System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a captured image as data; means for extracting text using the data; means for analyzing the extracted text to generate an abstract and event information; means for registering the abstract and the event information in a calendar; and means for generating a response to a question based on the abstract and the event information.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] In modern society, managing the large amount of printed materials distributed at schools and workplaces is extremely time-consuming, making it difficult to grasp important information. As a result, important appointments are often overlooked, and time management is often hindered due to insufficient organization of information. The present invention aims to solve these problems, efficiently manage printed information, and improve the time performance of users' lifestyles. [Means for solving the problem]

[0005] The present invention solves the above problems by providing a system that includes: means for receiving captured images as data; means for extracting text from the data; means for analyzing the extracted text to generate summaries and event information; means for registering the summaries and event information in a calendar; and means for generating responses to questions based on the summaries and event information. Furthermore, by using optical character recognition (OCR) technology to convert received images into text data and utilizing an API to automatically register the generated summaries and event information in a calendar application, the system significantly reduces user effort and enables efficient information management and rapid responses.

[0006] "System" refers to the entire mechanism in which multiple means work together to achieve the functions desired by the user.

[0007] "Means" refers to a method, apparatus, or program for achieving a specific function or operation.

[0008] An "image" is a digital representation of visual information, and refers to something captured using a camera or the like.

[0009] "Data" refers to a collection of information processed within a system, having a particular format or structure, and stored and processed electronically.

[0010] "Text" refers to a string of characters such as alphabets and kanji characters.

[0011] "Analysis" refers to the process of examining given data or information in detail and understanding its meaning and structure.

[0012] A summary is a short summary that extracts only the important points from a long piece of text or a large amount of information.

[0013] "Event information" refers to information about events or plans relating to a specific date, time, and location.

[0014] A "calendar" refers to a schedule management tool for managing appointments and events by date.

[0015] A "question" refers to an inquiry a user makes to the system about information they want to know or about something they are unsure about.

[0016] "Response" refers to the answer or information that the system returns to a user in response to a question.

[0017] "Optical character recognition (OCR)" refers to the technology that reads characters from an image and extracts them as digital text.

[0018] An "API" refers to a set of definitions and protocols used by different software components to interact with each other. [Brief explanation of the drawings]

[0019] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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, a 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), and an APU (Accelerated Processing Unit).

[0023] 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.

[0024] 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.

[0025] 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), Bluetooth (registered trademark), etc.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0031] 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.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0041] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0042] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0043] The server then sends the generated summary and the event information contained in the printout (e.g., meeting schedules, school event dates, etc.) to the device, which receives the information and visually displays it to the user. The device also uses a calendar application to automatically add the extracted event information to the schedule.

[0044] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses generative AI to generate an appropriate response to the question and sends the response back to the device, which displays the response to the user and provides an immediate answer to the question.

[0045] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text from the schedule. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0046] The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends this question to the server, and the generation AI generates a response saying "It will be held on June 15th." The response is sent to the device and displayed to the user.

[0047] In this way, this system provides a means to easily digitize received printouts and efficiently manage important information. This allows users to prevent missing information and easily manage their schedules. Furthermore, the question and answer function allows users to instantly obtain the information they need.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The user takes a photo of the print with their smartphone using the smartphone's camera app, taking a picture that captures the entire print clearly.

[0051] Step 2:

[0052] The device temporarily stores the captured image and then sends it to the server as image data via a communication method such as an HTTP request.

[0053] Step 3:

[0054] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as a string of characters.

[0055] Step 4:

[0056] The server inputs the extracted text data into the generative AI, which analyzes the text data using natural language processing (NLP) techniques.

[0057] Step 5:

[0058] Generative AI analyzes text data, extracts key information and events, and generates summaries that include information such as dates, event names, and locations.

[0059] Step 6:

[0060] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0061] Step 7:

[0062] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0063] Step 8:

[0064] The user inputs a question into the terminal, for example, "On what date is the school festival in June held?"

[0065] Step 9:

[0066] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0067] Step 10:

[0068] The server inputs the received question into the generation AI, which then generates a response to the question. The generation AI analyzes the question and constructs an appropriate answer.

[0069] Step 11:

[0070] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0071] Step 12:

[0072] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0073] Example 1

[0074] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0075] Conventional methods for digitizing and managing paper-based print information require manual input and organization, which is time-consuming and labor-intensive. There is also a risk of missing important event information. Furthermore, when a question arises, users have to search for the file to confirm the information again, which is inefficient. There is a need for a system that can solve these problems, efficiently digitize paper-based print information, make it easier to manage, and enable users to quickly obtain information.

[0076] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0077] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate summaries and event information, means for registering the summaries and the event information in a calendar, means for generating responses to questions based on the summaries and the event information, means for temporarily storing the image data, means for analyzing the analyzed text data using natural language processing technology, and means for transmitting the generated responses to a user terminal. This makes it possible to efficiently digitize and manage paper print information and quickly obtain important information without missing it.

[0078] A "photographed image" is digital image data of a paper print or the like captured by a user using the camera of the terminal.

[0079] "Means for receiving as data" refers to a technology that enables the procedure for sending captured images to a server and for the server to receive them.

[0080] The "means for extracting text" is a technology that uses optical character recognition (OCR) technology to identify character information from an image and extract it as text data.

[0081] The "means for generating summary and event information" refers to a technology for analyzing extracted text data, identifying important information and summarizing it briefly, and extracting information related to a specific event.

[0082] "Means of registering to a calendar" refers to a technology that automatically inputs the extracted event information into a schedule management application, and typically uses an API.

[0083] "Means for generating responses to questions" refers to technology that uses a generative AI model to create appropriate answers to questions from users.

[0084] "Means for temporarily storing image data" refers to technology that temporarily stores captured images within the terminal.

[0085] The "means of analysis using natural language processing technology" is a technology that analyzes the extracted text data using natural language processing technology, and extracts and summarizes important information.

[0086] The "means for transmitting the generated response to the user terminal" is a technique for transmitting the response generated by the server to the user terminal.

[0087] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0088] First, the user takes a photo of a paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data. The device then uses the HTTP POST method over the Internet.

[0089] The server processes the received image data using optical character recognition (OCR) technology and extracts text data from the image. Specifically, text extraction is performed using Google Cloud Vision or Tesseract. Using this OCR technology, the server recognizes the character information in the image and extracts it as text data.

[0090] The server then analyzes the extracted text data using natural language processing (NLP) techniques, such as SpaCy and NLTK. The server identifies important information from the analyzed text data and generates summaries and event information, which is then converted into JSON format.

[0091] The server sends the generated summary and event information to the user's device, which receives the information and visually displays it to the user. In addition, the device automatically schedules the extracted event information using a calendar application such as Google Calendar or iOS Calendar.

[0092] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses a generative AI model (e.g., GPT-4) to generate an appropriate response to the question and sends the response back to the device. The generated response is displayed on the user's device, providing an immediate answer to the question.

[0093] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule with their smartphone camera, and the device sends this image to the server. The server uses OCR technology to extract the text from the schedule and analyzes it. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0094] This generated information is sent from the server to the device, and the device automatically registers this information in a calendar. For example, if a user inputs a question such as "What day is the school festival held in June?", the device sends this question to the server. The server uses a generative AI model (e.g., GPT-4) to generate a response such as "It will be held on June 15th" and sends it to the device. The device then displays this response to the user.

[0095] An example of a prompt is the question, "What day is the school festival in June?" Using such prompts, the generative AI model can generate accurate responses and provide them to the user quickly.

[0096] As described above, the present invention provides a means for easily digitizing received printouts and efficiently managing important information. This allows users to prevent overlooking information and easily manage their schedules. In addition, the question-and-answer function allows users to instantly obtain the information they need.

[0097] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0098] Step 1:

[0099] A user photographs a paper print.

[0100] Specific behavior:

[0101] The user opens the camera app on their smartphone and takes a picture of the paper print.

[0102] input:

[0103] Paper print.

[0104] output:

[0105] Digital image data stored on a smartphone.

[0106] Step 2:

[0107] The terminal temporarily stores the image data and sends it to the server.

[0108] Specific behavior:

[0109] The device temporarily stores the captured image data in its internal storage, and then sends the image data to the server using the HTTP POST method.

[0110] input:

[0111] The captured image data.

[0112] output:

[0113] Image data sent to the server.

[0114] Step 3:

[0115] The server converts the image data into text using OCR technology.

[0116] Specific behavior:

[0117] The server uses OCR technology such as Google Cloud Vision API to extract text from the received image data.

[0118] input:

[0119] Image data received by the server.

[0120] output:

[0121] The extracted text data.

[0122] Step 4:

[0123] The server analyzes the text data and extracts and summarizes important information.

[0124] Specific behavior:

[0125] The server uses natural language processing technologies such as SpaCy and NLTK to analyze the text data, extract key information, and generate summaries.

[0126] input:

[0127] The extracted text data.

[0128] output:

[0129] Parsed summary and event information.

[0130] Step 5:

[0131] The server sends the summary and event information to the terminal.

[0132] Specific behavior:

[0133] The server converts the summary and event information into JSON format and sends it to the terminal using the HTTP POST method.

[0134] input:

[0135] Abstract and event information.

[0136] output:

[0137] Summary and event information sent to the terminal.

[0138] Step 6:

[0139] The information received by the device is automatically registered in the calendar.

[0140] Specific behavior:

[0141] The device parses the received JSON data and automatically registers the schedule using the Google Calendar API.

[0142] input:

[0143] Summary and event information received from the server.

[0144] output:

[0145] Event information registered in Google Calendar.

[0146] Step 7:

[0147] The user enters a question for information into the terminal.

[0148] Specific behavior:

[0149] Users enter questions into the device via a dedicated app.

[0150] input:

[0151] Question content.

[0152] output:

[0153] Questions typed into the terminal.

[0154] Step 8:

[0155] The terminal sends a question to the server.

[0156] Specific behavior:

[0157] The device uses a REST API to send the user's question in JSON format to the server.

[0158] input:

[0159] The question entered by the user.

[0160] output:

[0161] The question data sent to the server.

[0162] Step 9:

[0163] The server generates a response using a generative AI model.

[0164] Specific behavior:

[0165] The server uses a generative AI model (e.g., GPT-4) to generate appropriate responses to questions.

[0166] input:

[0167] User question data.

[0168] output:

[0169] The generated response data.

[0170] Step 10:

[0171] The terminal receives the response and displays it to the user.

[0172] Specific behavior:

[0173] The terminal receives the response data from the server and displays it on the screen.

[0174] input:

[0175] Response data from the server.

[0176] output:

[0177] The response shown to the user.

[0178] (Application example 1)

[0179] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0180] In brick-and-mortar stores, managing information such as paper promotional materials and event posters is time-consuming and laborious. Furthermore, while there is a need to digitize and share paper information to manage schedules and obtain information instantly, there is a lack of efficient ways to do this. This often results in oversight of promotional content and event information, leading to insufficient information sharing among staff.

[0181] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0182] In this invention, the server includes means for digitizing photographed paper promotional materials and automatically registering the extracted event information in a store's event calendar, means for using optical character recognition (OCR) technology to convert the received images into text data, and means for utilizing an API to automatically register the generated summary and event information in a calendar application, thereby enabling efficient digitization of paper information and automatic management and sharing of important event information.

[0183] "Captured images" are still image data captured by devices such as smartphones and cameras.

[0184] "Means for receiving as data" refers to the functions and protocols for transferring captured images to a server or other storage device.

[0185] "Means for extracting text" refers to the function of analyzing and extracting text information from image data.

[0186] The "means for generating summary and event information" refers to a function for selecting important information from the extracted text and generating a concise summary or specific event information.

[0187] "Means for registering in a calendar" refers to a function that automatically inputs the generated summary and event information into a calendar application and registers it as a schedule.

[0188] The "means for generating a response to a question" refers to a function for generating an appropriate answer to a question from a user based on the summary and event information.

[0189] "Optical character recognition (OCR) technology" refers to technology for reading character data from images.

[0190] "Using an API" means using an interface to exchange functions and data between software.

[0191] The "means for automatically registering event information in the store's event calendar" is a function that automatically adds the generated event information to the calendar system used by the store staff.

[0192] "Digitizing promotional materials" refers to the process of converting promotional content written on paper into electronic data.

[0193] This invention is a system that improves the efficiency of information management for promotional materials and event posters in brick-and-mortar stores. This system provides a means for photographing paper promotional materials with a smartphone and sending the data to a server for processing.

[0194] First, a user takes a photo of a paper promotional material using a smartphone. The captured image is temporarily saved on the smartphone and then sent to a server as image data. The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image. For example, the pytesseract library is used for this OCR technology.

[0195] The server then analyzes the extracted text data and generates important information as summaries and event information, which are then automatically added to the store's event calendar using an API, such as the Google Calendar API.

[0196] Users can enter questions about promotions and events through a smartphone app. These questions are sent to a server, which uses a generative AI model to generate an appropriate response to the question. The generated response is displayed on the smartphone and provided to the user instantly. This AI model uses, for example, OpenAI's GPT-3.

[0197] As a concrete example, let's explain how a store staff member takes a photo of a new promotional poster with their smartphone, and the system automatically registers that information in the event calendar. The staff member takes a photo of the poster and immediately sends the image to the server. The server uses OCR to extract the text and generates a summary and event information, such as "There will be a Christmas sale on December 5th and a year-end special sale on December 12th." This information is automatically registered in the calendar app.

[0198] If a staff member types a question like, "What date is the next event?", the system sends the following prompt to the generative AI model:

[0199] Examples of prompts:

[0200] Answer the questions based on the event information below: "There will be a Christmas sale on December 5th and a year-end sale on December 12th."

[0201] Question: "What date is the next event?"

[0202] answer:

[0203] Based on this prompt, the server uses a generative AI model to generate a response to the question and displays an answer such as "The next event is on December 5th" on the staff member's smartphone.

[0204] This allows store staff to efficiently digitize and manage promotional materials, and makes it easier to manage and share important event information.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] The user takes a photo of a paper promotional material with their smartphone. The input data is the captured image, which is temporarily saved on the smartphone. The output is the image data saved on the smartphone.

[0208] Step 2:

[0209] The smartphone sends the stored image data to the server. The input data is the image data stored on the smartphone, which is uploaded to the server. The output is the image data sent to the server.

[0210] Step 3:

[0211] The server converts the received image data into text data using optical character recognition (OCR) technology. Specifically, it uses the pytesseract library to extract text information from the image. The input data is the image data sent to the server, and the output is the extracted text data.

[0212] Step 4:

[0213] The server analyzes the extracted text data and generates important information as summaries and event information. Here, important keywords and date information are extracted to create summaries. The input data is the extracted text data, and the output is the summarized information and generated event information.

[0214] Step 5:

[0215] The server automatically registers the generated summary and event information in the store's event calendar using an API. Specifically, the event information is added to the calendar using the Google Calendar API, etc. The input data is the summary and event information, and the output is the event data registered in the calendar.

[0216] Step 6:

[0217] Users enter questions about promotions and events through a smartphone app. The input data is the question text entered by the user, which is sent to the server. The output is the question data sent to the server.

[0218] Step 7:

[0219] The server uses a generative AI model to generate an appropriate response to the question. Specifically, it generates a prompt sentence that combines the question data with summary and event information, and inputs it into a generative AI model such as OpenAI's GPT-3. The server then receives the generated answer. The input data is the question data and event information, and the output is the response data to the question.

[0220] Step 8:

[0221] The server sends the generated response to the smartphone. The input data is the response data to the question, and the output is the response data sent to the smartphone. The user can check the answer on the smartphone.

[0222] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0223] The present invention combines a system that photographs paper prints received by a user, digitizes and summarizes the contents using OCR technology and generative AI, and further combines it with an emotion engine that recognizes the user's emotions. The main embodiments of the present invention are described below.

[0224] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0225] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0226] The generative AI uses the analyzed text data to generate summaries and event information, while the emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends the recognition results to the server.

[0227] The server then tailors the content of the summary and event information based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, the server can generate a summary in a format that highlights important information.

[0228] The server then sends the generated summary and event information to the device, which then displays the information on its user interface and automatically registers the event information in its schedule using a calendar application.

[0229] When a user enters a question about the summary or event information, the device sends the question to the server. The server uses generative AI to generate an appropriate response to the question, again incorporating the recognition results of the emotion engine. For example, if the user is feeling doubtful or anxious, the tone of the response can be gentler.

