system

Abstract

We provide the system. [Solution] A conversion means that receives voice input from a user and converts it into text data, Processing means for analyzing the aforementioned character data and generating a response by referring to past dialogue history, An output means that provides the generated response as an audio output, A means of collecting user lifestyle data and monitoring their health status and daily routines, Security measures that detect suspicious communications and user anomalies and issue warnings, A support system that generates suggestions based on environmental information and past health data to assist users in their daily activities, 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 persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the progress of an aging society, the number of elderly people living alone has increased, and it has become a serious problem that they suffer from loneliness and social isolation. In particular, there are problems such as insufficient communication in daily life and difficulties in health management. Furthermore, since the possibility of facing social risks such as fraud has increased, a technical solution for enabling the elderly to live with peace of mind is required.

Means for Solving the Problems

[0005] This invention provides an AI system that recognizes user voice in real time and enables dialogue using natural language processing technology. Voice recognition converts voice input into text data, which is then analyzed by natural language processing and used to generate appropriate responses based on past dialogue history. The generated responses are then provided to the user via voice synthesis. Furthermore, sensor data is collected to monitor the user's health status and lifestyle, generating and providing advice for health management and lifestyle improvement. Security measures detect suspicious phone calls and abnormal activity, promptly issuing warnings. This reduces feelings of loneliness and social risks for the elderly, creating a safe and secure living environment.

[0006] A "speech recognition means" is a mechanism that receives speech input from a user and converts it into text data.

[0007] A "natural language processing system" is a mechanism that analyzes speech input converted into text data and generates an appropriate response from past dialogue history.

[0008] A "speech synthesis means" is a mechanism that converts text into speech in order to present the generated response to the user as speech.

[0009] A "sensor device" is a mechanism that collects user lifestyle data to monitor the user's health status and daily rhythm.

[0010] "Security measures" are mechanisms for detecting suspicious behavior in user communications and activities and issuing warnings as needed.

[0011] An "advice generation means" is a mechanism that generates advice for health management and lifestyle improvement based on data collected by sensor means.

[0012] A "content suggestion mechanism" is a system that stores the user's dialogue history in a database and suggests individual content to the user based on that history. [Brief explanation of the drawing]

[0013] [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] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0014] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] 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 CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), and the like.

[0017] 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.

[0018] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disk (e.g., hard disk), or magnetic tape, etc.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The present invention aims to build an AI agent that enables natural interaction with users and supports the lives of the elderly. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, and content suggestion means.

[0035] First, when the user speaks to the AI ​​agent, the device receives the voice data. The device then converts this voice into text data through speech recognition and sends it to the server.

[0036] The server analyzes the received text data using natural language processing techniques. In this process, the server refers to past conversation history and generates appropriate responses that are relevant to the context. For example, if a user asks, "What should I do today?", the server considers past conversations and the user's tendencies to create a response such as, "The weather is nice today, how about going for a walk?"

[0037] The generated response is then sent from the server to the terminal and converted into audio data by a speech synthesis system. The terminal then plays the response back to the user as a smooth audio output.

[0038] Furthermore, the sensors in the device continuously collect the user's lifestyle data and transmit it to the server. The server analyzes this data to monitor the user's health and lifestyle. For example, it analyzes the user's step count and sleep patterns, and if a lack of exercise is detected, it generates specific advice such as, "It seems you haven't been exercising much this week. How about taking a short walk?"

[0039] Security measures also play a crucial role in protecting user safety. The server immediately alerts family members and relevant parties if it detects suspicious calls or unusual activity, allowing users to live their daily lives with peace of mind.

[0040] Finally, the content suggestion system proposes the most suitable music, movies, books, and other content to the user based on their past conversation history and preferences. This allows users to enjoy a richer experience.

[0041] In this way, by following the embodiments of the invention, it is possible to provide a system that improves user communication, supports health management, and enhances security.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user speaks to the AI ​​agent. The device receives the user's voice via its microphone.

[0045] Step 2:

[0046] The terminal converts the received audio data into text data using speech recognition technology. This text data is then sent to the server.

[0047] Step 3:

[0048] The server analyzes the received text data using natural language processing techniques. Here, the server refers to a database of past dialogue history and generates an appropriate response based on the context.

[0049] Step 4:

[0050] The generated response is sent from the server to the terminal, which then uses speech synthesis technology to convert the text into speech data.

[0051] Step 5:

[0052] The device plays audio data to the user and provides the generated response in voice.

[0053] Step 6:

[0054] The sensor device collects user behavior and environmental data and transmits it to the server.

[0055] Step 7:

[0056] The server analyzes the user's health status and lifestyle based on data from sensor devices. It then generates health management and lifestyle improvement advice and sends it to the terminal.

[0057] Step 8:

[0058] The device notifies the user of the generated advice and conveys the advice via voice or on-screen display.

[0059] Step 9:

[0060] The server uses security measures to monitor for suspicious calls and unusual activity, and if detected, it generates an alert and notifies the device and family members.

[0061] Step 10:

[0062] Based on past conversation history, the server uses a content suggestion mechanism to select content suitable for the user and sends the suggestion to the terminal.

[0063] Step 11:

[0064] The device displays or plays suggested content to the user and provides options.

[0065] (Example 1)

[0066] 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."

[0067] An effective support system is needed that simultaneously facilitates communication, improves health management, and enhances security in the daily lives of users, including the elderly. Existing technologies often provide these elements individually, lacking integrated services, which compromises user convenience.

[0068] 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.

[0069] In this invention, the server includes a recognition device, a language analysis device, a synthesis device, a measurement device, a protection device, and a suggestion device. This enables natural interaction with the user, monitoring of health status, ensuring safety, and suggestion of personalized content.

[0070] A "recognition device" is a device that has the function of converting voice data into text data, and converts voice input from a user into digital text information.

[0071] A "language analysis device" is a device that analyzes text data and generates natural-sounding responses while referring to past dialogue history.

[0072] A "synthesizer" is a device that converts the generated response into audio data and provides it to the user as audio output.

[0073] A "measuring device" is a device that continuously collects a user's lifestyle data and uses that data to monitor their health status and lifestyle rhythms.

[0074] A "protection device" is a device that protects user safety by detecting suspicious communications or user abnormalities and issuing warnings.

[0075] A "suggestion device" is a device that selects and suggests content that will interest the user based on their past history and preferences.

[0076] This invention is an integrated AI agent system designed to support the lives of users, such as the elderly. This system is optimized for natural interaction with users and offers numerous conveniences. Specifically, it is implemented using a combination of the following hardware and software.

[0077] First, the terminal receives voice input and converts the voice data into text data using a speech recognition device. A recognition system employing natural language processing technology is used for speech recognition. For example, a common speech recognition API can be used as the recognition engine.

[0078] Next, the text data received by the server is analyzed by a language analysis device. This process utilizes a generative AI model to perform contextual analysis based on past dialogue history and generate a response. The latest generative AI model is used as the natural language processing model here.

[0079] The generated response is sent to a synthesis device on the terminal and converted into speech. A speech synthesis engine is used for speech synthesis, enabling natural-sounding speech output in real time.

[0080] Furthermore, the device collects user lifestyle data through its built-in measuring device and transmits it to a server. This data includes steps taken and heart rate, and is used to analyze the user's health status and lifestyle rhythm.

[0081] The server monitors for suspicious activity and anomalies via a protection device and issues a warning if detected. It also uses a suggestion device to recommend content based on the user's history and preferences. For example, it might suggest, "You've recently become interested in classical music. Why not listen to Beethoven today?"

[0082] A concrete example of a prompt message is: "The user is looking for a hobby they can do at home. Based on the information that it is raining today, please suggest something."

[0083] Thus, the system of the present invention is an embodiment that provides users with improved daily life and ensured safety, thereby aiming to improve the quality of life for the user.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user speaks to the AI ​​agent and inputs voice data. The device captures this voice with its microphone and passes it to a speech recognition device. The speech recognition device analyzes the input analog voice data and converts it into digital text data. During this process, speech processing is performed to accommodate the intonation and speed of speech. The converted text data is then generated as output.

[0087] Step 2:

[0088] The terminal sends the acquired text data to the server. The server inputs the text data into a language analysis device and retrieves past dialogue data from a database to understand the context. Based on this data, a generative AI model infers the user's intent and generates an appropriate response. Specifically, text generation is performed to implement question answering and recommendation functions, and a finished response sentence is output.

[0089] Step 3:

[0090] The server sends the response text to the terminal. The terminal inputs this text response into a speech synthesizer and converts it into speech data. The speech synthesizer operates functions to adjust the tone and pacing to produce a natural and easy-to-understand voice. The output is speech data intended for the user to hear.

[0091] Step 4:

[0092] The device plays the generated audio data through its speaker, providing the user with a continuation of the conversation. This allows the user to naturally receive responses and suggestions to their questions. This step is performed in real time, enhancing the user experience.

[0093] Step 5:

[0094] The device continuously collects the user's lifestyle patterns (steps, heart rate, etc.) through a measuring device. This data is periodically sent to the server as input. The server analyzes this data and monitors the user's health status. It assesses the health status and, if necessary, outputs advice for lifestyle improvements.

[0095] Step 6:

[0096] The server uses protective devices to monitor security. If suspicious communication is detected, it immediately generates a warning message and notifies registered contacts. This process includes detecting unauthorized access and reviewing login history.

[0097] Step 7:

[0098] The suggestion device selects and suggests individual content based on the user's past history and preferences. The server uses a generation AI model to generate suggestion content in the form of prompts and outputs content tailored to the user. The suggested content is then provided to the user as music, movies, or books.

[0099] (Application Example 1)

[0100] 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."

[0101] There is a need for systems that support elderly people in living independent and safe daily lives. However, conventional technologies lack the ability to provide appropriate advice and content tailored to the individual needs of the elderly, and also lack sufficient safety features to respond quickly in emergencies. As a result, it is difficult for the elderly to live a secure and fulfilling life.

[0102] 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.

[0103] In this invention, the server includes a conversion means for receiving voice input from a user and converting it into text data; a processing means for analyzing the text data and generating a response by referring to past dialogue history; and a support means for generating suggestions based on environmental information and past health data to support the user's daily activities. This enables daily life support and safety assurance suitable for the elderly, and further enables the provision of advice tailored to individual needs.

[0104] "Conversion means" refers to a device or process that has the function of receiving voice input and converting it into text data.

[0105] "Processing means" refers to a device or process that has the function of analyzing character data and generating an appropriate response by referring to past dialogue history.

[0106] "Output means" refers to a device or process that has the function of outputting the generated response as audio and providing it to the user.

[0107] "Collection means" refers to a device or process that has the function of continuously collecting user lifestyle data and monitoring their health status and lifestyle rhythms.

[0108] "Safety measures" refer to devices or processes that have the function of detecting suspicious communications or user abnormalities and issuing warnings.

[0109] "Support means" refers to a device or process that has the function of generating appropriate suggestions based on environmental information and past health data in order to support the user's daily activities.

[0110] The system for implementing the present invention constructs an AI agent for the purpose of supporting the daily lives of the elderly. Its main components include conversion means, processing means, output means, collection means, safety means, and support means.

[0111] First, the terminal receives voice input from the user and converts it into text data using a conversion mechanism. A speech recognition API is used as the conversion mechanism. The server receives this text data and analyzes it using a processing mechanism. In this process, a natural language processing library is used to refer to past dialogue history and generate an appropriate response.

[0112] The generated response is converted into audio data by an output device, and the terminal provides this to the user in audio format. This is achieved using a speech synthesis library.

[0113] Furthermore, the device continuously collects user lifestyle data using collection methods and transmits it to a server. This data collection utilizes the smartphone's built-in sensors, and data analysis is performed using Pandas and NumPy. The analysis results are used to understand the user's health status and lifestyle.

[0114] The safety measures monitor data in real time to detect abnormal communications and activity, and alert relevant parties when an anomaly is detected. This ensures user safety.

[0115] The support system provides users with optimal daily activity suggestions based on environmental information and past health data to facilitate their daily activities. For example, if a user asks, "What should I do today?", the support system, based on weather information and past activity data, might suggest, "The weather is nice today, so how about taking a walk in the park?"

[0116] An example of a prompt from a generative AI model would be the text, "To support the user's daily activities, we will create exercise suggestions based on weather forecasts and past health data."

[0117] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0118] Step 1:

[0119] The device receives voice input from the user via the microphone. The received voice data is passed to a speech recognition API and converted into text data. This process inputs the user's verbal questions as parseable text.

[0120] Step 2:

[0121] The server passes the text data obtained from the speech recognition API to the processing unit, where it is analyzed by a natural language processing engine. Here, the data is compared with past dialogue history to generate a contextually appropriate response. The output of this step is text data indicating an appropriate response to the user.

