System

Abstract

A system is provided.SOLUTION: A system comprising: means for converting voice input from a user into text data; means for transmitting the converted text data to a server; means for processing the text data received by the server and retrieving and generating corresponding advice or information; means for reconverting the generated advice or information from text to voice and replying to the user; and means for accumulating the user's child care information and generating an individually customized child care guide.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Today's parenting generation is extremely busy, making it difficult for them to find time to obtain information about child-rearing or to find people to seek appropriate advice. Furthermore, the worries and anxieties parents face about child-rearing are highly individualized, and general parenting books and consultation services often do not provide sufficient support. It is particularly difficult to obtain appropriate advice immediately, especially at night or in emergencies. Furthermore, there is a lack of systems for centrally managing child-rearing data and providing individually tailored advice tailored to the child's development. The objective of this invention is to provide a system that solves these problems and supports parents in raising their children with peace of mind. [Means for solving the problem]

[0005] To solve this problem, the present invention provides a system that includes: a means for converting a user's voice input into text data; a means for transmitting the converted text data to a server; a means for the server to process the received text data, search for and generate corresponding advice or information; a means for converting the generated advice or information back into speech and sending a response to the user; and a means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide. The system also includes a means for receiving the user's concerns and complaints via voice input and providing appropriate counseling or advice related to the concerns and complaints; and a means for anonymizing and collecting the user's input data and selling the data to product development companies to further improve the accuracy of the child-rearing support information. In this way, the present invention can provide even busy parents with instant, individually optimized child-rearing support.

[0006] "User" refers to the parent or guardian who uses the child-rearing support AI system.

[0007] "Voice input" refers to the process by which user speech is captured by the system.

[0008] "Text data" refers to data that has been analyzed and converted into text information from voice input.

[0009] "Server" refers to a computer system that analyzes voice input, accesses databases, and processes data.

[0010] "Advice or Information" refers to parenting-related advice or knowledge provided by the server in response to a user's question or request.

[0011] "Text-to-speech" refers to the process for converting text data into audio data.

[0012] "Parenting Information" refers to data relating to parenting that a User enters or records into the System.

[0013] A "childcare guide" refers to a document that compiles individually optimized advice and instructions based on accumulated childcare information.

[0014] "Counseling" refers to support that involves listening to the user's concerns and feelings and providing appropriate advice.

[0015] "Data anonymization" refers to the process of handling data in a way that removes any personally identifiable information.

[0016] "Data sales" refers to the act of receiving compensation by providing collected data to a third party.

[0017] "Product development companies" refer to companies that use data from child-rearing support systems to develop new products and services.

[0018] A "system with processes" refers to a state in which a system has the functionality to execute a series of procedures or operations.

[0019] By specifically defining each term in this way, the scope of the claims is clarified. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The present invention relates to a child-rearing support system that supports users' various child-rearing needs 24 hours a day, 365 days a year. This system provides appropriate advice and information by conducting voice dialogue with the user through a smart speaker or application and linking with a server. Specific embodiments are described below.

[0042] composition

[0043] The system mainly consists of the following components:

[0044] 1. User (Parent or Guardian)

[0045] 2. Device (smart speaker or device with application installed)

[0046] 3. Server

[0047] Program processing

[0048] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[0049] 2. The device records the voice input and converts it into text using speech recognition technology. This is the speech-to-text process.

[0050] 3. The device sends the converted text data to the server. Communication is usually via an HTTP request over the Internet.

[0051] 4. The server receives the text data and searches the database for appropriate advice or information. This is the database query process.

[0052] 5. The server generates advice and information based on the search results to answer the user's question. The generated text is organized as an answer.

[0053] 6. The server sends the generated answer text back to the device. This is done by sending an HTTP response.

[0054] 7. The device receives the response text and converts it back into speech using speech synthesis technology. This is the text-to-speech conversion process.

[0055] 8. The device will output a response to the user as a voice output. For example, "Possible causes of nighttime crying include loneliness or hunger. Try responding by cuddling your baby or giving him milk."

[0056] Specific examples

[0057] Case 1: Instant answers to questions

[0058] Scenario: A user asks a question about parenting.