[0230] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text of the schedule. The emotion engine also analyzes the voice and facial expressions used by the user when taking the photo, and sends emotional data to the server.

[0231] Based on the analysis results and emotion data, the AI ​​generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation start," and summarizes it according to the emotion. For example, if the user is excited, the AI ​​will present a summary in a positive tone.

[0232] The generated information is sent from the server to the device, which then automatically registers it in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends the question to the server, and the generation AI generates a response saying "It will be held on June 15th." Here too, the results of the emotion engine are reflected, and the response is displayed in an appropriate tone.

[0233] In this way, the system not only digitizes received prints and efficiently manages important information, but also provides flexible responses that take user emotions into consideration, significantly improving the user experience.

[0234] The processing flow will be explained below.

[0235] Step 1:

[0236] Users take a photo of the print using their smartphone camera, and audio guidance is displayed to help them take a clear photo.

[0237] Step 2:

[0238] The device temporarily stores the captured image and then sends it to the server as image data. The image data is sent securely using HTTP requests and SSL.

[0239] Step 3:

[0240] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as string data.

[0241] Step 4:

[0242] The server activates an emotion engine to analyze the voice and facial expression data emitted by the user when taking a photo. The emotion engine analyzes the voice waveform and facial features to generate data that identifies the user's emotional state.

[0243] Step 5:

[0244] The server inputs the text data extracted by OCR into the generation AI, and at the same time, the user's emotional data is also passed to the generation AI, which analyzes it using natural language processing (NLP) technology.

[0245] Step 6:

[0246] The generative AI extracts key information and events from text and emotion data to generate summaries, adjusting the tone and emphasis of the summaries depending on the emotion.

[0247] Step 7:

[0248] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0249] Step 8:

[0250] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0251] Step 9:

[0252] The user enters a question about the summarized information or event information, and the question can be entered by text or voice.

[0253] Step 10:

[0254] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0255] Step 11:

[0256] The server uses generative AI and an emotion engine to generate appropriate responses to questions, adjusting the content and tone of the response depending on the user's emotional state.

[0257] Step 12:

[0258] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0259] Step 13:

[0260] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0261] In this way, users can not only easily digitize prints and efficiently manage important information, but also receive more personalized information through the emotion engine.

[0262] Example 2

[0263] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0264] Traditional paper printouts are not digitized, making it difficult to manage important information. Furthermore, there are insufficient means to efficiently extract necessary information from digitized information and provide flexible responses based on user emotions. Therefore, improving user information management and user experience has become a challenge.

[0265] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0266] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for analyzing the user's voice and facial expression to recognize the user's emotion, means for adjusting the content of the summary and the event information based on the emotion, means for registering the summary and the event information in a calendar, and means for generating responses to questions based on the summary and the event information. This makes it possible to efficiently digitize paper printouts and flexibly provide information and responses that take the user's emotion into consideration.

[0267] The "means for receiving captured images as data" refers to a device or program for receiving captured image data sent from the user's terminal.

[0268] "Means for extracting text using said data" refers to a device or program that analyzes and extracts text data from received image data using optical character recognition technology.

[0269] The "means for analyzing the extracted text and generating a summary and event information" refers to a device or program that analyzes the extracted text data, summarizes important information, and generates event information.

[0270] "Means for analyzing the user's voice and facial expressions in order to recognize the user's emotions" refers to a device or program that acquires data on the voice and facial expressions made by the user while taking a photograph, and recognizes and analyzes the user's emotions from that data.

[0271] The "means for adjusting the content of the summary and the event information based on the emotion" refers to a device or program that adjusts and optimizes the content and tone of the generated summary and event information based on the analyzed user emotion data.

[0272] The "means for registering in a calendar using the summary and the event information" is a device or program that automatically registers the generated summary and event information in a calendar application.

[0273] The "means for generating a response to a question based on the summary and the event information" refers to a device or program that generates an appropriate response to a question from a user related to the summary and the event information.

[0274] The present invention relates to a system that combines a user terminal, a server, and related software to digitize paper prints, extract important information, and provide flexible responses to users based on that information. Furthermore, the present invention realizes a better user experience by recognizing the user's emotions and reflecting them in the information provided and responses.

[0275] First, the user takes a photo of a paper print using a device such as a smartphone. A dedicated application installed on the device supports this process. The captured image is temporarily stored on the device and then sent to a server. The server receives the captured image as data. This action is carried out over the Internet, and secure communication is ensured using encryption technology.

[0276] The server then converts the received image data into text using optical character recognition (OCR) technology, such as Tesseract, an OCR software that enables highly accurate character recognition and accurately extracts text from images.

[0277] The extracted text data is analyzed by a generative AI (e.g., OpenAI's GPT-4). This analysis summarizes important information and generates event information. For example, events such as "April entrance ceremony," "June school festival," and "December winter vacation start" are extracted.

[0278] At the same time, the server analyzes the user's voice and facial expressions to recognize their emotions. An emotion recognition engine (for example, Microsoft's Emotion API) is used to do this. The server analyzes the user's emotions from the voice and facial expressions the user makes when taking the photo.

[0279] The server adjusts the content of the summary and event information based on the acquired emotional data. For example, if the user is feeling stressed, the information can be presented in a more concise form with the important parts emphasized. The generative AI does this and provides information in a format that is easy for the user to understand.

[0280] The server sends the summary and event information to the device, which then displays the information on the user interface. Furthermore, the device uses an API to automatically register the information in a calendar application (e.g., Google Calendar), eliminating the need for the user to manually enter the information.

[0281] Additionally, when users input questions about the summary and event information, the device sends the questions to the server, which uses generative AI to generate appropriate responses and adjusts the tone of the response based on emotion recognition results. For example, if the user is feeling anxious, the response will be delivered in a gentler tone.

[0282] As a concrete example, let's consider the case where a user takes a photo of a printed annual schedule given to them by their school. The user takes a photo of the schedule using their smartphone camera. The device then sends this image to a server. The server uses OCR technology to extract the text from the schedule and analyzes it using a generation AI. The server also analyzes the user's voice and facial expressions while taking the photo and sends emotional data to the server. Based on the analysis results and emotional data, the generation AI generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation begins." If the user is excited, it presents a summary in a positive tone. The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user inputs a question such as "What day is the June school festival held?", the server uses the generation AI to generate a response such as "It will be held on June 15th," and displays the response in an appropriate tone reflecting the results of the emotion engine.

[0283] An example of a prompt is, "Use OCR technology to convert a photo of the user's annual schedule printout into text, and then use a generative AI to summarize it. Also, use an emotion engine to analyze the user's emotions, and provide information in a tone that corresponds to those emotions."

[0284] In this way, the present invention can efficiently digitize paper prints, automatically manage important information, and improve the user experience by providing flexible responses that take user emotions into consideration.

[0285] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0286] Step 1:

[0287] The user takes a photo of a paper print using the smartphone camera. The input is the captured image data, and the output is image data temporarily saved on the device. Specifically, the user launches the camera app and presses the capture button to generate image data. A dedicated application then automatically detects and saves the image data.

[0288] Step 2:

[0289] The device sends the captured image data to a server. The input is image data stored in the device, and the output is image data sent to the server. Specifically, a dedicated application sends the data to the server via the Internet. The data is sent using encryption technology to ensure security.

[0290] Step 3:

[0291] The server converts the received image data into text data using optical character recognition (OCR) technology. The input is the image data sent to the server, and the output is the extracted text data. Specifically, the server runs OCR software (e.g., Tesseract) to analyze the characters in the image and convert them into text. During this process, the characters in the image are detected and the corresponding character codes are generated.

[0292] Step 4:

[0293] The server analyzes the extracted text data and generates summaries and event information. The input is the text data extracted using OCR technology, and the output is the generated summaries and event information. Specifically, the server uses a generative AI (e.g., OpenAI's GPT-4) to analyze the text data and extract important information. The extracted information is then summarized and organized as event information.

[0294] Step 5:

[0295] Emotions are analyzed using the user's voice and facial expression data. The input is the voice and facial expression data emitted by the user when taking a photo, and the output is the recognized emotional data. Specifically, the server uses an emotion recognition engine (for example, Microsoft's Emotion API) to analyze the user's voice and facial expression. This analysis recognizes the user's emotional state (for example, joy, sadness, stress).

[0296] Step 6:

[0297] The server uses the recognized emotion data to adjust the content of the summary and event information. The input is the generated summary and event information and the recognized emotion data, and the output is the summary and event information adjusted based on the emotion. Specifically, the generation AI takes the emotion data into account and adjusts the tone and emphasis of the information. For example, if the user is feeling stressed, the information will be presented in a concise and emphasized form.

[0298] Step 7:

[0299] The adjusted summary and event information are sent to the terminal and displayed on the user interface. The input is the adjusted summary and event information, and the output is the information displayed on the terminal. Specifically, the server sends data to the terminal via the Internet, and a dedicated application on the terminal receives the information and displays it on the screen.

[0300] Step 8:

[0301] The device automatically registers event information in the calendar application. The input is the adjusted event information, and the output is the event information registered in the calendar application. Specifically, the device uses the calendar application's API to automatically register the event information in the schedule.

[0302] Step 9:

[0303] The user inputs a question about the summary and event information. The input is the question entered by the user, and the output is the question data sent to the server. In concrete terms, the user inputs a question into the application's input field and presses the "Submit" button.

[0304] Step 10:

[0305] The server generates a response to the question and provides it in a tone that reflects the emotion. The input is the question data and recognized emotion data sent to the server, and the output is the generated response data. Specifically, the server uses generative AI to create an appropriate response to the question and adjusts the response in tone according to the emotion data. The response data is then sent to the device, which displays it on the user interface.

[0306] (Application example 2)

[0307] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0308] Information management based on paper printouts is often inefficient and requires time and effort, creating a need for digitalization. Current digitalization systems also face the challenge of providing flexible responses and suggestions based on user emotions and preferences. In particular, food delivery services require efficient digitalization of paper menus and promotional information, allowing for suggestions based on user emotions.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0310] In this invention, the server includes means for receiving a captured image as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for recognizing a user's emotion based on the received image, means for adjusting the summary and event information based on the emotion recognition result, and means for adjusting the tone of a response based on the emotion recognition result, thereby enabling the paper menu received by the user to be digitized and enabling flexible suggestions and responses based on emotions.

[0311] The "photographed image" is still image data acquired by the user using the camera function.

[0312] "Means for receiving as data" refers to the function or process by which the server or terminal receives the captured image.

[0313] "Means for extracting text" refers to the process of obtaining text information from image data using OCR technology.

[0314] The "means for generating summary and event information" is the process of analyzing the extracted text to summarize important information.

[0315] The "calendar registration means" is a function that adds the generated summary and event information to the schedule management system.

[0316] The "means for generating a response to a question" is a process for generating an appropriate response to a question from a user based on information obtained in advance.

[0317] "Means for recognizing emotions" refers to technologies and processes that analyze and determine a user's emotional state from images and sounds.

[0318] The "means for adjusting the summary and event information based on the recognition results" is a function that dynamically changes the format and content of the summary and event information using data obtained by the emotion engine.

[0319] A "means for adjusting the tone of a response" is a process that changes the tone and phrasing of the generated response depending on the user's emotional state.

[0320] The invention is a system that allows users to digitize paper prints and further adjust the content based on the user's emotions. The system can be implemented using a smartphone or other device.

[0321] First, a user takes a photo of a paper menu or printout using their smartphone camera. The captured image is temporarily saved on the device and then sent to the server as image data. The server processes the received image data using optical character recognition (OCR) technology (e.g., pytesseract) to extract text data from the image. This extracted text data is then further analyzed to summarize important information and generate event information.

[0322] On the other hand, to recognize the user's emotions, emotion recognition technology (e.g., EmotionRecognition library) is used to analyze the voice and facial expressions of the user when taking a photo. The emotion recognition results are sent to the server, which then uses this data to adjust the content of the generated summary and event information, as well as the tone of the response.

[0323] The generated summary and event information are sent from the server to the terminal, which then displays this information on the user interface. As a specific example, if a user takes a photo of a paper menu they have received, the system digitizes the menu and generates menu recommendations based on the user's emotions. For example, if the user is excited, the system will recommend special menus or set menus that match their excitement level.

[0324] The generated information is automatically registered in a calendar application. When a user enters a question about the generated information, the question is sent to a server, and an appropriate response is generated using a generative AI model (e.g., GPT-3). The tone of this response is also adjusted based on emotion recognition data.

[0325] Examples of prompts when using a generative AI model include:

[0326] "Menu: XXXXXX

[0327] User sentiment: XXX

[0328] Please let me know what menu items you recommend."

[0329] Through prompt sentences, the system can respond flexibly according to the user's emotions. In this way, the system can digitize the paper printouts received by the user, efficiently manage important information, and provide flexible responses that take emotions into consideration.

[0330] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0331] Step 1:

[0332] The user takes a photo of the paper print using the smartphone camera.

[0333] Input: Paper print

[0334] Output: Captured image data

[0335] Specific operation: The user takes a photo of the paper menu or promotional information they received with their smartphone camera. This image data is temporarily stored in the device's memory.

[0336] Step 2:

[0337] The terminal transmits the captured image data to the server.

[0338] Input: Photographed image data

[0339] Output: Image data sent to the server

[0340] Specific operation: Image data stored on the device is uploaded to the server via the network, which prepares the image data for OCR and emotion recognition processing.

[0341] Step 3:

[0342] The server extracts text data from the image data using OCR technology.

[0343] Input: Image data

[0344] Output: Text data

[0345] Specific operation: The server uses an OCR library such as pytesseract to convert the character information contained in the image data into text format and extract the necessary text data.

[0346] Step 4:

[0347] The server analyzes the user's emotions using emotion recognition technology.

[0348] Input: User's voice and facial expression data

[0349] Output: Emotion recognition result

[0350] Specific operation: The server uses the EmotionRecognition library to analyze the user's voice and facial expression data and recognize the user's emotional state (e.g., excitement, stress, relief, etc.).

[0351] Step 5:

[0352] The server analyzes the extracted text data and generates summaries and event information.

[0353] Input: Text data, emotion recognition results

[0354] Output: Summary and event information

[0355] Specific operation: The server uses the generative AI model to analyze the text data, summarize important information, and generate necessary event information. Based on the emotion recognition results, the generated summary and event information are appropriately adjusted.

[0356] Step 6:

[0357] The server transmits the generated summary and event information to the terminal.

[0358] Input: Abstract and event information

[0359] Output: Summary and event information sent to the terminal

[0360] Specific operation: The server transmits the generated summary and event information to the user's terminal via the network.

[0361] Step 7:

[0362] The terminal displays the received summary and event information on a user interface.

[0363] Input: Abstract and event information

[0364] Output: Information displayed in the user interface

[0365] Specific operation: The terminal displays the received summary and event information on the terminal display for easy access by the user.

[0366] Step 8:

[0367] The terminal automatically registers the summary and event information in the calendar application.

[0368] Input: Abstract and event information

[0369] Output: Event information registered in the calendar

[0370] Specific operation: The terminal uses the API to automatically register summary and event information in the calendar application, helping the user manage their schedule.

[0371] Step 9:

[0372] When the user inputs a question about the summary and event information, the terminal sends the question to the server.

[0373] Input: User question

[0374] Output: The question sent to the server

[0375] Specific operation: The terminal receives the question entered by the user and transfers it to the server.

[0376] Step 10:

[0377] The server uses a generative AI model to generate appropriate responses to questions and adjusts the tone of the response based on emotion recognition results.

[0378] Input: Question, emotion recognition result

[0379] Output: The generated response

[0380] Specific operation: The server uses a generative AI model (e.g., GPT-3) based on the question content and emotion recognition results to generate an appropriate response and adjust the tone of the response.

[0381] Step 11:

[0382] The server generates a response and sends it to the terminal, which displays it on its user interface.

[0383] Input: Generated response

[0384] Output: The response displayed in the user interface

[0385] Specific operation: The server sends the generated response to the terminal, which displays it on the user interface, providing the user with an answer.

[0386] 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.

[0387] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. 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.

[0388] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0389] [Second embodiment]

[0390] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0391] 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.

[0392] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0393] 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.