[0122] Step 3:

[0123] The text data generated by the server is converted into speech data using a speech synthesis engine and passed to the terminal. This allows the terminal to respond to the user in natural-sounding speech through its speech output device.

[0124] Step 4:

[0125] The device continuously collects user lifestyle data using built-in sensors. The acquired data is sent to a server and analyzed using Pandas and NumPy. This analysis provides information to understand the user's health status and lifestyle.

[0126] Step 5:

[0127] The server uses security measures to monitor the collected data in real time and detect any anomalies. If suspicious activity is detected, it automatically issues a warning to the relevant parties. This process is set up to ensure user peace of mind.

[0128] Step 6:

[0129] The server utilizes support tools to generate personalized suggestions to assist the user's daily activities. It takes environmental information and past health data into consideration to suggest suitable activities and schedules. This step utilizes a generative AI model, and the prompt message for it is "To assist the user's daily activities, we will create exercise suggestions based on the weather forecast and past health data."

[0130] Step 7:

[0131] The device either communicates the generated suggestions to the user via voice or displays them on its screen. If communicating via voice, the speech synthesis engine is used again. This output allows the user to understand the suggested activities and choose the appropriate action to take.

[0132] 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.

[0133] The present invention provides comprehensive support for the lives of the elderly by having an AI agent that includes emotion recognition in interaction with the user. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, content suggestion means, and emotion engine.

[0134] When a user speaks to the AI ​​agent, the device receives the voice input, converts it into text data using speech recognition, and sends it to the server. The server then uses natural language processing to analyze the text data and understand the user's utterance. The emotion engine also functions here, recognizing emotions from the user's tone of voice and word choice. For example, if the user says, "I'm a little tired today," the emotion engine detects fatigue or weariness.

[0135] The server adjusts the tone of the conversation based on this emotional information and generates an appropriate response for the user. For example, for a user who is feeling tired, it creates a gentle response such as, "Please get plenty of rest today." The generated response is sent to the terminal and provided to the user as speech through a speech synthesis system.

[0136] Furthermore, the sensor system continuously monitors the user's lifestyle data to understand their health status and daily rhythm. The server analyzes this data and generates health management advice based on the user's emotional and physical state. For example, if the sensor data indicates a lack of exercise and the emotion engine determines that the user is feeling down, it will generate advice such as, "Taking a short walk today might cheer you up."

[0137] Furthermore, the emotion engine interacts with content suggestion methods, proposing content best suited to the user's emotions. For example, if the user is feeling stressed, it will provide relaxing music or videos.

[0138] Thus, the present invention provides a system that aims to improve users' communication and quality of life through a variety of functions, including emotion recognition.

[0139] The following describes the processing flow.

[0140] Step 1:

[0141] The user asks the AI ​​agent a question using their voice. The device receives the voice through its microphone and records it as audio data.

[0142] Step 2:

[0143] The terminal inputs the received audio data into a speech recognition device and converts it into text data. This text data is then sent to the server.

[0144] Step 3:

[0145] The server uses natural language processing to analyze text data and understand the context of the speech. Simultaneously, an emotion engine operates to recognize the user's emotions based on their tone of voice and word choices.

[0146] Step 4:

[0147] The server combines the results of natural language processing with analysis from the emotion engine to generate an appropriate response. For example, if the user's emotions indicate sadness or fatigue, the server will create a response that includes empathy.

[0148] Step 5:

[0149] The generated response is sent from the server to the terminal and converted into speech data by a speech synthesis system.

[0150] Step 6:

[0151] The device plays audio data through its speaker and provides responses to the user. This enables a natural and user-friendly conversation.

[0152] Step 7:

[0153] The sensor device periodically collects user activity and environmental data and transmits this data to a server.

[0154] Step 8:

[0155] The server analyzes data from sensor devices to assess health status and daily lifestyle patterns. Based on this assessment, it generates health management advice as needed.

[0156] Step 9:

[0157] The server utilizes a content suggestion method that selects and proposes content that matches the user's emotional state, based on sentiment analysis obtained by the emotion engine.

[0158] Step 10:

[0159] The device helps improve the user's quality of life by presenting suggested content to the user and allowing them to select and play it.

[0160] (Example 2)

[0161] 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".

[0162] There is a growing societal demand for improved health management and safety in the lives of the elderly. In particular, maintaining a regular daily routine, detecting suspicious phone calls, and providing personalized responses tailored to their emotions are key challenges. Furthermore, understanding the user's emotional state and providing appropriate communication and content suggestions is also essential.

[0163] 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.

[0164] In this invention, the server includes speech recognition means for acquiring voice information and converting it into text information, natural language processing means for analyzing text information and identifying emotions, and sensor means for detecting living conditions and evaluating health status. This enables personalized responses and content suggestions based on the user's emotions and health status.

[0165] "Speech recognition means" refers to a technology that receives speech information input by a user and converts it into text information.

[0166] "Natural language processing means" refers to technologies that analyze converted text information to understand the user's intentions and emotions.

[0167] "Speech synthesis means" refers to a technology that converts responses generated on a server into speech data and provides it to the user as speech.

[0168] "Sensing means" refers to technology that collects information to monitor a user's living situation and health condition.

[0169] "Security management measures" refer to technologies for detecting suspicious communications and abnormal user behavior and generating warnings.

[0170] "Advice generation means" refers to a technology that creates and provides advice for maintaining the user's health and improving their lifestyle based on information acquired by sensor means.

[0171] "Content suggestion methods" refer to technologies that utilize past conversation records to suggest personalized information and entertainment to users.

[0172] The system of the present invention is designed to support the lives of the elderly and includes an AI agent that performs emotion recognition. When a user speaks to the AI ​​agent by voice, the terminal acquires voice data and converts it into text data using speech recognition means. This text data is sent to a server that uses natural language processing means. The server analyzes the text data using natural language processing techniques to understand the user's intentions and the content of their speech. This process also includes an emotion engine that identifies emotions from the tone and word choice of speech.

[0173] As a concrete example of emotion recognition, if a user says, "I'm a little tired today," the emotion engine detects the level of fatigue from the statement, and the server generates a gentle response based on that result. This response is sent back to the terminal and played back to the user as speech using a speech synthesis system. For example, a possible response might be, "Please get plenty of rest today."

[0174] This system includes sensors that monitor lifestyle data, continuously collecting data to understand the user's daily rhythm and health status. The server analyzes this data and employs a scheme to generate health management advice. For example, if the sensor data indicates a lack of exercise, it will generate advice such as, "Taking a short walk today might help you feel refreshed."

[0175] Content suggestions are also provided; the emotion engine analyzes the user's emotional state and suggests the most suitable music, videos, and other content based on the results. For example, if the user is feeling stressed, it will recommend music with a relaxing effect.

[0176] A concrete example of a prompt message might be: "Generate a system response for when the user says, 'I'm a little tired today.' Also, provide any relevant health advice."

[0177] Thus, the present invention aims to improve the quality of life for the elderly by integrating various technologies.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The device receives voice input from the user via a microphone. This voice data is converted into text data by a speech recognition system. Specifically, when the user says, "I'm a little tired today," the voice is converted into digital format and obtained as a string of characters. This text data is then sent to the server.

[0181] Step 2:

[0182] The server receives text data sent from the terminal. Using natural language processing, it analyzes the text data to understand the user's utterance. This analysis involves word recognition and contextual understanding to clarify what the user is trying to say. In addition, an emotion engine detects emotions based on the tone and word choice of the text. The input is text data, and the output is the analysis results and emotion information.

[0183] Step 3:

[0184] The server generates responses that reflect emotional information based on natural language processing. This response generation process creates responses in a tone appropriate to the user's emotional state. For example, if the user is expressing fatigue, the server will construct a reply such as, "Please take it easy and rest today." The input is the parsed data and emotional information, and the output is the response text.

[0185] Step 4:

[0186] The generated response text is sent to the terminal, which uses speech synthesis to convert this text into audio data. The converted audio is delivered to the user through the speaker. Specifically, the response text "Please rest well today" is played as audio. The input is the response text, and the output is the played audio.

[0187] Step 5:

[0188] Furthermore, the sensor continuously collects data on the user's lifestyle. The server analyzes this data to assess their health status and daily rhythm. If the sensor data indicates a lack of exercise, the server generates advice such as, "Taking a short walk today might help you feel refreshed." The input is the sensor data, and the output is the advice text.

[0189] Step 6:

[0190] The content suggestion system uses the user's emotional information to suggest relaxing music and videos. If the user's emotions indicate stress, content that promotes relaxation will be selected. The input is emotional information, and the output is a list of suggested content.

[0191] (Application Example 2)

[0192] 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".

[0193] Modern elderly people often experience loneliness in their daily lives, which can hinder their ability to manage their health and maintain a regular lifestyle. Furthermore, they often lack sufficient psychological support due to the difficulty in fully understanding and caring for their emotions. This, in turn, leads to a decline in their quality of life.

[0194] 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.

[0195] In this invention, the server includes speech recognition means for receiving voice input and converting it into text data, natural language processing means for generating and providing responses through natural language processing, and emotion engine means for recognizing the user's emotions and adjusting the responses. This makes it possible to provide comprehensive emotional support to the elderly and improve their quality of life.

[0196] "Voice recognition means" refers to technology that receives voice input from a user and converts it into text data.

[0197] "Natural language processing means" refers to technologies that analyze text data and generate appropriate responses based on past dialogue history.

[0198] "Speech synthesis means" refers to a technology that provides the generated response as speech output.

[0199] "Sensing means" refers to devices and technologies used to collect information about a user's lifestyle and monitor their health status and daily rhythm.

[0200] "Security measures" are technologies used to detect suspicious communications or user anomalies and issue warnings.

[0201] An "emotion engine" is a technology that analyzes the tone of voice and linguistic expressions to recognize the user's emotions and adjusts the tone of the dialogue accordingly.

[0202] A "content suggestion method" is a technology that suggests the most suitable content based on the user's emotions.

[0203] An "advice generation means" is a technology that generates and provides users with advice for health management and lifestyle improvement based on data collected by sensor means.

[0204] This system consists of an AI agent designed to comprehensively support the user's life. The system utilizes the speech recognition technology built into the device to receive voice input, and leverages the Google® Speech-to-Text API. The voice is converted into text data, which is then sent to the server. The server employs a natural language processing model using the TENSORFLOW® library to analyze the user's intent and emotions. During this analysis, the server also performs sentiment analysis using VADER, and the sentiment engine uses the results to adjust the tone of the response. The response sent to the user is generated using speech synthesis technology via the Google Text-to-Speech API and provided as voice from the device.

[0205] Furthermore, this system collects sensor data from wearable devices to monitor health status and lifestyle rhythms. This data is stored on a server and analyzed periodically. If necessary, the server generates advice for health management and lifestyle improvement based on this data. This advice generation is performed by a generative AI model, sent to the application, and then provided in voice.

[0206] Furthermore, as a content suggestion method, the system uses the Spotify API and YouTube® Data API to suggest appropriate content based on the user's emotions. This feature allows users to easily access music and videos that match their emotional state.

[0207] For example, if a user types "I'm not feeling well today" into their device, the system performs text conversion using the Google Speech-to-Text API, analyzes intent and sentiment using TensorFlow, and then performs sentiment analysis with VADER. As a result, encouraging words such as "Please take it easy and rest today" are provided as voice via the Google Text-to-Speech API. Furthermore, relaxing music is suggested via the Spotify API.

[0208] Examples of prompts for a generative AI model:

[0209] "Read the user's emotions from their statements and provide an appropriate response. For example, in response to 'I'm a little tired,' you might want to say, 'Maybe you should take it easy and rest today.'"

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The device receives voice input from the user. It sends the voice signal to the Google Speech-to-Text API, where it is converted into text data. This converted text data is then sent to the server.

[0213] Step 2:

[0214] The server uses TensorFlow to analyze the received text data and performs natural language processing. Specifically, it analyzes the intent behind the user's utterances and extracts elements that contain emotions. This process yields the user's current emotions as text.

[0215] Step 3:

[0216] The server uses VADER to perform emotion analysis based on the analysis results. The analysis outputs the user's emotional state (e.g., fatigue, excitement, relief) as numerical data.

[0217] Step 4:

[0218] The server uses the results of sentiment analysis to adjust the tone of its response. It uses a prompt sentence generated by a generative AI model, for example, to generate "words of encouragement for a slightly tired user." This response sentence is obtained as text data to be ultimately provided as audio.

[0219] Step 5:

[0220] The server converts the generated response text into speech via the Google Text-to-Speech API. The converted audio data is sent to the device. The device then plays this audio data for the user to listen to.

[0221] Step 6:

[0222] The server collects sensor data from wearable devices to monitor the user's health and lifestyle. It analyzes the collected data and generates appropriate advice if any abnormalities are detected.

