system

Abstract

We provide the system. [Solution] In order to collect user information, means of obtaining information from multiple data sources, A method for analyzing information obtained using natural language processing technology and extracting important topics and keywords, A means of analyzing user behavior patterns and schedules and providing relevant information, A means of receiving voice commands and input information from the user and performing related operations, A means of sending real-time notifications to users and presenting information, A means of integrating information from different domains and providing users with the optimal route and relevant news, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern information society, the amount of information received by individuals is increasing, and it is becoming difficult to quickly acquire and manage important information. As a result, the time and effort required to efficiently manage multiple pieces of information and tasks are increasing, and there is an increased likelihood of overlooking or mismanaging information, especially for busy business people and knowledge workers troubled by an overabundance of information. Furthermore, since information sources exist separately in multiple locations, it is difficult to integrally manage important information and quickly and accurately grasp the information necessary for daily life. There is a need for a system that can effectively solve these problems.

Means for Solving the Problems

[0005] This invention introduces a system that provides a server to acquire information from multiple data sources, analyzes the information using natural language processing technology, and extracts important topics and keywords. Furthermore, it provides a system that presents relevant information by analyzing the user's behavior patterns and schedule. The terminal is equipped with the ability to receive voice commands and input data from the user and operate in conjunction with them, enabling users to access information quickly by notifying them of information in real time. Through this means, users can centrally manage information, improve their personal productivity, prevent overlooking important information due to information overload, and realize efficient task management in daily work.

[0006] A "server" is a central computer device that sends and receives data to other computers via a network and performs specific tasks.

[0007] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate language spoken naturally by humans, and to automatically process the content of text and audio data.

[0008] A "data source" refers to a location or area where information is generated or recorded and accessible to a system, and includes databases, file systems, APIs, and so on.

[0009] A "topic" refers to a specific theme or subject extracted from information or data, and is treated as the core of that information in analysis and summarization.

[0010] A "keyword" is an important word or phrase within text or data that is used to identify or retrieve the subject or relevance of information.

[0011] A "terminal" is a device used by a user to access and operate information, and includes smartphones, computers, and other similar devices.

[0012] A "voice command" refers to a command given by a user via voice to a system to perform a specific operation.

[0013] "Behavioral patterns" refer to information used to predict future behavior by analyzing the tendencies of actions and choices that users have repeatedly taken in the past and identifying regularities.

[0014] "Real-time notification" refers to the process of immediately informing users when an event or piece of information occurs, enabling timely information delivery. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the 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.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0029] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] The system of this invention is designed to support users' information management and decision-making. It primarily involves a server and a terminal working together to provide users with the most relevant information. The server retrieves information from multiple data sources authorized by the user and analyzes this information using natural language processing technology. This allows it to extract important topics and keywords and create summaries.

[0037] The server analyzes user behavior patterns and schedules, and uses this data to make connections. This enables predictions based on the user's past behavior and provides optimal information. In particular, the server analyzes the user's past meeting and event participation history, as well as their daily activity time, to suggest the next necessary tasks.

[0038] On the other hand, the terminal is equipped with voice recognition capabilities and accepts voice commands from the user. The voice command analysis converts the voice into text, and then sends a request to the server according to the user's instructions, executing the necessary data and operations. This provides an environment in which the user can obtain information hands-free.

[0039] As a concrete example, when a user uses their smartphone and says, "Tell me my important appointments for today," the device recognizes the voice and converts it into text. This text information is sent to a server, which, based on previously collected data, provides a summary of the user's schedule and meeting details for the day. The device displays this summary on its screen and also informs the user verbally.

[0040] This system allows users to centrally manage necessary information from multiple sources, enabling them to efficiently carry out their daily tasks. Through the coordinated operation of the server and terminals, users can ensure they don't miss important information even in busy situations and clearly understand their priority tasks.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server connects to multiple data sources specified by the user and retrieves the latest email and message data via APIs. This prepares the server to collect information relevant to the user.

[0044] Step 2:

[0045] The server removes unnecessary information from the acquired data and formats the text data. In particular, it removes HTML tags and unnecessary header information to make it suitable for natural language processing.

[0046] Step 3:

[0047] The server uses natural language processing (NLP) techniques to analyze the formatted text data. It extracts important topics and keywords and generates a summary. This improves the readability and relevance of the information.

[0048] Step 4:

[0049] The server considers the user's activity history and schedule information, and associates extracted topics with the user's current situation and future plans. Based on this, it identifies necessary notifications and tasks.

[0050] Step 5:

[0051] The terminal receives voice commands from the user and converts them into text using its built-in speech recognition function. This prepares the user's instructions and questions for transmission to the server.

[0052] Step 6:

[0053] Upon receiving user instructions in text format, the server analyzes the content, extracts appropriate information from the database, and sends it back to the terminal. This enables the provision of information tailored to the user's requests.

[0054] Step 7:

[0055] The terminal displays summary information and support tasks received from the server on its screen and reports them to the user using text-to-speech functionality as needed. This allows the user to access important information in real time.

[0056] (Example 1)

[0057] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0058] In modern society, it is common to receive fragmented information from numerous sources, making it difficult for users to effectively manage this information. Furthermore, amidst the increasing volume of information, users are required to quickly acquire necessary information and make appropriate decisions. However, current technology does not adequately provide systems that centrally manage information from multiple sources and deliver optimal information based on user behavior patterns and plans. A system to address this challenge is needed.

[0059] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0060] In this invention, the server includes means for acquiring information from multiple information sources authorized by the user using an information processing device and aggregating the information; means for analyzing the acquired information using natural language processing technology and extracting important information and features; and means for analyzing the user's behavior patterns and schedules and presenting information in association with that data. As a result, the user can centrally manage information obtained from multiple information sources and make quick and accurate decisions in their daily life.

[0061] An "information processing device" is a device consisting of hardware and software for collecting, organizing, managing, and analyzing information.

[0062] "Natural language processing technology" is a field of artificial intelligence technology used to analyze human language, understand its meaning, and extract information.

[0063] "Behavioral patterns" refer to certain regular movements or tendencies identified based on a user's past activities and preferences.

[0064] "Speech recognition technology" is a technology that converts speech into digital signals and then analyzes them to understand them as language.

[0065] A "predictive model" is a statistical and machine learning technique used to predict future events or outcomes by analyzing past data.

[0066] A "generative AI model" is a learning model that uses artificial intelligence to assist in the generation of new data and information.

[0067] "Information sources" refer to databases and internet resources that function as sources of information provided to users.

[0068] This invention relates to an information processing system that efficiently collects, analyzes, and provides user information in an appropriate format. The following details each component and its operation.

[0069] The server uses an information processing device to retrieve information from multiple sources authorized by the user. Specifically, it aggregates news articles, emails, calendar entries, and other data from databases and web services accessible via the Internet Protocol.

[0070] The server uses natural language processing libraries such as Python's NLTK (Natural Language Toolkit) to analyze the collected information. This analysis extracts important information and features and generates a summary in a format that is easy for users to understand intuitively. This summary allows users to quickly access the information they need.

[0071] Furthermore, the server analyzes user behavior patterns. For example, it identifies typical user behavior patterns based on past email sending history and calendar event participation history. This allows it to build a predictive model that can optimally provide information relevant to the user.

[0072] Meanwhile, the terminal uses speech recognition technology to receive voice commands from the user and convert them into text. Specifically, it uses a voice API to convert voice data into text and sends it to the server. This procedure allows the user to operate the system hands-free.

[0073] The terminal is equipped with an interface for notifying the user of analysis results sent from the server. By displaying the information visually on the screen and also notifying the user via audio, it provides an environment where users can easily receive information in a variety of situations.

[0074] As a concrete example, consider a scenario where a user gives a voice command to their smartphone saying, "Tell me the latest information about the participants of the next meeting." The device recognizes this voice command, converts it to text, and sends it to the server. The server retrieves the details of the meeting based on the user's calendar information, and then collects, summarizes, and provides the latest news and related information about the participants.

[0075] An example of a prompt message is, "Tell me tomorrow's weather forecast." The system then retrieves the latest weather data and presents it to the user. In this way, users can utilize an advanced information environment in their daily activities.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The server retrieves data from sources authorized by the user. It uses the URL of the news API and email server credentials specified by the user as input. The server accesses these sources to retrieve the latest news articles, emails, and calendar entries. The raw data is stored on the server as output. Specifically, the server periodically executes data retrieval scripts at programmed intervals.

[0079] Step 2:

[0080] The server performs natural language processing on the acquired data. The raw data obtained in step 1 is used as input. The server analyzes the data using the Python NLTK library and extracts important topics and keywords. The output is a summarized data file after the analysis is complete. Specifically, the server applies natural language processing algorithms to extract sentences and rank keywords from the data.

[0081] Step 3:

[0082] The server analyzes user behavior patterns. It uses the user's past email history and calendar events as input. Based on this data, the server identifies typical user behavior patterns and predicts future behavior. As output, pattern analysis data is accumulated, and the predictive model is updated. Specifically, the server uses machine learning algorithms to cluster the data and extract behavior patterns.

[0083] Step 4:

[0084] The terminal receives voice commands from the user. It uses the user's voice commands as input. The terminal uses a speech recognition API to convert the voice to text and sends that text information to the server. The output is the textualized user instructions. Specifically, the terminal takes in voice input in real time and activates the speech recognition engine.

[0085] Step 5:

[0086] The server analyzes text information sent from the terminal and searches for appropriate information. It uses text generated by voice commands as input. Based on this text, the server searches relevant databases and selects information to provide to the user. The output is information prepared for notification to the user. Specifically, the server executes SQL queries to retrieve the relevant data.

[0087] Step 6:

[0088] The terminal notifies the user of information sent from the server. It uses the information received from the server as input. The terminal displays the information on the screen and also informs the user audibly. Output includes both visual and audible notifications. Specifically, the terminal displays text on its display and uses a speech synthesis engine to provide voice notifications.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] In today's information-saturated society, it is difficult for users to obtain the information they need quickly and efficiently. Furthermore, while it is crucial to provide users with timely and optimal information and commuting routes based on their individual behavioral patterns and schedules, the means to achieve this are limited. This invention aims to solve these problems and provide technology that makes life in a smart city environment more convenient.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes means for acquiring information from multiple data sources to collect user information, means for analyzing the acquired information using natural language processing technology and extracting important topics and keywords, and means for analyzing the user's behavior patterns and schedules and providing relevant information. As a result, users can receive optimal routes and relevant news in real time based on their own actions.

[0094] An "information processing device" is a device that has the function of collecting, analyzing, and providing user information.

[0095] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0096] A "topic" refers to a theme or group of themes that are important to the user.

[0097] A "keyword" is a specific word or phrase used to summarize and express a topic.

[0098] "Behavioral patterns" refer to characteristics that indicate a user's past behavioral history and tendencies.

[0099] "Plans" refer to the schedule of actions and events that the user has planned for the future.

[0100] A "communication terminal" is a device that serves as an interface with the user and is used for inputting and outputting information.

[0101] "Information" is a collection of knowledge and data that users need.

[0102] A "route" is the optimal path for a user to reach their destination.

[0103] "News" refers to new information and events that are relevant to the user's life and decisions.

[0104] This invention provides a system that enables the provision of optimal information to users of smart cities. This system consists of an information processing device and a communication terminal, and by analyzing information collected from multiple data sources, it provides users with relevant information and optimal routes.

[0105] The information processing device analyzes acquired information using natural language processing technology and extracts topics and keywords. This makes it possible to efficiently organize information related to the user's behavior patterns and schedules. Specifically, it selects important news and event information based on the user's past behavior history and schedule information.

[0106] The communication terminal uses speech recognition technology to process voice commands from the user as text input and transmits the results to the information processing device. This allows the user to obtain the necessary information and select the optimal route hands-free. For example, if a user voice-inputs "Tell me today's commute route" in the morning, the information processing device analyzes traffic information and presents the fastest or most efficient route.

[0107] For implementation, the specific hardware that can be used includes smartphones, tablets, or wearable devices. For software, Google® Speech-to-Text API can be used for speech recognition, and NLTK or spaCy can be used for text information analysis.

[0108] One example of using a generation AI model for prompt messages is to input the following into the system: "Based on the provided user history, generate a daily summary of 'commute routes' and 'important news'," which will enable the provision of optimal information.