[0394] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0395] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0396] 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.

[0397] 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.

[0398] 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 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.

[0399] 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.

[0400] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0401] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0402] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0403] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0404] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0405] The server then sends the generated summary and the event information contained in the printout (e.g., meeting schedules, school event dates, etc.) to the device, which receives the information and visually displays it to the user. The device also uses a calendar application to automatically add the extracted event information to the schedule.

[0406] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses generative AI to generate an appropriate response to the question and sends the response back to the device, which displays the response to the user and provides an immediate answer to the question.

[0407] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text from the schedule. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0408] The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends this question to the server, and the generation AI generates a response saying "It will be held on June 15th." The response is sent to the device and displayed to the user.

[0409] In this way, this system provides a means to easily digitize received printouts and efficiently manage important information. This allows users to prevent missing information and easily manage their schedules. Furthermore, the question and answer function allows users to instantly obtain the information they need.

[0410] The processing flow will be explained below.

[0411] Step 1:

[0412] The user takes a photo of the print with their smartphone using the smartphone's camera app, taking a picture that captures the entire print clearly.

[0413] Step 2:

[0414] The device temporarily stores the captured image and then sends it to the server as image data via a communication method such as an HTTP request.

[0415] Step 3:

[0416] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as a string of characters.

[0417] Step 4:

[0418] The server inputs the extracted text data into the generative AI, which analyzes the text data using natural language processing (NLP) techniques.

[0419] Step 5:

[0420] Generative AI analyzes text data, extracts key information and events, and generates summaries that include information such as dates, event names, and locations.

[0421] Step 6:

[0422] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0423] Step 7:

[0424] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0425] Step 8:

[0426] The user inputs a question into the terminal, for example, "On what date is the school festival in June held?"

[0427] Step 9:

[0428] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0429] Step 10:

[0430] The server inputs the received question into the generation AI, which then generates a response to the question. The generation AI analyzes the question and constructs an appropriate answer.

[0431] Step 11:

[0432] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0433] Step 12:

[0434] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0435] Example 1

[0436] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0437] Conventional methods for digitizing and managing paper-based print information require manual input and organization, which is time-consuming and labor-intensive. There is also a risk of missing important event information. Furthermore, when a question arises, users have to search for the file to confirm the information again, which is inefficient. There is a need for a system that can solve these problems, efficiently digitize paper-based print information, make it easier to manage, and enable users to quickly obtain information.

[0438] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0439] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate summaries and event information, means for registering the summaries and the event information in a calendar, means for generating responses to questions based on the summaries and the event information, means for temporarily storing the image data, means for analyzing the analyzed text data using natural language processing technology, and means for transmitting the generated responses to a user terminal. This makes it possible to efficiently digitize and manage paper print information and quickly obtain important information without missing it.

[0440] A "photographed image" is digital image data of a paper print or the like captured by a user using the camera of the terminal.

[0441] "Means for receiving as data" refers to a technology that enables the procedure for sending captured images to a server and for the server to receive them.

[0442] The "means for extracting text" is a technology that uses optical character recognition (OCR) technology to identify character information from an image and extract it as text data.

[0443] The "means for generating summary and event information" refers to a technology for analyzing extracted text data, identifying important information and summarizing it briefly, and extracting information related to a specific event.

[0444] "Means of registering to a calendar" refers to a technology that automatically inputs the extracted event information into a schedule management application, and typically uses an API.

[0445] "Means for generating responses to questions" refers to technology that uses a generative AI model to create appropriate answers to questions from users.

[0446] "Means for temporarily storing image data" refers to technology that temporarily stores captured images within the terminal.

[0447] The "means of analysis using natural language processing technology" is a technology that analyzes the extracted text data using natural language processing technology, and extracts and summarizes important information.

[0448] The "means for transmitting the generated response to the user terminal" is a technique for transmitting the response generated by the server to the user terminal.

[0449] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0450] First, the user takes a photo of a paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data. The device then uses the HTTP POST method over the Internet.

[0451] The server processes the received image data using optical character recognition (OCR) technology and extracts text data from the image. Specifically, it uses Google Cloud Vision and Tesseract to extract text. Using this OCR technology, the server recognizes the text information in the image and extracts it as text data.

[0452] The server then analyzes the extracted text data using natural language processing (NLP) techniques, such as SpaCy and NLTK. The server identifies important information from the analyzed text data and generates summaries and event information, which is then converted into JSON format.

[0453] The server sends the generated summary and event information to the user's device, which receives the information and visually displays it to the user. In addition, the device automatically schedules the extracted event information using a calendar application such as Google Calendar or iOS Calendar.

[0454] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses a generative AI model (e.g., GPT-4) to generate an appropriate response to the question and sends the response back to the device. The generated response is displayed on the user's device, providing an immediate answer to the question.

[0455] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule with their smartphone camera, and the device sends this image to the server. The server uses OCR technology to extract the text from the schedule and analyzes it. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0456] This generated information is sent from the server to the device, and the device automatically registers this information in a calendar. For example, if a user inputs a question such as "What day is the school festival held in June?", the device sends this question to the server. The server uses a generative AI model (e.g., GPT-4) to generate a response such as "It will be held on June 15th" and sends it to the device. The device then displays this response to the user.

[0457] An example of a prompt is the question, "What day is the school festival in June?" Using such prompts, the generative AI model can generate accurate responses and provide them to the user quickly.

[0458] As described above, the present invention provides a means for easily digitizing received printouts and efficiently managing important information. This allows users to prevent overlooking information and easily manage their schedules. In addition, the question-and-answer function allows users to instantly obtain the information they need.

[0459] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0460] Step 1:

[0461] A user photographs a paper print.

[0462] Specific behavior:

[0463] The user opens the camera app on their smartphone and takes a picture of the paper print.

[0464] input:

[0465] Paper print.

[0466] output:

[0467] Digital image data stored on a smartphone.

[0468] Step 2:

[0469] The terminal temporarily stores the image data and sends it to the server.

[0470] Specific behavior:

[0471] The device temporarily stores the captured image data in its internal storage, and then sends the image data to the server using the HTTP POST method.

[0472] input:

[0473] The captured image data.

[0474] output:

[0475] Image data sent to the server.

[0476] Step 3:

[0477] The server converts the image data into text using OCR technology.

[0478] Specific behavior:

[0479] The server uses OCR technology such as Google Cloud Vision API to extract text from the received image data.

[0480] input:

[0481] Image data received by the server.

[0482] output:

[0483] The extracted text data.

[0484] Step 4:

[0485] The server analyzes the text data and extracts and summarizes important information.

[0486] Specific behavior:

[0487] The server uses natural language processing technologies such as SpaCy and NLTK to analyze the text data, extract key information, and generate summaries.

[0488] input:

[0489] The extracted text data.

[0490] output:

[0491] Parsed summary and event information.

[0492] Step 5:

[0493] The server sends the summary and event information to the terminal.

[0494] Specific behavior:

[0495] The server converts the summary and event information into JSON format and sends it to the terminal using the HTTP POST method.

[0496] input:

[0497] Abstract and event information.

[0498] output:

[0499] Summary and event information sent to the terminal.

[0500] Step 6:

[0501] The information received by the device is automatically registered in the calendar.

[0502] Specific behavior:

[0503] The device parses the received JSON data and automatically registers the schedule using the Google Calendar API.

[0504] input:

[0505] Summary and event information received from the server.

[0506] output:

[0507] Event information registered in Google Calendar.

[0508] Step 7:

[0509] The user enters a question for information into the terminal.

[0510] Specific behavior:

[0511] Users enter questions into the device via a dedicated app.

[0512] input:

[0513] Question content.

[0514] output:

[0515] Questions typed into the terminal.

[0516] Step 8:

[0517] The terminal sends a question to the server.

[0518] Specific behavior:

[0519] The device uses a REST API to send the user's question in JSON format to the server.

[0520] input:

[0521] The question entered by the user.

[0522] output:

[0523] The question data sent to the server.

[0524] Step 9:

[0525] The server generates a response using a generative AI model.

[0526] Specific behavior:

[0527] The server uses a generative AI model (e.g., GPT-4) to generate appropriate responses to questions.

[0528] input:

[0529] User question data.

[0530] output:

[0531] The generated response data.

[0532] Step 10:

[0533] The terminal receives the response and displays it to the user.

[0534] Specific behavior:

[0535] The terminal receives the response data from the server and displays it on the screen.

[0536] input:

[0537] Response data from the server.

[0538] output:

[0539] The response shown to the user.

[0540] (Application example 1)

[0541] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0542] In brick-and-mortar stores, managing information such as paper promotional materials and event posters is time-consuming and laborious. Furthermore, while there is a need to digitize and share paper information to manage schedules and obtain information instantly, there is a lack of efficient ways to do this. This often results in oversight of promotional content and event information, leading to insufficient information sharing among staff.

[0543] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0544] In this invention, the server includes means for digitizing photographed paper promotional materials and automatically registering the extracted event information in a store's event calendar, means for using optical character recognition (OCR) technology to convert the received images into text data, and means for utilizing an API to automatically register the generated summary and event information in a calendar application, thereby enabling efficient digitization of paper information and automatic management and sharing of important event information.

[0545] "Captured images" are still image data captured by devices such as smartphones and cameras.

[0546] "Means for receiving as data" refers to the functions and protocols for transferring captured images to a server or other storage device.

[0547] "Means for extracting text" refers to the function of analyzing and extracting text information from image data.

[0548] The "means for generating summary and event information" refers to a function for selecting important information from the extracted text and generating a concise summary or specific event information.

[0549] "Means for registering in a calendar" refers to a function that automatically inputs the generated summary and event information into a calendar application and registers it as a schedule.

[0550] The "means for generating a response to a question" refers to a function for generating an appropriate answer to a question from a user based on the summary and event information.

[0551] "Optical character recognition (OCR) technology" refers to technology for reading character data from images.

[0552] "Using an API" means using an interface to exchange functions and data between software.

[0553] The "means for automatically registering event information in the store's event calendar" is a function that automatically adds the generated event information to the calendar system used by the store staff.

[0554] "Digitizing promotional materials" refers to the process of converting promotional content written on paper into electronic data.

[0555] This invention is a system that improves the efficiency of information management for promotional materials and event posters in brick-and-mortar stores. This system provides a means for photographing paper promotional materials with a smartphone and sending the data to a server for processing.

[0556] First, a user takes a photo of a paper promotional material using a smartphone. The captured image is temporarily saved on the smartphone and then sent to a server as image data. The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image. For example, the pytesseract library is used for this OCR technology.

[0557] The server then analyzes the extracted text data and generates important information as summaries and event information, which are then automatically added to the store's event calendar using an API, such as the Google Calendar API.

[0558] Users can enter questions about promotions and events through a smartphone app. These questions are sent to a server, which uses a generative AI model to generate an appropriate response to the question. The generated response is displayed on the smartphone and provided to the user instantly. This AI model uses, for example, OpenAI's GPT-3.

[0559] As a concrete example, let's explain how a store staff member takes a photo of a new promotional poster with their smartphone, and the system automatically registers that information in the event calendar. The staff member takes a photo of the poster and immediately sends the image to the server. The server uses OCR to extract the text and generates a summary and event information, such as "There will be a Christmas sale on December 5th and a year-end special sale on December 12th." This information is automatically registered in the calendar app.

[0560] If a staff member types a question like, "What date is the next event?", the system sends the following prompt to the generative AI model:

[0561] Examples of prompts:

[0562] Answer the questions based on the event information below: "There will be a Christmas sale on December 5th and a year-end sale on December 12th."

[0563] Question: "What date is the next event?"

[0564] answer:

[0565] Based on this prompt, the server uses a generative AI model to generate a response to the question and displays an answer such as "The next event is on December 5th" on the staff member's smartphone.

[0566] This allows store staff to efficiently digitize and manage promotional materials, and makes it easier to manage and share important event information.

[0567] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0568] Step 1:

[0569] The user takes a photo of a paper promotional material with their smartphone. The input data is the captured image, which is temporarily saved on the smartphone. The output is the image data saved on the smartphone.

[0570] Step 2:

[0571] The smartphone sends the stored image data to the server. The input data is the image data stored on the smartphone, which is uploaded to the server. The output is the image data sent to the server.

[0572] Step 3:

[0573] The server converts the received image data into text data using optical character recognition (OCR) technology. Specifically, it uses the pytesseract library to extract text information from the image. The input data is the image data sent to the server, and the output is the extracted text data.

[0574] Step 4:

[0575] The server analyzes the extracted text data and generates important information as summaries and event information. Here, important keywords and date information are extracted to create summaries. The input data is the extracted text data, and the output is the summarized information and generated event information.

[0576] Step 5:

[0577] The server automatically registers the generated summary and event information in the store's event calendar using an API. Specifically, the event information is added to the calendar using the Google Calendar API, etc. The input data is the summary and event information, and the output is the event data registered in the calendar.

[0578] Step 6:

[0579] Users enter questions about promotions and events through a smartphone app. The input data is the question text entered by the user, which is sent to the server. The output is the question data sent to the server.

[0580] Step 7:

[0581] The server uses a generative AI model to generate an appropriate response to the question. Specifically, it generates a prompt sentence that combines the question data with summary and event information, and inputs it into a generative AI model such as OpenAI's GPT-3. The server then receives the generated answer. The input data is the question data and event information, and the output is the response data to the question.

[0582] Step 8:

[0583] The server sends the generated response to the smartphone. The input data is the response data to the question, and the output is the response data sent to the smartphone. The user can check the answer on the smartphone.

[0584] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0585] The present invention combines a system that photographs paper prints received by a user, digitizes and summarizes the contents using OCR technology and generative AI, and further combines it with an emotion engine that recognizes the user's emotions. The main embodiments of the present invention are described below.

[0586] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0587] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0588] The generative AI uses the analyzed text data to generate summaries and event information, while the emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends the recognition results to the server.

[0589] The server then tailors the content of the summary and event information based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, the server can generate a summary in a format that highlights important information.

[0590] The server then sends the generated summary and event information to the device, which then displays the information on its user interface and automatically registers the event information in its schedule using a calendar application.

[0591] When a user enters a question about the summary or event information, the device sends the question to the server. The server uses generative AI to generate an appropriate response to the question, again incorporating the recognition results of the emotion engine. For example, if the user is feeling doubtful or anxious, the tone of the response can be gentler.

[0592] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text of the schedule. The emotion engine also analyzes the voice and facial expressions used by the user when taking the photo, and sends emotional data to the server.

[0593] Based on the analysis results and emotion data, the AI ​​generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation start," and summarizes it according to the emotion. For example, if the user is excited, the AI ​​will present a summary in a positive tone.

[0594] The generated information is sent from the server to the device, which then automatically registers it in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends the question to the server, and the generation AI generates a response saying "It will be held on June 15th." Here too, the results of the emotion engine are reflected, and the response is displayed in an appropriate tone.

[0595] In this way, the system not only digitizes received prints and efficiently manages important information, but also provides flexible responses that take user emotions into consideration, significantly improving the user experience.

[0596] The processing flow will be explained below.

[0597] Step 1:

[0598] Users take a photo of the print using their smartphone camera, and audio guidance is displayed to help them take a clear photo.

[0599] Step 2:

[0600] The device temporarily stores the captured image and then sends it to the server as image data. The image data is sent securely using HTTP requests and SSL.

[0601] Step 3:

[0602] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as string data.

[0603] Step 4:

[0604] The server activates an emotion engine to analyze the voice and facial expression data emitted by the user when taking a photo. The emotion engine analyzes the voice waveform and facial features to generate data that identifies the user's emotional state.

[0605] Step 5:

[0606] The server inputs the text data extracted by OCR into the generation AI, and at the same time, the user's emotional data is also passed to the generation AI, which analyzes it using natural language processing (NLP) technology.

[0607] Step 6:

[0608] The generative AI extracts key information and events from text and emotion data to generate summaries, adjusting the tone and emphasis of the summaries depending on the emotion.

[0609] Step 7:

[0610] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0611] Step 8:

[0612] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0613] Step 9:

[0614] The user enters a question about the summarized information or event information, and the question can be entered by text or voice.

[0615] Step 10:

[0616] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0617] Step 11:

[0618] The server uses generative AI and an emotion engine to generate appropriate responses to questions, adjusting the content and tone of the response depending on the user's emotional state.