[0059] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0060] Device: Converts speech to text and sends it to the server.

[0061] Server: Searches the database for corresponding countermeasure information and generates a response.

[0062] Terminal: Converts the answer into speech and conveys it to the user.

[0063] User: "To prevent diaper rash, it's important to change diapers frequently and keep the skin clean."

[0064] Case 2: Generating specialized parenting books

[0065] Scenario: A user records daily childcare information.

[0066] User: "Today was my first time walking."

[0067] Device: Converts speech to text and sends it to the server.

[0068] Server: Stores and analyzes data.

[0069] Server: Periodically generates a parenting guide based on the accumulated data.

[0070] Device: Notifies the user of updates to the parenting guide via voice.

[0071] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0072] Other Features

[0073] counseling

[0074] User: "I'm feeling stressed today. What should I do?"

[0075] Device: Converts speech to text and sends it to the server.

[0076] Server: Generates appropriate counseling and advice.

[0077] Terminal: Converts advice into voice and conveys it to the user.

[0078] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[0079] Data collection and sales

[0080] Server: Collects and anonymizes daily conversation data.

[0081] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[0082] In this way, the present invention can provide individual and optimal responses to the various childcare support needs of users.

[0083] The processing flow will be explained below.

[0084] Instant answers to your questions

[0085] Step 1:

[0086] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[0087] Step 2:

[0088] The device records the user's voice and converts it into text data using speech recognition technology, a process known as speech-to-text conversion.

[0089] Step 3:

[0090] The device sends the converted text data to the server, which is done using an HTTP request.

[0091] Step 4:

[0092] The server analyzes the received text data and searches the database for appropriate advice, which is a database query process.

[0093] Step 5:

[0094] The server generates advice based on the search results and writes answers in text format.

[0095] Step 6:

[0096] The server sends the generated answer text back to the device, by sending an HTTP response.

[0097] Step 7:

[0098] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[0099] Step 8:

[0100] The user listens to the audio advice played from the terminal.

[0101] Creation of specialized childcare books

[0102] Step 1:

[0103] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[0104] Step 2:

[0105] The device records the user's voice and converts it into text data using voice recognition technology.

[0106] Step 3:

[0107] The terminal transmits the converted text data to the server.

[0108] Step 4:

[0109] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[0110] Step 5:

[0111] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[0112] Step 6:

[0113] The server notifies the terminal of the generated child-rearing guide.

[0114] Step 7:

[0115] The device will notify the user of updates to the parenting guide via voice notification.

[0116] Step 8:

[0117] The user refers to the parenting guide provided and incorporates it into parenting.

[0118] Counselling and problem-solving

[0119] Step 1:

[0120] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[0121] Step 2:

[0122] The device records the user's voice and converts it into text data using voice recognition technology.

[0123] Step 3:

[0124] The terminal transmits the converted text data to the server.

[0125] Step 4:

[0126] The server receives the text data and searches the database for appropriate counseling and advice.

[0127] Step 5:

[0128] The server generates counseling advice based on the search results and creates answers in text format.

[0129] Step 6:

[0130] The server sends the generated answer text back to the terminal.

[0131] Step 7:

[0132] The terminal converts the answer text into speech and responds to the user.

[0133] Step 8:

[0134] The user listens to the audio advice played from the terminal and receives counseling.

[0135] Data collection and sales

[0136] Step 1:

[0137] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[0138] Step 2:

[0139] The server stores the anonymized data in a database.

[0140] Step 3:

[0141] The server periodically exports the data and sells it to product development companies.

[0142] Step 4:

[0143] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[0144] The above is a specific processing flow in the child-rearing support system.

[0145] Example 1

[0146] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] There is a demand for immediate and appropriate support for various questions and concerns about child-rearing. However, current systems only provide limited answers to users' questions and do not offer customized advice. Furthermore, there are issues with systems that do not adequately generate child-rearing guides tailored to each user's individual situation or provide appropriate counseling based on daily child-rearing records.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0149] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching a database for corresponding advice or information to generate it, means for reconverting the generated advice or information from text to voice using a generative AI model and sending a reply to the user, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, thereby enabling the system to respond promptly and appropriately to the diverse child-rearing needs of users.