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The user inputs a voice command into a communication terminal. The terminal converts this voice command into text data using speech recognition technology. Here, the input is the user's voice command, and the output is the converted text data. Specifically, the user says, "Tell me today's commute route," and the terminal converts this voice into the text, "Tell me today's commute route."

[0112] Step 2:

[0113] The terminal sends text data to the server. The server analyzes the received text data and determines the type of information the user is requesting. Here, the input is the converted text data, and the output is the identification result of the user request. Specifically, the server starts the process of acquiring traffic information based on the keyword "commute route".

[0114] Step 3:

[0115] The server retrieves the latest traffic information from an external data source (e.g., a traffic information API). In this step, the input is a request based on the user's request, and the output is the retrieved real-time traffic information. For example, the server collects information on current road conditions and public transport delays.

[0116] Step 4:

[0117] The server uses natural language processing technology to analyze acquired traffic information and generate the optimal commute route. The input is real-time traffic information, and the output is optimal route information presented to the user. Specifically, the server uses a decision algorithm to select a route that avoids traffic congestion.

[0118] Step 5:

[0119] The server sends the generated optimal route information to the terminal. The terminal presents this information to the user visually or audibly. The input here is the optimal route information, and the output is the information displayed on the user's terminal. Specifically, the terminal displays a map on the screen and also announces aloud, "The current optimal commute route is via XX."

[0120] Step 6:

[0121] The user makes decisions based on the information presented. For the user, the input is route information from the device, and the output is the selected mode of transportation and route. Specifically, the user starts commuting using the newly presented route.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] The present invention provides a personal assistant incorporating emotion recognition technology to efficiently manage user information and support decision-making. First, a server acquires information from multiple data sources and analyzes that information using natural language processing technology. This extracts important topics and keywords and generates a summary of the information.

[0124] Next, the server analyzes the user's behavior patterns and schedule, and uses an emotion engine to analyze the user's emotional state from voice input and other data. Based on this emotion analysis, it becomes possible to customize how the user wants to receive information or how they want to proceed with tasks.

[0125] The emotion engine recognizes emotions such as joy, anger, sadness, and surprise by judging and numerically representing the characteristics of voice tone and word choice. The server then takes these emotional states into account and adjusts the way information is presented and the content of notifications to provide more appropriate and user-centric support.

[0126] For example, if a user asks their device in a depressed voice, "Tell me what's on my schedule today," the device, using voice recognition and an emotion engine, will determine that the user is feeling stressed or sad. The server can then take the user's emotional state into consideration and return a tailored response in a softer tone, such as, "Today isn't particularly busy, so you should be able to act without rushing." This allows the user to receive information more comfortably and reduce daily stress.

[0127] The introduction of this system will enable users to receive emotionally-driven information management and decision-making support, leading to a more fulfilling life. The collaborative operation of the server and terminals will allow users to receive support tailored to their individual needs, enabling the AI ​​personal assistant to truly fulfill the role of a secretary.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] The server retrieves information from multiple data sources configured by the user using an API. During this process, data is securely collected through an authentication protocol, and the retrieved information is stored in a database.

[0131] Step 2:

[0132] The server analyzes the stored data using natural language processing techniques. It extracts important topics and keywords from the text data and generates a summary. This summary is organized in a user-friendly format.

[0133] Step 3:

[0134] The server analyzes the user's past behavior patterns and schedule data. Based on this information, it predicts necessary tasks and stores them in a database as a prioritized list.

[0135] Step 4:

[0136] The terminal receives voice commands from the user. It uses speech recognition to convert the speech into text and prepares to send this text data to the server.

[0137] Step 5:

[0138] The server analyzes the user's emotions from transcribed voice commands using an emotion engine. It analyzes features such as voice intonation and speed to identify the user's emotional state. Based on this information, it adjusts the response and how tasks are presented.

[0139] Step 6:

[0140] Based on the analysis results, the server generates information and task notifications tailored to the user's current emotions. For example, if the user is feeling stressed, it presents information in simplified language and adds a positive message.

[0141] Step 7:

[0142] The terminal presents the user with pre-configured information and notifications received from the server. By displaying visual information on the screen and using speech synthesis technology to play audio information in an appropriate tone, it provides the user with the necessary information in the most optimal way.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] In modern society, the amount of information users access is increasing, and consequently, there is a need to efficiently manage this information and support decision-making that takes into account the user's emotional state. However, conventional systems have found it difficult to simultaneously manage information and provide personalized support based on the user's emotional state. Therefore, the present invention aims to construct a system that provides necessary information in a timely and appropriate manner while being attentive to the user's emotions.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes a storage device that acquires user-related data from multiple information sources, an information processing device that analyzes the acquired data using natural language processing techniques and extracts important topics and components, and an information processing device that analyzes the user's behavior patterns and schedules and provides relevant information. This makes it possible to manage and provide appropriate information while taking into account the user's emotional state.

[0148] A "storage device" refers to a storage medium that retains data for a long period of time and allows information processing devices to access it as needed.

[0149] An "information processing device" refers to an electronic device that analyzes input data and generates or extracts information according to its intended use.

[0150] "Natural language processing techniques" refer to a collection of technologies and methods that enable computers to understand and analyze human language.

[0151] An "emotion analysis device" refers to a device designed to analyze voice, text, and other data to determine the emotional state of a user.

[0152] "Generative AI technology" refers to artificial intelligence technology used to generate new data and responses based on large amounts of data.

[0153] A "computational device" refers to a computer system that processes data quickly and outputs the processing results.

[0154] The embodiments for carrying out the present invention are described below.

[0155] This system aims to efficiently manage user information and provide appropriate information based on emotions. The following details how the server, terminal, and user are involved.

[0156] First, the server operates in a cloud environment and retrieves user-related data from numerous sources within the storage system. This process utilizes database technology to incorporate information from news feeds, social media, calendars, and more. Next, the server analyzes the data using natural language processing technologies, such as Python's NLTK or spaCy. This extracts important topics and keywords and summarizes useful information.

[0157] Furthermore, the server acts as an emotion analyzer, analyzing voice input and text data to determine the user's emotions. In this process, it utilizes voice processing libraries such as OpenAI's Whisper and Google Cloud Speech-to-Text to quantify voice tone and word choice, identifying emotions such as joy, anger, and sadness.

[0158] When a user inputs a voice command into the terminal, the terminal analyzes it and sends it to the server. The server, based on generative AI technology, generates a response that matches the user's emotional state. This generated response is then presented to the user via the terminal. During this process, the server predicts the next task that is likely to be needed based on past behavioral data and notifies the user.

[0159] For example, if a user requests "What's on my schedule today?" in a depressed voice, the server, using an emotion analyzer, determines that the user is feeling stressed. Based on this, a customized response such as "Today isn't particularly busy, so you can relax" is generated and communicated to the user from the device.

[0160] An example of a prompt might be a question like, "If the user is showing positive emotions, how would you summarize the information and respond?"

[0161] In this configuration, the system can provide personalized information that takes into account the user's emotional state, enabling effective decision-making support.

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The server starts with a cloud-based storage system and collects user-related data from multiple sources. This input includes news feeds, social media, and calendar information. To retrieve this data, the server performs API calls and database queries. The output is a diverse collection of raw data.

[0165] Step 2:

[0166] The server performs natural language processing on the acquired raw data. Specifically, it analyzes the data using Python's NLTK and spaCy to extract important topics and keywords. The keywords extracted from the input data are output, and this summarizes the information necessary for the user.

[0167] Step 3:

[0168] The server analyzes the user's behavior patterns and schedule. Past behavioral history and schedule information are used as input data. Machine learning algorithms (e.g., using scikit-learn) are utilized to model the user's behavioral trends. The output is a prediction of the user's future behavior.

[0169] Step 4:

[0170] The server processes the voice data acquired from the user using an emotion analysis device. The input includes the user's voice tone and text data. The server uses an emotion analysis library (e.g., OpenAI's Whisper) to analyze the voice and quantify the emotion. This outputs the user's emotional state, facilitating the generation of responses based on that state.

[0171] Step 5:

[0172] The server adjusts how information is presented based on the user's emotional state. Here, generative AI technology is used to generate appropriate responses. The input includes the results of emotion analysis and keyword information extracted through natural language processing. The output is a customized response tailored to the user's emotions.

[0173] Step 6:

[0174] The terminal presents the response provided by the server to the user. Specifically, the terminal uses audio output and a screen display to inform the user of the generated response. This makes it possible to effectively provide information and support decision-making to the user.

[0175] (Application Example 2)

[0176] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0177] In modern society, individual lifestyles are diversifying, and there is a need to respond quickly to daily stress and emotional changes. This is especially important for the elderly and those with physical limitations, as their daily activities must be adapted to their individual emotional states. However, current information presentation systems are insufficient in providing personalized information and customizing tasks that take into account the user's emotional state, making improvement a pressing need.

[0178] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0179] In this invention, the server includes an emotion analysis means for analyzing the user's emotional state, a means for analyzing information acquired using natural language processing technology and extracting important topics and keywords, and a means for analyzing the user's activity trends and schedule and providing relevant information. This makes it possible to appropriately adjust the method of presenting information and the method of progressing tasks according to the user's emotional state.

[0180] An "information processing system" is a computer system used to collect and analyze user information. Its role is to extract important information from the obtained data and provide it to the user.

[0181] An "information display device" is a terminal that receives commands from a user, performs related operations, and presents information to the user in real time.

[0182] "Emotional analysis methods" are technologies that analyze a user's emotional state from their voice and behavioral data, and are used to determine what kind of emotions the user is experiencing.

[0183] "Adjustment methods" refer to methods for optimizing the presentation of information and the progress of tasks based on the user's emotional state, thereby providing beneficial support to the user.

[0184] To implement this invention, the server first collects information from multiple data sources. The server then analyzes the collected information using natural language processing technology, specifically the Python NLTK library, and extracts important topics and keywords. This organizes the information relevant to the user.

[0185] Next, the server uses Azure Cognitive Services to analyze the user's emotions from their voice data. This emotion analysis method provides a numerical evaluation of the user's emotional state. Furthermore, the server analyzes the user's activity patterns based on past data and predicts the information and tasks they will need next.

[0186] The device, specifically a smartphone or tablet, displays information sent from the server to the user in real time. A Web UI using Flask allows for intuitive operation. Furthermore, if the user is restless and issues a voice command, the system provides optimized information and advice tailored to their emotional state.

[0187] For example, when a user wants to relax, the device can suggest playing calming music. Furthermore, the following prompt statements are used for the generative AI model.

[0188] Prompt: Users are currently feeling anxious. Please provide calming news and gentle advice.

[0189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0190] Step 1:

[0191] The server collects user-related information from multiple data sources. Specifically, it retrieves information from sources such as news feeds and schedule databases. It uses access information to the data sources as input and generates an organized data set as output.

[0192] Step 2:

[0193] The server analyzes the collected data set using natural language processing techniques. It extracts important topics and keywords using the Python NLTK library. The input is the data set, and the output is a list of important keywords and topics.

[0194] Step 3:

[0195] The server analyzes user activity trends and past schedule data. Specifically, it retrieves past behavioral patterns from an SQL database and predicts the next tasks required. The input is activity history and schedule data, and the output is a predicted task list.

[0196] Step 4:

[0197] When a user inputs a voice command into the device, that voice data is sent to the server. The server uses Google Speech Recognition to convert this voice data into text data. The input is voice data, and the output is text data.

[0198] Step 5:

[0199] The server uses Azure Cognitive Services to analyze the user's emotional state based on text data. Specifically, it analyzes the vocabulary and tone of voice in the text to quantify the emotion. The input is text data, and the output is quantified emotion data.

[0200] Step 6:

[0201] The server optimizes how information is presented based on extracted key keywords and sentiment data. In some cases, a generative AI model is used at this stage to generate prompt text. The input is a keyword list and sentiment data, and the output is optimized prompt text and information display settings.

[0202] Step 7:

[0203] The terminal uses information display settings sent from the server to present information to the user in real time. Specifically, it displays information on the screen using a Web UI based on Flask. The input is the information display settings, and the output is the information screen displayed to the user.

[0204] Step 8:

[0205] The user reviews the presented information and enters the necessary commands into the terminal. The terminal sends these commands to the server, prompting further information updates or the start of new tasks. The input is the user's commands, and the output is the updated task list.