[0619] Step 12:

[0620] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0621] Step 13:

[0622] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0623] In this way, users can not only easily digitize prints and efficiently manage important information, but also receive more personalized information through the emotion engine.

[0624] Example 2

[0625] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0626] Traditional paper printouts are not digitized, making it difficult to manage important information. Furthermore, there are insufficient means to efficiently extract necessary information from digitized information and provide flexible responses based on user emotions. Therefore, improving user information management and user experience has become a challenge.

[0627] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0628] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for analyzing the user's voice and facial expression to recognize the user's emotion, means for adjusting the content of the summary and the event information based on the emotion, means for registering the summary and the event information in a calendar, and means for generating responses to questions based on the summary and the event information. This makes it possible to efficiently digitize paper printouts and flexibly provide information and responses that take the user's emotion into consideration.

[0629] The "means for receiving captured images as data" refers to a device or program for receiving captured image data sent from the user's terminal.

[0630] "Means for extracting text using said data" refers to a device or program that analyzes and extracts text data from received image data using optical character recognition technology.

[0631] The "means for analyzing the extracted text and generating a summary and event information" refers to a device or program that analyzes the extracted text data, summarizes important information, and generates event information.

[0632] "Means for analyzing the user's voice and facial expressions in order to recognize the user's emotions" refers to a device or program that acquires data on the voice and facial expressions made by the user while taking a photograph, and recognizes and analyzes the user's emotions from that data.

[0633] The "means for adjusting the content of the summary and the event information based on the emotion" refers to a device or program that adjusts and optimizes the content and tone of the generated summary and event information based on the analyzed user emotion data.

[0634] The "means for registering in a calendar using the summary and the event information" is a device or program that automatically registers the generated summary and event information in a calendar application.

[0635] The "means for generating a response to a question based on the summary and the event information" refers to a device or program that generates an appropriate response to a question from a user related to the summary and the event information.

[0636] The present invention relates to a system that combines a user terminal, a server, and related software to digitize paper prints, extract important information, and provide flexible responses to users based on that information. Furthermore, the present invention realizes a better user experience by recognizing the user's emotions and reflecting them in the information provided and responses.

[0637] First, the user takes a photo of a paper print using a device such as a smartphone. A dedicated application installed on the device supports this process. The captured image is temporarily stored on the device and then sent to a server. The server receives the captured image as data. This action is carried out over the Internet, and secure communication is ensured using encryption technology.

[0638] The server then converts the received image data into text using optical character recognition (OCR) technology, such as Tesseract, an OCR software that enables highly accurate character recognition and accurately extracts text from images.

[0639] The extracted text data is analyzed by a generative AI (e.g., OpenAI's GPT-4). This analysis summarizes important information and generates event information. For example, events such as "April entrance ceremony," "June school festival," and "December winter vacation start" are extracted.

[0640] At the same time, the server analyzes the user's voice and facial expressions to recognize their emotions. An emotion recognition engine (for example, Microsoft's Emotion API) is used to do this. The server analyzes the user's emotions from the voice and facial expressions the user makes when taking the photo.

[0641] The server adjusts the content of the summary and event information based on the acquired emotional data. For example, if the user is feeling stressed, the information can be presented in a more concise form with the important parts emphasized. The generative AI does this and provides information in a format that is easy for the user to understand.

[0642] The server sends the summary and event information to the device, which then displays the information on the user interface. Furthermore, the device uses an API to automatically register the information in a calendar application (e.g., Google Calendar), eliminating the need for the user to manually enter the information.

[0643] Additionally, when users input questions about the summary and event information, the device sends the questions to the server, which uses generative AI to generate appropriate responses and adjusts the tone of the response based on emotion recognition results. For example, if the user is feeling anxious, the response will be delivered in a gentler tone.

[0644] As a concrete example, let's consider the case where a user takes a photo of a printed annual schedule given to them by their school. The user takes a photo of the schedule using their smartphone camera. The device then sends this image to a server. The server uses OCR technology to extract the text from the schedule and analyzes it using a generation AI. The server also analyzes the user's voice and facial expressions while taking the photo and sends emotional data to the server. Based on the analysis results and emotional data, the generation AI generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation begins." If the user is excited, it presents a summary in a positive tone. The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user inputs a question such as "What day is the June school festival held?", the server uses the generation AI to generate a response such as "It will be held on June 15th," and displays the response in an appropriate tone reflecting the results of the emotion engine.

[0645] An example of a prompt is, "Use OCR technology to convert a photo of the user's annual schedule printout into text, and then use a generative AI to summarize it. Also, use an emotion engine to analyze the user's emotions, and provide information in a tone that corresponds to those emotions."

[0646] In this way, the present invention can efficiently digitize paper prints, automatically manage important information, and improve the user experience by providing flexible responses that take user emotions into consideration.

[0647] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0648] Step 1:

[0649] The user takes a photo of a paper print using the smartphone camera. The input is the captured image data, and the output is image data temporarily saved on the device. Specifically, the user launches the camera app and presses the capture button to generate image data. A dedicated application then automatically detects and saves the image data.

[0650] Step 2:

[0651] The device sends the captured image data to a server. The input is image data stored in the device, and the output is image data sent to the server. Specifically, a dedicated application sends the data to the server via the Internet. The data is sent using encryption technology to ensure security.

[0652] Step 3:

[0653] The server converts the received image data into text data using optical character recognition (OCR) technology. The input is the image data sent to the server, and the output is the extracted text data. Specifically, the server runs OCR software (e.g., Tesseract) to analyze the characters in the image and convert them into text. During this process, the characters in the image are detected and the corresponding character codes are generated.

[0654] Step 4:

[0655] The server analyzes the extracted text data and generates summaries and event information. The input is the text data extracted using OCR technology, and the output is the generated summaries and event information. Specifically, the server uses a generative AI (e.g., OpenAI's GPT-4) to analyze the text data and extract important information. The extracted information is then summarized and organized as event information.

[0656] Step 5:

[0657] Emotions are analyzed using the user's voice and facial expression data. The input is the voice and facial expression data emitted by the user when taking a photo, and the output is the recognized emotional data. Specifically, the server uses an emotion recognition engine (for example, Microsoft's Emotion API) to analyze the user's voice and facial expression. This analysis recognizes the user's emotional state (for example, joy, sadness, stress).

[0658] Step 6:

[0659] The server uses the recognized emotion data to adjust the content of the summary and event information. The input is the generated summary and event information and the recognized emotion data, and the output is the summary and event information adjusted based on the emotion. Specifically, the generation AI takes the emotion data into account and adjusts the tone and emphasis of the information. For example, if the user is feeling stressed, the information will be presented in a concise and emphasized form.

[0660] Step 7:

[0661] The adjusted summary and event information are sent to the terminal and displayed on the user interface. The input is the adjusted summary and event information, and the output is the information displayed on the terminal. Specifically, the server sends data to the terminal via the Internet, and a dedicated application on the terminal receives the information and displays it on the screen.

[0662] Step 8:

[0663] The device automatically registers event information in the calendar application. The input is the adjusted event information, and the output is the event information registered in the calendar application. Specifically, the device uses the calendar application's API to automatically register the event information in the schedule.

[0664] Step 9:

[0665] The user inputs a question about the summary and event information. The input is the question entered by the user, and the output is the question data sent to the server. In concrete terms, the user inputs a question into the application's input field and presses the "Submit" button.

[0666] Step 10:

[0667] The server generates a response to the question and provides it in a tone that reflects the emotion. The input is the question data and recognized emotion data sent to the server, and the output is the generated response data. Specifically, the server uses generative AI to create an appropriate response to the question and adjusts the response in tone according to the emotion data. The response data is then sent to the device, which displays it on the user interface.

[0668] (Application example 2)

[0669] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0670] Information management based on paper printouts is often inefficient and requires time and effort, creating a need for digitalization. Current digitalization systems also face the challenge of providing flexible responses and suggestions based on user emotions and preferences. In particular, food delivery services require efficient digitalization of paper menus and promotional information, allowing for suggestions based on user emotions.

[0671] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0672] In this invention, the server includes means for receiving a captured image as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for recognizing a user's emotion based on the received image, means for adjusting the summary and event information based on the emotion recognition result, and means for adjusting the tone of a response based on the emotion recognition result, thereby enabling the paper menu received by the user to be digitized and enabling flexible suggestions and responses based on emotions.

[0673] The "photographed image" is still image data acquired by the user using the camera function.

[0674] "Means for receiving as data" refers to the function or process by which the server or terminal receives the captured image.

[0675] "Means for extracting text" refers to the process of obtaining text information from image data using OCR technology.

[0676] The "means for generating summary and event information" is the process of analyzing the extracted text to summarize important information.

[0677] The "calendar registration means" is a function that adds the generated summary and event information to the schedule management system.

[0678] The "means for generating a response to a question" is a process for generating an appropriate response to a question from a user based on information obtained in advance.

[0679] "Means for recognizing emotions" refers to technologies and processes that analyze and determine a user's emotional state from images and sounds.

[0680] The "means for adjusting the summary and event information based on the recognition results" is a function that dynamically changes the format and content of the summary and event information using data obtained by the emotion engine.

[0681] A "means for adjusting the tone of a response" is a process that changes the tone and phrasing of the generated response depending on the user's emotional state.

[0682] The invention is a system that allows users to digitize paper prints and further adjust the content based on the user's emotions. The system can be implemented using a smartphone or other device.

[0683] First, a user takes a photo of a paper menu or printout using their smartphone camera. The captured image is temporarily saved on the device and then sent to the server as image data. The server processes the received image data using optical character recognition (OCR) technology (e.g., pytesseract) to extract text data from the image. This extracted text data is then further analyzed to summarize important information and generate event information.

[0684] On the other hand, to recognize the user's emotions, emotion recognition technology (e.g., EmotionRecognition library) is used to analyze the voice and facial expressions of the user when taking a photo. The emotion recognition results are sent to the server, which then uses this data to adjust the content of the generated summary and event information, as well as the tone of the response.

[0685] The generated summary and event information are sent from the server to the terminal, which then displays this information on the user interface. As a specific example, if a user takes a photo of a paper menu they have received, the system digitizes the menu and generates menu recommendations based on the user's emotions. For example, if the user is excited, the system will recommend special menus or set menus that match their excitement level.

[0686] The generated information is automatically registered in a calendar application. When a user enters a question about the generated information, the question is sent to a server, and an appropriate response is generated using a generative AI model (e.g., GPT-3). The tone of this response is also adjusted based on emotion recognition data.

[0687] Examples of prompts when using a generative AI model include:

[0688] "Menu: XXXXXX

[0689] User sentiment: XXX

[0690] Please let me know what menu items you recommend."

[0691] Through prompt sentences, the system can respond flexibly according to the user's emotions. In this way, the system can digitize the paper printouts received by the user, efficiently manage important information, and provide flexible responses that take emotions into consideration.

[0692] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0693] Step 1:

[0694] The user takes a photo of the paper print using the smartphone camera.

[0695] Input: Paper print

[0696] Output: Captured image data

[0697] Specific operation: The user takes a photo of the paper menu or promotional information they received with their smartphone camera. This image data is temporarily stored in the device's memory.

[0698] Step 2:

[0699] The terminal transmits the captured image data to the server.

[0700] Input: Photographed image data

[0701] Output: Image data sent to the server

[0702] Specific operation: Image data stored on the device is uploaded to the server via the network, which prepares the image data for OCR and emotion recognition processing.

[0703] Step 3:

[0704] The server extracts text data from the image data using OCR technology.

[0705] Input: Image data

[0706] Output: Text data

[0707] Specific operation: The server uses an OCR library such as pytesseract to convert the character information contained in the image data into text format and extract the necessary text data.

[0708] Step 4:

[0709] The server analyzes the user's emotions using emotion recognition technology.

[0710] Input: User's voice and facial expression data

[0711] Output: Emotion recognition result

[0712] Specific operation: The server uses the EmotionRecognition library to analyze the user's voice and facial expression data and recognize the user's emotional state (e.g., excitement, stress, relief, etc.).

[0713] Step 5:

[0714] The server analyzes the extracted text data and generates summaries and event information.

[0715] Input: Text data, emotion recognition results

[0716] Output: Summary and event information

[0717] Specific operation: The server uses the generative AI model to analyze the text data, summarize important information, and generate necessary event information. Based on the emotion recognition results, the generated summary and event information are appropriately adjusted.

[0718] Step 6:

[0719] The server transmits the generated summary and event information to the terminal.

[0720] Input: Abstract and event information

[0721] Output: Summary and event information sent to the terminal

[0722] Specific operation: The server transmits the generated summary and event information to the user's terminal via the network.

[0723] Step 7:

[0724] The terminal displays the received summary and event information on a user interface.

[0725] Input: Abstract and event information

[0726] Output: Information displayed in the user interface

[0727] Specific operation: The terminal displays the received summary and event information on the terminal display for easy access by the user.

[0728] Step 8:

[0729] The terminal automatically registers the summary and event information in the calendar application.

[0730] Input: Abstract and event information

[0731] Output: Event information registered in the calendar

[0732] Specific operation: The terminal uses the API to automatically register summary and event information in the calendar application, helping the user manage their schedule.

[0733] Step 9:

[0734] When the user inputs a question about the summary and event information, the terminal sends the question to the server.

[0735] Input: User question

[0736] Output: The question sent to the server

[0737] Specific operation: The terminal receives the question entered by the user and transfers it to the server.

[0738] Step 10:

[0739] The server uses a generative AI model to generate appropriate responses to questions and adjusts the tone of the response based on emotion recognition results.

[0740] Input: Question, emotion recognition result

[0741] Output: The generated response

[0742] Specific operation: The server uses a generative AI model (e.g., GPT-3) based on the question content and emotion recognition results to generate an appropriate response and adjust the tone of the response.

[0743] Step 11:

[0744] The server generates a response and sends it to the terminal, which displays it on its user interface.

[0745] Input: Generated response

[0746] Output: The response displayed in the user interface

[0747] Specific operation: The server sends the generated response to the terminal, which displays it on the user interface, providing the user with an answer.

[0748] 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.

[0749] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. 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.

[0750] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0751] [Third embodiment]

[0752] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0753] 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.

[0754] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[0755] 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.

[0756] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0757] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0758] 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.

[0759] 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.

[0760] 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 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.

[0761] 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.

[0762] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0763] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0764] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0765] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0766] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0767] The server then sends the generated summary and the event information contained in the printout (e.g., meeting schedules, school event dates, etc.) to the device, which receives the information and visually displays it to the user. The device also uses a calendar application to automatically add the extracted event information to the schedule.

[0768] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses generative AI to generate an appropriate response to the question and sends the response back to the device, which displays the response to the user and provides an immediate answer to the question.

[0769] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text from the schedule. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0770] The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends this question to the server, and the generation AI generates a response saying "It will be held on June 15th." The response is sent to the device and displayed to the user.

[0771] In this way, this system provides a means to easily digitize received printouts and efficiently manage important information. This allows users to prevent missing information and easily manage their schedules. Furthermore, the question and answer function allows users to instantly obtain the information they need.

[0772] The processing flow will be explained below.

[0773] Step 1:

[0774] The user takes a photo of the print with their smartphone using the smartphone's camera app, taking a picture that captures the entire print clearly.

[0775] Step 2:

[0776] The device temporarily stores the captured image and then sends it to the server as image data via a communication method such as an HTTP request.

[0777] Step 3:

[0778] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as a string of characters.

[0779] Step 4:

[0780] The server inputs the extracted text data into the generative AI, which analyzes the text data using natural language processing (NLP) techniques.

[0781] Step 5:

[0782] Generative AI analyzes text data, extracts key information and events, and generates summaries that include information such as dates, event names, and locations.

[0783] Step 6:

[0784] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0785] Step 7:

[0786] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0787] Step 8:

[0788] The user inputs a question into the terminal, for example, "On what date is the school festival in June held?"

[0789] Step 9:

[0790] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0791] Step 10:

[0792] The server inputs the received question into the generation AI, which then generates a response to the question. The generation AI analyzes the question and constructs an appropriate answer.