[0150] "User" refers to a parent or guardian who has questions or concerns about childcare.

[0151] "Voice input" refers to the act of a user providing voice data to a terminal.

[0152] "Text data" refers to character string data converted from voice input using voice recognition technology.

[0153] "Terminal" refers to a device that has the ability to record voice input and convert voice data into text data.

[0154] "Conversion means" refers to software or hardware for converting voice data into text data.

[0155] "Server" refers to a computer system that has the ability to process received text data, search a database for appropriate advice or information, and generate it.

[0156] "Generative AI model" refers to the artificial intelligence model used by the server to generate answers to users' questions.

[0157] "Speech synthesis technology" refers to technology that reconverts generated text data into voice data.

[0158] "Database" refers to an information resource that stores information related to childcare.

[0159] "Parenting Guide" refers to documents and data that provide individually customized advice and information based on a user's parenting information.

[0160] "Counseling" refers to the act of providing psychological support and advice to users regarding their worries and complaints.

[0161] "Anonymization" refers to a data processing method that renders a user's personal information unidentifiable.

[0162] "Product development companies" refer to companies that develop new products and services that meet market needs.

[0163] "Childcare support information" refers to advice and necessary information for questions and concerns about childcare.

[0164] MODE FOR CARRYING OUT THE INVENTION

[0165] The present invention is a system for responding to various childcare needs of users, and is highly convenient for users by providing support 24 hours a day, 365 days a year through voice input and responses. The system mainly consists of the following components: a user, a terminal, and a server.

[0166] Hardware and Software Examples

[0167] 1. User (Parent or Guardian):

[0168] Users input questions and concerns about childcare by voice.

[0169] 2. Device (smart speaker or device with application installed):

[0170] A device that receives voice input using a built-in microphone and speech recognition software, such as Google Speech-to-Text, and can also use Google Text-to-Speech as a speech synthesis technology.

[0171] 3. Server:

[0172] The server receives the text data, searches for appropriate information from a database, and generates answers for the user using SQL database queries and a generative AI model (e.g., OpenAI's GPT-3).

[0173] Example Details

[0174] Voice Input and Conversion Process

[0175] The user asks a question about childcare to the device: "My baby cries at night. What should I do?"

[0176] The device records the user's voice and converts it into text data using Google Speech-to-Text technology.

[0177] The device sends the converted text data to the server via the Internet, specifically via an HTTP request.

[0178] Data Processing and Information Retrieval

[0179] The server analyzes the HTTP request received from the terminal and extracts the text data.

[0180] The server uses a MySQL or PostgreSQL database to look up relevant childcare information.

[0181] After searching the database, a generative AI model (e.g., GPT-3) is used to generate a customized answer for the user.

[0182] Text retranslation and response

[0183] The server returns the generated response text data to the terminal as an HTTP response.

[0184] The text data received by the device is converted into speech using speech synthesis technology such as Google Text-to-Speech.

[0185] The device will then provide the user with a converted voice response: "Possible causes of nighttime crying include loneliness and hunger. Try cuddling your baby and offering them milk."

[0186] Specific use cases

[0187] For immediate answers to questions

[0188] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0189] Device: Converts speech to text and sends it to the server.

[0190] Server: Searches the database and uses a generative AI model to generate the answer, "To prevent diaper rash, it is important to change diapers frequently and keep the skin clean."

[0191] Terminal: Converts the answer into speech and conveys it to the user.

[0192] Prompt Sentence Examples

[0193] "My baby cries at night, what should I do?"

[0194] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0195] This system allows users to receive prompt and appropriate childcare support regardless of time or place.

[0196] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0197] Step 1:

[0198] The user speaks into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" This speech becomes the input.

[0199] Step 2:

[0200] The device uses a built-in microphone to record the user's voice. It then uses speech recognition technology (e.g., Google Speech-to-Text) to convert the recorded voice data into text data. This is the process by which voice input is converted into text data. The output is the converted text data. Specifically, the speech recognition software analyzes the voice waveform and generates the corresponding text.