[0223] Step 7:

[0224] The server uses the Spotify API or YouTube Data API to suggest music and videos that are appropriate for the user, based on their emotional state. Because this content suggestion takes the user's emotions into consideration, it contributes to relaxation and a change of pace.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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).

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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".

[0241] The present invention aims to build an AI agent that enables natural interaction with users and supports the lives of the elderly. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, and content suggestion means.

[0242] First, when the user speaks to the AI ​​agent, the device receives the voice data. The device then converts this voice into text data through speech recognition and sends it to the server.

[0243] The server analyzes the received text data using natural language processing techniques. In this process, the server refers to past conversation history and generates appropriate responses that are relevant to the context. For example, if a user asks, "What should I do today?", the server considers past conversations and the user's tendencies to create a response such as, "The weather is nice today, how about going for a walk?"

[0244] The generated response is then sent from the server to the terminal and converted into audio data by a speech synthesis system. The terminal then plays the response back to the user as a smooth audio output.

[0245] Furthermore, the sensors in the device continuously collect the user's lifestyle data and transmit it to the server. The server analyzes this data to monitor the user's health and lifestyle. For example, it analyzes the user's step count and sleep patterns, and if a lack of exercise is detected, it generates specific advice such as, "It seems you haven't been exercising much this week. How about taking a short walk?"

[0246] Security measures also play a crucial role in protecting user safety. The server immediately alerts family members and relevant parties if it detects suspicious calls or unusual activity, allowing users to live their daily lives with peace of mind.

[0247] Finally, the content suggestion system proposes the most suitable music, movies, books, and other content to the user based on their past conversation history and preferences. This allows users to enjoy a richer experience.

[0248] In this way, by following the embodiments of the invention, it is possible to provide a system that improves user communication, supports health management, and enhances security.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The user speaks to the AI ​​agent. The device receives the user's voice via its microphone.

[0252] Step 2:

[0253] The terminal converts the received audio data into text data using speech recognition technology. This text data is then sent to the server.

[0254] Step 3:

[0255] The server analyzes the received text data using natural language processing techniques. Here, the server refers to a database of past dialogue history and generates an appropriate response based on the context.

[0256] Step 4:

[0257] The generated response is sent from the server to the terminal, which then uses speech synthesis technology to convert the text into speech data.

[0258] Step 5:

[0259] The device plays audio data to the user and provides the generated response in voice.

[0260] Step 6:

[0261] The sensor device collects user behavior and environmental data and transmits it to the server.

[0262] Step 7:

[0263] The server analyzes the user's health status and lifestyle based on data from sensor devices. It then generates health management and lifestyle improvement advice and sends it to the terminal.

[0264] Step 8:

[0265] The device notifies the user of the generated advice and conveys the advice via voice or on-screen display.

[0266] Step 9:

[0267] The server uses security measures to monitor for suspicious calls and unusual activity, and if detected, it generates an alert and notifies the device and family members.

[0268] Step 10:

[0269] Based on past conversation history, the server uses a content suggestion mechanism to select content suitable for the user and sends the suggestion to the terminal.

[0270] Step 11:

[0271] The device displays or plays suggested content to the user and provides options.

[0272] (Example 1)

[0273] 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".

[0274] An effective support system is needed that simultaneously facilitates communication, improves health management, and enhances security in the daily lives of users, including the elderly. Existing technologies often provide these elements individually, lacking integrated services, which compromises user convenience.

[0275] 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.

[0276] In this invention, the server includes a recognition device, a language analysis device, a synthesis device, a measurement device, a protection device, and a suggestion device. This enables natural interaction with the user, monitoring of health status, ensuring safety, and suggestion of personalized content.

[0277] A "recognition device" is a device that has the function of converting voice data into text data, and converts voice input from a user into digital text information.

[0278] A "language analysis device" is a device that analyzes text data and generates natural-sounding responses while referring to past dialogue history.

[0279] A "synthesizer" is a device that converts the generated response into audio data and provides it to the user as audio output.

[0280] A "measuring device" is a device that continuously collects a user's lifestyle data and uses that data to monitor their health status and lifestyle rhythms.

[0281] A "protection device" is a device that protects user safety by detecting suspicious communications or user abnormalities and issuing warnings.

[0282] A "suggestion device" is a device that selects and suggests content that will interest the user based on their past history and preferences.

[0283] This invention is an integrated AI agent system designed to support the lives of users, such as the elderly. This system is optimized for natural interaction with users and offers numerous conveniences. Specifically, it is implemented using a combination of the following hardware and software.

[0284] First, the terminal receives voice input and converts the voice data into text data using a speech recognition device. A recognition system employing natural language processing technology is used for speech recognition. For example, a common speech recognition API can be used as the recognition engine.

[0285] Next, the character data received by the server is analyzed by a language analysis device. Among these, a generation AI model is utilized to perform context analysis based on past conversation histories and generate responses. As the natural language processing model used here, the latest generation AI model is employed.

[0286] The generated response is sent to the synthesis device on the terminal and converted into voice. For voice synthesis, a synthetic voice engine is adopted, enabling real-time natural voice output.

[0287] Furthermore, through the measurement device installed on the terminal, the user's life data is collected and sent to the server. This data includes the number of steps, heart rate, etc., and based on this, the health status and life rhythm are analyzed.

[0288] The server monitors suspicious activities and abnormalities via a protection device and issues a warning if detected. Also, using a proposal device, content based on the user's history and preferences is recommended. As an example, a proposal such as "You seem to be interested in classical music lately. How about listening to Beethoven today?" is made.

[0289] As an example of a specific prompt sentence, there is "The user is looking for hobbies that can be done at home. Based on the information that it is raining today, please make a proposal."

[0290] In this way, the system of the present invention is an embodiment that provides the user with an improvement in daily life and security, and aims to improve the quality of the user's life thereby.

[0291] The flow of specific processing in Example 1 will be described using FIG. 11.

[0292] Step 1:

[0293] The user speaks to the AI ​​agent and inputs voice data. The device captures this voice with its microphone and passes it to a speech recognition device. The speech recognition device analyzes the input analog voice data and converts it into digital text data. During this process, speech processing is performed to accommodate the intonation and speed of speech. The converted text data is then generated as output.

[0294] Step 2:

[0295] The terminal sends the acquired text data to the server. The server inputs the text data into a language analysis device and retrieves past dialogue data from a database to understand the context. Based on this data, a generative AI model infers the user's intent and generates an appropriate response. Specifically, text generation is performed to implement question answering and recommendation functions, and a finished response sentence is output.

[0296] Step 3:

[0297] The server sends the response text to the terminal. The terminal inputs this text response into a speech synthesizer and converts it into speech data. The speech synthesizer operates functions to adjust the tone and pacing to produce a natural and easy-to-understand voice. The output is speech data intended for the user to hear.

[0298] Step 4:

[0299] The device plays the generated audio data through its speaker, providing the user with a continuation of the conversation. This allows the user to naturally receive responses and suggestions to their questions. This step is performed in real time, enhancing the user experience.

[0300] Step 5:

[0301] The terminal continuously collects the user's living patterns (such as the number of steps and heart rate) through the measuring device. These data are periodically transmitted to the server as input. The server analyzes the data and monitors the user's health status. It determines the health status and outputs advice for improving life if necessary.

[0302] Step 6:

[0303] The server uses a protection device to perform security monitoring. If suspicious communication is detected, it immediately generates a warning message and notifies the registered contacts. In this process, detection of unauthorized access and confirmation of login history are carried out.

[0304] Step 7:

[0305] The proposing device selects and proposes individual content based on the user's past history and preferences. The server uses a generated AI model to generate the proposed content in a prompt sentence and outputs content tailored to the user. The proposed content is provided to the user as music, movies, or books.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0308] There is a need for a system that supports the elderly to live their daily lives independently and safely. However, in the conventional technology, there is a lack of appropriate advice and content provided according to the individual needs of the elderly, and the safety functions that can respond quickly in an emergency are not sufficient. Therefore, it is difficult for the elderly to live a rich life with peace of mind.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0310] In this invention, the server includes a conversion means for receiving voice input from a user and converting it into text data; a processing means for analyzing the text data and generating a response by referring to past dialogue history; and a support means for generating suggestions based on environmental information and past health data to support the user's daily activities. This enables daily life support and safety assurance suitable for the elderly, and further enables the provision of advice tailored to individual needs.

[0311] "Conversion means" refers to a device or process that has the function of receiving voice input and converting it into text data.

[0312] "Processing means" refers to a device or process that has the function of analyzing character data and generating an appropriate response by referring to past dialogue history.

[0313] "Output means" refers to a device or process that has the function of outputting the generated response as audio and providing it to the user.

[0314] "Collection means" refers to a device or process that has the function of continuously collecting user lifestyle data and monitoring their health status and lifestyle rhythms.

[0315] "Safety measures" refer to devices or processes that have the function of detecting suspicious communications or user abnormalities and issuing warnings.

[0316] "Support means" refers to a device or process that has the function of generating appropriate suggestions based on environmental information and past health data in order to support the user's daily activities.

[0317] The system for implementing the present invention constructs an AI agent for the purpose of supporting the daily lives of the elderly. Its main components include conversion means, processing means, output means, collection means, safety means, and support means.

[0318] First, the terminal receives voice input from the user and converts it into text data using a conversion mechanism. A speech recognition API is used as the conversion mechanism. The server receives this text data and analyzes it using a processing mechanism. In this process, a natural language processing library is used to refer to past dialogue history and generate an appropriate response.

[0319] The generated response is converted into audio data by an output device, and the terminal provides this to the user in audio format. This is achieved using a speech synthesis library.

[0320] Furthermore, the device continuously collects user lifestyle data using collection methods and transmits it to a server. This data collection utilizes the smartphone's built-in sensors, and data analysis is performed using Pandas and NumPy. The analysis results are used to understand the user's health status and lifestyle.

[0321] The safety measures monitor data in real time to detect abnormal communications and activity, and alert relevant parties when an anomaly is detected. This ensures user safety.

[0322] The support system provides users with optimal daily activity suggestions based on environmental information and past health data to facilitate their daily activities. For example, if a user asks, "What should I do today?", the support system, based on weather information and past activity data, might suggest, "The weather is nice today, so how about taking a walk in the park?"

[0323] An example of a prompt from a generative AI model would be the text, "To support the user's daily activities, we will create exercise suggestions based on weather forecasts and past health data."

[0324] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0325] Step 1:

[0326] The device receives voice input from the user via the microphone. The received voice data is passed to a speech recognition API and converted into text data. This process inputs the user's verbal questions as parseable text.

[0327] Step 2:

[0328] The server passes the text data obtained from the speech recognition API to the processing unit, where it is analyzed by a natural language processing engine. Here, the data is compared with past dialogue history to generate a contextually appropriate response. The output of this step is text data indicating an appropriate response to the user.

[0329] Step 3:

[0330] The text data generated by the server is converted into speech data using a speech synthesis engine and passed to the terminal. This allows the terminal to respond to the user in natural-sounding speech through its speech output device.

[0331] Step 4:

[0332] The device continuously collects user lifestyle data using built-in sensors. The acquired data is sent to a server and analyzed using Pandas and NumPy. This analysis provides information to understand the user's health status and lifestyle.

[0333] Step 5:

[0334] The server uses security measures to monitor the collected data in real time and detect any anomalies. If suspicious activity is detected, it automatically issues a warning to the relevant parties. This process is set up to ensure user peace of mind.

[0335] Step 6:

[0336] The server utilizes support tools to generate personalized suggestions to assist the user's daily activities. It takes environmental information and past health data into consideration to suggest suitable activities and schedules. This step utilizes a generative AI model, and the prompt message for it is "To assist the user's daily activities, we will create exercise suggestions based on the weather forecast and past health data."

[0337] Step 7:

[0338] The device either communicates the generated suggestions to the user via voice or displays them on its screen. If communicating via voice, the speech synthesis engine is used again. This output allows the user to understand the suggested activities and choose the appropriate action to take.

[0339] 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.

[0340] The present invention provides comprehensive support for the lives of the elderly by having an AI agent that includes emotion recognition in interaction with the user. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, content suggestion means, and emotion engine.

[0341] When a user speaks to the AI ​​agent, the device receives the voice input, converts it into text data using speech recognition, and sends it to the server. The server then uses natural language processing to analyze the text data and understand the user's utterance. The emotion engine also functions here, recognizing emotions from the user's tone of voice and word choice. For example, if the user says, "I'm a little tired today," the emotion engine detects fatigue or weariness.

[0342] The server adjusts the tone of the conversation based on this emotional information and generates an appropriate response for the user. For example, for a user who is feeling tired, it creates a gentle response such as, "Please get plenty of rest today." The generated response is sent to the terminal and provided to the user as speech through a speech synthesis system.