[0793] Step 11:

[0794] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0795] Step 12:

[0796] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0797] Example 1

[0798] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0799] Conventional methods for digitizing and managing paper-based print information require manual input and organization, which is time-consuming and labor-intensive. There is also a risk of missing important event information. Furthermore, when a question arises, users have to search for the file to confirm the information again, which is inefficient. There is a need for a system that can solve these problems, efficiently digitize paper-based print information, make it easier to manage, and enable users to quickly obtain information.

[0800] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0801] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate summaries and event information, means for registering the summaries and the event information in a calendar, means for generating responses to questions based on the summaries and the event information, means for temporarily storing the image data, means for analyzing the analyzed text data using natural language processing technology, and means for transmitting the generated responses to a user terminal. This makes it possible to efficiently digitize and manage paper print information and quickly obtain important information without missing it.

[0802] A "photographed image" is digital image data of a paper print or the like captured by a user using the camera of the terminal.

[0803] "Means for receiving as data" refers to a technology that enables the procedure for sending captured images to a server and for the server to receive them.

[0804] The "means for extracting text" is a technology that uses optical character recognition (OCR) technology to identify character information from an image and extract it as text data.

[0805] The "means for generating summary and event information" refers to a technology for analyzing extracted text data, identifying important information and summarizing it briefly, and extracting information related to a specific event.

[0806] "Means of registering to a calendar" refers to a technology that automatically inputs the extracted event information into a schedule management application, and typically uses an API.

[0807] "Means for generating responses to questions" refers to technology that uses a generative AI model to create appropriate answers to questions from users.

[0808] "Means for temporarily storing image data" refers to technology that temporarily stores captured images within the terminal.

[0809] The "means of analysis using natural language processing technology" is a technology that analyzes the extracted text data using natural language processing technology, and extracts and summarizes important information.

[0810] The "means for transmitting the generated response to the user terminal" is a technique for transmitting the response generated by the server to the user terminal.

[0811] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[0812] First, the user takes a photo of a paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data. The device then uses the HTTP POST method over the Internet.

[0813] The server processes the received image data using optical character recognition (OCR) technology and extracts text data from the image. Specifically, text extraction is performed using Google Cloud Vision or Tesseract. Using this OCR technology, the server recognizes the character information in the image and extracts it as text data.

[0814] The server then analyzes the extracted text data using natural language processing (NLP) techniques, such as SpaCy and NLTK. The server identifies important information from the analyzed text data and generates summaries and event information, which is then converted into JSON format.

[0815] The server sends the generated summary and event information to the user's device, which receives the information and visually displays it to the user. In addition, the device automatically schedules the extracted event information using a calendar application such as Google Calendar or iOS Calendar.

[0816] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses a generative AI model (e.g., GPT-4) to generate an appropriate response to the question and sends the response back to the device. The generated response is displayed on the user's device, providing an immediate answer to the question.

[0817] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule with their smartphone camera, and the device sends this image to the server. The server uses OCR technology to extract the text from the schedule and analyzes it. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[0818] This generated information is sent from the server to the device, and the device automatically registers this information in a calendar. For example, if a user inputs a question such as "What day is the school festival held in June?", the device sends this question to the server. The server uses a generative AI model (e.g., GPT-4) to generate a response such as "It will be held on June 15th" and sends it to the device. The device then displays this response to the user.

[0819] An example of a prompt is the question, "What day is the school festival in June?" Using such prompts, the generative AI model can generate accurate responses and provide them to the user quickly.

[0820] As described above, the present invention provides a means for easily digitizing received printouts and efficiently managing important information. This allows users to prevent overlooking information and easily manage their schedules. In addition, the question-and-answer function allows users to instantly obtain the information they need.

[0821] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0822] Step 1:

[0823] A user photographs a paper print.

[0824] Specific behavior:

[0825] The user opens the camera app on their smartphone and takes a picture of the paper print.

[0826] input:

[0827] Paper print.

[0828] output:

[0829] Digital image data stored on a smartphone.

[0830] Step 2:

[0831] The terminal temporarily stores the image data and sends it to the server.

[0832] Specific behavior:

[0833] The device temporarily stores the captured image data in its internal storage, and then sends the image data to the server using the HTTP POST method.

[0834] input:

[0835] The captured image data.

[0836] output:

[0837] Image data sent to the server.

[0838] Step 3:

[0839] The server converts the image data into text using OCR technology.

[0840] Specific behavior:

[0841] The server uses OCR technology such as Google Cloud Vision API to extract text from the received image data.

[0842] input:

[0843] Image data received by the server.

[0844] output:

[0845] The extracted text data.

[0846] Step 4:

[0847] The server analyzes the text data and extracts and summarizes important information.

[0848] Specific behavior:

[0849] The server uses natural language processing technologies such as SpaCy and NLTK to analyze the text data, extract key information, and generate summaries.

[0850] input:

[0851] The extracted text data.

[0852] output:

[0853] Parsed summary and event information.

[0854] Step 5:

[0855] The server sends the summary and event information to the terminal.

[0856] Specific behavior:

[0857] The server converts the summary and event information into JSON format and sends it to the terminal using the HTTP POST method.

[0858] input:

[0859] Abstract and event information.

[0860] output:

[0861] Summary and event information sent to the terminal.

[0862] Step 6:

[0863] The information received by the device is automatically registered in the calendar.

[0864] Specific behavior:

[0865] The device parses the received JSON data and automatically registers the schedule using the Google Calendar API.

[0866] input:

[0867] Summary and event information received from the server.

[0868] output:

[0869] Event information registered in Google Calendar.

[0870] Step 7:

[0871] The user enters a question for information into the terminal.

[0872] Specific behavior:

[0873] Users enter questions into the device via a dedicated app.

[0874] input:

[0875] Question content.

[0876] output:

[0877] Questions typed into the terminal.

[0878] Step 8:

[0879] The terminal sends a question to the server.

[0880] Specific behavior:

[0881] The device uses a REST API to send the user's question in JSON format to the server.

[0882] input:

[0883] The question entered by the user.

[0884] output:

[0885] The question data sent to the server.

[0886] Step 9:

[0887] The server generates a response using a generative AI model.

[0888] Specific behavior:

[0889] The server uses a generative AI model (e.g., GPT-4) to generate appropriate responses to questions.

[0890] input:

[0891] User question data.

[0892] output:

[0893] The generated response data.

[0894] Step 10:

[0895] The terminal receives the response and displays it to the user.

[0896] Specific behavior:

[0897] The terminal receives the response data from the server and displays it on the screen.

[0898] input:

[0899] Response data from the server.

[0900] output:

[0901] The response shown to the user.

[0902] (Application example 1)

[0903] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0904] In brick-and-mortar stores, managing information such as paper promotional materials and event posters is time-consuming and laborious. Furthermore, while there is a need to digitize and share paper information to manage schedules and obtain information instantly, there is a lack of efficient ways to do this. This often results in oversight of promotional content and event information, leading to insufficient information sharing among staff.

[0905] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0906] In this invention, the server includes means for digitizing photographed paper promotional materials and automatically registering the extracted event information in a store's event calendar, means for using optical character recognition (OCR) technology to convert the received images into text data, and means for utilizing an API to automatically register the generated summary and event information in a calendar application, thereby enabling efficient digitization of paper information and automatic management and sharing of important event information.

[0907] "Captured images" are still image data captured by devices such as smartphones and cameras.

[0908] "Means for receiving as data" refers to the functions and protocols for transferring captured images to a server or other storage device.

[0909] "Means for extracting text" refers to the function of analyzing and extracting text information from image data.

[0910] The "means for generating summary and event information" refers to a function for selecting important information from the extracted text and generating a concise summary or specific event information.

[0911] "Means for registering in a calendar" refers to a function that automatically inputs the generated summary and event information into a calendar application and registers it as a schedule.

[0912] The "means for generating a response to a question" refers to a function for generating an appropriate answer to a question from a user based on the summary and event information.

[0913] "Optical character recognition (OCR) technology" refers to technology for reading character data from images.

[0914] "Using an API" means using an interface to exchange functions and data between software.

[0915] The "means for automatically registering event information in the store's event calendar" is a function that automatically adds the generated event information to the calendar system used by the store staff.

[0916] "Digitizing promotional materials" refers to the process of converting promotional content written on paper into electronic data.

[0917] This invention is a system that improves the efficiency of information management for promotional materials and event posters in brick-and-mortar stores. This system provides a means for photographing paper promotional materials with a smartphone and sending the data to a server for processing.

[0918] First, a user takes a photo of a paper promotional material using a smartphone. The captured image is temporarily saved on the smartphone and then sent to a server as image data. The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image. For example, the pytesseract library is used for this OCR technology.

[0919] The server then analyzes the extracted text data and generates important information as summaries and event information, which are then automatically added to the store's event calendar using an API, such as the Google Calendar API.

[0920] Users can enter questions about promotions and events through a smartphone app. These questions are sent to a server, which uses a generative AI model to generate an appropriate response to the question. The generated response is displayed on the smartphone and provided to the user instantly. This AI model uses, for example, OpenAI's GPT-3.

[0921] As a concrete example, let's explain how a store staff member takes a photo of a new promotional poster with their smartphone, and the system automatically registers that information in the event calendar. The staff member takes a photo of the poster and immediately sends the image to the server. The server uses OCR to extract the text and generates a summary and event information, such as "There will be a Christmas sale on December 5th and a year-end special sale on December 12th." This information is automatically registered in the calendar app.

[0922] If a staff member types a question like, "What date is the next event?", the system sends the following prompt to the generative AI model:

[0923] Examples of prompts:

[0924] Answer the questions based on the event information below: "There will be a Christmas sale on December 5th and a year-end sale on December 12th."

[0925] Question: "What date is the next event?"

[0926] answer:

[0927] Based on this prompt, the server uses a generative AI model to generate a response to the question and displays an answer such as "The next event is on December 5th" on the staff member's smartphone.

[0928] This allows store staff to efficiently digitize and manage promotional materials, and makes it easier to manage and share important event information.

[0929] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0930] Step 1:

[0931] The user takes a photo of a paper promotional material with their smartphone. The input data is the captured image, which is temporarily saved on the smartphone. The output is the image data saved on the smartphone.

[0932] Step 2:

[0933] The smartphone sends the stored image data to the server. The input data is the image data stored on the smartphone, which is uploaded to the server. The output is the image data sent to the server.

[0934] Step 3:

[0935] The server converts the received image data into text data using optical character recognition (OCR) technology. Specifically, it uses the pytesseract library to extract text information from the image. The input data is the image data sent to the server, and the output is the extracted text data.

[0936] Step 4:

[0937] The server analyzes the extracted text data and generates important information as summaries and event information. Here, important keywords and date information are extracted to create summaries. The input data is the extracted text data, and the output is the summarized information and generated event information.

[0938] Step 5:

[0939] The server automatically registers the generated summary and event information in the store's event calendar using an API. Specifically, the event information is added to the calendar using the Google Calendar API, etc. The input data is the summary and event information, and the output is the event data registered in the calendar.

[0940] Step 6:

[0941] Users enter questions about promotions and events through a smartphone app. The input data is the question text entered by the user, which is sent to the server. The output is the question data sent to the server.

[0942] Step 7:

[0943] The server uses a generative AI model to generate an appropriate response to the question. Specifically, it generates a prompt sentence that combines the question data with summary and event information, and inputs it into a generative AI model such as OpenAI's GPT-3. The server then receives the generated answer. The input data is the question data and event information, and the output is the response data to the question.

[0944] Step 8:

[0945] The server sends the generated response to the smartphone. The input data is the response data to the question, and the output is the response data sent to the smartphone. The user can check the answer on the smartphone.

[0946] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0947] The present invention combines a system that photographs paper prints received by a user, digitizes and summarizes the contents using OCR technology and generative AI, and further combines it with an emotion engine that recognizes the user's emotions. The main embodiments of the present invention are described below.

[0948] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[0949] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[0950] The generative AI uses the analyzed text data to generate summaries and event information, while the emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends the recognition results to the server.

[0951] The server then tailors the content of the summary and event information based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, the server can generate a summary in a format that highlights important information.

[0952] The server then sends the generated summary and event information to the device, which then displays the information on its user interface and automatically registers the event information in its schedule using a calendar application.

[0953] When a user enters a question about the summary or event information, the device sends the question to the server. The server uses generative AI to generate an appropriate response to the question, again incorporating the recognition results of the emotion engine. For example, if the user is feeling doubtful or anxious, the tone of the response can be gentler.

[0954] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text of the schedule. The emotion engine also analyzes the voice and facial expressions used by the user when taking the photo, and sends emotional data to the server.

[0955] Based on the analysis results and emotion data, the AI ​​generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation start," and summarizes it according to the emotion. For example, if the user is excited, the AI ​​will present a summary in a positive tone.

[0956] The generated information is sent from the server to the device, which then automatically registers it in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends the question to the server, and the generation AI generates a response saying "It will be held on June 15th." Here too, the results of the emotion engine are reflected, and the response is displayed in an appropriate tone.

[0957] In this way, the system not only digitizes received prints and efficiently manages important information, but also provides flexible responses that take user emotions into consideration, significantly improving the user experience.

[0958] The processing flow will be explained below.

[0959] Step 1:

[0960] Users take a photo of the print using their smartphone camera, and audio guidance is displayed to help them take a clear photo.

[0961] Step 2:

[0962] The device temporarily stores the captured image and then sends it to the server as image data. The image data is sent securely using HTTP requests and SSL.

[0963] Step 3:

[0964] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as string data.

[0965] Step 4:

[0966] The server activates an emotion engine to analyze the voice and facial expression data emitted by the user when taking a photo. The emotion engine analyzes the voice waveform and facial features to generate data that identifies the user's emotional state.

[0967] Step 5:

[0968] The server inputs the text data extracted by OCR into the generation AI, and at the same time, the user's emotional data is also passed to the generation AI, which analyzes it using natural language processing (NLP) technology.

[0969] Step 6:

[0970] The generative AI extracts key information and events from text and emotion data to generate summaries, adjusting the tone and emphasis of the summaries depending on the emotion.

[0971] Step 7:

[0972] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[0973] Step 8:

[0974] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[0975] Step 9:

[0976] The user enters a question about the summarized information or event information, and the question can be entered by text or voice.

[0977] Step 10:

[0978] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[0979] Step 11:

[0980] The server uses generative AI and an emotion engine to generate appropriate responses to questions, adjusting the content and tone of the response depending on the user's emotional state.

[0981] Step 12:

[0982] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[0983] Step 13:

[0984] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[0985] In this way, users can not only easily digitize prints and efficiently manage important information, but also receive more personalized information through the emotion engine.

[0986] Example 2

[0987] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0988] Traditional paper printouts are not digitized, making it difficult to manage important information. Furthermore, there are insufficient means to efficiently extract necessary information from digitized information and provide flexible responses based on user emotions. Therefore, improving user information management and user experience has become a challenge.

[0989] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0990] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for analyzing the user's voice and facial expression to recognize the user's emotion, means for adjusting the content of the summary and the event information based on the emotion, means for registering the summary and the event information in a calendar, and means for generating responses to questions based on the summary and the event information. This makes it possible to efficiently digitize paper printouts and flexibly provide information and responses that take the user's emotion into consideration.

[0991] The "means for receiving captured images as data" refers to a device or program for receiving captured image data sent from the user's terminal.

[0992] "Means for extracting text using said data" refers to a device or program that analyzes and extracts text data from received image data using optical character recognition technology.

[0993] The "means for analyzing the extracted text and generating a summary and event information" refers to a device or program that analyzes the extracted text data, summarizes important information, and generates event information.

[0994] "Means for analyzing the user's voice and facial expressions in order to recognize the user's emotions" refers to a device or program that acquires data on the voice and facial expressions made by the user while taking a photograph, and recognizes and analyzes the user's emotions from that data.

[0995] The "means for adjusting the content of the summary and the event information based on the emotion" refers to a device or program that adjusts and optimizes the content and tone of the generated summary and event information based on the analyzed user emotion data.

[0996] The "means for registering in a calendar using the summary and the event information" is a device or program that automatically registers the generated summary and event information in a calendar application.

[0997] The "means for generating a response to a question based on the summary and the event information" refers to a device or program that generates an appropriate response to a question from a user related to the summary and the event information.

[0998] The present invention relates to a system that combines a user terminal, a server, and related software to digitize paper prints, extract important information, and provide flexible responses to users based on that information. Furthermore, the present invention realizes a better user experience by recognizing the user's emotions and reflecting them in the information provided and responses.