[0201] Step 3:

[0202] The terminal sends the converted text data to the server. The text data is sent via the Internet using an HTTP request (POST method). The input is the converted text data, and the output is the HTTP request sent to the server.

[0203] Step 4:

[0204] The server receives an HTTP request sent from a terminal. The server extracts and analyzes text data from the HTTP request. The input is the HTTP request, and the output is the analyzed text data. Specifically, the server analyzes the body of the request and obtains the necessary information.

[0205] Step 5:

[0206] The server searches the database based on the parsed text data. The server uses an SQL query to retrieve childcare-related information from the database. In this process, the input is the parsed text data, and the output is information from the database as search results. Specifically, the server generates an SQL query and sends it to the database to retrieve information.

[0207] Step 6:

[0208] Based on the information the server retrieves from the database, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate answer to the user's question. In this process, the input is the database information of the search results, and the output is the generated answer text. The generative AI model generates text data using natural language processing techniques.

[0209] Step 7:

[0210] The server sends the generated answer text to the terminal as an HTTP response. In this process, the input is the generated answer text and the output is the HTTP response.

[0211] Step 8:

[0212] The response text received by the terminal as an HTTP response is converted into voice data using speech synthesis technology (e.g., Google Text-to-Speech). In this process, the input is the received response text, and the output is voice data. Specifically, the speech synthesis software converts the text into an audio file.

[0213] Step 9:

[0214] The terminal uses a device (such as a speaker) to play back the audio data and communicates the answer to the user. In this process, the input is audio data and the output is the played audio. Specifically, the terminal sends the audio data to the speaker and the audio is played back. This audio is then provided to the user.

[0215] (Application example 1)

[0216] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0217] Childcare is a time-consuming and labor-intensive task for parents and guardians, and meal preparation, among other daily tasks, often places an additional burden on them. Therefore, there is a need for a support system that can address the diverse needs of parents and guardians raising children. The present invention aims to provide a system that not only provides advice and information on childcare, but also suggests healthy foods and beverages to reduce the burden of meal preparation.

[0218] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0219] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and retrieving and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's childcare information and generating an individually customized childcare guide, and means for suggesting healthy foods and beverages when the user's question is related to diet, thereby enabling parents and guardians raising children to receive not only the childcare information and advice they need, but also specific suggestions for meal preparation.

[0220] "Voice input" is a means by which a user verbally asks questions or gives instructions and conveys them to the system.

[0221] "Text data" is voice input converted into text information, and the system uses this data for further information processing.

[0222] A "server" is a computer system that receives text data and generates appropriate advice and information.

[0223] "Speech-to-text" is the process of recognizing a user's voice input and converting it into written information.

[0224] "Advice or Information" refers to advice or knowledge provided in response to a user's parenting questions.

[0225] "Text-to-speech reconversion" is the process of converting the generated textual information back into speech and providing it audibly to the user.

[0226] "Childcare information" refers to records and data relating to the growth and development of a user's baby or child.

[0227] A "customized parenting guide" is a parenting instruction manual created to meet the needs of a particular user based on individual parenting information.

[0228] The "means for suggesting healthy food and drink options" is a means for presenting health-conscious food and drink options when the user's question is related to diet.

[0229] This invention relates to a child-rearing support system that provides 24-hour support to parents and guardians raising children. This system is primarily composed of a user (parent or guardian), a device (such as a smartphone or smart speaker), and a server. The entire system works in cooperation with each device and the server to provide appropriate advice and information to the user.

[0230] Program implementation and processing explanation

[0231] The system program is implemented using the following hardware and software. The speech_recognition library is used to receive voice input from the user as a signal and convert it into text data. This allows the device to accurately identify the user's voice input and convert it into text format. The converted text data is sent to the server using the requests library. After receiving the text data, the server is responsible for searching for and generating appropriate childcare information.

[0232] Server Processing

[0233] The server processes the received text data and queries a database. It generates appropriate advice and information and sends it back to the device. This process is typically achieved using a database management system (DBMS) and a natural language processing model (e.g., GPT-3). The generated text data is then sent back to the device using the requests library.