[0343] Furthermore, the sensor system continuously monitors the user's lifestyle data to understand their health status and daily rhythm. The server analyzes this data and generates health management advice based on the user's emotional and physical state. For example, if the sensor data indicates a lack of exercise and the emotion engine determines that the user is feeling down, it will generate advice such as, "Taking a short walk today might cheer you up."

[0344] Furthermore, the emotion engine interacts with content suggestion methods, proposing content best suited to the user's emotions. For example, if the user is feeling stressed, it will provide relaxing music or videos.

[0345] Thus, the present invention provides a system that aims to improve users' communication and quality of life through a variety of functions, including emotion recognition.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The user asks the AI ​​agent a question using their voice. The device receives the voice through its microphone and records it as audio data.

[0349] Step 2:

[0350] The terminal inputs the received audio data into a speech recognition device and converts it into text data. This text data is then sent to the server.

[0351] Step 3:

[0352] The server uses natural language processing to analyze text data and understand the context of the speech. Simultaneously, an emotion engine operates to recognize the user's emotions based on their tone of voice and word choices.

[0353] Step 4:

[0354] The server combines the results of natural language processing with analysis from the emotion engine to generate an appropriate response. For example, if the user's emotions indicate sadness or fatigue, the server will create a response that includes empathy.

[0355] Step 5:

[0356] The generated response is sent from the server to the terminal and converted into speech data by a speech synthesis system.

[0357] Step 6:

[0358] The device plays audio data through its speaker and provides responses to the user. This enables a natural and user-friendly conversation.

[0359] Step 7:

[0360] The sensor device periodically collects user activity and environmental data and transmits this data to a server.

[0361] Step 8:

[0362] The server analyzes data from sensor devices to assess health status and daily lifestyle patterns. Based on this assessment, it generates health management advice as needed.

[0363] Step 9:

[0364] The server utilizes a content suggestion method that selects and proposes content that matches the user's emotional state, based on sentiment analysis obtained by the emotion engine.

[0365] Step 10:

[0366] The device helps improve the user's quality of life by presenting suggested content to the user and allowing them to select and play it.

[0367] (Example 2)

[0368] 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".

[0369] There is a growing societal demand for improved health management and safety in the lives of the elderly. In particular, maintaining a regular daily routine, detecting suspicious phone calls, and providing personalized responses tailored to their emotions are key challenges. Furthermore, understanding the user's emotional state and providing appropriate communication and content suggestions is also essential.

[0370] 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.

[0371] In this invention, the server includes speech recognition means for acquiring voice information and converting it into text information, natural language processing means for analyzing text information and identifying emotions, and sensor means for detecting living conditions and evaluating health status. This enables personalized responses and content suggestions based on the user's emotions and health status.

[0372] "Speech recognition means" refers to a technology that receives speech information input by a user and converts it into text information.

[0373] "Natural language processing means" refers to technologies that analyze converted text information to understand the user's intentions and emotions.

[0374] "Speech synthesis means" refers to a technology that converts responses generated on a server into speech data and provides it to the user as speech.

[0375] "Sensing means" refers to technology that collects information to monitor a user's living situation and health condition.

[0376] "Security management measures" refer to technologies for detecting suspicious communications and abnormal user behavior and generating warnings.

[0377] "Advice generation means" refers to a technology that creates and provides advice for maintaining the user's health and improving their lifestyle based on information acquired by sensor means.

[0378] "Content suggestion methods" refer to technologies that utilize past conversation records to suggest personalized information and entertainment to users.

[0379] The system of the present invention is designed to support the lives of the elderly and includes an AI agent that performs emotion recognition. When a user speaks to the AI ​​agent by voice, the terminal acquires voice data and converts it into text data using speech recognition means. This text data is sent to a server that uses natural language processing means. The server analyzes the text data using natural language processing techniques to understand the user's intentions and the content of their speech. This process also includes an emotion engine that identifies emotions from the tone and word choice of speech.

[0380] As a concrete example of emotion recognition, if a user says, "I'm a little tired today," the emotion engine detects the level of fatigue from the statement, and the server generates a gentle response based on that result. This response is sent back to the terminal and played back to the user as speech using a speech synthesis system. For example, a possible response might be, "Please get plenty of rest today."

[0381] This system includes sensors that monitor lifestyle data, continuously collecting data to understand the user's daily rhythm and health status. The server analyzes this data and employs a scheme to generate health management advice. For example, if the sensor data indicates a lack of exercise, it will generate advice such as, "Taking a short walk today might help you feel refreshed."

[0382] Content suggestions are also provided; the emotion engine analyzes the user's emotional state and suggests the most suitable music, videos, and other content based on the results. For example, if the user is feeling stressed, it will recommend music with a relaxing effect.

[0383] A concrete example of a prompt message might be: "Generate a system response for when the user says, 'I'm a little tired today.' Also, provide any relevant health advice."

[0384] Thus, the present invention aims to improve the quality of life for the elderly by integrating various technologies.

[0385] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0386] Step 1:

[0387] The device receives voice input from the user via a microphone. This voice data is converted into text data by a speech recognition system. Specifically, when the user says, "I'm a little tired today," the voice is converted into digital format and obtained as a string of characters. This text data is then sent to the server.

[0388] Step 2:

[0389] The server receives text data sent from the terminal. Using natural language processing, it analyzes the text data to understand the user's utterance. This analysis involves word recognition and contextual understanding to clarify what the user is trying to say. In addition, an emotion engine detects emotions based on the tone and word choice of the text. The input is text data, and the output is the analysis results and emotion information.

[0390] Step 3:

[0391] The server generates responses that reflect emotional information based on natural language processing. This response generation process creates responses in a tone appropriate to the user's emotional state. For example, if the user is expressing fatigue, the server will construct a reply such as, "Please take it easy and rest today." The input is the parsed data and emotional information, and the output is the response text.

[0392] Step 4:

[0393] The generated response text is sent to the terminal, which uses speech synthesis to convert this text into audio data. The converted audio is delivered to the user through the speaker. Specifically, the response text "Please rest well today" is played as audio. The input is the response text, and the output is the played audio.

[0394] Step 5:

[0395] Furthermore, the sensor continuously collects data on the user's lifestyle. The server analyzes this data to assess their health status and daily rhythm. If the sensor data indicates a lack of exercise, the server generates advice such as, "Taking a short walk today might help you feel refreshed." The input is the sensor data, and the output is the advice text.

[0396] Step 6:

[0397] The content suggestion system uses the user's emotional information to suggest relaxing music and videos. If the user's emotions indicate stress, content that promotes relaxation will be selected. The input is emotional information, and the output is a list of suggested content.

[0398] (Application Example 2)

[0399] 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."

[0400] Modern elderly people often experience loneliness in their daily lives, which can hinder their ability to manage their health and maintain a regular lifestyle. Furthermore, they often lack sufficient psychological support due to the difficulty in fully understanding and caring for their emotions. This, in turn, leads to a decline in their quality of life.

[0401] 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.

[0402] In this invention, the server includes speech recognition means for receiving voice input and converting it into text data, natural language processing means for generating and providing responses through natural language processing, and emotion engine means for recognizing the user's emotions and adjusting the responses. This makes it possible to provide comprehensive emotional support to the elderly and improve their quality of life.

[0403] "Voice recognition means" refers to technology that receives voice input from a user and converts it into text data.

[0404] "Natural language processing means" refers to technologies that analyze text data and generate appropriate responses based on past dialogue history.

[0405] "Speech synthesis means" refers to a technology that provides the generated response as speech output.

[0406] "Sensing means" refers to devices and technologies used to collect information about a user's lifestyle and monitor their health status and daily rhythm.

[0407] "Security measures" are technologies used to detect suspicious communications or user anomalies and issue warnings.

[0408] An "emotion engine" is a technology that analyzes the tone of voice and linguistic expressions to recognize the user's emotions and adjusts the tone of the dialogue accordingly.

[0409] A "content suggestion method" is a technology that suggests the most suitable content based on the user's emotions.

[0410] An "advice generation means" is a technology that generates and provides users with advice for health management and lifestyle improvement based on data collected by sensor means.

[0411] This system consists of an AI agent designed to comprehensively support the user's life. It utilizes the speech recognition technology built into the device to receive voice input, leveraging the Google Speech-to-Text API. The voice is converted into text data, which is then sent to the server. The server employs a natural language processing model using the TensorFlow library to analyze the user's intent and emotions. During this analysis, the server also performs sentiment analysis using VADER, and the sentiment engine uses the results to adjust the tone of the response. The response sent to the user is generated using speech synthesis technology via the Google Text-to-Speech API and provided as voice from the device.

[0412] Furthermore, this system collects sensor data from wearable devices to monitor health status and lifestyle rhythms. This data is stored on a server and analyzed periodically. If necessary, the server generates advice for health management and lifestyle improvement based on this data. This advice generation is performed by a generative AI model, sent to the application, and then provided in voice.

[0413] Furthermore, as a content suggestion method, the system uses the Spotify API and YouTube Data API to suggest appropriate content based on the user's emotions. This feature allows users to easily access music and videos that match their emotional state.

[0414] For example, if a user types "I'm not feeling well today" into their device, the system performs text conversion using the Google Speech-to-Text API, analyzes intent and sentiment using TensorFlow, and then performs sentiment analysis with VADER. As a result, encouraging words such as "Please take it easy and rest today" are provided as voice via the Google Text-to-Speech API. Furthermore, relaxing music is suggested via the Spotify API.

[0415] Examples of prompts for a generative AI model:

[0416] "Read the user's emotions from their statements and provide an appropriate response. For example, in response to 'I'm a little tired,' you might want to say, 'Maybe you should take it easy and rest today.'"

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] The device receives voice input from the user. It sends the voice signal to the Google Speech-to-Text API, where it is converted into text data. This converted text data is then sent to the server.

[0420] Step 2:

[0421] The server uses TensorFlow to analyze the received text data and performs natural language processing. Specifically, it analyzes the intent behind the user's utterances and extracts elements that contain emotions. This process yields the user's current emotions as text.

[0422] Step 3:

[0423] The server uses VADER to perform emotion analysis based on the analysis results. The analysis outputs the user's emotional state (e.g., fatigue, excitement, relief) as numerical data.

[0424] Step 4:

[0425] The server uses the results of sentiment analysis to adjust the tone of its response. It uses a prompt sentence generated by a generative AI model, for example, to generate "words of encouragement for a slightly tired user." This response sentence is obtained as text data to be ultimately provided as audio.

[0426] Step 5:

[0427] The server converts the generated response text into speech via the Google Text-to-Speech API. The converted audio data is sent to the device. The device then plays this audio data for the user to listen to.

[0428] Step 6:

[0429] The server collects sensor data from wearable devices to monitor the user's health and lifestyle. It analyzes the collected data and generates appropriate advice if any abnormalities are detected.

[0430] Step 7:

[0431] The server uses the Spotify API or YouTube Data API to suggest music and videos that are appropriate for the user, based on their emotional state. Because this content suggestion takes the user's emotions into consideration, it contributes to relaxation and a change of pace.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] [Third Embodiment]

[0436] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0437] 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.

[0438] 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).

[0439] 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.

[0440] 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.

[0441] 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).

[0442] 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.

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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".

[0448] The present invention aims to build an AI agent that enables natural interaction with users and supports the lives of the elderly. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, and content suggestion means.

[0449] First, when the user speaks to the AI ​​agent, the device receives the voice data. The device then converts this voice into text data through speech recognition and sends it to the server.

[0450] The server analyzes the received text data using natural language processing techniques. In this process, the server refers to past conversation history and generates appropriate responses that are relevant to the context. For example, if a user asks, "What should I do today?", the server considers past conversations and the user's tendencies to create a response such as, "The weather is nice today, how about going for a walk?"

[0451] The generated response is then sent from the server to the terminal and converted into audio data by a speech synthesis system. The terminal then plays the response back to the user as a smooth audio output.

[0452] Furthermore, the sensors in the device continuously collect the user's lifestyle data and transmit it to the server. The server analyzes this data to monitor the user's health and lifestyle. For example, it analyzes the user's step count and sleep patterns, and if a lack of exercise is detected, it generates specific advice such as, "It seems you haven't been exercising much this week. How about taking a short walk?"

[0453] Security measures also play a crucial role in protecting user safety. The server immediately alerts family members and relevant parties if it detects suspicious calls or unusual activity, allowing users to live their daily lives with peace of mind.

[0454] Finally, the content suggestion system proposes the most suitable music, movies, books, and other content to the user based on their past conversation history and preferences. This allows users to enjoy a richer experience.

[0455] In this way, by following the embodiments of the invention, it is possible to provide a system that improves user communication, supports health management, and enhances security.

[0456] The following describes the processing flow.

[0457] Step 1:

[0458] The user speaks to the AI ​​agent. The device receives the user's voice via its microphone.

[0459] Step 2:

[0460] The terminal converts the received audio data into text data using speech recognition technology. This text data is then sent to the server.