[0999] First, the user takes a photo of a paper print using a device such as a smartphone. A dedicated application installed on the device supports this process. The captured image is temporarily stored on the device and then sent to a server. The server receives the captured image as data. This action is carried out over the Internet, and secure communication is ensured using encryption technology.

[1000] The server then converts the received image data into text using optical character recognition (OCR) technology, such as Tesseract, an OCR software that enables highly accurate character recognition and accurately extracts text from images.

[1001] The extracted text data is analyzed by a generative AI (e.g., OpenAI's GPT-4). This analysis summarizes important information and generates event information. For example, events such as "April entrance ceremony," "June school festival," and "December winter vacation start" are extracted.

[1002] At the same time, the server analyzes the user's voice and facial expressions to recognize their emotions. An emotion recognition engine (for example, Microsoft's Emotion API) is used to do this. The server analyzes the user's emotions from the voice and facial expressions the user makes when taking the photo.

[1003] The server adjusts the content of the summary and event information based on the acquired emotional data. For example, if the user is feeling stressed, the information can be presented in a more concise form with the important parts emphasized. The generative AI does this and provides information in a format that is easy for the user to understand.

[1004] The server sends the summary and event information to the device, which then displays the information on the user interface. Furthermore, the device uses an API to automatically register the information in a calendar application (e.g., Google Calendar), eliminating the need for the user to manually enter the information.

[1005] Additionally, when users input questions about the summary and event information, the device sends the questions to the server, which uses generative AI to generate appropriate responses and adjusts the tone of the response based on emotion recognition results. For example, if the user is feeling anxious, the response will be delivered in a gentler tone.

[1006] As a concrete example, let's consider the case where a user takes a photo of a printed annual schedule given to them by their school. The user takes a photo of the schedule using their smartphone camera. The device then sends this image to a server. The server uses OCR technology to extract the text from the schedule and analyzes it using a generation AI. The server also analyzes the user's voice and facial expressions while taking the photo and sends emotional data to the server. Based on the analysis results and emotional data, the generation AI generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation begins." If the user is excited, it presents a summary in a positive tone. The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user inputs a question such as "What day is the June school festival held?", the server uses the generation AI to generate a response such as "It will be held on June 15th," and displays the response in an appropriate tone reflecting the results of the emotion engine.

[1007] An example of a prompt is, "Use OCR technology to convert a photo of the user's annual schedule printout into text, and then use a generative AI to summarize it. Also, use an emotion engine to analyze the user's emotions, and provide information in a tone that corresponds to those emotions."

[1008] In this way, the present invention can efficiently digitize paper prints, automatically manage important information, and improve the user experience by providing flexible responses that take user emotions into consideration.

[1009] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1010] Step 1:

[1011] The user takes a photo of a paper print using the smartphone camera. The input is the captured image data, and the output is image data temporarily saved on the device. Specifically, the user launches the camera app and presses the capture button to generate image data. A dedicated application then automatically detects and saves the image data.

[1012] Step 2:

[1013] The device sends the captured image data to a server. The input is image data stored in the device, and the output is image data sent to the server. Specifically, a dedicated application sends the data to the server via the Internet. The data is sent using encryption technology to ensure security.

[1014] Step 3:

[1015] The server converts the received image data into text data using optical character recognition (OCR) technology. The input is the image data sent to the server, and the output is the extracted text data. Specifically, the server runs OCR software (e.g., Tesseract) to analyze the characters in the image and convert them into text. During this process, the characters in the image are detected and the corresponding character codes are generated.

[1016] Step 4:

[1017] The server analyzes the extracted text data and generates summaries and event information. The input is the text data extracted using OCR technology, and the output is the generated summaries and event information. Specifically, the server uses a generative AI (e.g., OpenAI's GPT-4) to analyze the text data and extract important information. The extracted information is then summarized and organized as event information.

[1018] Step 5:

[1019] Emotions are analyzed using the user's voice and facial expression data. The input is the voice and facial expression data emitted by the user when taking a photo, and the output is the recognized emotional data. Specifically, the server uses an emotion recognition engine (for example, Microsoft's Emotion API) to analyze the user's voice and facial expression. This analysis recognizes the user's emotional state (for example, joy, sadness, stress).

[1020] Step 6:

[1021] The server uses the recognized emotion data to adjust the content of the summary and event information. The input is the generated summary and event information and the recognized emotion data, and the output is the summary and event information adjusted based on the emotion. Specifically, the generation AI takes the emotion data into account and adjusts the tone and emphasis of the information. For example, if the user is feeling stressed, the information will be presented in a concise and emphasized form.

[1022] Step 7:

[1023] The adjusted summary and event information are sent to the terminal and displayed on the user interface. The input is the adjusted summary and event information, and the output is the information displayed on the terminal. Specifically, the server sends data to the terminal via the Internet, and a dedicated application on the terminal receives the information and displays it on the screen.

[1024] Step 8:

[1025] The device automatically registers event information in the calendar application. The input is the adjusted event information, and the output is the event information registered in the calendar application. Specifically, the device uses the calendar application's API to automatically register the event information in the schedule.

[1026] Step 9:

[1027] The user inputs a question about the summary and event information. The input is the question entered by the user, and the output is the question data sent to the server. In concrete terms, the user inputs a question into the application's input field and presses the "Submit" button.

[1028] Step 10:

[1029] The server generates a response to the question and provides it in a tone that reflects the emotion. The input is the question data and recognized emotion data sent to the server, and the output is the generated response data. Specifically, the server uses generative AI to create an appropriate response to the question and adjusts the response in tone according to the emotion data. The response data is then sent to the device, which displays it on the user interface.

[1030] (Application example 2)

[1031] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1032] Information management based on paper printouts is often inefficient and requires time and effort, creating a need for digitalization. Current digitalization systems also face the challenge of providing flexible responses and suggestions based on user emotions and preferences. In particular, food delivery services require efficient digitalization of paper menus and promotional information, allowing for suggestions based on user emotions.

[1033] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1034] In this invention, the server includes means for receiving a captured image as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for recognizing a user's emotion based on the received image, means for adjusting the summary and event information based on the emotion recognition result, and means for adjusting the tone of a response based on the emotion recognition result, thereby enabling the paper menu received by the user to be digitized and enabling flexible suggestions and responses based on emotions.

[1035] The "photographed image" is still image data acquired by the user using the camera function.

[1036] "Means for receiving as data" refers to the function or process by which the server or terminal receives the captured image.

[1037] "Means for extracting text" refers to the process of obtaining text information from image data using OCR technology.

[1038] The "means for generating summary and event information" is the process of analyzing the extracted text to summarize important information.

[1039] The "calendar registration means" is a function that adds the generated summary and event information to the schedule management system.

[1040] The "means for generating a response to a question" is a process for generating an appropriate response to a question from a user based on information obtained in advance.

[1041] "Means for recognizing emotions" refers to technologies and processes that analyze and determine a user's emotional state from images and sounds.

[1042] The "means for adjusting the summary and event information based on the recognition results" is a function that dynamically changes the format and content of the summary and event information using data obtained by the emotion engine.

[1043] A "means for adjusting the tone of a response" is a process that changes the tone and phrasing of the generated response depending on the user's emotional state.

[1044] The invention is a system that allows users to digitize paper prints and further adjust the content based on the user's emotions. The system can be implemented using a smartphone or other device.

[1045] First, a user takes a photo of a paper menu or printout using their smartphone camera. The captured image is temporarily saved on the device and then sent to the server as image data. The server processes the received image data using optical character recognition (OCR) technology (e.g., pytesseract) to extract text data from the image. This extracted text data is then further analyzed to summarize important information and generate event information.

[1046] On the other hand, to recognize the user's emotions, emotion recognition technology (e.g., EmotionRecognition library) is used to analyze the voice and facial expressions of the user when taking a photo. The emotion recognition results are sent to the server, which then uses this data to adjust the content of the generated summary and event information, as well as the tone of the response.

[1047] The generated summary and event information are sent from the server to the terminal, which then displays this information on the user interface. As a specific example, if a user takes a photo of a paper menu they have received, the system digitizes the menu and generates menu recommendations based on the user's emotions. For example, if the user is excited, the system will recommend special menus or set menus that match their excitement level.

[1048] The generated information is automatically registered in a calendar application. When a user enters a question about the generated information, the question is sent to a server, and an appropriate response is generated using a generative AI model (e.g., GPT-3). The tone of this response is also adjusted based on emotion recognition data.

[1049] Examples of prompts when using a generative AI model include:

[1050] "Menu: XXXXXX

[1051] User sentiment: XXX

[1052] Please let me know what menu items you recommend."

[1053] Through prompt sentences, the system can respond flexibly according to the user's emotions. In this way, the system can digitize the paper printouts received by the user, efficiently manage important information, and provide flexible responses that take emotions into consideration.

[1054] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1055] Step 1:

[1056] The user takes a photo of the paper print using the smartphone camera.

[1057] Input: Paper print

[1058] Output: Captured image data

[1059] Specific operation: The user takes a photo of the paper menu or promotional information they received with their smartphone camera. This image data is temporarily stored in the device's memory.

[1060] Step 2:

[1061] The terminal transmits the captured image data to the server.

[1062] Input: Photographed image data

[1063] Output: Image data sent to the server

[1064] Specific operation: Image data stored on the device is uploaded to the server via the network, which prepares the image data for OCR and emotion recognition processing.

[1065] Step 3:

[1066] The server extracts text data from the image data using OCR technology.

[1067] Input: Image data

[1068] Output: Text data

[1069] Specific operation: The server uses an OCR library such as pytesseract to convert the character information contained in the image data into text format and extract the necessary text data.

[1070] Step 4:

[1071] The server analyzes the user's emotions using emotion recognition technology.

[1072] Input: User's voice and facial expression data

[1073] Output: Emotion recognition result

[1074] Specific operation: The server uses the EmotionRecognition library to analyze the user's voice and facial expression data and recognize the user's emotional state (e.g., excitement, stress, relief, etc.).

[1075] Step 5:

[1076] The server analyzes the extracted text data and generates summaries and event information.

[1077] Input: Text data, emotion recognition results

[1078] Output: Summary and event information

[1079] Specific operation: The server uses the generative AI model to analyze the text data, summarize important information, and generate necessary event information. Based on the emotion recognition results, the generated summary and event information are appropriately adjusted.

[1080] Step 6:

[1081] The server transmits the generated summary and event information to the terminal.

[1082] Input: Abstract and event information

[1083] Output: Summary and event information sent to the terminal

[1084] Specific operation: The server transmits the generated summary and event information to the user's terminal via the network.

[1085] Step 7:

[1086] The terminal displays the received summary and event information on a user interface.

[1087] Input: Abstract and event information

[1088] Output: Information displayed in the user interface

[1089] Specific operation: The terminal displays the received summary and event information on the terminal display for easy access by the user.

[1090] Step 8:

[1091] The terminal automatically registers the summary and event information in the calendar application.

[1092] Input: Abstract and event information

[1093] Output: Event information registered in the calendar

[1094] Specific operation: The terminal uses the API to automatically register summary and event information in the calendar application, helping the user manage their schedule.

[1095] Step 9:

[1096] When the user inputs a question about the summary and event information, the terminal sends the question to the server.

[1097] Input: User question

[1098] Output: The question sent to the server

[1099] Specific operation: The terminal receives the question entered by the user and transfers it to the server.

[1100] Step 10:

[1101] The server uses a generative AI model to generate appropriate responses to questions and adjusts the tone of the response based on emotion recognition results.

[1102] Input: Question, emotion recognition result

[1103] Output: The generated response

[1104] Specific operation: The server uses a generative AI model (e.g., GPT-3) based on the question content and emotion recognition results to generate an appropriate response and adjust the tone of the response.

[1105] Step 11:

[1106] The server generates a response and sends it to the terminal, which displays it on its user interface.

[1107] Input: Generated response

[1108] Output: The response displayed in the user interface

[1109] Specific operation: The server sends the generated response to the terminal, which displays it on the user interface, providing the user with an answer.

[1110] 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.

[1111] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. 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.

[1112] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1113] [Fourth embodiment]

[1114] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1115] 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.

[1116] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. 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).

[1117] 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.

[1118] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1119] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1120] 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.

[1121] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1122] 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.

[1123] 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 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.

[1124] 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.

[1125] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1126] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1127] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[1128] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[1129] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[1130] The server then sends the generated summary and the event information contained in the printout (e.g., meeting schedules, school event dates, etc.) to the device, which receives the information and visually displays it to the user. The device also uses a calendar application to automatically add the extracted event information to the schedule.

[1131] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses generative AI to generate an appropriate response to the question and sends the response back to the device, which displays the response to the user and provides an immediate answer to the question.

[1132] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text from the schedule. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[1133] The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends this question to the server, and the generation AI generates a response saying "It will be held on June 15th." The response is sent to the device and displayed to the user.

[1134] In this way, this system provides a means to easily digitize received printouts and efficiently manage important information. This allows users to prevent missing information and easily manage their schedules. Furthermore, the question and answer function allows users to instantly obtain the information they need.

[1135] The processing flow will be explained below.

[1136] Step 1:

[1137] The user takes a photo of the print with their smartphone using the smartphone's camera app, taking a picture that captures the entire print clearly.

[1138] Step 2:

[1139] The device temporarily stores the captured image and then sends it to the server as image data via a communication method such as an HTTP request.

[1140] Step 3:

[1141] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as a string of characters.

[1142] Step 4:

[1143] The server inputs the extracted text data into the generative AI, which analyzes the text data using natural language processing (NLP) techniques.

[1144] Step 5:

[1145] Generative AI analyzes text data, extracts key information and events, and generates summaries that include information such as dates, event names, and locations.

[1146] Step 6:

[1147] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[1148] Step 7:

[1149] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[1150] Step 8:

[1151] The user inputs a question into the terminal, for example, "On what date is the school festival in June held?"

[1152] Step 9:

[1153] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[1154] Step 10:

[1155] The server inputs the received question into the generation AI, which then generates a response to the question. The generation AI analyzes the question and constructs an appropriate answer.

[1156] Step 11:

[1157] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[1158] Step 12:

[1159] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[1160] Example 1

[1161] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1162] Conventional methods for digitizing and managing paper-based print information require manual input and organization, which is time-consuming and labor-intensive. There is also a risk of missing important event information. Furthermore, when a question arises, users have to search for the file to confirm the information again, which is inefficient. There is a need for a system that can solve these problems, efficiently digitize paper-based print information, make it easier to manage, and enable users to quickly obtain information.

[1163] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1164] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate summaries and event information, means for registering the summaries and the event information in a calendar, means for generating responses to questions based on the summaries and the event information, means for temporarily storing the image data, means for analyzing the analyzed text data using natural language processing technology, and means for transmitting the generated responses to a user terminal. This makes it possible to efficiently digitize and manage paper print information and quickly obtain important information without missing it.

[1165] A "photographed image" is digital image data of a paper print or the like captured by a user using the camera of the terminal.

[1166] "Means for receiving as data" refers to a technology that enables the procedure for sending captured images to a server and for the server to receive them.

[1167] The "means for extracting text" is a technology that uses optical character recognition (OCR) technology to identify character information from an image and extract it as text data.

[1168] The "means for generating summary and event information" refers to a technology for analyzing extracted text data, identifying important information and summarizing it briefly, and extracting information related to a specific event.

[1169] "Means of registering to a calendar" refers to a technology that automatically inputs the extracted event information into a schedule management application, and typically uses an API.

[1170] "Means for generating responses to questions" refers to technology that uses a generative AI model to create appropriate answers to questions from users.

[1171] "Means for temporarily storing image data" refers to technology that temporarily stores captured images within the terminal.

[1172] The "means of analysis using natural language processing technology" is a technology that analyzes the extracted text data using natural language processing technology, and extracts and summarizes important information.

[1173] The "means for transmitting the generated response to the user terminal" is a technique for transmitting the response generated by the server to the user terminal.

[1174] The present invention is a system for efficiently digitizing paper prints received by a user and managing the contents thereof. The main embodiments of the present invention will be described below.

[1175] First, the user takes a photo of a paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data. The device then uses the HTTP POST method over the Internet.

[1176] The server processes the received image data using optical character recognition (OCR) technology and extracts text data from the image. Specifically, text extraction is performed using Google Cloud Vision or Tesseract. Using this OCR technology, the server recognizes the character information in the image and extracts it as text data.

