows the user to select a preferred color or font. The display unit may also build a system that allows the user to customize the symbolized information. For example, icon sets with different themes or styles may be provided and the user may select from them. The display unit may also develop an interface that allows the user to customize the symbolized information according to the user's visual preferences. For example, a function may be added that allows the size and placement of icons to be adjusted. This allows the user to customize the symbolized information according to their preferences.

[0082] The analysis unit can use the emotion estimation function to analyze the user's emotions regarding the analysis results and make adjustments to elicit positive emotions. For example, it can make the analysis results more positive. The analysis unit can also use the emotion estimation function to monitor the user's emotions regarding the analysis results in real time and provide feedback to elicit positive emotions. For example, it can display a message such as "These results are very useful." Furthermore, the analysis unit can build a system that makes adjustments to elicit positive emotions based on the user's emotional data regarding the analysis results. For example, it can adjust the analysis results based on the user's emotion score. This makes it possible to provide analysis results that correspond to the user's emotions.

[0083] The photographing unit can add a voice input function to the smartphone camera, allowing the user to take a photograph by giving voice instructions. For example, the user can take a photograph by issuing a voice command such as "start shooting." The photographing unit can also use the voice input function to have the camera automatically start taking a photograph when the user utters a specific phrase. For example, it can recognize instructions such as "take a photograph of this sentence." Furthermore, the photographing unit can enhance the voice input function to allow the user to specify the photographing conditions by voice. For example, it can accept detailed instructions such as "adjust the brightness and take a photograph." This allows the user to easily take photographs by voice.

[0084] The display unit can use the emotion estimation function to monitor the user's emotion toward the displayed symbols in real time and provide a display method based on the emotion. For example, the user's facial expressions and voice are analyzed to calculate an emotion score. The display unit can also analyze the user's emotion toward the displayed symbols in real time and provide a display method based on the emotion. For example, the design of the symbols can be adjusted to elicit positive emotions. Furthermore, the display unit can use the emotion estimation function to develop a system that monitors the user's emotion toward the displayed symbols in real time and provides a display method based on the emotion. For example, the display method can be customized based on the user's emotion score. This makes it possible to provide a display method that suits the user's emotion.

[0085] The analysis unit can simultaneously analyze not only image data, but also audio data and video data. For example, it can use voice recognition technology to convert audio data into text and use it for analysis. The analysis unit can also perform an integrated analysis of image data and audio data to generate more accurate analysis results. For example, it can understand the context based on audio information extracted from video data. Furthermore, the analysis unit can develop a system that simultaneously analyzes image data, audio data, and video data to generate comprehensive analysis results. For example, it can analyze the audio and video in a video in conjunction with each other. This allows for the analysis of a variety of data and provides more accurate results.

[0086] The feature extraction unit can also take into account the emotional nuances of the text and perform symbolization based on emotions. For example, it can analyze the emotional nuances of the text and use an icon that indicates a positive emotion. The feature extraction unit can also use an emotion estimation function to analyze the emotional nuances of the text and perform symbolization based on that. For example, it can display a warning icon for parts that indicate a negative emotion. Furthermore, the feature extraction unit can also build a system that takes into account the emotional nuances of the text and performs symbolization based on emotions. For example, it can use symbols of different colors and shapes depending on the emotion score. This makes it possible to perform symbolization that reflects the emotional nuances of the text.

[0087] The display unit can also display the encoded information on other devices such as smartwatches and smart glasses. For example, a system can be built to display encoded information on a smartwatch. The display unit can also develop a system to display encoded information on smart glasses. For example, information captured with a smartphone can be transferred to smart glasses and displayed overlaid on the field of view. Furthermore, the display unit can also build a system that allows encoded information to be displayed on other devices. For example, information captured with a smartphone can also be displayed on a tablet or PC. This allows information to be displayed on other devices.

[0088] The processing flow of the second embodiment will be briefly explained below.

[0089] Step 1: The camera uses the smartphone's camera to capture text. For example, the camera can capture a poster in a store or a description on a product package. The camera can also capture text at high resolution and save it as image data. Step 2: The analysis unit analyzes the image data captured by the image capture unit. For example, the analysis unit may extract text from the image data using OCR (optical character recognition) technology. The analysis unit may also analyze the image data using an image processing algorithm. Step 3: The feature extraction unit extracts important features from the content of the text analyzed by the analysis unit. For example, the feature extraction unit extracts product features, advertising slogans, important messages from signage, etc. The feature extraction unit can also extract keywords and analyze grammatical features. Step 4: The symbolization unit symbolizes the features extracted by the feature extraction unit. For example, the symbolization unit generates an icon that indicates the features of a product or a symbol that indicates a catchy slogan for an advertisement. The symbolization unit can also express the main points of a sentence with concise symbols or icons. Step 5: The display unit displays the information encoded by the encoding unit. For example, the display unit displays the encoded information on a smartphone screen. The display unit also allows the user to check the encoded information. This allows the system according to the embodiment to easily grasp the main points of the text. For example, the user can understand at a glance what features the product has by seeing an icon indicating the product's features.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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).

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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."

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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]

[0157] 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 photography section that takes photos of text using a smartphone camera; an analysis unit that analyzes image data captured by the imaging unit; a feature extraction unit that extracts important features from the content of the sentence analyzed by the analysis unit; a symbolization unit that symbols the features extracted by the feature extraction unit; a display unit that displays the information encoded by the encoding unit. A system characterized by:

2. The imaging unit is Adds an AR (Augmented Reality) function to smartphone cameras, highlighting key points of the text in real time when a photo is taken.

2. The system of claim 1.

3. The analysis unit When analyzing the image data, reference is made to relevant external data to understand the context of the text.

2. The system of claim 1.

4. The feature extraction unit The emotional nuance of the text is also taken into account, and the encoding is based on emotion.

2. The system of claim 1.

5. The display unit The encoded information is displayed overlaid on the real world using the AR (Augmented Reality) technology.

2. The system of claim 1.

6. The imaging unit is Analyze the emotions users feel when taking photos and provide feedback to elicit positive emotions.

2. The system of claim 1.

7. The analysis unit Analyze the user's feelings about the analysis results and make adjustments to elicit positive emotions.

2. The system of claim 1.

8. The display unit To analyze a user's feelings toward a displayed symbol and to provide a display method for eliciting the positive feelings.

2. The system of claim 1.

Images