[0461] Step 3:

[0462] The server analyzes the received text data using natural language processing techniques. Here, the server refers to a database of past dialogue history and generates an appropriate response based on the context.

[0463] Step 4:

[0464] The generated response is sent from the server to the terminal, which then uses speech synthesis technology to convert the text into speech data.

[0465] Step 5:

[0466] The device plays audio data to the user and provides the generated response in voice.

[0467] Step 6:

[0468] The sensor device collects user behavior and environmental data and transmits it to the server.

[0469] Step 7:

[0470] The server analyzes the user's health status and lifestyle based on data from sensor devices. It then generates health management and lifestyle improvement advice and sends it to the terminal.

[0471] Step 8:

[0472] The device notifies the user of the generated advice and conveys the advice via voice or on-screen display.

[0473] Step 9:

[0474] The server uses security measures to monitor for suspicious calls and unusual activity, and if detected, it generates an alert and notifies the device and family members.

[0475] Step 10:

[0476] Based on past conversation history, the server uses a content suggestion mechanism to select content suitable for the user and sends the suggestion to the terminal.

[0477] Step 11:

[0478] The device displays or plays suggested content to the user and provides options.

[0479] (Example 1)

[0480] 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."

[0481] An effective support system is needed that simultaneously facilitates communication, improves health management, and enhances security in the daily lives of users, including the elderly. Existing technologies often provide these elements individually, lacking integrated services, which compromises user convenience.

[0482] 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.

[0483] In this invention, the server includes a recognition device, a language analysis device, a synthesis device, a measurement device, a protection device, and a suggestion device. This enables natural interaction with the user, monitoring of health status, ensuring safety, and suggestion of personalized content.

[0484] A "recognition device" is a device that has the function of converting voice data into text data, and converts voice input from a user into digital text information.

[0485] A "language analysis device" is a device that analyzes text data and generates natural-sounding responses while referring to past dialogue history.

[0486] A "synthesizer" is a device that converts the generated response into audio data and provides it to the user as audio output.

[0487] A "measuring device" is a device that continuously collects a user's lifestyle data and uses that data to monitor their health status and lifestyle rhythms.

[0488] A "protection device" is a device that protects user safety by detecting suspicious communications or user abnormalities and issuing warnings.

[0489] A "suggestion device" is a device that selects and suggests content that will interest the user based on their past history and preferences.

[0490] This invention is an integrated AI agent system designed to support the lives of users, such as the elderly. This system is optimized for natural interaction with users and offers numerous conveniences. Specifically, it is implemented using a combination of the following hardware and software.

[0491] First, the terminal receives voice input and converts the voice data into text data using a speech recognition device. A recognition system employing natural language processing technology is used for speech recognition. For example, a common speech recognition API can be used as the recognition engine.

[0492] Next, the text data received by the server is analyzed by a language analysis device. This process utilizes a generative AI model to perform contextual analysis based on past dialogue history and generate a response. The latest generative AI model is used as the natural language processing model here.

[0493] The generated response is sent to a synthesis device on the terminal and converted into speech. A speech synthesis engine is used for speech synthesis, enabling natural-sounding speech output in real time.

[0494] Furthermore, the device collects user lifestyle data through its built-in measuring device and transmits it to a server. This data includes steps taken and heart rate, and is used to analyze the user's health status and lifestyle rhythm.

[0495] The server monitors for suspicious activity and anomalies via a protection device and issues a warning if detected. It also uses a suggestion device to recommend content based on the user's history and preferences. For example, it might suggest, "You've recently become interested in classical music. Why not listen to Beethoven today?"

[0496] A concrete example of a prompt message is: "The user is looking for a hobby they can do at home. Based on the information that it is raining today, please suggest something."

[0497] Thus, the system of the present invention is an embodiment that provides users with improved daily life and ensured safety, thereby aiming to improve the quality of life for the user.

[0498] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0499] Step 1:

[0500] The user speaks to the AI ​​agent and inputs voice data. The device captures this voice with its microphone and passes it to a speech recognition device. The speech recognition device analyzes the input analog voice data and converts it into digital text data. During this process, speech processing is performed to accommodate the intonation and speed of speech. The converted text data is then generated as output.

[0501] Step 2:

[0502] The terminal sends the acquired text data to the server. The server inputs the text data into a language analysis device and retrieves past dialogue data from a database to understand the context. Based on this data, a generative AI model infers the user's intent and generates an appropriate response. Specifically, text generation is performed to implement question answering and recommendation functions, and a finished response sentence is output.

[0503] Step 3:

[0504] The server sends the response text to the terminal. The terminal inputs this text response into a speech synthesizer and converts it into speech data. The speech synthesizer operates functions to adjust the tone and pacing to produce a natural and easy-to-understand voice. The output is speech data intended for the user to hear.

[0505] Step 4:

[0506] The device plays the generated audio data through its speaker, providing the user with a continuation of the conversation. This allows the user to naturally receive responses and suggestions to their questions. This step is performed in real time, enhancing the user experience.

[0507] Step 5:

[0508] The device continuously collects the user's lifestyle patterns (steps, heart rate, etc.) through a measuring device. This data is periodically sent to the server as input. The server analyzes this data and monitors the user's health status. It assesses the health status and, if necessary, outputs advice for lifestyle improvements.

[0509] Step 6:

[0510] The server uses protective devices to monitor security. If suspicious communication is detected, it immediately generates a warning message and notifies registered contacts. This process includes detecting unauthorized access and reviewing login history.

[0511] Step 7:

[0512] The suggestion device selects and suggests individual content based on the user's past history and preferences. The server uses a generation AI model to generate suggestion content in the form of prompts and outputs content tailored to the user. The suggested content is then provided to the user as music, movies, or books.

[0513] (Application Example 1)

[0514] 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."

[0515] There is a need for systems that support elderly people in living independent and safe daily lives. However, conventional technologies lack the ability to provide appropriate advice and content tailored to the individual needs of the elderly, and also lack sufficient safety features to respond quickly in emergencies. As a result, it is difficult for the elderly to live a secure and fulfilling life.

[0516] 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.

[0517] In this invention, the server includes a conversion means for receiving voice input from a user and converting it into text data; a processing means for analyzing the text data and generating a response by referring to past dialogue history; and a support means for generating suggestions based on environmental information and past health data to support the user's daily activities. This enables daily life support and safety assurance suitable for the elderly, and further enables the provision of advice tailored to individual needs.

[0518] "Conversion means" refers to a device or process that has the function of receiving voice input and converting it into text data.

[0519] "Processing means" refers to a device or process that has the function of analyzing character data and generating an appropriate response by referring to past dialogue history.

[0520] "Output means" refers to a device or process that has the function of outputting the generated response as audio and providing it to the user.

[0521] "Collection means" refers to a device or process that has the function of continuously collecting user lifestyle data and monitoring their health status and lifestyle rhythms.

[0522] "Safety measures" refer to devices or processes that have the function of detecting suspicious communications or user abnormalities and issuing warnings.

[0523] "Support means" refers to a device or process that has the function of generating appropriate suggestions based on environmental information and past health data in order to support the user's daily activities.

[0524] The system for implementing the present invention constructs an AI agent for the purpose of supporting the daily lives of the elderly. Its main components include conversion means, processing means, output means, collection means, safety means, and support means.

[0525] First, the terminal receives voice input from the user and converts it into text data using a conversion mechanism. A speech recognition API is used as the conversion mechanism. The server receives this text data and analyzes it using a processing mechanism. In this process, a natural language processing library is used to refer to past dialogue history and generate an appropriate response.

[0526] The generated response is converted into audio data by an output device, and the terminal provides this to the user in audio format. This is achieved using a speech synthesis library.

[0527] Furthermore, the device continuously collects user lifestyle data using collection methods and transmits it to a server. This data collection utilizes the smartphone's built-in sensors, and data analysis is performed using Pandas and NumPy. The analysis results are used to understand the user's health status and lifestyle.

[0528] The safety measures monitor data in real time to detect abnormal communications and activity, and alert relevant parties when an anomaly is detected. This ensures user safety.

[0529] The support system provides users with optimal daily activity suggestions based on environmental information and past health data to facilitate their daily activities. For example, if a user asks, "What should I do today?", the support system, based on weather information and past activity data, might suggest, "The weather is nice today, so how about taking a walk in the park?"

[0530] An example of a prompt from a generative AI model would be the text, "To support the user's daily activities, we will create exercise suggestions based on weather forecasts and past health data."

[0531] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0532] Step 1:

[0533] The device receives voice input from the user via the microphone. The received voice data is passed to a speech recognition API and converted into text data. This process inputs the user's verbal questions as parseable text.

[0534] Step 2:

[0535] The server passes the text data obtained from the speech recognition API to the processing unit, where it is analyzed by a natural language processing engine. Here, the data is compared with past dialogue history to generate a contextually appropriate response. The output of this step is text data indicating an appropriate response to the user.

[0536] Step 3:

[0537] The text data generated by the server is converted into speech data using a speech synthesis engine and passed to the terminal. This allows the terminal to respond to the user in natural-sounding speech through its speech output device.

[0538] Step 4:

[0539] The device continuously collects user lifestyle data using built-in sensors. The acquired data is sent to a server and analyzed using Pandas and NumPy. This analysis provides information to understand the user's health status and lifestyle.

[0540] Step 5:

[0541] The server uses security measures to monitor the collected data in real time and detect any anomalies. If suspicious activity is detected, it automatically issues a warning to the relevant parties. This process is set up to ensure user peace of mind.

[0542] Step 6:

[0543] The server utilizes support tools to generate personalized suggestions to assist the user's daily activities. It takes environmental information and past health data into consideration to suggest suitable activities and schedules. This step utilizes a generative AI model, and the prompt message for it is "To assist the user's daily activities, we will create exercise suggestions based on the weather forecast and past health data."

[0544] Step 7:

[0545] The device either communicates the generated suggestions to the user via voice or displays them on its screen. If communicating via voice, the speech synthesis engine is used again. This output allows the user to understand the suggested activities and choose the appropriate action to take.

[0546] 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.

[0547] The present invention provides comprehensive support for the lives of the elderly by having an AI agent that includes emotion recognition in interaction with the user. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, content suggestion means, and emotion engine.

[0548] When a user speaks to the AI ​​agent, the device receives the voice input, converts it into text data using speech recognition, and sends it to the server. The server then uses natural language processing to analyze the text data and understand the user's utterance. The emotion engine also functions here, recognizing emotions from the user's tone of voice and word choice. For example, if the user says, "I'm a little tired today," the emotion engine detects fatigue or weariness.

[0549] The server adjusts the tone of the conversation based on this emotional information and generates an appropriate response for the user. For example, for a user who is feeling tired, it creates a gentle response such as, "Please get plenty of rest today." The generated response is sent to the terminal and provided to the user as speech through a speech synthesis system.

[0550] Furthermore, the sensor system continuously monitors the user's lifestyle data to understand their health status and daily rhythm. The server analyzes this data and generates health management advice based on the user's emotional and physical state. For example, if the sensor data indicates a lack of exercise and the emotion engine determines that the user is feeling down, it will generate advice such as, "Taking a short walk today might cheer you up."

[0551] Furthermore, the emotion engine interacts with content suggestion methods, proposing content best suited to the user's emotions. For example, if the user is feeling stressed, it will provide relaxing music or videos.

[0552] Thus, the present invention provides a system that aims to improve users' communication and quality of life through a variety of functions, including emotion recognition.

[0553] The following describes the processing flow.

[0554] Step 1:

[0555] The user asks the AI ​​agent a question using their voice. The device receives the voice through its microphone and records it as audio data.

[0556] Step 2:

[0557] The terminal inputs the received audio data into a speech recognition device and converts it into text data. This text data is then sent to the server.

[0558] Step 3:

[0559] The server uses natural language processing to analyze text data and understand the context of the speech. Simultaneously, an emotion engine operates to recognize the user's emotions based on their tone of voice and word choices.

[0560] Step 4:

[0561] The server combines the results of natural language processing with analysis from the emotion engine to generate an appropriate response. For example, if the user's emotions indicate sadness or fatigue, the server will create a response that includes empathy.

[0562] Step 5:

[0563] The generated response is sent from the server to the terminal and converted into speech data by a speech synthesis system.

[0564] Step 6:

[0565] The device plays audio data through its speaker and provides responses to the user. This enables a natural and user-friendly conversation.

[0566] Step 7:

[0567] The sensor device periodically collects user activity and environmental data and transmits this data to a server.

[0568] Step 8:

[0569] The server analyzes data from sensor devices to assess health status and daily lifestyle patterns. Based on this assessment, it generates health management advice as needed.

[0570] Step 9:

[0571] The server utilizes a content suggestion method that selects and proposes content that matches the user's emotional state, based on sentiment analysis obtained by the emotion engine.