[0206] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0207] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0208] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0209] [Second Embodiment]

[0210] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0211] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0212] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0213] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0214] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0215] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0216] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0217] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0218] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0219] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0220] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0221] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0222] The system of this invention is designed to support users' information management and decision-making. It primarily involves a server and a terminal working together to provide users with the most relevant information. The server retrieves information from multiple data sources authorized by the user and analyzes this information using natural language processing technology. This allows it to extract important topics and keywords and create summaries.

[0223] The server analyzes user behavior patterns and schedules, and uses this data to make connections. This enables predictions based on the user's past behavior and provides optimal information. In particular, the server analyzes the user's past meeting and event participation history, as well as their daily activity time, to suggest the next necessary tasks.

[0224] On the other hand, the terminal is equipped with voice recognition capabilities and accepts voice commands from the user. The voice command analysis converts the voice into text, and then sends a request to the server according to the user's instructions, executing the necessary data and operations. This provides an environment in which the user can obtain information hands-free.

[0225] As a concrete example, when a user uses their smartphone and says, "Tell me my important appointments for today," the device recognizes the voice and converts it into text. This text information is sent to a server, which, based on previously collected data, provides a summary of the user's schedule and meeting details for the day. The device displays this summary on its screen and also informs the user verbally.

[0226] This system allows users to centrally manage necessary information from multiple sources, enabling them to efficiently carry out their daily tasks. Through the coordinated operation of the server and terminals, users can ensure they don't miss important information even in busy situations and clearly understand their priority tasks.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The server connects to multiple data sources specified by the user and retrieves the latest email and message data via APIs. This prepares the server to collect information relevant to the user.

[0230] Step 2:

[0231] The server removes unnecessary information from the acquired data and formats the text data. In particular, it removes HTML tags and unnecessary header information to make it suitable for natural language processing.

[0232] Step 3:

[0233] The server uses natural language processing (NLP) techniques to analyze the formatted text data. It extracts important topics and keywords and generates a summary. This improves the readability and relevance of the information.

[0234] Step 4:

[0235] The server considers the user's activity history and schedule information, and associates extracted topics with the user's current situation and future plans. Based on this, it identifies necessary notifications and tasks.

[0236] Step 5:

[0237] The terminal receives voice commands from the user and converts them into text using its built-in speech recognition function. This prepares the user's instructions and questions for transmission to the server.

[0238] Step 6:

[0239] Upon receiving user instructions in text format, the server analyzes the content, extracts appropriate information from the database, and sends it back to the terminal. This enables the provision of information tailored to the user's requests.

[0240] Step 7:

[0241] The terminal displays summary information and support tasks received from the server on its screen and reports them to the user using text-to-speech functionality as needed. This allows the user to access important information in real time.

[0242] (Example 1)

[0243] Next, we will describe Example 1. 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."

[0244] In modern society, it is common to receive fragmented information from numerous sources, making it difficult for users to effectively manage this information. Furthermore, amidst the increasing volume of information, users are required to quickly acquire necessary information and make appropriate decisions. However, current technology does not adequately provide systems that centrally manage information from multiple sources and deliver optimal information based on user behavior patterns and plans. A system to address this challenge is needed.

[0245] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0246] In this invention, the server includes means for acquiring information from multiple information sources authorized by the user using an information processing device and aggregating the information; means for analyzing the acquired information using natural language processing technology and extracting important information and features; and means for analyzing the user's behavior patterns and schedules and presenting information in association with that data. As a result, the user can centrally manage information obtained from multiple information sources and make quick and accurate decisions in their daily life.

[0247] An "information processing device" is a device consisting of hardware and software for collecting, organizing, managing, and analyzing information.

[0248] "Natural language processing technology" is a field of artificial intelligence technology used to analyze human language, understand its meaning, and extract information.

[0249] "Behavioral patterns" refer to certain regular movements or tendencies identified based on a user's past activities and preferences.

[0250] "Speech recognition technology" is a technology that converts speech into digital signals and then analyzes them to understand them as language.

[0251] A "predictive model" is a statistical and machine learning technique used to predict future events or outcomes by analyzing past data.

[0252] A "generative AI model" is a learning model that uses artificial intelligence to assist in the generation of new data and information.

[0253] "Information sources" refer to databases and internet resources that function as sources of information provided to users.

[0254] This invention relates to an information processing system that efficiently collects, analyzes, and provides user information in an appropriate format. The following details each component and its operation.

[0255] The server uses an information processing device to retrieve information from multiple sources authorized by the user. Specifically, it aggregates news articles, emails, calendar entries, and other data from databases and web services accessible via the Internet Protocol.

[0256] The server uses natural language processing libraries such as Python's NLTK (Natural Language Toolkit) to analyze the collected information. This analysis extracts important information and features and generates a summary in a format that is easy for users to understand intuitively. This summary allows users to quickly access the information they need.

[0257] Furthermore, the server analyzes user behavior patterns. For example, it identifies typical user behavior patterns based on past email sending history and calendar event participation history. This allows it to build a predictive model that can optimally provide information relevant to the user.

[0258] Meanwhile, the terminal uses speech recognition technology to receive voice commands from the user and convert them into text. Specifically, it uses a voice API to convert voice data into text and sends it to the server. This procedure allows the user to operate the system hands-free.

[0259] The terminal is equipped with an interface for notifying the user of analysis results sent from the server. By displaying the information visually on the screen and also notifying the user via audio, it provides an environment where users can easily receive information in a variety of situations.

[0260] As a concrete example, consider a scenario where a user gives a voice command to their smartphone saying, "Tell me the latest information about the participants of the next meeting." The device recognizes this voice command, converts it to text, and sends it to the server. The server retrieves the details of the meeting based on the user's calendar information, and then collects, summarizes, and provides the latest news and related information about the participants.

[0261] An example of a prompt message is, "Tell me tomorrow's weather forecast." The system then retrieves the latest weather data and presents it to the user. In this way, users can utilize an advanced information environment in their daily activities.

[0262] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0263] Step 1:

[0264] The server retrieves data from sources authorized by the user. It uses the URL of the news API and email server credentials specified by the user as input. The server accesses these sources to retrieve the latest news articles, emails, and calendar entries. The raw data is stored on the server as output. Specifically, the server periodically executes data retrieval scripts at programmed intervals.

[0265] Step 2:

[0266] The server performs natural language processing on the acquired data. The raw data obtained in step 1 is used as input. The server analyzes the data using the Python NLTK library and extracts important topics and keywords. The output is a summarized data file after the analysis is complete. Specifically, the server applies natural language processing algorithms to extract sentences and rank keywords from the data.

[0267] Step 3:

[0268] The server analyzes user behavior patterns. It uses the user's past email history and calendar events as input. Based on this data, the server identifies typical user behavior patterns and predicts future behavior. As output, pattern analysis data is accumulated, and the predictive model is updated. Specifically, the server uses machine learning algorithms to cluster the data and extract behavior patterns.

[0269] Step 4:

[0270] The terminal receives voice commands from the user. It uses the user's voice commands as input. The terminal uses a speech recognition API to convert the voice to text and sends that text information to the server. The output is the textualized user instructions. Specifically, the terminal takes in voice input in real time and activates the speech recognition engine.

[0271] Step 5:

[0272] The server analyzes text information sent from the terminal and searches for appropriate information. It uses text generated by voice commands as input. Based on this text, the server searches relevant databases and selects information to provide to the user. The output is information prepared for notification to the user. Specifically, the server executes SQL queries to retrieve the relevant data.

[0273] Step 6:

[0274] The terminal notifies the user of information sent from the server. It uses the information received from the server as input. The terminal displays the information on the screen and also informs the user audibly. Output includes both visual and audible notifications. Specifically, the terminal displays text on its display and uses a speech synthesis engine to provide voice notifications.

[0275] (Application Example 1)

[0276] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0277] In today's information-saturated society, it is difficult for users to obtain the information they need quickly and efficiently. Furthermore, while it is crucial to provide users with timely and optimal information and commuting routes based on their individual behavioral patterns and schedules, the means to achieve this are limited. This invention aims to solve these problems and provide technology that makes life in a smart city environment more convenient.

[0278] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0279] In this invention, the server includes means for acquiring information from multiple data sources to collect user information, means for analyzing the acquired information using natural language processing technology and extracting important topics and keywords, and means for analyzing the user's behavior patterns and schedules and providing relevant information. As a result, users can receive optimal routes and relevant news in real time based on their own actions.

[0280] An "information processing device" is a device that has the function of collecting, analyzing, and providing user information.

[0281] "Natural language processing technology" is a technology for a computer to understand and analyze human language.

[0282] "Topic" refers to the theme or group of themes of important information for the user.

[0283] "Keyword" refers to specific words or phrases for summarizing and expressing a topic.

[0284] "Behavior pattern" refers to the characteristics indicating the past behavior history and tendency of the user.

[0285] "Schedule" refers to the schedule of actions or events planned by the user in the future.

[0286] "Communication terminal" is a device that serves as an interface with the user and is used for input and output of information.

[0287] "Information" refers to the collection of knowledge and data required by the user.

[0288] "Route" refers to the optimal path for the user to reach the destination.

[0289] "News" refers to new information and events related to the user's life and decisions.

[0290] The present invention is a system that realizes optimal information provision for users of a smart city. This system is composed of an information processing device and a communication terminal, and by analyzing information collected from a plurality of data sources, it provides information related to the user and an optimal route.

[0291] The information processing device analyzes the information obtained using natural language processing technology and extracts topics and keywords. Thereby, it is possible to efficiently organize information related to the user's behavior pattern and schedule. Specifically, based on the past behavior history and schedule information of the user, important news and event information are selected.

[0292] The communication terminal uses speech recognition technology to process voice commands from the user as text input and transmits the results to the information processing device. This allows the user to obtain the necessary information and select the optimal route hands-free. For example, if a user voice-inputs "Tell me today's commute route" in the morning, the information processing device analyzes traffic information and presents the fastest or most efficient route.

[0293] For implementation, the specific hardware that can be used includes smartphones, tablets, or wearable devices. For software, Google Speech-to-Text API can be used for speech recognition, and NLTK or spaCy can be used for text information analysis.

[0294] One example of using a generation AI model for prompt messages is to input the following into the system: "Based on the provided user history, generate a daily summary of 'commute routes' and 'important news'," which will enable the provision of optimal information.

[0295] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0296] Step 1:

[0297] The user inputs a voice command into a communication terminal. The terminal converts this voice command into text data using speech recognition technology. Here, the input is the user's voice command, and the output is the converted text data. Specifically, the user says, "Tell me today's commute route," and the terminal converts this voice into the text, "Tell me today's commute route."

[0298] Step 2:

[0299] The terminal sends text data to the server. The server analyzes the received text data and determines the type of information the user is requesting. Here, the input is the converted text data, and the output is the identification result of the user request. Specifically, the server starts the process of acquiring traffic information based on the keyword "commute route".

[0300] Step 3:

[0301] The server retrieves the latest traffic information from an external data source (e.g., a traffic information API). In this step, the input is a request based on the user's request, and the output is the retrieved real-time traffic information. For example, the server collects information on current road conditions and public transport delays.

[0302] Step 4:

[0303] The server uses natural language processing technology to analyze acquired traffic information and generate the optimal commute route. The input is real-time traffic information, and the output is optimal route information presented to the user. Specifically, the server uses a decision algorithm to select a route that avoids traffic congestion.

[0304] Step 5:

[0305] The server sends the generated optimal route information to the terminal. The terminal presents this information to the user visually or audibly. The input here is the optimal route information, and the output is the information displayed on the user's terminal. Specifically, the terminal displays a map on the screen and also announces aloud, "The current optimal commute route is via XX."

[0306] Step 6:

[0307] The user makes decisions based on the information presented. For the user, the input is route information from the device, and the output is the selected mode of transportation and route. Specifically, the user starts commuting using the newly presented route.

[0308] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0309] The system of the present invention provides a personal assistant incorporating emotion recognition technology in order to efficiently manage user information and support decision-making. First, the server acquires information from a plurality of data sources and analyzes the information using natural language processing technology. Thereby, important topics and keywords are extracted, and a summary of the information is generated.

[0310] Next, the server analyzes the user's behavior pattern and schedule, and uses an emotion engine to analyze the emotional state from the user's voice input and other data. Based on this emotion analysis, it becomes possible to customize how the user wants to receive information or how to proceed with a task.