[1177] The server then analyzes the extracted text data using natural language processing (NLP) techniques, such as SpaCy and NLTK. The server identifies important information from the analyzed text data and generates summaries and event information, which is then converted into JSON format.

[1178] The server sends the generated summary and event information to the user's device, which receives the information and visually displays it to the user. In addition, the device automatically schedules the extracted event information using a calendar application such as Google Calendar or iOS Calendar.

[1179] When a user inputs a question about the summarized information or event information, the device sends the question to the server, which uses a generative AI model (e.g., GPT-4) to generate an appropriate response to the question and sends the response back to the device. The generated response is displayed on the user's device, providing an immediate answer to the question.

[1180] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule with their smartphone camera, and the device sends this image to the server. The server uses OCR technology to extract the text from the schedule and analyzes it. As a result of the analysis, important event information such as "entrance ceremony in April," "school festival in June," and "start of winter vacation in December" is generated.

[1181] This generated information is sent from the server to the device, and the device automatically registers this information in a calendar. For example, if a user inputs a question such as "What day is the school festival held in June?", the device sends this question to the server. The server uses a generative AI model (e.g., GPT-4) to generate a response such as "It will be held on June 15th" and sends it to the device. The device then displays this response to the user.

[1182] An example of a prompt is the question, "What day is the school festival in June?" Using such prompts, the generative AI model can generate accurate responses and provide them to the user quickly.

[1183] As described above, the present invention provides a means for easily digitizing received printouts and efficiently managing important information. This allows users to prevent overlooking information and easily manage their schedules. In addition, the question-and-answer function allows users to instantly obtain the information they need.

[1184] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1185] Step 1:

[1186] A user photographs a paper print.

[1187] Specific behavior:

[1188] The user opens the camera app on their smartphone and takes a picture of the paper print.

[1189] input:

[1190] Paper print.

[1191] output:

[1192] Digital image data stored on a smartphone.

[1193] Step 2:

[1194] The terminal temporarily stores the image data and sends it to the server.

[1195] Specific behavior:

[1196] The device temporarily stores the captured image data in its internal storage, and then sends the image data to the server using the HTTP POST method.

[1197] input:

[1198] The captured image data.

[1199] output:

[1200] Image data sent to the server.

[1201] Step 3:

[1202] The server converts the image data into text using OCR technology.

[1203] Specific behavior:

[1204] The server uses OCR technology such as Google Cloud Vision API to extract text from the received image data.

[1205] input:

[1206] Image data received by the server.

[1207] output:

[1208] The extracted text data.

[1209] Step 4:

[1210] The server analyzes the text data and extracts and summarizes important information.

[1211] Specific behavior:

[1212] The server uses natural language processing technologies such as SpaCy and NLTK to analyze the text data, extract key information, and generate summaries.

[1213] input:

[1214] The extracted text data.

[1215] output:

[1216] Parsed summary and event information.

[1217] Step 5:

[1218] The server sends the summary and event information to the terminal.

[1219] Specific behavior:

[1220] The server converts the summary and event information into JSON format and sends it to the terminal using the HTTP POST method.

[1221] input:

[1222] Abstract and event information.

[1223] output:

[1224] Summary and event information sent to the terminal.

[1225] Step 6:

[1226] The information received by the device is automatically registered in the calendar.

[1227] Specific behavior:

[1228] The device parses the received JSON data and automatically registers the schedule using the Google Calendar API.

[1229] input:

[1230] Summary and event information received from the server.

[1231] output:

[1232] Event information registered in Google Calendar.

[1233] Step 7:

[1234] The user enters a question for information into the terminal.

[1235] Specific behavior:

[1236] Users enter questions into the device via a dedicated app.

[1237] input:

[1238] Question content.

[1239] output:

[1240] Questions typed into the terminal.

[1241] Step 8:

[1242] The terminal sends a question to the server.

[1243] Specific behavior:

[1244] The device uses a REST API to send the user's question in JSON format to the server.

[1245] input:

[1246] The question entered by the user.

[1247] output:

[1248] The question data sent to the server.

[1249] Step 9:

[1250] The server generates a response using a generative AI model.

[1251] Specific behavior:

[1252] The server uses a generative AI model (e.g., GPT-4) to generate appropriate responses to questions.

[1253] input:

[1254] User question data.

[1255] output:

[1256] The generated response data.

[1257] Step 10:

[1258] The terminal receives the response and displays it to the user.

[1259] Specific behavior:

[1260] The terminal receives the response data from the server and displays it on the screen.

[1261] input:

[1262] Response data from the server.

[1263] output:

[1264] The response shown to the user.

[1265] (Application example 1)

[1266] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1267] In brick-and-mortar stores, managing information such as paper promotional materials and event posters is time-consuming and laborious. Furthermore, while there is a need to digitize and share paper information to manage schedules and obtain information instantly, there is a lack of efficient ways to do this. This often results in oversight of promotional content and event information, leading to insufficient information sharing among staff.

[1268] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1269] In this invention, the server includes means for digitizing photographed paper promotional materials and automatically registering the extracted event information in a store's event calendar, means for using optical character recognition (OCR) technology to convert the received images into text data, and means for utilizing an API to automatically register the generated summary and event information in a calendar application, thereby enabling efficient digitization of paper information and automatic management and sharing of important event information.

[1270] "Captured images" are still image data captured by devices such as smartphones and cameras.

[1271] "Means for receiving as data" refers to the functions and protocols for transferring captured images to a server or other storage device.

[1272] "Means for extracting text" refers to the function of analyzing and extracting text information from image data.

[1273] The "means for generating summary and event information" refers to a function for selecting important information from the extracted text and generating a concise summary or specific event information.

[1274] "Means for registering in a calendar" refers to a function that automatically inputs the generated summary and event information into a calendar application and registers it as a schedule.

[1275] The "means for generating a response to a question" refers to a function for generating an appropriate answer to a question from a user based on the summary and event information.

[1276] "Optical character recognition (OCR) technology" refers to technology for reading character data from images.

[1277] "Using an API" means using an interface to exchange functions and data between software.

[1278] The "means for automatically registering event information in the store's event calendar" is a function that automatically adds the generated event information to the calendar system used by the store staff.

[1279] "Digitizing promotional materials" refers to the process of converting promotional content written on paper into electronic data.

[1280] This invention is a system that improves the efficiency of information management for promotional materials and event posters in brick-and-mortar stores. This system provides a means for photographing paper promotional materials with a smartphone and sending the data to a server for processing.

[1281] First, a user takes a photo of a paper promotional material using a smartphone. The captured image is temporarily saved on the smartphone and then sent to a server as image data. The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image. For example, the pytesseract library is used for this OCR technology.

[1282] The server then analyzes the extracted text data and generates important information as summaries and event information, which are then automatically added to the store's event calendar using an API, such as the Google Calendar API.

[1283] Users can enter questions about promotions and events through a smartphone app. These questions are sent to a server, which uses a generative AI model to generate an appropriate response to the question. The generated response is displayed on the smartphone and provided to the user instantly. This AI model uses, for example, OpenAI's GPT-3.

[1284] As a concrete example, let's explain how a store staff member takes a photo of a new promotional poster with their smartphone, and the system automatically registers that information in the event calendar. The staff member takes a photo of the poster and immediately sends the image to the server. The server uses OCR to extract the text and generates a summary and event information, such as "There will be a Christmas sale on December 5th and a year-end special sale on December 12th." This information is automatically registered in the calendar app.

[1285] If a staff member types a question like, "What date is the next event?", the system sends the following prompt to the generative AI model:

[1286] Examples of prompts:

[1287] Answer the questions based on the event information below: "There will be a Christmas sale on December 5th and a year-end sale on December 12th."

[1288] Question: "What date is the next event?"

[1289] answer:

[1290] Based on this prompt, the server uses a generative AI model to generate a response to the question and displays an answer such as "The next event is on December 5th" on the staff member's smartphone.

[1291] This allows store staff to efficiently digitize and manage promotional materials, and makes it easier to manage and share important event information.

[1292] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1293] Step 1:

[1294] The user takes a photo of a paper promotional material with their smartphone. The input data is the captured image, which is temporarily saved on the smartphone. The output is the image data saved on the smartphone.

[1295] Step 2:

[1296] The smartphone sends the stored image data to the server. The input data is the image data stored on the smartphone, which is uploaded to the server. The output is the image data sent to the server.

[1297] Step 3:

[1298] The server converts the received image data into text data using optical character recognition (OCR) technology. Specifically, it uses the pytesseract library to extract text information from the image. The input data is the image data sent to the server, and the output is the extracted text data.

[1299] Step 4:

[1300] The server analyzes the extracted text data and generates important information as summaries and event information. Here, important keywords and date information are extracted to create summaries. The input data is the extracted text data, and the output is the summarized information and generated event information.

[1301] Step 5:

[1302] The server automatically registers the generated summary and event information in the store's event calendar using an API. Specifically, the event information is added to the calendar using the Google Calendar API, etc. The input data is the summary and event information, and the output is the event data registered in the calendar.

[1303] Step 6:

[1304] Users enter questions about promotions and events through a smartphone app. The input data is the question text entered by the user, which is sent to the server. The output is the question data sent to the server.

[1305] Step 7:

[1306] The server uses a generative AI model to generate an appropriate response to the question. Specifically, it generates a prompt sentence that combines the question data with summary and event information, and inputs it into a generative AI model such as OpenAI's GPT-3. The server then receives the generated answer. The input data is the question data and event information, and the output is the response data to the question.

[1307] Step 8:

[1308] The server sends the generated response to the smartphone. The input data is the response data to the question, and the output is the response data sent to the smartphone. The user can check the answer on the smartphone.

[1309] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1310] The present invention combines a system that photographs paper prints received by a user, digitizes and summarizes the contents using OCR technology and generative AI, and further combines it with an emotion engine that recognizes the user's emotions. The main embodiments of the present invention are described below.

[1311] First, the user takes a photo of the paper print using a device such as a smartphone. The captured image is temporarily saved on the device and then sent to the server as image data.

[1312] The server processes the received image data using optical character recognition (OCR) technology to extract text data from the image, which is then further analyzed within the server to summarize key information.

[1313] The generative AI uses the analyzed text data to generate summaries and event information, while the emotion engine analyzes the user's voice and facial expressions to recognize emotions and sends the recognition results to the server.

[1314] The server then tailors the content of the summary and event information based on the user's emotions as recognized by the emotion engine. For example, if the user is feeling stressed, the server can generate a summary in a format that highlights important information.

[1315] The server then sends the generated summary and event information to the device, which then displays the information on its user interface and automatically registers the event information in its schedule using a calendar application.

[1316] When a user enters a question about the summary or event information, the device sends the question to the server. The server uses generative AI to generate an appropriate response to the question, again incorporating the recognition results of the emotion engine. For example, if the user is feeling doubtful or anxious, the tone of the response can be gentler.

[1317] As a concrete example, let's consider the case where a user takes a photo of a printout of an annual schedule given to them by their school. The user takes a photo of the annual schedule using the camera on their smartphone. The device then sends this image to a server. The server uses OCR technology to extract and analyze the text of the schedule. The emotion engine also analyzes the voice and facial expressions used by the user when taking the photo, and sends emotional data to the server.

[1318] Based on the analysis results and emotion data, the AI ​​generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation start," and summarizes it according to the emotion. For example, if the user is excited, the AI ​​will present a summary in a positive tone.

[1319] The generated information is sent from the server to the device, which then automatically registers it in its calendar. When a user enters a question such as "What day is the school festival in June?", the device sends the question to the server, and the generation AI generates a response saying "It will be held on June 15th." Here too, the results of the emotion engine are reflected, and the response is displayed in an appropriate tone.

[1320] In this way, the system not only digitizes received prints and efficiently manages important information, but also provides flexible responses that take user emotions into consideration, significantly improving the user experience.

[1321] The processing flow will be explained below.

[1322] Step 1:

[1323] Users take a photo of the print using their smartphone camera, and audio guidance is displayed to help them take a clear photo.

[1324] Step 2:

[1325] The device temporarily stores the captured image and then sends it to the server as image data. The image data is sent securely using HTTP requests and SSL.

[1326] Step 3:

[1327] The server processes the received image data using optical character recognition (OCR) technology. The OCR software extracts text data from the image and stores it as string data.

[1328] Step 4:

[1329] The server activates an emotion engine to analyze the voice and facial expression data emitted by the user when taking a photo. The emotion engine analyzes the voice waveform and facial features to generate data that identifies the user's emotional state.

[1330] Step 5:

[1331] The server inputs the text data extracted by OCR into the generation AI, and at the same time, the user's emotional data is also passed to the generation AI, which analyzes it using natural language processing (NLP) technology.

[1332] Step 6:

[1333] The generative AI extracts key information and events from text and emotion data to generate summaries, adjusting the tone and emphasis of the summaries depending on the emotion.

[1334] Step 7:

[1335] The server sends the generated summary and event information to the terminal, allowing the data to be displayed on the user's device, such as a smartphone.

[1336] Step 8:

[1337] The device displays the received summary on the user interface and automatically registers the extracted event information in the calendar using the calendar application's API.

[1338] Step 9:

[1339] The user enters a question about the summarized information or event information, and the question can be entered by text or voice.

[1340] Step 10:

[1341] The terminal sends the entered question to the server, where it is preprocessed by a program and passed to the server.

[1342] Step 11:

[1343] The server uses generative AI and an emotion engine to generate appropriate responses to questions, adjusting the content and tone of the response depending on the user's emotional state.

[1344] Step 12:

[1345] The server generates a response and sends it to the terminal, where it is converted into a format that can be displayed on the user interface.

[1346] Step 13:

[1347] The terminal displays the received response on the user interface and provides it to the user, thereby enabling the user to quickly obtain the required information.

[1348] In this way, users can not only easily digitize prints and efficiently manage important information, but also receive more personalized information through the emotion engine.

[1349] Example 2

[1350] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1351] Traditional paper printouts are not digitized, making it difficult to manage important information. Furthermore, there are insufficient means to efficiently extract necessary information from digitized information and provide flexible responses based on user emotions. Therefore, improving user information management and user experience has become a challenge.

[1352] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1353] In this invention, the server includes means for receiving captured images as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for analyzing the user's voice and facial expression to recognize the user's emotion, means for adjusting the content of the summary and the event information based on the emotion, means for registering the summary and the event information in a calendar, and means for generating responses to questions based on the summary and the event information. This makes it possible to efficiently digitize paper printouts and flexibly provide information and responses that take the user's emotion into consideration.

[1354] The "means for receiving captured images as data" refers to a device or program for receiving captured image data sent from the user's terminal.

[1355] "Means for extracting text using said data" refers to a device or program that analyzes and extracts text data from received image data using optical character recognition technology.

[1356] The "means for analyzing the extracted text and generating a summary and event information" refers to a device or program that analyzes the extracted text data, summarizes important information, and generates event information.

[1357] "Means for analyzing the user's voice and facial expressions in order to recognize the user's emotions" refers to a device or program that acquires data on the voice and facial expressions made by the user while taking a photograph, and recognizes and analyzes the user's emotions from that data.

[1358] The "means for adjusting the content of the summary and the event information based on the emotion" refers to a device or program that adjusts and optimizes the content and tone of the generated summary and event information based on the analyzed user emotion data.

[1359] The "means for registering in a calendar using the summary and the event information" is a device or program that automatically registers the generated summary and event information in a calendar application.

[1360] The "means for generating a response to a question based on the summary and the event information" refers to a device or program that generates an appropriate response to a question from a user related to the summary and the event information.

[1361] The present invention relates to a system that combines a user terminal, a server, and related software to digitize paper prints, extract important information, and provide flexible responses to users based on that information. Furthermore, the present invention realizes a better user experience by recognizing the user's emotions and reflecting them in the information provided and responses.

[1362] First, the user takes a photo of a paper print using a device such as a smartphone. A dedicated application installed on the device supports this process. The captured image is temporarily stored on the device and then sent to a server. The server receives the captured image as data. This action is carried out over the Internet, and secure communication is ensured using encryption technology.

[1363] The server then converts the received image data into text using optical character recognition (OCR) technology, such as Tesseract, an OCR software that enables highly accurate character recognition and accurately extracts text from images.