[0234] Terminal handling

[0235] The device receives the returned text data and converts it back into audio using the gTTS (Google Text-to-Speech) library, allowing the user to receive advice and information in audio format. If a question is related to diet, the server also generates healthy food and drink recommendations and presents them to the user via the device.

[0236] Specific examples

[0237] 1. Scenario 1: User asks a parenting question

[0238] User: "My baby cries at night, what should I do?"

[0239] Device: Converts voice input into text and sends it to the server.

[0240] Server: Searches and generates appropriate advice from a database.

[0241] Terminal: Converts advice into voice and responds to the user.

[0242] 2. Scenario 2: Asking a question about food

[0243] User: "What should we have for dinner tonight?"

[0244] Device: Converts voice input into text and sends it to the server.

[0245] Server: Generates advice suggesting healthy food and drink offerings.

[0246] Device: "Recommended delivery services offer healthy food and drinks."

[0247] Prompt Sentence Examples

[0248] "Parents are asking, 'What should we have for dinner tonight?' Generate answers that include healthy eating suggestions along with parenting advice."

[0249] This system allows parents and guardians to receive appropriate childcare advice 24 hours a day, 365 days a year, and also helps ease the burden of childcare by suggesting healthy options for dietary questions.

[0250] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0251] Step 1:

[0252] Users can voice-input questions or concerns about childcare via devices such as smartphones or smart speakers. For example, a question might be, "My baby cries at night. What should I do?"

[0253] Step 2:

[0254] The device records voice input and converts it to text data using speech recognition technology. Specifically, it uses the speech_recognition library to convert voice to text information. The input is voice data, and the output is the corresponding text data.

[0255] Step 3:

[0256] The terminal sends the converted text data to the server. Using the requests library, it sends an HTTP request over the Internet. The input is text data, and the output is an HTTP request.

[0257] Step 4:

[0258] The server receives the text data. The input received here is the HTTP request, which contains the text data. The server analyzes the received text data and extracts the necessary information.

[0259] Step 5:

[0260] The server uses a natural language processing model (e.g., GPT-3) to generate advice or information based on the text data. The input is the analyzed text data, and the output is the generated advice or information text data.

[0261] Step 6:

[0262] The server sends the generated advice and information back to the terminal, again using the requests library to send text data as an HTTP response. The input is the generated text data, and the output is the HTTP response.

[0263] Step 7:

[0264] The terminal receives the returned text data. The input is the HTTP response, and the text data is extracted from it.

[0265] Step 8:

[0266] The text data received by the terminal is converted back into speech using speech synthesis technology (for example, the gTTS library). The input is text data and the output is speech data.

[0267] Step 9:

[0268] The terminal plays back the audio data and provides advice and information to the user by voice. Specifically, it executes a playback command to play back the audio data. The input is the audio data, and the output is the played audio.

[0269] Through this series of steps, users can receive real-time parenting advice and information in audio format, as well as meal suggestions if the question is related to diet.

[0270] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0271] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[0272] composition

[0273] The system mainly consists of the following components:

[0274] 1. User (Parent or Guardian)

[0275] 2. Device (smart speaker or device with application installed)

[0276] 3. Server

[0277] 4. Emotion Engine

[0278] Program processing

[0279] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[0280] 2. The device records the user's voice and converts it into text using voice recognition technology. This is the voice-to-text process.

[0281] 3. The device sends the converted text data to the server using an HTTP request.

[0282] 4. The server receives the text data and searches the database for appropriate advice. This is a database query process.

[0283] 5. The server generates advice based on the search results and creates an answer text.

[0284] 6. The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[0285] 7. The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[0286] 8. The server sends the final customized advice to the device via an HTTP response.

[0287] 9. The device converts the answer text into speech and responds to the user. This is the text-to-speech conversion process.

[0288] 10. The user listens to the audio advice played from the device.

[0289] Specific examples

[0290] Case 1: Instant answers based on user questions

[0291] Scenario: A user asks a question about parenting.

[0292] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0293] Device: Converts speech to text and sends it to the server.