[0311] The emotion engine recognizes emotions such as joy, anger, sadness, and surprise by judging the characteristics of voice tone and diction and expressing them numerically. The server provides more appropriate and user-friendly support by adjusting the information presentation method and the content of notifications while considering these emotional states.

[0312] As a specific example, when the user asks the terminal "Tell me today's schedule" in a depressed voice, the terminal judges that the user is feeling stress or sadness due to the functions of voice recognition and the emotion engine. The server can return an adjusted response such as "Today is not particularly busy, so I think you can act without rushing" in a gentle tone considering the user's emotional state. Thereby, the user can receive information more comfortably and reduce daily stress.

[0313] The introduction of this system will enable users to receive emotionally-driven information management and decision-making support, leading to a more fulfilling life. The collaborative operation of the server and terminals will allow users to receive support tailored to their individual needs, enabling the AI ​​personal assistant to truly fulfill the role of a secretary.

[0314] The following describes the processing flow.

[0315] Step 1:

[0316] The server retrieves information from multiple data sources configured by the user using an API. During this process, data is securely collected through an authentication protocol, and the retrieved information is stored in a database.

[0317] Step 2:

[0318] The server analyzes the stored data using natural language processing techniques. It extracts important topics and keywords from the text data and generates a summary. This summary is organized in a user-friendly format.

[0319] Step 3:

[0320] The server analyzes the user's past behavior patterns and schedule data. Based on this information, it predicts necessary tasks and stores them in a database as a prioritized list.

[0321] Step 4:

[0322] The terminal receives voice commands from the user. It uses speech recognition to convert the speech into text and prepares to send this text data to the server.

[0323] Step 5:

[0324] The server analyzes the user's emotions from transcribed voice commands using an emotion engine. It analyzes features such as voice intonation and speed to identify the user's emotional state. Based on this information, it adjusts the response and how tasks are presented.

[0325] Step 6:

[0326] Based on the analysis results, the server generates information and task notifications tailored to the user's current emotions. For example, if the user is feeling stressed, it presents information in simplified language and adds a positive message.

[0327] Step 7:

[0328] The terminal presents the user with pre-configured information and notifications received from the server. By displaying visual information on the screen and using speech synthesis technology to play audio information in an appropriate tone, it provides the user with the necessary information in the most optimal way.

[0329] (Example 2)

[0330] Next, we will describe Example 2. 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".

[0331] In modern society, the amount of information users access is increasing, and consequently, there is a need to efficiently manage this information and support decision-making that takes into account the user's emotional state. However, conventional systems have found it difficult to simultaneously manage information and provide personalized support based on the user's emotional state. Therefore, the present invention aims to construct a system that provides necessary information in a timely and appropriate manner while being attentive to the user's emotions.

[0332] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0333] In this invention, the server includes a storage device that acquires user-related data from multiple information sources, an information processing device that analyzes the acquired data using natural language processing techniques and extracts important topics and components, and an information processing device that analyzes the user's behavior patterns and schedules and provides relevant information. This makes it possible to manage and provide appropriate information while taking into account the user's emotional state.

[0334] A "storage device" refers to a storage medium that retains data for a long period of time and allows information processing devices to access it as needed.

[0335] An "information processing device" refers to an electronic device that analyzes input data and generates or extracts information according to its intended use.

[0336] "Natural language processing techniques" refer to a collection of technologies and methods that enable computers to understand and analyze human language.

[0337] An "emotion analysis device" refers to a device designed to analyze voice, text, and other data to determine the emotional state of a user.

[0338] "Generative AI technology" refers to artificial intelligence technology used to generate new data and responses based on large amounts of data.

[0339] A "computational device" refers to a computer system that processes data quickly and outputs the processing results.

[0340] The embodiments for carrying out the present invention are described below.

[0341] This system aims to efficiently manage user information and provide appropriate information based on emotions. The following details how the server, terminal, and user are involved.

[0342] First, the server operates in a cloud environment and retrieves user-related data from numerous sources within the storage system. This process utilizes database technology to incorporate information from news feeds, social media, calendars, and more. Next, the server analyzes the data using natural language processing technologies, such as Python's NLTK or spaCy. This extracts important topics and keywords and summarizes useful information.

[0343] Furthermore, the server acts as an emotion analyzer, analyzing voice input and text data to determine the user's emotions. In this process, it utilizes voice processing libraries such as OpenAI's Whisper and Google Cloud Speech-to-Text to quantify voice tone and word choice, identifying emotions such as joy, anger, and sadness.

[0344] When a user inputs a voice command into the terminal, the terminal analyzes it and sends it to the server. The server, based on generative AI technology, generates a response that matches the user's emotional state. This generated response is then presented to the user via the terminal. During this process, the server predicts the next task that is likely to be needed based on past behavioral data and notifies the user.

[0345] For example, if a user requests "What's on my schedule today?" in a depressed voice, the server, using an emotion analyzer, determines that the user is feeling stressed. Based on this, a customized response such as "Today isn't particularly busy, so you can relax" is generated and communicated to the user from the device.

[0346] An example of a prompt might be a question like, "If the user is showing positive emotions, how would you summarize the information and respond?"

[0347] In this configuration, the system can provide personalized information that takes into account the user's emotional state, enabling effective decision-making support.

[0348] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0349] Step 1:

[0350] The server starts with a cloud-based storage system and collects user-related data from multiple sources. This input includes news feeds, social media, and calendar information. To retrieve this data, the server performs API calls and database queries. The output is a diverse collection of raw data.

[0351] Step 2:

[0352] The server performs natural language processing on the acquired raw data. Specifically, it analyzes the data using Python's NLTK and spaCy to extract important topics and keywords. The keywords extracted from the input data are output, and this summarizes the information necessary for the user.

[0353] Step 3:

[0354] The server analyzes the user's behavior patterns and schedule. Past behavioral history and schedule information are used as input data. Machine learning algorithms (e.g., using scikit-learn) are utilized to model the user's behavioral trends. The output is a prediction of the user's future behavior.

[0355] Step 4:

[0356] The server processes the voice data acquired from the user using an emotion analysis device. The input includes the user's voice tone and text data. The server uses an emotion analysis library (e.g., OpenAI's Whisper) to analyze the voice and quantify the emotion. This outputs the user's emotional state, facilitating the generation of responses based on that state.

[0357] Step 5:

[0358] The server adjusts how information is presented based on the user's emotional state. Here, generative AI technology is used to generate appropriate responses. The input includes the results of emotion analysis and keyword information extracted through natural language processing. The output is a customized response tailored to the user's emotions.

[0359] Step 6:

[0360] The terminal presents the response provided by the server to the user. Specifically, the terminal uses audio output and a screen display to inform the user of the generated response. This makes it possible to effectively provide information and support decision-making to the user.

[0361] (Application Example 2)

[0362] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0363] In modern society, individual lifestyles are diversifying, and there is a need to respond quickly to daily stress and emotional changes. This is especially important for the elderly and those with physical limitations, as their daily activities must be adapted to their individual emotional states. However, current information presentation systems are insufficient in providing personalized information and customizing tasks that take into account the user's emotional state, making improvement a pressing need.

[0364] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0365] In this invention, the server includes an emotion analysis means for analyzing the user's emotional state, a means for analyzing information acquired using natural language processing technology and extracting important topics and keywords, and a means for analyzing the user's activity trends and schedule and providing relevant information. This makes it possible to appropriately adjust the method of presenting information and the method of progressing tasks according to the user's emotional state.

[0366] An "information processing system" is a computer system used to collect and analyze user information. Its role is to extract important information from the obtained data and provide it to the user.

[0367] An "information display device" is a terminal that receives commands from a user, performs related operations, and presents information to the user in real time.

[0368] "Emotional analysis methods" are technologies that analyze a user's emotional state from their voice and behavioral data, and are used to determine what kind of emotions the user is experiencing.

[0369] "Adjustment methods" refer to methods for optimizing the presentation of information and the progress of tasks based on the user's emotional state, thereby providing beneficial support to the user.

[0370] To implement this invention, the server first collects information from multiple data sources. The server then analyzes the collected information using natural language processing technology, specifically the Python NLTK library, and extracts important topics and keywords. This organizes the information relevant to the user.

[0371] Next, the server uses Azure Cognitive Services to analyze the user's emotions from their voice data. This emotion analysis provides a numerical evaluation of the user's emotional state. Furthermore, the server analyzes the user's activity patterns based on past data and predicts the information and tasks they will need next.

[0372] The device, specifically a smartphone or tablet, displays information sent from the server to the user in real time. A Web UI using Flask allows for intuitive operation. Furthermore, if the user is restless and issues a voice command, the system provides optimized information and advice tailored to their emotional state.

[0373] For example, when a user wants to relax, the device can suggest playing calming music. Furthermore, the following prompt statements are used for the generative AI model.

[0374] Prompt: Users are currently feeling anxious. Please provide calming news and gentle advice.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The server collects user-related information from multiple data sources. Specifically, it retrieves information from sources such as news feeds and schedule databases. It uses access information to the data sources as input and generates an organized data set as output.

[0378] Step 2:

[0379] The server analyzes the collected data set using natural language processing techniques. It extracts important topics and keywords using the Python NLTK library. The input is the data set, and the output is a list of important keywords and topics.

[0380] Step 3:

[0381] The server analyzes user activity trends and past schedule data. Specifically, it retrieves past behavioral patterns from an SQL database and predicts the next tasks required. The input is activity history and schedule data, and the output is a predicted task list.

[0382] Step 4:

[0383] When a user inputs a voice command into the device, that voice data is sent to the server. The server uses Google Speech Recognition to convert this voice data into text data. The input is voice data, and the output is text data.

[0384] Step 5:

[0385] The server uses Azure Cognitive Services to analyze the user's emotional state based on text data. Specifically, it analyzes the vocabulary and tone of voice in the text to quantify the emotion. The input is text data, and the output is quantified emotion data.

[0386] Step 6:

[0387] The server optimizes how information is presented based on extracted key keywords and sentiment data. In some cases, a generative AI model is used at this stage to generate prompt text. The input is a keyword list and sentiment data, and the output is optimized prompt text and information display settings.

[0388] Step 7:

[0389] The terminal uses information display settings sent from the server to present information to the user in real time. Specifically, it displays information on the screen using a Web UI based on Flask. The input is the information display settings, and the output is the information screen displayed to the user.

[0390] Step 8:

[0391] The user reviews the presented information and enters the necessary commands into the terminal. The terminal sends these commands to the server, prompting further information updates or the start of new tasks. The input is the user's commands, and the output is the updated task list.

[0392] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0393] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0395] [Third Embodiment]

[0396] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0397] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0398] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0399] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0400] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0401] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0402] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0403] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0404] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0405] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0406] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0407] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0408] The system of this invention is designed to support users' information management and decision-making. It primarily involves a server and a terminal working together to provide users with the most relevant information. The server retrieves information from multiple data sources authorized by the user and analyzes this information using natural language processing technology. This allows it to extract important topics and keywords and create summaries.

[0409] The server analyzes user behavior patterns and schedules, and uses this data to make connections. This enables predictions based on the user's past behavior and provides optimal information. In particular, the server analyzes the user's past meeting and event participation history, as well as their daily activity time, to suggest the next necessary tasks.

[0410] On the other hand, the terminal is equipped with voice recognition capabilities and accepts voice commands from the user. The voice command analysis converts the voice into text, and then sends a request to the server according to the user's instructions, executing the necessary data and operations. This provides an environment in which the user can obtain information hands-free.

[0411] As a concrete example, when a user uses their smartphone and says, "Tell me my important appointments for today," the device recognizes the voice and converts it into text. This text information is sent to a server, which, based on previously collected data, provides a summary of the user's schedule and meeting details for the day. The device displays this summary on its screen and also informs the user verbally.

[0412] This system allows users to centrally manage necessary information from multiple sources, enabling them to efficiently carry out their daily tasks. Through the coordinated operation of the server and terminals, users can ensure they don't miss important information even in busy situations and clearly understand their priority tasks.

[0413] The following describes the processing flow.

[0414] Step 1:

[0415] The server connects to multiple data sources specified by the user and retrieves the latest email and message data via APIs. This prepares the server to collect information relevant to the user.