[0572] Step 10:

[0573] The device helps improve the user's quality of life by presenting suggested content to the user and allowing them to select and play it.

[0574] (Example 2)

[0575] 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."

[0576] There is a growing societal demand for improved health management and safety in the lives of the elderly. In particular, maintaining a regular daily routine, detecting suspicious phone calls, and providing personalized responses tailored to their emotions are key challenges. Furthermore, understanding the user's emotional state and providing appropriate communication and content suggestions is also essential.

[0577] 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.

[0578] In this invention, the server includes speech recognition means for acquiring voice information and converting it into text information, natural language processing means for analyzing text information and identifying emotions, and sensor means for detecting living conditions and evaluating health status. This enables personalized responses and content suggestions based on the user's emotions and health status.

[0579] "Speech recognition means" refers to a technology that receives speech information input by a user and converts it into text information.

[0580] "Natural language processing means" refers to technologies that analyze converted text information to understand the user's intentions and emotions.

[0581] "Speech synthesis means" refers to a technology that converts responses generated on a server into speech data and provides it to the user as speech.

[0582] "Sensing means" refers to technology that collects information to monitor a user's living situation and health condition.

[0583] "Security management measures" refer to technologies for detecting suspicious communications and abnormal user behavior and generating warnings.

[0584] "Advice generation means" refers to a technology that creates and provides advice for maintaining the user's health and improving their lifestyle based on information acquired by sensor means.

[0585] "Content suggestion methods" refer to technologies that utilize past conversation records to suggest personalized information and entertainment to users.

[0586] The system of the present invention is designed to support the lives of the elderly and includes an AI agent that performs emotion recognition. When a user speaks to the AI ​​agent by voice, the terminal acquires voice data and converts it into text data using speech recognition means. This text data is sent to a server that uses natural language processing means. The server analyzes the text data using natural language processing techniques to understand the user's intentions and the content of their speech. This process also includes an emotion engine that identifies emotions from the tone and word choice of speech.

[0587] As a concrete example of emotion recognition, if a user says, "I'm a little tired today," the emotion engine detects the level of fatigue from the statement, and the server generates a gentle response based on that result. This response is sent back to the terminal and played back to the user as speech using a speech synthesis system. For example, a possible response might be, "Please get plenty of rest today."

[0588] This system includes sensors that monitor lifestyle data, continuously collecting data to understand the user's daily rhythm and health status. The server analyzes this data and employs a scheme to generate health management advice. For example, if the sensor data indicates a lack of exercise, it will generate advice such as, "Taking a short walk today might help you feel refreshed."

[0589] Content suggestions are also provided; the emotion engine analyzes the user's emotional state and suggests the most suitable music, videos, and other content based on the results. For example, if the user is feeling stressed, it will recommend music with a relaxing effect.

[0590] A concrete example of a prompt message might be: "Generate a system response for when the user says, 'I'm a little tired today.' Also, provide any relevant health advice."

[0591] Thus, the present invention aims to improve the quality of life for the elderly by integrating various technologies.

[0592] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0593] Step 1:

[0594] The device receives voice input from the user via a microphone. This voice data is converted into text data by a speech recognition system. Specifically, when the user says, "I'm a little tired today," the voice is converted into digital format and obtained as a string of characters. This text data is then sent to the server.

[0595] Step 2:

[0596] The server receives text data sent from the terminal. Using natural language processing, it analyzes the text data to understand the user's utterance. This analysis involves word recognition and contextual understanding to clarify what the user is trying to say. In addition, an emotion engine detects emotions based on the tone and word choice of the text. The input is text data, and the output is the analysis results and emotion information.

[0597] Step 3:

[0598] The server generates responses that reflect emotional information based on natural language processing. This response generation process creates responses in a tone appropriate to the user's emotional state. For example, if the user is expressing fatigue, the server will construct a reply such as, "Please take it easy and rest today." The input is the parsed data and emotional information, and the output is the response text.

[0599] Step 4:

[0600] The generated response text is sent to the terminal, which uses speech synthesis to convert this text into audio data. The converted audio is delivered to the user through the speaker. Specifically, the response text "Please rest well today" is played as audio. The input is the response text, and the output is the played audio.

[0601] Step 5:

[0602] Furthermore, the sensor continuously collects data on the user's lifestyle. The server analyzes this data to assess their health status and daily rhythm. If the sensor data indicates a lack of exercise, the server generates advice such as, "Taking a short walk today might help you feel refreshed." The input is the sensor data, and the output is the advice text.

[0603] Step 6:

[0604] The content suggestion system uses the user's emotional information to suggest relaxing music and videos. If the user's emotions indicate stress, content that promotes relaxation will be selected. The input is emotional information, and the output is a list of suggested content.

[0605] (Application Example 2)

[0606] 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."

[0607] Modern elderly people often experience loneliness in their daily lives, which can hinder their ability to manage their health and maintain a regular lifestyle. Furthermore, they often lack sufficient psychological support due to the difficulty in fully understanding and caring for their emotions. This, in turn, leads to a decline in their quality of life.

[0608] 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.

[0609] In this invention, the server includes speech recognition means for receiving voice input and converting it into text data, natural language processing means for generating and providing responses through natural language processing, and emotion engine means for recognizing the user's emotions and adjusting the responses. This makes it possible to provide comprehensive emotional support to the elderly and improve their quality of life.

[0610] "Voice recognition means" refers to technology that receives voice input from a user and converts it into text data.

[0611] "Natural language processing means" refers to technologies that analyze text data and generate appropriate responses based on past dialogue history.

[0612] "Speech synthesis means" refers to a technology that provides the generated response as speech output.

[0613] "Sensing means" refers to devices and technologies used to collect information about a user's lifestyle and monitor their health status and daily rhythm.

[0614] "Security measures" are technologies used to detect suspicious communications or user anomalies and issue warnings.

[0615] An "emotion engine" is a technology that analyzes the tone of voice and linguistic expressions to recognize the user's emotions and adjusts the tone of the dialogue accordingly.

[0616] A "content suggestion method" is a technology that suggests the most suitable content based on the user's emotions.

[0617] An "advice generation means" is a technology that generates and provides users with advice for health management and lifestyle improvement based on data collected by sensor means.

[0618] This system consists of an AI agent designed to comprehensively support the user's life. It utilizes the speech recognition technology built into the device to receive voice input, leveraging the Google Speech-to-Text API. The voice is converted into text data, which is then sent to the server. The server employs a natural language processing model using the TensorFlow library to analyze the user's intent and emotions. During this analysis, the server also performs sentiment analysis using VADER, and the sentiment engine uses the results to adjust the tone of the response. The response sent to the user is generated using speech synthesis technology via the Google Text-to-Speech API and provided as voice from the device.

[0619] Furthermore, this system collects sensor data from wearable devices to monitor health status and lifestyle rhythms. This data is stored on a server and analyzed periodically. If necessary, the server generates advice for health management and lifestyle improvement based on this data. This advice generation is performed by a generative AI model, sent to the application, and then provided in voice.

[0620] Furthermore, as a content suggestion method, the system uses the Spotify API and YouTube Data API to suggest appropriate content based on the user's emotions. This feature allows users to easily access music and videos that match their emotional state.

[0621] For example, if a user types "I'm not feeling well today" into their device, the system performs text conversion using the Google Speech-to-Text API, analyzes intent and sentiment using TensorFlow, and then performs sentiment analysis with VADER. As a result, encouraging words such as "Please take it easy and rest today" are provided as voice via the Google Text-to-Speech API. Furthermore, relaxing music is suggested via the Spotify API.

[0622] Examples of prompts for a generative AI model:

[0623] "Read the user's emotions from their statements and provide an appropriate response. For example, in response to 'I'm a little tired,' you might want to say, 'Maybe you should take it easy and rest today.'"

[0624] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0625] Step 1:

[0626] The device receives voice input from the user. It sends the voice signal to the Google Speech-to-Text API, where it is converted into text data. This converted text data is then sent to the server.

[0627] Step 2:

[0628] The server uses TensorFlow to analyze the received text data and performs natural language processing. Specifically, it analyzes the intent behind the user's utterances and extracts elements that contain emotions. This process yields the user's current emotions as text.

[0629] Step 3:

[0630] The server uses VADER to perform emotion analysis based on the analysis results. The analysis outputs the user's emotional state (e.g., fatigue, excitement, relief) as numerical data.

[0631] Step 4:

[0632] The server uses the results of sentiment analysis to adjust the tone of its response. It uses a prompt sentence generated by a generative AI model, for example, to generate "words of encouragement for a slightly tired user." This response sentence is obtained as text data to be ultimately provided as audio.

[0633] Step 5:

[0634] The server converts the generated response text into speech via the Google Text-to-Speech API. The converted audio data is sent to the device. The device then plays this audio data for the user to listen to.

[0635] Step 6:

[0636] The server collects sensor data from wearable devices to monitor the user's health and lifestyle. It analyzes the collected data and generates appropriate advice if any abnormalities are detected.

[0637] Step 7:

[0638] The server uses the Spotify API or YouTube Data API to suggest music and videos that are appropriate for the user, based on their emotional state. Because this content suggestion takes the user's emotions into consideration, it contributes to relaxation and a change of pace.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] [Fourth Embodiment]

[0643] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0644] 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.

[0645] 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).

[0646] 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.

[0647] 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.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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".

[0656] The present invention aims to build an AI agent that enables natural interaction with users and supports the lives of the elderly. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, and content suggestion means.

[0657] First, when the user speaks to the AI ​​agent, the device receives the voice data. The device then converts this voice into text data through speech recognition and sends it to the server.

[0658] The server analyzes the received text data using natural language processing techniques. In this process, the server refers to past conversation history and generates appropriate responses that are relevant to the context. For example, if a user asks, "What should I do today?", the server considers past conversations and the user's tendencies to create a response such as, "The weather is nice today, how about going for a walk?"

[0659] The generated response is then sent from the server to the terminal and converted into audio data by a speech synthesis system. The terminal then plays the response back to the user as a smooth audio output.

[0660] Furthermore, the sensors in the device continuously collect the user's lifestyle data and transmit it to the server. The server analyzes this data to monitor the user's health and lifestyle. For example, it analyzes the user's step count and sleep patterns, and if a lack of exercise is detected, it generates specific advice such as, "It seems you haven't been exercising much this week. How about taking a short walk?"

[0661] Security measures also play a crucial role in protecting user safety. The server immediately alerts family members and relevant parties if it detects suspicious calls or unusual activity, allowing users to live their daily lives with peace of mind.

[0662] Finally, the content suggestion system proposes the most suitable music, movies, books, and other content to the user based on their past conversation history and preferences. This allows users to enjoy a richer experience.

[0663] In this way, by following the embodiments of the invention, it is possible to provide a system that improves user communication, supports health management, and enhances security.

[0664] The following describes the processing flow.

[0665] Step 1:

[0666] The user speaks to the AI ​​agent. The device receives the user's voice via its microphone.

[0667] Step 2:

[0668] The terminal converts the received audio data into text data using speech recognition technology. This text data is then sent to the server.

[0669] Step 3:

[0670] The server analyzes the received text data using natural language processing techniques. Here, the server refers to a database of past dialogue history and generates an appropriate response based on the context.

[0671] Step 4:

[0672] The generated response is sent from the server to the terminal, which then uses speech synthesis technology to convert the text into speech data.

[0673] Step 5:

[0674] The device plays audio data to the user and provides the generated response in voice.

[0675] Step 6:

[0676] The sensor device collects user behavior and environmental data and transmits it to the server.

[0677] Step 7:

[0678] The server analyzes the user's health status and lifestyle based on data from sensor devices. It then generates health management and lifestyle improvement advice and sends it to the terminal.

[0679] Step 8:

[0680] The device notifies the user of the generated advice and conveys the advice via voice or on-screen display.

[0681] Step 9:

[0682] The server uses security measures to monitor for suspicious calls and unusual activity, and if detected, it generates an alert and notifies the device and family members.

[0683] Step 10:

[0684] Based on past conversation history, the server uses a content suggestion mechanism to select content suitable for the user and sends the suggestion to the terminal.

[0685] Step 11:

[0686] The device displays or plays suggested content to the user and provides options.

[0687] (Example 1)

[0688] 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".

[0689] An effective support system is needed that simultaneously facilitates communication, improves health management, and enhances security in the daily lives of users, including the elderly. Existing technologies often provide these elements individually, lacking integrated services, which compromises user convenience.

[0690] 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.

[0691] In this invention, the server includes a recognition device, a language analysis device, a synthesis device, a measurement device, a protection device, and a suggestion device. This enables natural interaction with the user, monitoring of health status, ensuring safety, and suggestion of personalized content.

[0692] A "recognition device" is a device that has the function of converting voice data into text data, and converts voice input from a user into digital text information.