[0294] Server: Searches the database for corresponding countermeasure information and generates a response.

[0295] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[0296] Terminal: Converts the answer into speech and conveys it to the user.

[0297] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[0298] Case 2: Generating specialized parenting books

[0299] Scenario: A user logs daily childcare information.

[0300] User: "Today was my first time walking."

[0301] Device: Converts speech to text and sends it to the server.

[0302] Server: Stores and analyzes text data.

[0303] Emotion engine: Analyzes user emotion data and uses it for analysis.

[0304] Server: Generates an individually optimized parenting guide and notifies the device.

[0305] Device: Notify users of updates to the parenting guide via voice notification.

[0306] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0307] Other Features

[0308] counseling

[0309] User: "I'm stressed out today. What should I do?"

[0310] Device: Converts speech to text and sends it to the server.

[0311] Server: Searches for counseling information from a database and generates answers.

[0312] Emotion Engine: Analyzes the user's stress level from their voice and suggests ways to relax.

[0313] Terminal: Converts advice into voice and conveys it to the user.

[0314] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[0315] Data collection and sales

[0316] Server: Collects and anonymizes daily conversation data.

[0317] Emotion engine: Emotional data is collected and anonymized.

[0318] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[0319] In this way, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[0320] The processing flow will be explained below.

[0321] Embodiments of the invention combining emotion engines

[0322] Instant answers to your questions

[0323] Step 1:

[0324] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[0325] Step 2:

[0326] The device records the user's voice and converts it into text data using voice recognition technology. This is a voice-to-text conversion process.

[0327] Step 3:

[0328] The device sends the converted text data to the server, which is done using an HTTP request.

[0329] Step 4:

[0330] The server receives the text data and searches the database for appropriate advice, which is a database query process.

[0331] Step 5:

[0332] The server generates advice based on the search results and creates answer text.

[0333] Step 6:

[0334] The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[0335] Step 7:

[0336] The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[0337] Step 8:

[0338] The server sends the final customized advice to the device, which is done by sending an HTTP response.

[0339] Step 9:

[0340] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[0341] Step 10:

[0342] The user listens to the audio advice played from the terminal.

[0343] Creation of specialized childcare books

[0344] Step 1:

[0345] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[0346] Step 2:

[0347] The device records the user's voice and converts it into text data using voice recognition technology.

[0348] Step 3:

[0349] The terminal transmits the converted text data to the server.

[0350] Step 4:

[0351] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[0352] Step 5:

[0353] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[0354] Step 6:

[0355] The emotion engine generates parenting guides based on the user's parenting information, taking into account their emotional state. For example, if the user is happy, it will include many positive words.

[0356] Step 7:

[0357] The server notifies the terminal of the generated child-rearing guide.

[0358] Step 8:

[0359] The device will notify the user of updates to the parenting guide via voice notification.

[0360] Step 9:

[0361] The user refers to the parenting guide provided and incorporates it into parenting.

[0362] Counselling and problem-solving

[0363] Step 1:

[0364] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[0365] Step 2:

[0366] The device records the user's voice and converts it into text data using voice recognition technology.

[0367] Step 3:

[0368] The terminal transmits the converted text data to the server.

[0369] Step 4:

[0370] The server receives the text data and searches the database for appropriate counseling and advice.

[0371] Step 5:

[0372] The server generates counseling advice based on the search results and creates an answer text.

[0373] Step 6:

[0374] The server sends the generated answer text to the emotion engine, which analyzes the user's emotional state and customizes the advice accordingly.

[0375] Step 7:

[0376] The emotion engine generates customized advice text that takes into account factors such as stress level.

[0377] Step 8:

[0378] The server sends the final advice to the terminal.

[0379] Step 9:

[0380] The device converts the advice into voice and conveys it to the user.

[0381] Step 10:

[0382] The user listens to the audio advice played from the terminal and receives counseling.

[0383] Data collection and sales

[0384] Step 1:

[0385] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[0386] Step 2:

[0387] The emotion engine also collects and anonymizes user emotion data, making it possible to obtain comprehensive data.