[0416] Step 2:

[0417] The server removes unnecessary information from the acquired data and formats the text data. In particular, it removes HTML tags and unnecessary header information to make it suitable for natural language processing.

[0418] Step 3:

[0419] The server uses natural language processing (NLP) techniques to analyze the formatted text data. It extracts important topics and keywords and generates a summary. This improves the readability and relevance of the information.

[0420] Step 4:

[0421] The server considers the user's activity history and schedule information, and associates extracted topics with the user's current situation and future plans. Based on this, it identifies necessary notifications and tasks.

[0422] Step 5:

[0423] The terminal receives voice commands from the user and converts them into text using its built-in speech recognition function. This prepares the user's instructions and questions for transmission to the server.

[0424] Step 6:

[0425] Upon receiving user instructions in text format, the server analyzes the content, extracts appropriate information from the database, and sends it back to the terminal. This enables the provision of information tailored to the user's requests.

[0426] Step 7:

[0427] The terminal displays summary information and support tasks received from the server on its screen and reports them to the user using text-to-speech functionality as needed. This allows the user to access important information in real time.

[0428] (Example 1)

[0429] Next, we will describe Example 1. 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."

[0430] In modern society, it is common to receive fragmented information from numerous sources, making it difficult for users to effectively manage this information. Furthermore, amidst the increasing volume of information, users are required to quickly acquire necessary information and make appropriate decisions. However, current technology does not adequately provide systems that centrally manage information from multiple sources and deliver optimal information based on user behavior patterns and plans. A system to address this challenge is needed.

[0431] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0432] In this invention, the server includes means for acquiring information from multiple information sources authorized by the user using an information processing device and aggregating the information; means for analyzing the acquired information using natural language processing technology and extracting important information and features; and means for analyzing the user's behavior patterns and schedules and presenting information in association with that data. As a result, the user can centrally manage information obtained from multiple information sources and make quick and accurate decisions in their daily life.

[0433] An "information processing device" is a device consisting of hardware and software for collecting, organizing, managing, and analyzing information.

[0434] "Natural language processing technology" is a field of artificial intelligence technology used to analyze human language, understand its meaning, and extract information.

[0435] "Behavioral patterns" refer to certain regular movements or tendencies identified based on a user's past activities and preferences.

[0436] "Speech recognition technology" is a technology that converts speech into digital signals and then analyzes them to understand them as language.

[0437] A "predictive model" is a statistical and machine learning technique used to predict future events or outcomes by analyzing past data.

[0438] A "generative AI model" is a learning model that uses artificial intelligence to assist in the generation of new data and information.

[0439] "Information sources" refer to databases and internet resources that function as sources of information provided to users.

[0440] This invention relates to an information processing system that efficiently collects, analyzes, and provides user information in an appropriate format. The following details each component and its operation.

[0441] The server uses an information processing device to retrieve information from multiple sources authorized by the user. Specifically, it aggregates news articles, emails, calendar entries, and other data from databases and web services accessible via the Internet Protocol.

[0442] The server uses natural language processing libraries such as Python's NLTK (Natural Language Toolkit) to analyze the collected information. This analysis extracts important information and features and generates a summary in a format that is easy for users to understand intuitively. This summary allows users to quickly access the information they need.

[0443] Furthermore, the server analyzes user behavior patterns. For example, it identifies typical user behavior patterns based on past email sending history and calendar event participation history. This allows it to build a predictive model that can optimally provide information relevant to the user.

[0444] Meanwhile, the terminal uses speech recognition technology to receive voice commands from the user and convert them into text. Specifically, it uses a voice API to convert voice data into text and sends it to the server. This procedure allows the user to operate the system hands-free.

[0445] The terminal is equipped with an interface for notifying the user of analysis results sent from the server. By displaying the information visually on the screen and also notifying the user via audio, it provides an environment where users can easily receive information in a variety of situations.

[0446] As a concrete example, consider a scenario where a user gives a voice command to their smartphone saying, "Tell me the latest information about the participants of the next meeting." The device recognizes this voice command, converts it to text, and sends it to the server. The server retrieves the details of the meeting based on the user's calendar information, and then collects, summarizes, and provides the latest news and related information about the participants.

[0447] An example of a prompt message is, "Tell me tomorrow's weather forecast." The system then retrieves the latest weather data and presents it to the user. In this way, users can utilize an advanced information environment in their daily activities.

[0448] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0449] Step 1:

[0450] The server retrieves data from sources authorized by the user. It uses the URL of the news API and email server credentials specified by the user as input. The server accesses these sources to retrieve the latest news articles, emails, and calendar entries. The raw data is stored on the server as output. Specifically, the server periodically executes data retrieval scripts at programmed intervals.

[0451] Step 2:

[0452] The server performs natural language processing on the acquired data. The raw data obtained in step 1 is used as input. The server analyzes the data using the Python NLTK library and extracts important topics and keywords. The output is a summarized data file after the analysis is complete. Specifically, the server applies natural language processing algorithms to extract sentences and rank keywords from the data.

[0453] Step 3:

[0454] The server analyzes user behavior patterns. It uses the user's past email history and calendar events as input. Based on this data, the server identifies typical user behavior patterns and predicts future behavior. As output, pattern analysis data is accumulated, and the predictive model is updated. Specifically, the server uses machine learning algorithms to cluster the data and extract behavior patterns.

[0455] Step 4:

[0456] The terminal receives voice commands from the user. It uses the user's voice commands as input. The terminal uses a speech recognition API to convert the voice to text and sends that text information to the server. The output is the textualized user instructions. Specifically, the terminal takes in voice input in real time and activates the speech recognition engine.

[0457] Step 5:

[0458] The server analyzes text information sent from the terminal and searches for appropriate information. It uses text generated by voice commands as input. Based on this text, the server searches relevant databases and selects information to provide to the user. The output is information prepared for notification to the user. Specifically, the server executes SQL queries to retrieve the relevant data.

[0459] Step 6:

[0460] The terminal notifies the user of information sent from the server. It uses the information received from the server as input. The terminal displays the information on the screen and also informs the user audibly. Output includes both visual and audible notifications. Specifically, the terminal displays text on its display and uses a speech synthesis engine to provide voice notifications.

[0461] (Application Example 1)

[0462] Next, we will explain Application Example 1. In the following explanation, 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."

[0463] In today's information-saturated society, it is difficult for users to obtain the information they need quickly and efficiently. Furthermore, while it is crucial to provide users with timely and optimal information and commuting routes based on their individual behavioral patterns and schedules, the means to achieve this are limited. This invention aims to solve these problems and provide technology that makes life in a smart city environment more convenient.

[0464] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0465] In this invention, the server includes means for acquiring information from multiple data sources to collect user information, means for analyzing the acquired information using natural language processing technology and extracting important topics and keywords, and means for analyzing the user's behavior patterns and schedules and providing relevant information. As a result, users can receive optimal routes and relevant news in real time based on their own actions.

[0466] An "information processing device" is a device that has the function of collecting, analyzing, and providing user information.

[0467] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0468] A "topic" refers to a theme or group of themes that are important to the user.

[0469] A "keyword" is a specific word or phrase used to summarize and express a topic.

[0470] "Behavioral patterns" refer to characteristics that indicate a user's past behavioral history and tendencies.

[0471] "Plans" refer to the schedule of actions and events that the user has planned for the future.

[0472] A "communication terminal" is a device that serves as an interface with the user and is used for inputting and outputting information.

[0473] "Information" is a collection of knowledge and data that users need.

[0474] A "route" is the optimal path for a user to reach their destination.

[0475] "News" refers to new information and events that are relevant to the user's life and decisions.

[0476] This invention provides a system that enables the provision of optimal information to users of smart cities. This system consists of an information processing device and a communication terminal, and by analyzing information collected from multiple data sources, it provides users with relevant information and optimal routes.

[0477] The information processing device analyzes acquired information using natural language processing technology and extracts topics and keywords. This makes it possible to efficiently organize information related to the user's behavior patterns and schedules. Specifically, it selects important news and event information based on the user's past behavior history and schedule information.

[0478] The communication terminal uses speech recognition technology to process voice commands from the user as text input and transmits the results to the information processing device. This allows the user to obtain the necessary information and select the optimal route hands-free. For example, if a user voice-inputs "Tell me today's commute route" in the morning, the information processing device analyzes traffic information and presents the fastest or most efficient route.

[0479] For implementation, the specific hardware that can be used includes smartphones, tablets, or wearable devices. For software, Google Speech-to-Text API can be used for speech recognition, and NLTK or spaCy can be used for text information analysis.

[0480] One example of using a generation AI model for prompt messages is to input the following into the system: "Based on the provided user history, generate a daily summary of 'commute routes' and 'important news'," which will enable the provision of optimal information.

[0481] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0482] Step 1:

[0483] The user inputs a voice command into a communication terminal. The terminal converts this voice command into text data using speech recognition technology. Here, the input is the user's voice command, and the output is the converted text data. Specifically, the user says, "Tell me today's commute route," and the terminal converts this voice into the text, "Tell me today's commute route."

[0484] Step 2:

[0485] The terminal sends text data to the server. The server analyzes the received text data and determines the type of information the user is requesting. Here, the input is the converted text data, and the output is the identification result of the user request. Specifically, the server starts the process of acquiring traffic information based on the keyword "commute route".

[0486] Step 3:

[0487] The server retrieves the latest traffic information from an external data source (e.g., a traffic information API). In this step, the input is a request based on the user's request, and the output is the retrieved real-time traffic information. For example, the server collects information on current road conditions and public transport delays.

[0488] Step 4:

[0489] The server uses natural language processing technology to analyze acquired traffic information and generate the optimal commute route. The input is real-time traffic information, and the output is optimal route information presented to the user. Specifically, the server uses a decision algorithm to select a route that avoids traffic congestion.

[0490] Step 5:

[0491] The server sends the generated optimal route information to the terminal. The terminal presents this information to the user visually or audibly. The input here is the optimal route information, and the output is the information displayed on the user's terminal. Specifically, the terminal displays a map on the screen and also announces aloud, "The current optimal commute route is via XX."

[0492] Step 6:

[0493] The user makes decisions based on the information presented. For the user, the input is route information from the device, and the output is the selected mode of transportation and route. Specifically, the user starts commuting using the newly presented route.

[0494] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0495] The present invention provides a personal assistant incorporating emotion recognition technology to efficiently manage user information and support decision-making. First, a server acquires information from multiple data sources and analyzes that information using natural language processing technology. This extracts important topics and keywords and generates a summary of the information.

[0496] Next, the server analyzes the user's behavior patterns and schedule, and uses an emotion engine to analyze the user's emotional state from voice input and other data. Based on this emotion analysis, it becomes possible to customize how the user wants to receive information or how they want to proceed with tasks.

[0497] The emotion engine recognizes emotions such as joy, anger, sadness, and surprise by judging and numerically representing the characteristics of voice tone and word choice. The server then takes these emotional states into account and adjusts the way information is presented and the content of notifications to provide more appropriate and user-centric support.

[0498] For example, if a user asks their device in a depressed voice, "Tell me what's on my schedule today," the device, using voice recognition and an emotion engine, will determine that the user is feeling stressed or sad. The server can then take the user's emotional state into consideration and return a tailored response in a softer tone, such as, "Today isn't particularly busy, so you should be able to act without rushing." This allows the user to receive information more comfortably and reduce daily stress.

[0499] The introduction of this system will enable users to receive emotionally-driven information management and decision-making support, leading to a more fulfilling life. The collaborative operation of the server and terminals will allow users to receive support tailored to their individual needs, enabling the AI ​​personal assistant to truly fulfill the role of a secretary.

[0500] The following describes the processing flow.

[0501] Step 1:

[0502] The server retrieves information from multiple data sources configured by the user using an API. During this process, data is securely collected through an authentication protocol, and the retrieved information is stored in a database.

[0503] Step 2:

[0504] The server analyzes the stored data using natural language processing techniques. It extracts important topics and keywords from the text data and generates a summary. This summary is organized in a user-friendly format.

[0505] Step 3:

[0506] The server analyzes the user's past behavior patterns and schedule data. Based on this information, it predicts necessary tasks and stores them in a database as a prioritized list.

[0507] Step 4:

[0508] The terminal receives voice commands from the user. It uses speech recognition to convert the speech into text and prepares to send this text data to the server.