[0693] A "language analysis device" is a device that analyzes text data and generates natural-sounding responses while referring to past dialogue history.

[0694] A "synthesizer" is a device that converts the generated response into audio data and provides it to the user as audio output.

[0695] A "measuring device" is a device that continuously collects a user's lifestyle data and uses that data to monitor their health status and lifestyle rhythms.

[0696] A "protection device" is a device that protects user safety by detecting suspicious communications or user abnormalities and issuing warnings.

[0697] A "suggestion device" is a device that selects and suggests content that will interest the user based on their past history and preferences.

[0698] This invention is an integrated AI agent system designed to support the lives of users, such as the elderly. This system is optimized for natural interaction with users and offers numerous conveniences. Specifically, it is implemented using a combination of the following hardware and software.

[0699] First, the terminal receives voice input and converts the voice data into text data using a speech recognition device. A recognition system employing natural language processing technology is used for speech recognition. For example, a common speech recognition API can be used as the recognition engine.

[0700] Next, the text data received by the server is analyzed by a language analysis device. This process utilizes a generative AI model to perform contextual analysis based on past dialogue history and generate a response. The latest generative AI model is used as the natural language processing model here.

[0701] The generated response is sent to a synthesis device on the terminal and converted into speech. A speech synthesis engine is used for speech synthesis, enabling natural-sounding speech output in real time.

[0702] Furthermore, the device collects user lifestyle data through its built-in measuring device and transmits it to a server. This data includes steps taken and heart rate, and is used to analyze the user's health status and lifestyle rhythm.

[0703] The server monitors for suspicious activity and anomalies via a protection device and issues a warning if detected. It also uses a suggestion device to recommend content based on the user's history and preferences. For example, it might suggest, "You've recently become interested in classical music. Why not listen to Beethoven today?"

[0704] A concrete example of a prompt message is: "The user is looking for a hobby they can do at home. Based on the information that it is raining today, please suggest something."

[0705] Thus, the system of the present invention is an embodiment that provides users with improved daily life and ensured safety, thereby aiming to improve the quality of life for the user.

[0706] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0707] Step 1:

[0708] The user speaks to the AI ​​agent and inputs voice data. The device captures this voice with its microphone and passes it to a speech recognition device. The speech recognition device analyzes the input analog voice data and converts it into digital text data. During this process, speech processing is performed to accommodate the intonation and speed of speech. The converted text data is then generated as output.

[0709] Step 2:

[0710] The terminal sends the acquired text data to the server. The server inputs the text data into a language analysis device and retrieves past dialogue data from a database to understand the context. Based on this data, a generative AI model infers the user's intent and generates an appropriate response. Specifically, text generation is performed to implement question answering and recommendation functions, and a finished response sentence is output.

[0711] Step 3:

[0712] The server sends the response text to the terminal. The terminal inputs this text response into a speech synthesizer and converts it into speech data. The speech synthesizer operates functions to adjust the tone and pacing to produce a natural and easy-to-understand voice. The output is speech data intended for the user to hear.

[0713] Step 4:

[0714] The device plays the generated audio data through its speaker, providing the user with a continuation of the conversation. This allows the user to naturally receive responses and suggestions to their questions. This step is performed in real time, enhancing the user experience.

[0715] Step 5:

[0716] The device continuously collects the user's lifestyle patterns (steps, heart rate, etc.) through a measuring device. This data is periodically sent to the server as input. The server analyzes this data and monitors the user's health status. It assesses the health status and, if necessary, outputs advice for lifestyle improvements.

[0717] Step 6:

[0718] The server uses protective devices to monitor security. If suspicious communication is detected, it immediately generates a warning message and notifies registered contacts. This process includes detecting unauthorized access and reviewing login history.

[0719] Step 7:

[0720] The suggestion device selects and suggests individual content based on the user's past history and preferences. The server uses a generation AI model to generate suggestion content in the form of prompts and outputs content tailored to the user. The suggested content is then provided to the user as music, movies, or books.

[0721] (Application Example 1)

[0722] 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".

[0723] There is a need for systems that support elderly people in living independent and safe daily lives. However, conventional technologies lack the ability to provide appropriate advice and content tailored to the individual needs of the elderly, and also lack sufficient safety features to respond quickly in emergencies. As a result, it is difficult for the elderly to live a secure and fulfilling life.

[0724] 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.

[0725] In this invention, the server includes a conversion means for receiving voice input from a user and converting it into text data; a processing means for analyzing the text data and generating a response by referring to past dialogue history; and a support means for generating suggestions based on environmental information and past health data to support the user's daily activities. This enables daily life support and safety assurance suitable for the elderly, and further enables the provision of advice tailored to individual needs.

[0726] "Conversion means" refers to a device or process that has the function of receiving voice input and converting it into text data.

[0727] "Processing means" refers to a device or process that has the function of analyzing character data and generating an appropriate response by referring to past dialogue history.

[0728] "Output means" refers to a device or process that has the function of outputting the generated response as audio and providing it to the user.

[0729] "Collection means" refers to a device or process that has the function of continuously collecting user lifestyle data and monitoring their health status and lifestyle rhythms.

[0730] "Safety measures" refer to devices or processes that have the function of detecting suspicious communications or user abnormalities and issuing warnings.

[0731] "Support means" refers to a device or process that has the function of generating appropriate suggestions based on environmental information and past health data in order to support the user's daily activities.

[0732] The system for implementing the present invention constructs an AI agent for the purpose of supporting the daily lives of the elderly. Its main components include conversion means, processing means, output means, collection means, safety means, and support means.

[0733] First, the terminal receives voice input from the user and converts it into text data using a conversion mechanism. A speech recognition API is used as the conversion mechanism. The server receives this text data and analyzes it using a processing mechanism. In this process, a natural language processing library is used to refer to past dialogue history and generate an appropriate response.

[0734] The generated response is converted into audio data by an output device, and the terminal provides this to the user in audio format. This is achieved using a speech synthesis library.

[0735] Furthermore, the device continuously collects user lifestyle data using collection methods and transmits it to a server. This data collection utilizes the smartphone's built-in sensors, and data analysis is performed using Pandas and NumPy. The analysis results are used to understand the user's health status and lifestyle.

[0736] The safety measures monitor data in real time to detect abnormal communications and activity, and alert relevant parties when an anomaly is detected. This ensures user safety.

[0737] The support system provides users with optimal daily activity suggestions based on environmental information and past health data to facilitate their daily activities. For example, if a user asks, "What should I do today?", the support system, based on weather information and past activity data, might suggest, "The weather is nice today, so how about taking a walk in the park?"

[0738] An example of a prompt from a generative AI model would be the text, "To support the user's daily activities, we will create exercise suggestions based on weather forecasts and past health data."

[0739] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0740] Step 1:

[0741] The device receives voice input from the user via the microphone. The received voice data is passed to a speech recognition API and converted into text data. This process inputs the user's verbal questions as parseable text.

[0742] Step 2:

[0743] The server passes the text data obtained from the speech recognition API to the processing unit, where it is analyzed by a natural language processing engine. Here, the data is compared with past dialogue history to generate a contextually appropriate response. The output of this step is text data indicating an appropriate response to the user.

[0744] Step 3:

[0745] The text data generated by the server is converted into speech data using a speech synthesis engine and passed to the terminal. This allows the terminal to respond to the user in natural-sounding speech through its speech output device.

[0746] Step 4:

[0747] The device continuously collects user lifestyle data using built-in sensors. The acquired data is sent to a server and analyzed using Pandas and NumPy. This analysis provides information to understand the user's health status and lifestyle.

[0748] Step 5:

[0749] The server uses security measures to monitor the collected data in real time and detect any anomalies. If suspicious activity is detected, it automatically issues a warning to the relevant parties. This process is set up to ensure user peace of mind.

[0750] Step 6:

[0751] The server utilizes support tools to generate personalized suggestions to assist the user's daily activities. It takes environmental information and past health data into consideration to suggest suitable activities and schedules. This step utilizes a generative AI model, and the prompt message for it is "To assist the user's daily activities, we will create exercise suggestions based on the weather forecast and past health data."

[0752] Step 7:

[0753] The device either communicates the generated suggestions to the user via voice or displays them on its screen. If communicating via voice, the speech synthesis engine is used again. This output allows the user to understand the suggested activities and choose the appropriate action to take.

[0754] 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.

[0755] The present invention provides comprehensive support for the lives of the elderly by having an AI agent that includes emotion recognition in interaction with the user. This system consists of speech recognition means, natural language processing means, speech synthesis means, sensor means, security means, advice generation means, content suggestion means, and emotion engine.

[0756] When a user speaks to the AI ​​agent, the device receives the voice input, converts it into text data using speech recognition, and sends it to the server. The server then uses natural language processing to analyze the text data and understand the user's utterance. The emotion engine also functions here, recognizing emotions from the user's tone of voice and word choice. For example, if the user says, "I'm a little tired today," the emotion engine detects fatigue or weariness.

[0757] The server adjusts the tone of the conversation based on this emotional information and generates an appropriate response for the user. For example, for a user who is feeling tired, it creates a gentle response such as, "Please get plenty of rest today." The generated response is sent to the terminal and provided to the user as speech through a speech synthesis system.

[0758] Furthermore, the sensor system continuously monitors the user's lifestyle data to understand their health status and daily rhythm. The server analyzes this data and generates health management advice based on the user's emotional and physical state. For example, if the sensor data indicates a lack of exercise and the emotion engine determines that the user is feeling down, it will generate advice such as, "Taking a short walk today might cheer you up."

[0759] Furthermore, the emotion engine interacts with content suggestion methods, proposing content best suited to the user's emotions. For example, if the user is feeling stressed, it will provide relaxing music or videos.

[0760] Thus, the present invention provides a system that aims to improve users' communication and quality of life through a variety of functions, including emotion recognition.

[0761] The following describes the processing flow.

[0762] Step 1:

[0763] The user asks the AI ​​agent a question using their voice. The device receives the voice through its microphone and records it as audio data.

[0764] Step 2:

[0765] The terminal inputs the received audio data into a speech recognition device and converts it into text data. This text data is then sent to the server.

[0766] Step 3:

[0767] The server uses natural language processing to analyze text data and understand the context of the speech. Simultaneously, an emotion engine operates to recognize the user's emotions based on their tone of voice and word choices.

[0768] Step 4:

[0769] The server combines the results of natural language processing with analysis from the emotion engine to generate an appropriate response. For example, if the user's emotions indicate sadness or fatigue, the server will create a response that includes empathy.

[0770] Step 5:

[0771] The generated response is sent from the server to the terminal and converted into speech data by a speech synthesis system.

[0772] Step 6:

[0773] The device plays audio data through its speaker and provides responses to the user. This enables a natural and user-friendly conversation.

[0774] Step 7:

[0775] The sensor device periodically collects user activity and environmental data and transmits this data to a server.

[0776] Step 8:

[0777] The server analyzes data from sensor devices to assess health status and daily lifestyle patterns. Based on this assessment, it generates health management advice as needed.

[0778] Step 9:

[0779] The server utilizes a content suggestion method that selects and proposes content that matches the user's emotional state, based on sentiment analysis obtained by the emotion engine.

[0780] Step 10:

[0781] The device helps improve the user's quality of life by presenting suggested content to the user and allowing them to select and play it.

[0782] (Example 2)

[0783] 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".

[0784] There is a growing societal demand for improved health management and safety in the lives of the elderly. In particular, maintaining a regular daily routine, detecting suspicious phone calls, and providing personalized responses tailored to their emotions are key challenges. Furthermore, understanding the user's emotional state and providing appropriate communication and content suggestions is also essential.

[0785] 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.

[0786] In this invention, the server includes speech recognition means for acquiring voice information and converting it into text information, natural language processing means for analyzing text information and identifying emotions, and sensor means for detecting living conditions and evaluating health status. This enables personalized responses and content suggestions based on the user's emotions and health status.

[0787] "Speech recognition means" refers to a technology that receives speech information input by a user and converts it into text information.

[0788] "Natural language processing means" refers to technologies that analyze converted text information to understand the user's intentions and emotions.

[0789] "Speech synthesis means" refers to a technology that converts responses generated on a server into speech data and provides it to the user as speech.

[0790] "Sensing means" refers to technology that collects information to monitor a user's living situation and health condition.

[0791] "Security management measures" refer to technologies for detecting suspicious communications and abnormal user behavior and generating warnings.

[0792] "Advice generation means" refers to a technology that creates and provides advice for maintaining the user's health and improving their lifestyle based on information acquired by sensor means.

[0793] "Content suggestion methods" refer to technologies that utilize past conversation records to suggest personalized information and entertainment to users.