[1364] The extracted text data is analyzed by a generative AI (e.g., OpenAI's GPT-4). This analysis summarizes important information and generates event information. For example, events such as "April entrance ceremony," "June school festival," and "December winter vacation start" are extracted.

[1365] At the same time, the server analyzes the user's voice and facial expressions to recognize their emotions. An emotion recognition engine (for example, Microsoft's Emotion API) is used to do this. The server analyzes the user's emotions from the voice and facial expressions the user makes when taking the photo.

[1366] The server adjusts the content of the summary and event information based on the acquired emotional data. For example, if the user is feeling stressed, the information can be presented in a more concise form with the important parts emphasized. The generative AI does this and provides information in a format that is easy for the user to understand.

[1367] The server sends the summary and event information to the device, which then displays the information on the user interface. Furthermore, the device uses an API to automatically register the information in a calendar application (e.g., Google Calendar), eliminating the need for the user to manually enter the information.

[1368] Additionally, when users input questions about the summary and event information, the device sends the questions to the server, which uses generative AI to generate appropriate responses and adjusts the tone of the response based on emotion recognition results. For example, if the user is feeling anxious, the response will be delivered in a gentler tone.

[1369] As a concrete example, let's consider the case where a user takes a photo of a printed annual schedule given to them by their school. The user takes a photo of the schedule using their smartphone camera. The device then sends this image to a server. The server uses OCR technology to extract the text from the schedule and analyzes it using a generation AI. The server also analyzes the user's voice and facial expressions while taking the photo and sends emotional data to the server. Based on the analysis results and emotional data, the generation AI generates important event information such as "April entrance ceremony," "June school festival," and "December winter vacation begins." If the user is excited, it presents a summary in a positive tone. The generated information is sent from the server to the device, and the device automatically registers this information in its calendar. When a user inputs a question such as "What day is the June school festival held?", the server uses the generation AI to generate a response such as "It will be held on June 15th," and displays the response in an appropriate tone reflecting the results of the emotion engine.

[1370] An example of a prompt is, "Use OCR technology to convert a photo of the user's annual schedule printout into text, and then use a generative AI to summarize it. Also, use an emotion engine to analyze the user's emotions, and provide information in a tone that corresponds to those emotions."

[1371] In this way, the present invention can efficiently digitize paper prints, automatically manage important information, and improve the user experience by providing flexible responses that take user emotions into consideration.

[1372] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1373] Step 1:

[1374] The user takes a photo of a paper print using the smartphone camera. The input is the captured image data, and the output is image data temporarily saved on the device. Specifically, the user launches the camera app and presses the capture button to generate image data. A dedicated application then automatically detects and saves the image data.

[1375] Step 2:

[1376] The device sends the captured image data to a server. The input is image data stored in the device, and the output is image data sent to the server. Specifically, a dedicated application sends the data to the server via the Internet. The data is sent using encryption technology to ensure security.

[1377] Step 3:

[1378] The server converts the received image data into text data using optical character recognition (OCR) technology. The input is the image data sent to the server, and the output is the extracted text data. Specifically, the server runs OCR software (e.g., Tesseract) to analyze the characters in the image and convert them into text. During this process, the characters in the image are detected and the corresponding character codes are generated.

[1379] Step 4:

[1380] The server analyzes the extracted text data and generates summaries and event information. The input is the text data extracted using OCR technology, and the output is the generated summaries and event information. Specifically, the server uses a generative AI (e.g., OpenAI's GPT-4) to analyze the text data and extract important information. The extracted information is then summarized and organized as event information.

[1381] Step 5:

[1382] Emotions are analyzed using the user's voice and facial expression data. The input is the voice and facial expression data emitted by the user when taking a photo, and the output is the recognized emotional data. Specifically, the server uses an emotion recognition engine (for example, Microsoft's Emotion API) to analyze the user's voice and facial expression. This analysis recognizes the user's emotional state (for example, joy, sadness, stress).

[1383] Step 6:

[1384] The server uses the recognized emotion data to adjust the content of the summary and event information. The input is the generated summary and event information and the recognized emotion data, and the output is the summary and event information adjusted based on the emotion. Specifically, the generation AI takes the emotion data into account and adjusts the tone and emphasis of the information. For example, if the user is feeling stressed, the information will be presented in a concise and emphasized form.

[1385] Step 7:

[1386] The adjusted summary and event information are sent to the terminal and displayed on the user interface. The input is the adjusted summary and event information, and the output is the information displayed on the terminal. Specifically, the server sends data to the terminal via the Internet, and a dedicated application on the terminal receives the information and displays it on the screen.

[1387] Step 8:

[1388] The device automatically registers event information in the calendar application. The input is the adjusted event information, and the output is the event information registered in the calendar application. Specifically, the device uses the calendar application's API to automatically register the event information in the schedule.

[1389] Step 9:

[1390] The user inputs a question about the summary and event information. The input is the question entered by the user, and the output is the question data sent to the server. In concrete terms, the user inputs a question into the application's input field and presses the "Submit" button.

[1391] Step 10:

[1392] The server generates a response to the question and provides it in a tone that reflects the emotion. The input is the question data and recognized emotion data sent to the server, and the output is the generated response data. Specifically, the server uses generative AI to create an appropriate response to the question and adjusts the response in tone according to the emotion data. The response data is then sent to the device, which displays it on the user interface.

[1393] (Application example 2)

[1394] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1395] Information management based on paper printouts is often inefficient and requires time and effort, creating a need for digitalization. Current digitalization systems also face the challenge of providing flexible responses and suggestions based on user emotions and preferences. In particular, food delivery services require efficient digitalization of paper menus and promotional information, allowing for suggestions based on user emotions.

[1396] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1397] In this invention, the server includes means for receiving a captured image as data, means for extracting text using the data, means for analyzing the extracted text to generate a summary and event information, means for recognizing a user's emotion based on the received image, means for adjusting the summary and event information based on the emotion recognition result, and means for adjusting the tone of a response based on the emotion recognition result, thereby enabling the paper menu received by the user to be digitized and enabling flexible suggestions and responses based on emotions.

[1398] The "photographed image" is still image data acquired by the user using the camera function.

[1399] "Means for receiving as data" refers to the function or process by which the server or terminal receives the captured image.

[1400] "Means for extracting text" refers to the process of obtaining text information from image data using OCR technology.

[1401] The "means for generating summary and event information" is the process of analyzing the extracted text to summarize important information.

[1402] The "calendar registration means" is a function that adds the generated summary and event information to the schedule management system.

[1403] The "means for generating a response to a question" is a process for generating an appropriate response to a question from a user based on information obtained in advance.

[1404] "Means for recognizing emotions" refers to technologies and processes that analyze and determine a user's emotional state from images and sounds.

[1405] The "means for adjusting the summary and event information based on the recognition results" is a function that dynamically changes the format and content of the summary and event information using data obtained by the emotion engine.

[1406] A "means for adjusting the tone of a response" is a process that changes the tone and phrasing of the generated response depending on the user's emotional state.

[1407] The invention is a system that allows users to digitize paper prints and further adjust the content based on the user's emotions. The system can be implemented using a smartphone or other device.

[1408] First, a user takes a photo of a paper menu or printout using their smartphone camera. The captured image is temporarily saved on the device and then sent to the server as image data. The server processes the received image data using optical character recognition (OCR) technology (e.g., pytesseract) to extract text data from the image. This extracted text data is then further analyzed to summarize important information and generate event information.

[1409] On the other hand, to recognize the user's emotions, emotion recognition technology (e.g., EmotionRecognition library) is used to analyze the voice and facial expressions of the user when taking a photo. The emotion recognition results are sent to the server, which then uses this data to adjust the content of the generated summary and event information, as well as the tone of the response.

[1410] The generated summary and event information are sent from the server to the terminal, which then displays this information on the user interface. As a specific example, if a user takes a photo of a paper menu they have received, the system digitizes the menu and generates menu recommendations based on the user's emotions. For example, if the user is excited, the system will recommend special menus or set menus that match their excitement level.

[1411] The generated information is automatically registered in a calendar application. When a user enters a question about the generated information, the question is sent to a server, and an appropriate response is generated using a generative AI model (e.g., GPT-3). The tone of this response is also adjusted based on emotion recognition data.

[1412] Examples of prompts when using a generative AI model include:

[1413] "Menu: XXXXXX

[1414] User sentiment: XXX

[1415] Please let me know what menu items you recommend."

[1416] Through prompt sentences, the system can respond flexibly according to the user's emotions. In this way, the system can digitize the paper printouts received by the user, efficiently manage important information, and provide flexible responses that take emotions into consideration.

[1417] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1418] Step 1:

[1419] The user takes a photo of the paper print using the smartphone camera.

[1420] Input: Paper print

[1421] Output: Captured image data

[1422] Specific operation: The user takes a photo of the paper menu or promotional information they received with their smartphone camera. This image data is temporarily stored in the device's memory.

[1423] Step 2:

[1424] The terminal transmits the captured image data to the server.

[1425] Input: Photographed image data

[1426] Output: Image data sent to the server

[1427] Specific operation: Image data stored on the device is uploaded to the server via the network, which prepares the image data for OCR and emotion recognition processing.

[1428] Step 3:

[1429] The server extracts text data from the image data using OCR technology.

[1430] Input: Image data

[1431] Output: Text data

[1432] Specific operation: The server uses an OCR library such as pytesseract to convert the character information contained in the image data into text format and extract the necessary text data.

[1433] Step 4:

[1434] The server analyzes the user's emotions using emotion recognition technology.

[1435] Input: User's voice and facial expression data

[1436] Output: Emotion recognition result

[1437] Specific operation: The server uses the EmotionRecognition library to analyze the user's voice and facial expression data and recognize the user's emotional state (e.g., excitement, stress, relief, etc.).

[1438] Step 5:

[1439] The server analyzes the extracted text data and generates summaries and event information.

[1440] Input: Text data, emotion recognition results

[1441] Output: Summary and event information

[1442] Specific operation: The server uses the generative AI model to analyze the text data, summarize important information, and generate necessary event information. Based on the emotion recognition results, the generated summary and event information are appropriately adjusted.

[1443] Step 6:

[1444] The server transmits the generated summary and event information to the terminal.

[1445] Input: Abstract and event information

[1446] Output: Summary and event information sent to the terminal

[1447] Specific operation: The server transmits the generated summary and event information to the user's terminal via the network.

[1448] Step 7:

[1449] The terminal displays the received summary and event information on a user interface.

[1450] Input: Abstract and event information

[1451] Output: Information displayed in the user interface

[1452] Specific operation: The terminal displays the received summary and event information on the terminal display for easy access by the user.

[1453] Step 8:

[1454] The terminal automatically registers the summary and event information in the calendar application.

[1455] Input: Abstract and event information

[1456] Output: Event information registered in the calendar

[1457] Specific operation: The terminal uses the API to automatically register summary and event information in the calendar application, helping the user manage their schedule.

[1458] Step 9:

[1459] When the user inputs a question about the summary and event information, the terminal sends the question to the server.

[1460] Input: User question

[1461] Output: The question sent to the server

[1462] Specific operation: The terminal receives the question entered by the user and transfers it to the server.

[1463] Step 10:

[1464] The server uses a generative AI model to generate appropriate responses to questions and adjusts the tone of the response based on emotion recognition results.

[1465] Input: Question, emotion recognition result

[1466] Output: The generated response

[1467] Specific operation: The server uses a generative AI model (e.g., GPT-3) based on the question content and emotion recognition results to generate an appropriate response and adjust the tone of the response.

[1468] Step 11:

[1469] The server generates a response and sends it to the terminal, which displays it on its user interface.

[1470] Input: Generated response

[1471] Output: The response displayed in the user interface

[1472] Specific operation: The server sends the generated response to the terminal, which displays it on the user interface, providing the user with an answer.

[1473] 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.

[1474] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. 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.

[1475] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1476] 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.

[1477] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[1478] 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.

[1479] 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).

[1480] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1481] 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."

[1482] 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.

[1483] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1484] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1485] 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.

[1486] 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.

[1487] 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.

[1488] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[1489] The hardware resource that executes the specific processing 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 processing may be a single processor.

[1490] 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.

[1491] 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.

[1492] 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.

[1493] 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.

[1494] The following is further disclosed regarding the above embodiment.

[1495] (Claim 1)

[1496] means for receiving the captured image as data;

[1497] means for extracting text using said data;

[1498] means for analyzing the extracted text to generate summary and event information;

[1499] a means for registering the summary and the event information in a calendar;

[1500] The system includes means for generating a response to a question based on the summary and the event information.

[1501] (Claim 2)

[1502] 10. The system of claim 1, wherein the system uses optical character recognition (OCR) technology to convert the received image into text data.

[1503] (Claim 3)

[1504] 10. The system of claim 1, utilizing an API for automatically registering the generated summaries and event information with a calendar application.

[1505] "Example 1"

[1506] (Claim 1)

[1507] means for receiving the captured image as data;

[1508] means for extracting text using said data;

[1509] means for analyzing the extracted text to generate summary and event information;

[1510] a means for registering the summary and the event information in a calendar;

[1511] means for generating a response to a question based on the summary and the event information;

[1512] means for temporarily storing the image data;

[1513] means for analyzing the analyzed text data using natural language processing technology;

[1514] The system includes means for transmitting the generated response to the user terminal.

[1515] (Claim 2)

[1516] 10. The system of claim 1, wherein the system uses optical character recognition (OCR) technology to convert the received image into text data.

[1517] (Claim 3)

[1518] 10. The system of claim 1, utilizing an API for automatically registering the generated summaries and event information with a scheduling application.

[1519] "Application Example 1"

[1520] (Claim 1)

[1521] means for receiving the captured image as data;

[1522] means for extracting text using said data;

[1523] means for analyzing the extracted text to generate summary and event information;

[1524] a means for registering the summary and the event information in a calendar;

[1525] A method for digitizing photographed paper promotional materials and automatically registering the extracted event information in the store's event calendar.

[1526] The system includes means for generating a response to a question based on the summary and the event information.

[1527] (Claim 2)

[1528] 10. The system of claim 1, wherein the system uses optical character recognition (OCR) technology to convert the received image into text data.

[1529] (Claim 3)

[1530] 10. The system of claim 1, utilizing an API for automatically registering the generated summaries and event information with a calendar application.

[1531] "Example 2: Combining Emotion Engines"

[1532] (Claim 1)

[1533] means for receiving the captured image as data;

[1534] means for extracting text using said data;

[1535] means for analyzing the extracted text to generate summary and event information;

[1536] means for analyzing the user's voice and facial expressions to recognize the user's emotions;

[1537] means for adjusting the content of the summary and the event information based on the emotion;

[1538] a means for registering the summary and the event information in a calendar;

[1539] The system includes means for generating a response to a question based on the summary and the event information.

[1540] (Claim 2)

[1541] 10. The system of claim 1, wherein the system uses optical character recognition technology to convert the received image into text data.

[1542] (Claim 3)

[1543] 10. The system of claim 1, utilizing an application program interface for automatically registering the generated summary and event information with a calendar application.

[1544] "Application example 2 when combining emotion engines"

[1545] (Claim 1)

[1546] means for receiving the captured image as data;

[1547] means for extracting text using said data;

[1548] means for analyzing the extracted text to generate summary and event information;

[1549] a means for registering the summary and the event information in a calendar;

[1550] means for generating a response to a question based on the summary and the event information;

[1551] means for recognizing a user's emotion based on the received image;

[1552] means for adjusting summary and event information based on the emotion recognition results;

[1553] means for adjusting the tone of a response based on the emotion recognition result.

[1554] (Claim 2)

[1555] 10. The system of claim 1, wherein the system uses optical character recognition (OCR) technology to convert the received image into text data.

[1556] (Claim 3)

[1557] 10. The system of claim 1, utilizing an API for automatically registering the generated summaries and event information with a calendar application. [Explanation of symbols]

[1558] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving the captured image as data; means for extracting text using said data; means for analyzing the extracted text to generate summary and event information; a means for registering the summary and the event information in a calendar; The system includes means for generating a response to a question based on the summary and the event information.

2. 10. The system of claim 1, wherein the system uses optical character recognition (OCR) technology to convert the received image into text data.

3. The system of claim 1 , further comprising an API for automatically registering the generated summary and event information with a calendar application.

Images