[0509] Step 5:

[0510] The server analyzes the user's emotions from transcribed voice commands using an emotion engine. It analyzes features such as voice intonation and speed to identify the user's emotional state. Based on this information, it adjusts the response and how tasks are presented.

[0511] Step 6:

[0512] Based on the analysis results, the server generates information and task notifications tailored to the user's current emotions. For example, if the user is feeling stressed, it presents information in simplified language and adds a positive message.

[0513] Step 7:

[0514] The terminal presents the user with pre-configured information and notifications received from the server. By displaying visual information on the screen and using speech synthesis technology to play audio information in an appropriate tone, it provides the user with the necessary information in the most optimal way.

[0515] (Example 2)

[0516] Next, we will describe Example 2. 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."

[0517] In modern society, the amount of information users access is increasing, and consequently, there is a need to efficiently manage this information and support decision-making that takes into account the user's emotional state. However, conventional systems have found it difficult to simultaneously manage information and provide personalized support based on the user's emotional state. Therefore, the present invention aims to construct a system that provides necessary information in a timely and appropriate manner while being attentive to the user's emotions.

[0518] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0519] In this invention, the server includes a storage device that acquires user-related data from multiple information sources, an information processing device that analyzes the acquired data using natural language processing techniques and extracts important topics and components, and an information processing device that analyzes the user's behavior patterns and schedules and provides relevant information. This makes it possible to manage and provide appropriate information while taking into account the user's emotional state.

[0520] A "storage device" refers to a storage medium that retains data for a long period of time and allows information processing devices to access it as needed.

[0521] An "information processing device" refers to an electronic device that analyzes input data and generates or extracts information according to its intended use.

[0522] "Natural language processing techniques" refer to a collection of technologies and methods that enable computers to understand and analyze human language.

[0523] An "emotion analysis device" refers to a device designed to analyze voice, text, and other data to determine the emotional state of a user.

[0524] "Generative AI technology" refers to artificial intelligence technology used to generate new data and responses based on large amounts of data.

[0525] A "computational device" refers to a computer system that processes data quickly and outputs the processing results.

[0526] The embodiments for carrying out the present invention are described below.

[0527] This system aims to efficiently manage user information and provide appropriate information based on emotions. The following details how the server, terminal, and user are involved.

[0528] First, the server operates in a cloud environment and retrieves user-related data from numerous sources within the storage system. This process utilizes database technology to incorporate information from news feeds, social media, calendars, and more. Next, the server analyzes the data using natural language processing technologies, such as Python's NLTK or spaCy. This extracts important topics and keywords and summarizes useful information.

[0529] Furthermore, the server acts as an emotion analyzer, analyzing voice input and text data to determine the user's emotions. In this process, it utilizes voice processing libraries such as OpenAI's Whisper and Google Cloud Speech-to-Text to quantify voice tone and word choice, identifying emotions such as joy, anger, and sadness.

[0530] When a user inputs a voice command into the terminal, the terminal analyzes it and sends it to the server. The server, based on generative AI technology, generates a response that matches the user's emotional state. This generated response is then presented to the user via the terminal. During this process, the server predicts the next task that is likely to be needed based on past behavioral data and notifies the user.

[0531] For example, if a user requests "What's on my schedule today?" in a depressed voice, the server, using an emotion analyzer, determines that the user is feeling stressed. Based on this, a customized response such as "Today isn't particularly busy, so you can relax" is generated and communicated to the user from the device.

[0532] An example of a prompt might be a question like, "If the user is showing positive emotions, how would you summarize the information and respond?"

[0533] In this configuration, the system can provide personalized information that takes into account the user's emotional state, enabling effective decision-making support.

[0534] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0535] Step 1:

[0536] The server starts with a cloud-based storage system and collects user-related data from multiple sources. This input includes news feeds, social media, and calendar information. To retrieve this data, the server performs API calls and database queries. The output is a diverse collection of raw data.

[0537] Step 2:

[0538] The server performs natural language processing on the acquired raw data. Specifically, it analyzes the data using Python's NLTK and spaCy to extract important topics and keywords. The keywords extracted from the input data are output, and this summarizes the information necessary for the user.

[0539] Step 3:

[0540] The server analyzes the user's behavior patterns and schedule. Past behavioral history and schedule information are used as input data. Machine learning algorithms (e.g., using scikit-learn) are utilized to model the user's behavioral trends. The output is a prediction of the user's future behavior.

[0541] Step 4:

[0542] The server processes the voice data acquired from the user using an emotion analysis device. The input includes the user's voice tone and text data. The server uses an emotion analysis library (e.g., OpenAI's Whisper) to analyze the voice and quantify the emotion. This outputs the user's emotional state, facilitating the generation of responses based on that state.

[0543] Step 5:

[0544] The server adjusts how information is presented based on the user's emotional state. Here, generative AI technology is used to generate appropriate responses. The input includes the results of emotion analysis and keyword information extracted through natural language processing. The output is a customized response tailored to the user's emotions.

[0545] Step 6:

[0546] The terminal presents the response provided by the server to the user. Specifically, the terminal uses audio output and a screen display to inform the user of the generated response. This makes it possible to effectively provide information and support decision-making to the user.

[0547] (Application Example 2)

[0548] Next, we will explain application example 2. In the following explanation, 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."

[0549] In modern society, individual lifestyles are diversifying, and there is a need to respond quickly to daily stress and emotional changes. This is especially important for the elderly and those with physical limitations, as their daily activities must be adapted to their individual emotional states. However, current information presentation systems are insufficient in providing personalized information and customizing tasks that take into account the user's emotional state, making improvement a pressing need.

[0550] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0551] In this invention, the server includes an emotion analysis means for analyzing the user's emotional state, a means for analyzing information acquired using natural language processing technology and extracting important topics and keywords, and a means for analyzing the user's activity trends and schedule and providing relevant information. This makes it possible to appropriately adjust the method of presenting information and the method of progressing tasks according to the user's emotional state.

[0552] An "information processing system" is a computer system used to collect and analyze user information. Its role is to extract important information from the obtained data and provide it to the user.

[0553] An "information display device" is a terminal that receives commands from a user, performs related operations, and presents information to the user in real time.

[0554] "Emotional analysis methods" are technologies that analyze a user's emotional state from their voice and behavioral data, and are used to determine what kind of emotions the user is experiencing.

[0555] "Adjustment methods" refer to methods for optimizing the presentation of information and the progress of tasks based on the user's emotional state, thereby providing beneficial support to the user.

[0556] To implement this invention, the server first collects information from multiple data sources. The server then analyzes the collected information using natural language processing technology, specifically the Python NLTK library, and extracts important topics and keywords. This organizes the information relevant to the user.

[0557] Next, the server uses Azure Cognitive Services to analyze the user's emotions from their voice data. This emotion analysis provides a numerical evaluation of the user's emotional state. Furthermore, the server analyzes the user's activity patterns based on past data and predicts the information and tasks they will need next.

[0558] The device, specifically a smartphone or tablet, displays information sent from the server to the user in real time. A Web UI using Flask allows for intuitive operation. Furthermore, if the user is restless and issues a voice command, the system provides optimized information and advice tailored to their emotional state.

[0559] For example, when a user wants to relax, the device can suggest playing calming music. Furthermore, the following prompt statements are used for the generative AI model.

[0560] Prompt: Users are currently feeling anxious. Please provide calming news and gentle advice.

[0561] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0562] Step 1:

[0563] The server collects user-related information from multiple data sources. Specifically, it retrieves information from sources such as news feeds and schedule databases. It uses access information to the data sources as input and generates an organized data set as output.

[0564] Step 2:

[0565] The server analyzes the collected data set using natural language processing techniques. It extracts important topics and keywords using the Python NLTK library. The input is the data set, and the output is a list of important keywords and topics.

[0566] Step 3:

[0567] The server analyzes user activity trends and past schedule data. Specifically, it retrieves past behavioral patterns from an SQL database and predicts the next tasks required. The input is activity history and schedule data, and the output is a predicted task list.

[0568] Step 4:

[0569] When a user inputs a voice command into the device, that voice data is sent to the server. The server uses Google Speech Recognition to convert this voice data into text data. The input is voice data, and the output is text data.

[0570] Step 5:

[0571] The server uses Azure Cognitive Services to analyze the user's emotional state based on text data. Specifically, it analyzes the vocabulary and tone of voice in the text to quantify the emotion. The input is text data, and the output is quantified emotion data.

[0572] Step 6:

[0573] The server optimizes how information is presented based on extracted key keywords and sentiment data. In some cases, a generative AI model is used at this stage to generate prompt text. The input is a keyword list and sentiment data, and the output is optimized prompt text and information display settings.

[0574] Step 7:

[0575] The terminal uses information display settings sent from the server to present information to the user in real time. Specifically, it displays information on the screen using a Web UI based on Flask. The input is the information display settings, and the output is the information screen displayed to the user.

[0576] Step 8:

[0577] The user reviews the presented information and enters the necessary commands into the terminal. The terminal sends these commands to the server, prompting further information updates or the start of new tasks. The input is the user's commands, and the output is the updated task list.

[0578] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0579] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0580] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0581] [Fourth Embodiment]

[0582] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0583] As shown in Figure 7, the 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.

[0584] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0585] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0586] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0587] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0588] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0589] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0590] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0591] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0592] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0593] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0594] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0595] The system of this invention is designed to support users' information management and decision-making. It primarily involves a server and a terminal working together to provide users with the most relevant information. The server retrieves information from multiple data sources authorized by the user and analyzes this information using natural language processing technology. This allows it to extract important topics and keywords and create summaries.

[0596] The server analyzes user behavior patterns and schedules, and uses this data to make connections. This enables predictions based on the user's past behavior and provides optimal information. In particular, the server analyzes the user's past meeting and event participation history, as well as their daily activity time, to suggest the next necessary tasks.

[0597] On the other hand, the terminal is equipped with voice recognition capabilities and accepts voice commands from the user. The voice command analysis converts the voice into text, and then sends a request to the server according to the user's instructions, executing the necessary data and operations. This provides an environment in which the user can obtain information hands-free.

[0598] As a concrete example, when a user uses their smartphone and says, "Tell me my important appointments for today," the device recognizes the voice and converts it into text. This text information is sent to a server, which, based on previously collected data, provides a summary of the user's schedule and meeting details for the day. The device displays this summary on its screen and also informs the user verbally.

[0599] This system allows users to centrally manage necessary information from multiple sources, enabling them to efficiently carry out their daily tasks. Through the coordinated operation of the server and terminals, users can ensure they don't miss important information even in busy situations and clearly understand their priority tasks.

[0600] The following describes the processing flow.

[0601] Step 1:

[0602] The server connects to multiple data sources specified by the user and retrieves the latest email and message data via APIs. This prepares the server to collect information relevant to the user.

[0603] Step 2:

[0604] The server removes unnecessary information from the acquired data and formats the text data. In particular, it removes HTML tags and unnecessary header information to make it suitable for natural language processing.

[0605] Step 3:

[0606] The server uses natural language processing (NLP) techniques to analyze the formatted text data. It extracts important topics and keywords and generates a summary. This improves the readability and relevance of the information.

[0607] Step 4:

[0608] The server considers the user's activity history and schedule information, and associates extracted topics with the user's current situation and future plans. Based on this, it identifies necessary notifications and tasks.

[0609] Step 5:

[0610] The terminal receives voice commands from the user and converts them into text using its built-in speech recognition function. This prepares the user's instructions and questions for transmission to the server.

[0611] Step 6:

[0612] Upon receiving user instructions in text format, the server analyzes the content, extracts appropriate information from the database, and sends it back to the terminal. This enables the provision of information tailored to the user's requests.

[0613] Step 7:

[0614] The terminal displays summary information and support tasks received from the server on its screen and reports them to the user using text-to-speech functionality as needed. This allows the user to access important information in real time.

[0615] (Example 1)

[0616] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0617] In modern society, it is common to receive fragmented information from numerous sources, making it difficult for users to effectively manage this information. Furthermore, amidst the increasing volume of information, users are required to quickly acquire necessary information and make appropriate decisions. However, current technology does not adequately provide systems that centrally manage information from multiple sources and deliver optimal information based on user behavior patterns and plans. A system to address this challenge is needed.