[0794] The system of the present invention is designed to support the lives of the elderly and includes an AI agent that performs emotion recognition. When a user speaks to the AI ​​agent by voice, the terminal acquires voice data and converts it into text data using speech recognition means. This text data is sent to a server that uses natural language processing means. The server analyzes the text data using natural language processing techniques to understand the user's intentions and the content of their speech. This process also includes an emotion engine that identifies emotions from the tone and word choice of speech.

[0795] As a concrete example of emotion recognition, if a user says, "I'm a little tired today," the emotion engine detects the level of fatigue from the statement, and the server generates a gentle response based on that result. This response is sent back to the terminal and played back to the user as speech using a speech synthesis system. For example, a possible response might be, "Please get plenty of rest today."

[0796] This system includes sensors that monitor lifestyle data, continuously collecting data to understand the user's daily rhythm and health status. The server analyzes this data and employs a scheme to generate health management advice. For example, if the sensor data indicates a lack of exercise, it will generate advice such as, "Taking a short walk today might help you feel refreshed."

[0797] Content suggestions are also provided; the emotion engine analyzes the user's emotional state and suggests the most suitable music, videos, and other content based on the results. For example, if the user is feeling stressed, it will recommend music with a relaxing effect.

[0798] A concrete example of a prompt message might be: "Generate a system response for when the user says, 'I'm a little tired today.' Also, provide any relevant health advice."

[0799] Thus, the present invention aims to improve the quality of life for the elderly by integrating various technologies.

[0800] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0801] Step 1:

[0802] The device receives voice input from the user via a microphone. This voice data is converted into text data by a speech recognition system. Specifically, when the user says, "I'm a little tired today," the voice is converted into digital format and obtained as a string of characters. This text data is then sent to the server.

[0803] Step 2:

[0804] The server receives text data sent from the terminal. Using natural language processing, it analyzes the text data to understand the user's utterance. This analysis involves word recognition and contextual understanding to clarify what the user is trying to say. In addition, an emotion engine detects emotions based on the tone and word choice of the text. The input is text data, and the output is the analysis results and emotion information.

[0805] Step 3:

[0806] The server generates responses that reflect emotional information based on natural language processing. This response generation process creates responses in a tone appropriate to the user's emotional state. For example, if the user is expressing fatigue, the server will construct a reply such as, "Please take it easy and rest today." The input is the parsed data and emotional information, and the output is the response text.

[0807] Step 4:

[0808] The generated response text is sent to the terminal, which uses speech synthesis to convert this text into audio data. The converted audio is delivered to the user through the speaker. Specifically, the response text "Please rest well today" is played as audio. The input is the response text, and the output is the played audio.

[0809] Step 5:

[0810] Furthermore, the sensor continuously collects data on the user's lifestyle. The server analyzes this data to assess their health status and daily rhythm. If the sensor data indicates a lack of exercise, the server generates advice such as, "Taking a short walk today might help you feel refreshed." The input is the sensor data, and the output is the advice text.

[0811] Step 6:

[0812] The content suggestion system uses the user's emotional information to suggest relaxing music and videos. If the user's emotions indicate stress, content that promotes relaxation will be selected. The input is emotional information, and the output is a list of suggested content.

[0813] (Application Example 2)

[0814] 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".

[0815] Modern elderly people often experience loneliness in their daily lives, which can hinder their ability to manage their health and maintain a regular lifestyle. Furthermore, they often lack sufficient psychological support due to the difficulty in fully understanding and caring for their emotions. This, in turn, leads to a decline in their quality of life.

[0816] 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.

[0817] In this invention, the server includes speech recognition means for receiving voice input and converting it into text data, natural language processing means for generating and providing responses through natural language processing, and emotion engine means for recognizing the user's emotions and adjusting the responses. This makes it possible to provide comprehensive emotional support to the elderly and improve their quality of life.

[0818] "Voice recognition means" refers to technology that receives voice input from a user and converts it into text data.

[0819] "Natural language processing means" refers to technologies that analyze text data and generate appropriate responses based on past dialogue history.

[0820] "Speech synthesis means" refers to a technology that provides the generated response as speech output.

[0821] "Sensing means" refers to devices and technologies used to collect information about a user's lifestyle and monitor their health status and daily rhythm.

[0822] "Security measures" are technologies used to detect suspicious communications or user anomalies and issue warnings.

[0823] An "emotion engine" is a technology that analyzes the tone of voice and linguistic expressions to recognize the user's emotions and adjusts the tone of the dialogue accordingly.

[0824] A "content suggestion method" is a technology that suggests the most suitable content based on the user's emotions.

[0825] An "advice generation means" is a technology that generates and provides users with advice for health management and lifestyle improvement based on data collected by sensor means.

[0826] This system consists of an AI agent designed to comprehensively support the user's life. It utilizes the speech recognition technology built into the device to receive voice input, leveraging the Google Speech-to-Text API. The voice is converted into text data, which is then sent to the server. The server employs a natural language processing model using the TensorFlow library to analyze the user's intent and emotions. During this analysis, the server also performs sentiment analysis using VADER, and the sentiment engine uses the results to adjust the tone of the response. The response sent to the user is generated using speech synthesis technology via the Google Text-to-Speech API and provided as voice from the device.

[0827] Furthermore, this system collects sensor data from wearable devices to monitor health status and lifestyle rhythms. This data is stored on a server and analyzed periodically. If necessary, the server generates advice for health management and lifestyle improvement based on this data. This advice generation is performed by a generative AI model, sent to the application, and then provided in voice.

[0828] Furthermore, as a content suggestion method, the system uses the Spotify API and YouTube Data API to suggest appropriate content based on the user's emotions. This feature allows users to easily access music and videos that match their emotional state.

[0829] For example, if a user types "I'm not feeling well today" into their device, the system performs text conversion using the Google Speech-to-Text API, analyzes intent and sentiment using TensorFlow, and then performs sentiment analysis with VADER. As a result, encouraging words such as "Please take it easy and rest today" are provided as voice via the Google Text-to-Speech API. Furthermore, relaxing music is suggested via the Spotify API.

[0830] Examples of prompts for a generative AI model:

[0831] "Read the user's emotions from their statements and provide an appropriate response. For example, in response to 'I'm a little tired,' you might want to say, 'Maybe you should take it easy and rest today.'"

[0832] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0833] Step 1:

[0834] The device receives voice input from the user. It sends the voice signal to the Google Speech-to-Text API, where it is converted into text data. This converted text data is then sent to the server.

[0835] Step 2:

[0836] The server uses TensorFlow to analyze the received text data and performs natural language processing. Specifically, it analyzes the intent behind the user's utterances and extracts elements that contain emotions. This process yields the user's current emotions as text.

[0837] Step 3:

[0838] The server uses VADER to perform emotion analysis based on the analysis results. The analysis outputs the user's emotional state (e.g., fatigue, excitement, relief) as numerical data.

[0839] Step 4:

[0840] The server uses the results of sentiment analysis to adjust the tone of its response. It uses a prompt sentence generated by a generative AI model, for example, to generate "words of encouragement for a slightly tired user." This response sentence is obtained as text data to be ultimately provided as audio.

[0841] Step 5:

[0842] The server converts the generated response text into speech via the Google Text-to-Speech API. The converted audio data is sent to the device. The device then plays this audio data for the user to listen to.

[0843] Step 6:

[0844] The server collects sensor data from wearable devices to monitor the user's health and lifestyle. It analyzes the collected data and generates appropriate advice if any abnormalities are detected.

[0845] Step 7:

[0846] The server uses the Spotify API or YouTube Data API to suggest music and videos that are appropriate for the user, based on their emotional state. Because this content suggestion takes the user's emotions into consideration, it contributes to relaxation and a change of pace.

[0847] 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.

[0848] 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.

[0849] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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."

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] The following is further disclosed regarding the embodiments described above.

[0869] (Claim 1)

[0870] A speech recognition means that receives voice input from a user and converts it into text data,

[0871] A natural language processing means that analyzes the aforementioned character data and generates a response by referring to past dialogue history,

[0872] A speech synthesis means that provides the generated response as an audio output,

[0873] A sensor system that collects user lifestyle data and monitors health status and daily rhythms,

[0874] Security measures that detect suspicious phone calls and user anomalies and issue warnings,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, further comprising an advice generation means that generates and provides to the user advice for health management and lifestyle improvement based on data collected by the aforementioned sensor means.

[0878] (Claim 3)

[0879] The system according to claim 1, comprising a content suggestion means that stores the content of a user's dialogue analyzed by a natural language processing means in a database and suggests individual content using past dialogue data.

[0880] "Example 1"

[0881] (Claim 1)

[0882] A recognition device that receives voice input from a user and converts it into text data,

[0883] A language analysis device that analyzes the aforementioned text data and generates a response by referring to past dialogue history,

[0884] A synthesis device that provides the generated response as an audio output,

[0885] A measuring device that collects user lifestyle data and monitors health status and daily rhythms,

[0886] A protective device that detects suspicious communications and user anomalies and issues warnings,

[0887] A suggestion device that selects and proposes content of interest based on the user's past history and preferences,

[0888] A system that includes this.

[0889] (Claim 2)

[0890] The system according to claim 1, further comprising an advice generation device that generates and provides to the user advice for health management and lifestyle improvement based on data collected by the aforementioned measuring device.

[0891] (Claim 3)

[0892] The system according to claim 1, comprising a guidance device that stores the content of a user's dialogue analyzed by a language analysis device in a storage medium and suggests individual content using past dialogue data.

[0893] "Application Example 1"

[0894] (Claim 1)

[0895] A conversion means that receives voice input from a user and converts it into text data,

[0896] Processing means for analyzing the aforementioned character data and generating a response by referring to past dialogue history,

[0897] An output means that provides the generated response as an audio output,

[0898] A means of collecting user lifestyle data and monitoring their health status and daily routines,

[0899] Security measures that detect suspicious communications and user anomalies and issue warnings,

[0900] A support system that generates suggestions based on environmental information and past health data to assist users in their daily activities,

[0901] A system that includes this.

[0902] (Claim 2)

[0903] The system according to claim 1, further comprising a generation means for generating and providing to the user advice for health management and lifestyle improvement based on the data collected by the collection means.

[0904] (Claim 3)

[0905] The system according to claim 1, comprising a means for storing the user's dialogue content analyzed by a processing means in a recording medium, and a means for suggesting individual information using past dialogue data.

[0906] "Example 2 of combining an emotion engine"

[0907] (Claim 1)

[0908] A speech recognition means that acquires voice information from a user and converts it into text information,

[0909] A natural language processing means that analyzes the aforementioned textual information and identifies emotions,

[0910] A speech synthesis means that constructs a response based on the user's emotional information and transmits it as voice output,

[0911] A sensor means that detects the user's living situation and evaluates their health status and lifestyle patterns,

[0912] A security management system that detects suspicious communications and abnormal user behavior and generates warnings,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, further comprising advice generation means for creating and communicating advice for maintaining health and improving lifestyle based on information acquired by the aforementioned sensor means.

[0916] (Claim 3)

[0917] The system according to claim 1, comprising a data management device that stores user dialogue records analyzed by natural language processing means, and a content suggestion means that suggests individual information using past dialogue records.

[0918] "Application example 2 when combining with an emotional engine"

[0919] (Claim 1)

[0920] A speech recognition means that receives voice input from a user and converts it into text data,

[0921] A natural language processing means that analyzes the aforementioned character data and generates a response by referring to past dialogue history,

[0922] A speech synthesis means that provides the generated response as an audio output,

[0923] A sensor system that collects user lifestyle information and monitors health status and daily rhythm,

[0924] Security measures that detect suspicious communications and user anomalies and issue warnings,

[0925] An emotion engine means that recognizes emotions and adjusts the tone of response,

[0926] A content suggestion method that proposes the most suitable content based on the user's emotions,

[0927] A system that includes this.

[0928] (Claim 2)

[0929] The system according to claim 1, further comprising an advice generation means that generates and provides to the user advice for health management and lifestyle improvement based on data collected by the aforementioned sensor means.

[0930] (Claim 3)

[0931] The system according to claim 1, comprising a content suggestion means that stores the content of a user's dialogue analyzed by a natural language processing means in a database and suggests individual content using past dialogue data. [Explanation of symbols]

[0932] 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. A conversion means that receives voice input from a user and converts it into text data, Processing means for analyzing the aforementioned character data and generating a response by referring to past dialogue history, An output means that provides the generated response as an audio output, A means of collecting user lifestyle data and monitoring their health status and daily routines, Security measures that detect suspicious communications and user anomalies and issue warnings, A support system that generates suggestions based on environmental information and past health data to assist users in their daily activities, A system that includes this.

2. The system according to claim 1, further comprising a generation means for generating and providing to the user advice for health management and lifestyle improvement based on the data collected by the collection means.

3. The system according to claim 1, comprising a suggestion means that stores the user's dialogue content analyzed by a processing means in a recording medium and suggests individual information using past dialogue data.

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