[0618] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0619] In this invention, the server includes means for acquiring information from multiple information sources authorized by the user using an information processing device and aggregating the information; means for analyzing the acquired information using natural language processing technology and extracting important information and features; and means for analyzing the user's behavior patterns and schedules and presenting information in association with that data. As a result, the user can centrally manage information obtained from multiple information sources and make quick and accurate decisions in their daily life.

[0620] An "information processing device" is a device consisting of hardware and software for collecting, organizing, managing, and analyzing information.

[0621] "Natural language processing technology" is a field of artificial intelligence technology used to analyze human language, understand its meaning, and extract information.

[0622] "Behavioral patterns" refer to certain regular movements or tendencies identified based on a user's past activities and preferences.

[0623] "Speech recognition technology" is a technology that converts speech into digital signals and then analyzes them to understand them as language.

[0624] A "predictive model" is a statistical and machine learning technique used to predict future events or outcomes by analyzing past data.

[0625] A "generative AI model" is a learning model that uses artificial intelligence to assist in the generation of new data and information.

[0626] "Information sources" refer to databases and internet resources that function as sources of information provided to users.

[0627] This invention relates to an information processing system that efficiently collects, analyzes, and provides user information in an appropriate format. The following details each component and its operation.

[0628] The server uses an information processing device to retrieve information from multiple sources authorized by the user. Specifically, it aggregates news articles, emails, calendar entries, and other data from databases and web services accessible via the Internet Protocol.

[0629] The server uses natural language processing libraries such as Python's NLTK (Natural Language Toolkit) to analyze the collected information. This analysis extracts important information and features and generates a summary in a format that is easy for users to understand intuitively. This summary allows users to quickly access the information they need.

[0630] Furthermore, the server analyzes user behavior patterns. For example, it identifies typical user behavior patterns based on past email sending history and calendar event participation history. This allows it to build a predictive model that can optimally provide information relevant to the user.

[0631] Meanwhile, the terminal uses speech recognition technology to receive voice commands from the user and convert them into text. Specifically, it uses a voice API to convert voice data into text and sends it to the server. This procedure allows the user to operate the system hands-free.

[0632] The terminal is equipped with an interface for notifying the user of analysis results sent from the server. By displaying the information visually on the screen and also notifying the user via audio, it provides an environment where users can easily receive information in a variety of situations.

[0633] As a concrete example, consider a scenario where a user gives a voice command to their smartphone saying, "Tell me the latest information about the participants of the next meeting." The device recognizes this voice command, converts it to text, and sends it to the server. The server retrieves the details of the meeting based on the user's calendar information, and then collects, summarizes, and provides the latest news and related information about the participants.

[0634] An example of a prompt message is, "Tell me tomorrow's weather forecast." The system then retrieves the latest weather data and presents it to the user. In this way, users can utilize an advanced information environment in their daily activities.

[0635] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0636] Step 1:

[0637] The server retrieves data from sources authorized by the user. It uses the URL of the news API and email server credentials specified by the user as input. The server accesses these sources to retrieve the latest news articles, emails, and calendar entries. The raw data is stored on the server as output. Specifically, the server periodically executes data retrieval scripts at programmed intervals.

[0638] Step 2:

[0639] The server performs natural language processing on the acquired data. The raw data obtained in step 1 is used as input. The server analyzes the data using the Python NLTK library and extracts important topics and keywords. The output is a summarized data file after the analysis is complete. Specifically, the server applies natural language processing algorithms to extract sentences and rank keywords from the data.

[0640] Step 3:

[0641] The server analyzes user behavior patterns. It uses the user's past email history and calendar events as input. Based on this data, the server identifies typical user behavior patterns and predicts future behavior. As output, pattern analysis data is accumulated, and the predictive model is updated. Specifically, the server uses machine learning algorithms to cluster the data and extract behavior patterns.

[0642] Step 4:

[0643] The terminal receives voice commands from the user. It uses the user's voice commands as input. The terminal uses a speech recognition API to convert the voice to text and sends that text information to the server. The output is the textualized user instructions. Specifically, the terminal takes in voice input in real time and activates the speech recognition engine.

[0644] Step 5:

[0645] The server analyzes text information sent from the terminal and searches for appropriate information. It uses text generated by voice commands as input. Based on this text, the server searches relevant databases and selects information to provide to the user. The output is information prepared for notification to the user. Specifically, the server executes SQL queries to retrieve the relevant data.

[0646] Step 6:

[0647] The terminal notifies the user of information sent from the server. It uses the information received from the server as input. The terminal displays the information on the screen and also informs the user audibly. Output includes both visual and audible notifications. Specifically, the terminal displays text on its display and uses a speech synthesis engine to provide voice notifications.

[0648] (Application Example 1)

[0649] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] In today's information-saturated society, it is difficult for users to obtain the information they need quickly and efficiently. Furthermore, while it is crucial to provide users with timely and optimal information and commuting routes based on their individual behavioral patterns and schedules, the means to achieve this are limited. This invention aims to solve these problems and provide technology that makes life in a smart city environment more convenient.

[0651] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0652] In this invention, the server includes means for acquiring information from multiple data sources to collect user information, means for analyzing the acquired information using natural language processing technology and extracting important topics and keywords, and means for analyzing the user's behavior patterns and schedules and providing relevant information. As a result, users can receive optimal routes and relevant news in real time based on their own actions.

[0653] An "information processing device" is a device that has the function of collecting, analyzing, and providing user information.

[0654] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0655] A "topic" refers to a theme or group of themes that are important to the user.

[0656] A "keyword" is a specific word or phrase used to summarize and express a topic.

[0657] "Behavioral patterns" refer to characteristics that indicate a user's past behavioral history and tendencies.

[0658] "Plans" refer to the schedule of actions and events that the user has planned for the future.

[0659] A "communication terminal" is a device that serves as an interface with the user and is used for inputting and outputting information.

[0660] "Information" is a collection of knowledge and data that users need.

[0661] A "route" is the optimal path for a user to reach their destination.

[0662] "News" refers to new information and events that are relevant to the user's life and decisions.

[0663] This invention provides a system that enables the provision of optimal information to users of smart cities. This system consists of an information processing device and a communication terminal, and by analyzing information collected from multiple data sources, it provides users with relevant information and optimal routes.

[0664] The information processing device analyzes acquired information using natural language processing technology and extracts topics and keywords. This makes it possible to efficiently organize information related to the user's behavior patterns and schedules. Specifically, it selects important news and event information based on the user's past behavior history and schedule information.

[0665] The communication terminal uses speech recognition technology to process voice commands from the user as text input and transmits the results to the information processing device. This allows the user to obtain the necessary information and select the optimal route hands-free. For example, if a user voice-inputs "Tell me today's commute route" in the morning, the information processing device analyzes traffic information and presents the fastest or most efficient route.

[0666] For implementation, the specific hardware that can be used includes smartphones, tablets, or wearable devices. For software, Google Speech-to-Text API can be used for speech recognition, and NLTK or spaCy can be used for text information analysis.

[0667] One example of using a generation AI model for prompt messages is to input the following into the system: "Based on the provided user history, generate a daily summary of 'commute routes' and 'important news'," which will enable the provision of optimal information.

[0668] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0669] Step 1:

[0670] The user inputs a voice command into a communication terminal. The terminal converts this voice command into text data using speech recognition technology. Here, the input is the user's voice command, and the output is the converted text data. Specifically, the user says, "Tell me today's commute route," and the terminal converts this voice into the text, "Tell me today's commute route."

[0671] Step 2:

[0672] The terminal sends text data to the server. The server analyzes the received text data and determines the type of information the user is requesting. Here, the input is the converted text data, and the output is the identification result of the user request. Specifically, the server starts the process of acquiring traffic information based on the keyword "commute route".

[0673] Step 3:

[0674] The server retrieves the latest traffic information from an external data source (e.g., a traffic information API). In this step, the input is a request based on the user's request, and the output is the retrieved real-time traffic information. For example, the server collects information on current road conditions and public transport delays.

[0675] Step 4:

[0676] The server uses natural language processing technology to analyze acquired traffic information and generate the optimal commute route. The input is real-time traffic information, and the output is optimal route information presented to the user. Specifically, the server uses a decision algorithm to select a route that avoids traffic congestion.

[0677] Step 5:

[0678] The server sends the generated optimal route information to the terminal. The terminal presents this information to the user visually or audibly. The input here is the optimal route information, and the output is the information displayed on the user's terminal. Specifically, the terminal displays a map on the screen and also announces aloud, "The current optimal commute route is via XX."

[0679] Step 6:

[0680] The user makes decisions based on the information presented. For the user, the input is route information from the device, and the output is the selected mode of transportation and route. Specifically, the user starts commuting using the newly presented route.

[0681] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0682] The present invention provides a personal assistant incorporating emotion recognition technology to efficiently manage user information and support decision-making. First, a server acquires information from multiple data sources and analyzes that information using natural language processing technology. This extracts important topics and keywords and generates a summary of the information.

[0683] Next, the server analyzes the user's behavior patterns and schedule, and uses an emotion engine to analyze the user's emotional state from voice input and other data. Based on this emotion analysis, it becomes possible to customize how the user wants to receive information or how they want to proceed with tasks.

[0684] The emotion engine recognizes emotions such as joy, anger, sadness, and surprise by judging and numerically representing the characteristics of voice tone and word choice. The server then takes these emotional states into account and adjusts the way information is presented and the content of notifications to provide more appropriate and user-centric support.

[0685] For example, if a user asks their device in a depressed voice, "Tell me what's on my schedule today," the device, using voice recognition and an emotion engine, will determine that the user is feeling stressed or sad. The server can then take the user's emotional state into consideration and return a tailored response in a softer tone, such as, "Today isn't particularly busy, so you should be able to act without rushing." This allows the user to receive information more comfortably and reduce daily stress.

[0686] The introduction of this system will enable users to receive emotionally-driven information management and decision-making support, leading to a more fulfilling life. The collaborative operation of the server and terminals will allow users to receive support tailored to their individual needs, enabling the AI ​​personal assistant to truly fulfill the role of a secretary.

[0687] The following describes the processing flow.

[0688] Step 1:

[0689] The server retrieves information from multiple data sources configured by the user using an API. During this process, data is securely collected through an authentication protocol, and the retrieved information is stored in a database.

[0690] Step 2:

[0691] The server analyzes the stored data using natural language processing techniques. It extracts important topics and keywords from the text data and generates a summary. This summary is organized in a user-friendly format.

[0692] Step 3:

[0693] The server analyzes the user's past behavior patterns and schedule data. Based on this information, it predicts necessary tasks and stores them in a database as a prioritized list.

[0694] Step 4:

[0695] The terminal receives voice commands from the user. It uses speech recognition to convert the speech into text and prepares to send this text data to the server.

[0696] Step 5:

[0697] The server analyzes the user's emotions from transcribed voice commands using an emotion engine. It analyzes features such as voice intonation and speed to identify the user's emotional state. Based on this information, it adjusts the response and how tasks are presented.

[0698] Step 6:

[0699] Based on the analysis results, the server generates information and task notifications tailored to the user's current emotions. For example, if the user is feeling stressed, it presents information in simplified language and adds a positive message.

[0700] Step 7:

[0701] The terminal presents the user with pre-configured information and notifications received from the server. By displaying visual information on the screen and using speech synthesis technology to play audio information in an appropriate tone, it provides the user with the necessary information in the most optimal way.

[0702] (Example 2)

[0703] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] In modern society, the amount of information users access is increasing, and consequently, there is a need to efficiently manage this information and support decision-making that takes into account the user's emotional state. However, conventional systems have found it difficult to simultaneously manage information and provide personalized support based on the user's emotional state. Therefore, the present invention aims to construct a system that provides necessary information in a timely and appropriate manner while being attentive to the user's emotions.

[0705] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0706] In this invention, the server includes a storage device that acquires user-related data from multiple information sources, an information processing device that analyzes the acquired data using natural language processing techniques and extracts important topics and components, and an information processing device that analyzes the user's behavior patterns and schedules and provides relevant information. This makes it possible to manage and provide appropriate information while taking into account the user's emotional state.

[0707] A "storage device" refers to a storage medium that retains data for a long period of time and allows information processing devices to access it as needed.

[0708] An "information processing device" refers to an electronic device that analyzes input data and generates or extracts information according to its intended use.

[0709] "Natural language processing techniques" refer to a collection of technologies and methods that enable computers to understand and analyze human language.

[0710] An "emotion analysis device" refers to a device designed to analyze voice, text, and other data to determine the emotional state of a user.

[0711] "Generative AI technology" refers to artificial intelligence technology used to generate new data and responses based on large amounts of data.

[0712] A "computational device" refers to a computer system that processes data quickly and outputs the processing results.

[0713] The embodiments for carrying out the present invention are described below.

[0714] This system aims to efficiently manage user information and provide appropriate information based on emotions. The following details how the server, terminal, and user are involved.

[0715] First, the server operates in a cloud environment and retrieves user-related data from numerous sources within the storage system. This process utilizes database technology to incorporate information from news feeds, social media, calendars, and more. Next, the server analyzes the data using natural language processing technologies, such as Python's NLTK or spaCy. This extracts important topics and keywords and summarizes useful information.

[0716] Furthermore, the server acts as an emotion analyzer, analyzing voice input and text data to determine the user's emotions. In this process, it utilizes voice processing libraries such as OpenAI's Whisper and Google Cloud Speech-to-Text to quantify voice tone and word choice, identifying emotions such as joy, anger, and sadness.

[0717] When a user inputs a voice command into the terminal, the terminal analyzes it and sends it to the server. The server, based on generative AI technology, generates a response that matches the user's emotional state. This generated response is then presented to the user via the terminal. During this process, the server predicts the next task that is likely to be needed based on past behavioral data and notifies the user.

[0718] For example, if a user requests "What's on my schedule today?" in a depressed voice, the server, using an emotion analyzer, determines that the user is feeling stressed. Based on this, a customized response such as "Today isn't particularly busy, so you can relax" is generated and communicated to the user from the device.

[0719] An example of a prompt might be a question like, "If the user is showing positive emotions, how would you summarize the information and respond?"

[0720] In this configuration, the system can provide personalized information that takes into account the user's emotional state, enabling effective decision-making support.

[0721] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0722] Step 1:

[0723] The server starts with a cloud-based storage system and collects user-related data from multiple sources. This input includes news feeds, social media, and calendar information. To retrieve this data, the server performs API calls and database queries. The output is a diverse collection of raw data.

[0724] Step 2:

[0725] The server performs natural language processing on the acquired raw data. Specifically, it analyzes the data using Python's NLTK and spaCy to extract important topics and keywords. The keywords extracted from the input data are output, and this summarizes the information necessary for the user.

[0726] Step 3:

[0727] The server analyzes the user's behavior patterns and schedule. Past behavioral history and schedule information are used as input data. Machine learning algorithms (e.g., using scikit-learn) are utilized to model the user's behavioral trends. The output is a prediction of the user's future behavior.

[0728] Step 4:

[0729] The server processes the voice data acquired from the user using an emotion analysis device. The input includes the user's voice tone and text data. The server uses an emotion analysis library (e.g., OpenAI's Whisper) to analyze the voice and quantify the emotion. This outputs the user's emotional state, facilitating the generation of responses based on that state.

[0730] Step 5:

[0731] The server adjusts how information is presented based on the user's emotional state. Here, generative AI technology is used to generate appropriate responses. The input includes the results of emotion analysis and keyword information extracted through natural language processing. The output is a customized response tailored to the user's emotions.

[0732] Step 6:

[0733] The terminal presents the response provided by the server to the user. Specifically, the terminal uses audio output and a screen display to inform the user of the generated response. This makes it possible to effectively provide information and support decision-making to the user.

[0734] (Application Example 2)

[0735] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0736] In modern society, individual lifestyles are diversifying, and there is a need to respond quickly to daily stress and emotional changes. This is especially important for the elderly and those with physical limitations, as their daily activities must be adapted to their individual emotional states. However, current information presentation systems are insufficient in providing personalized information and customizing tasks that take into account the user's emotional state, making improvement a pressing need.

[0737] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0738] In this invention, the server includes an emotion analysis means for analyzing the user's emotional state, a means for analyzing information acquired using natural language processing technology and extracting important topics and keywords, and a means for analyzing the user's activity trends and schedule and providing relevant information. This makes it possible to appropriately adjust the method of presenting information and the method of progressing tasks according to the user's emotional state.

[0739] An "information processing system" is a computer system used to collect and analyze user information. Its role is to extract important information from the obtained data and provide it to the user.

[0740] An "information display device" is a terminal that receives commands from a user, performs related operations, and presents information to the user in real time.

[0741] "Emotional analysis methods" are technologies that analyze a user's emotional state from their voice and behavioral data, and are used to determine what kind of emotions the user is experiencing.

[0742] "Adjustment methods" refer to methods for optimizing the presentation of information and the progress of tasks based on the user's emotional state, thereby providing beneficial support to the user.

[0743] To implement this invention, the server first collects information from multiple data sources. The server then analyzes the collected information using natural language processing technology, specifically the Python NLTK library, and extracts important topics and keywords. This organizes the information relevant to the user.

[0744] Next, the server uses Azure Cognitive Services to analyze the user's emotions from their voice data. This emotion analysis provides a numerical evaluation of the user's emotional state. Furthermore, the server analyzes the user's activity patterns based on past data and predicts the information and tasks they will need next.

[0745] The device, specifically a smartphone or tablet, displays information sent from the server to the user in real time. A Web UI using Flask allows for intuitive operation. Furthermore, if the user is restless and issues a voice command, the system provides optimized information and advice tailored to their emotional state.

[0746] For example, when a user wants to relax, the device can suggest playing calming music. Furthermore, the following prompt statements are used for the generative AI model.

[0747] Prompt: Users are currently feeling anxious. Please provide calming news and gentle advice.

[0748] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0749] Step 1:

[0750] The server collects user-related information from multiple data sources. Specifically, it retrieves information from sources such as news feeds and schedule databases. It uses access information to the data sources as input and generates an organized data set as output.

[0751] Step 2:

[0752] The server analyzes the collected data set using natural language processing techniques. It extracts important topics and keywords using the Python NLTK library. The input is the data set, and the output is a list of important keywords and topics.

[0753] Step 3:

[0754] The server analyzes user activity trends and past schedule data. Specifically, it retrieves past behavioral patterns from an SQL database and predicts the next tasks required. The input is activity history and schedule data, and the output is a predicted task list.

[0755] Step 4:

[0756] When a user inputs a voice command into the device, that voice data is sent to the server. The server uses Google Speech Recognition to convert this voice data into text data. The input is voice data, and the output is text data.

[0757] Step 5:

[0758] The server uses Azure Cognitive Services to analyze the user's emotional state based on text data. Specifically, it analyzes the vocabulary and tone of voice in the text to quantify the emotion. The input is text data, and the output is quantified emotion data.

[0759] Step 6:

[0760] The server optimizes how information is presented based on extracted key keywords and sentiment data. In some cases, a generative AI model is used at this stage to generate prompt text. The input is a keyword list and sentiment data, and the output is optimized prompt text and information display settings.

[0761] Step 7:

[0762] The terminal uses information display settings sent from the server to present information to the user in real time. Specifically, it displays information on the screen using a Web UI based on Flask. The input is the information display settings, and the output is the information screen displayed to the user.

[0763] Step 8:

[0764] The user reviews the presented information and enters the necessary commands into the terminal. The terminal sends these commands to the server, prompting further information updates or the start of new tasks. The input is the user's commands, and the output is the updated task list.

[0765] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0766] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0767] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0768] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0769] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0770] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0771] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0772] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0773] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0774] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0775] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0776] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0777] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0778] 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.

[0779] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0780] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0781] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0782] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0783] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0784] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0785] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0786] The following is further disclosed regarding the embodiments described above.

[0787] (Claim 1)

[0788] A server that retrieves information from multiple data sources in order to collect user information,

[0789] A server that analyzes information obtained using natural language processing technology and extracts important topics and keywords,

[0790] A server that analyzes user behavior patterns and schedules and provides relevant information,

[0791] A terminal that receives voice commands and input data from the user and performs related operations,

[0792] A device that sends real-time notifications to users and presents information,

[0793] A system that includes this.

[0794] (Claim 2)

[0795] The system according to claim 1, which analyzes the user's voice instructions using speech recognition technology and processes them as input.

[0796] (Claim 3)

[0797] The system according to claim 1, which predicts and provides the next necessary task based on the user's past behavioral data.

[0798] "Example 1"

[0799] (Claim 1)

[0800] A means of acquiring information from multiple information sources authorized by the user using an information processing device, and aggregating that information,

[0801] A means of analyzing information obtained using natural language processing technology and extracting important information and features,

[0802] A means of analyzing user behavior patterns and schedules, and presenting related information based on that data,

[0803] A means of recognizing voice commands from a user using speech recognition technology, converting them to text, and processing them,

[0804] A means of notifying and presenting information to the user in real time, equipped with voice and display functions,

[0805] A method for building a predictive model based on the user's past behavioral data and suggesting the next task that is likely to be needed,

[0806] A system that includes this.

[0807] (Claim 2)

[0808] The system according to claim 1, which analyzes the user's voice instructions using speech recognition technology and determines an action according to the content of the user's instructions.

[0809] (Claim 3)

[0810] The system according to claim 1, which uses a generative AI model to analyze the user's past behavioral data and predict the optimal next action for the user.

[0811] "Application Example 1"

[0812] (Claim 1)

[0813] An information processing device that acquires information from multiple data sources in order to collect user information,

[0814] An information processing device that analyzes information acquired using natural language processing technology and extracts important topics and keywords,

[0815] An information processing device that analyzes user behavior patterns and schedules and provides relevant information,

[0816] A communication terminal that receives voice commands and input information from the user and performs related operations,

[0817] A communication terminal that sends real-time notifications to users and presents information,

[0818] An information processing device that integrates information from different domains and provides users with the optimal route and relevant news,

[0819] A system that includes this.

[0820] (Claim 2)

[0821] The system according to claim 1, which uses speech recognition technology to analyze a user's voice command, processes it as input, and presents the optimal route and related news.

[0822] (Claim 3)

[0823] The system according to claim 1, which predicts and provides the next necessary task based on the user's past behavior information, thereby supporting life within the smart domain.

[0824] "Example 2 of combining an emotion engine"

[0825] (Claim 1)

[0826] A storage device that acquires user-related data from multiple sources,

[0827] An information processing device that analyzes data acquired using natural language processing techniques and extracts important topics and components,

[0828] An information processing device that analyzes the user's behavior patterns and schedule and provides related information,

[0829] An information processing device that analyzes the user's voice input, identifies the emotional state using an emotion analysis device, and adjusts the information presentation method;

[0830] An information processing device that generates responses according to the user's emotional state based on generative AI technology,

[0831] A computing device that sends real-time optimized notifications to users,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, which analyzes the user's voice instructions using a voice recognition system and processes them as input.

[0835] (Claim 3)

[0836] The system according to claim 1, which predicts and provides the next necessary task based on the user's past behavioral data.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] An information processing device that acquires information from multiple data sources in order to collect user information,

[0840] An information processing device that analyzes information acquired using natural language processing technology and extracts important themes and keywords,

[0841] An information processing device that analyzes user activity trends and schedules and provides relevant information,

[0842] An information display device that receives voice commands and input data from the user and performs related operations,

[0843] An information display device that sends real-time notifications to the user and presents information,

[0844] A means of analyzing the emotional state of a user,

[0845] An adjustment mechanism that adjusts the way information is presented and the way tasks are carried out based on emotional state,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, which analyzes the user's voice instructions using speech recognition technology and processes them as input.

[0849] (Claim 3)

[0850] The system according to claim 1, which predicts and provides the next necessary task based on the user's past activity data. [Explanation of Symbols]

[0851] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In order to collect user information, means of obtaining information from multiple data sources, A method for analyzing information obtained using natural language processing technology and extracting important topics and keywords, A means of analyzing user behavior patterns and schedules and providing relevant information, A means of receiving voice commands and input information from the user and performing related operations, A means of sending real-time notifications to users and presenting information, A means of integrating information from different domains and providing users with the optimal route and relevant news, A system that includes this.

2. The system according to claim 1, which uses speech recognition technology to analyze a user's voice command, processes it as input, and presents the optimal route and related news.

3. The system according to claim 1, which predicts and provides the next necessary task based on the user's past behavior information, thereby supporting life within the smart domain.

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