[0388] Step 3:

[0389] The server stores the anonymized data in a database.

[0390] Step 4:

[0391] The server periodically exports the data and sells it to product development companies.

[0392] Step 5:

[0393] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[0394] Through these steps, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[0395] Example 2

[0396] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0397] In modern society, childcare support needs to be provided quickly and accurately, 24 hours a day, 365 days a year. However, conventional systems only provide general advice without considering the user's psychological state, making it difficult to address individual needs. In addition, there is a lack of means to provide advice tailored to the user's emotional state, making it difficult to provide stress relief or appropriate counseling.

[0398] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the communication device, means for processing the text data received by the communication device and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and returning it to the user, means for extracting emotional data from the user's voice and customizing advice based on the emotional data, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide. This makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[0399] "Voice input" refers to a digital device receiving spoken words from a user as voice data.

[0400] "Text data" refers to data converted from voice input into a string of characters.

[0401] "Communication device" refers to a device that receives text data and interacts with a server to process it.

[0402] "Server" refers to a computer system capable of processing received data and generating and transmitting advice or information.

[0403] "Advice" refers to answers or recommendations provided to a user's questions or requests.

[0404] "Information" refers to knowledge and data provided in response to a user's request.

[0405] "Speech recognition" refers to the process of converting voice data into text data.

[0406] "Speech synthesis" refers to the process of converting text data into speech data.

[0407] "Emotion data" refers to data that represents an emotional state extracted from a user's voice.

[0408] "Customization" refers to tailoring advice and information to a user's specific situation and emotions.

[0409] "Storage" refers to storing data collected from users and making it available at a later time.

[0410] "Parenting Guide" refers to a document that compiles parenting advice and information provided to users.

[0411] "Anonymization" refers to the removal of personally identifiable information from collected data.

[0412] "Product development companies" refer to companies that use collected data to develop new products and services.

[0413] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[0414] Components

[0415] The system mainly consists of the following components:

[0416] 1. User (Parent or Guardian)

[0417] 2. Device (smart speaker or device with application installed)

[0418] 3. Server

[0419] 4. Emotion Engine

[0420] System Details

[0421] Voice to text conversion

[0422] Users speak into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" The device then records the user's voice and converts it into text data using voice recognition technologies such as Google Cloud Speech-to-Text and Amazon Transcribe.

[0423] Sending text data

[0424] The terminal sends the converted text data to the server using an HTTP request, which causes the text data to arrive at the server.

[0425] Database Queries and Advice Generation

[0426] The server searches a database for appropriate advice based on the received text data. Possible database management systems (DBMS) used are MySQL and PostgreSQL. The server executes a database query to extract the appropriate countermeasure. For example, in response to the question, "My baby cries at night. What should I do?", the server generates information about "the causes of night crying and what to do about it."

[0427] Sentiment Analysis and Customization

[0428] The server sends the generated advice text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes the advice based on that data. For example, if the user is feeling stressed, the advice will include relaxation tips.

[0429] Customized advice notifications

[0430] The server then sends the final, customized advice to the device, again via an HTTP response. The device then converts the advice into speech using Google Cloud Text-to-Speech or Amazon Polly, and delivers it to the user.

[0431] Specific examples

[0432] Case 1: Instant answers based on user questions

[0433] Scenario: A user asks a question about parenting.

[0434] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0435] Device: Converts speech to text and sends it to the server.

[0436] Server: Searches the database for corresponding countermeasure information and generates a response.

[0437] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[0438] Terminal: Converts the answer into speech and conveys it to the user.

[0439] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[0440] Case 2: Generating specialized parenting books

[0441] Scenario: A user logs daily childcare information.

[0442] User: "Today was my first time walking."

[0443] Device: Converts speech to text and sends it to the server.

[0444] Server: Stores and analyzes text data.

[0445] Emotion engine: Analyzes user emotion data and uses it for analysis.

[0446] Server: Generates an individually optimized parenting guide and notifies the device.

[0447] Device: Notify users of updates to the parenting guide via voice notification.

[0448] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0449] Hardware and software used

[0450] Speech recognition software: Google Cloud Speech-to-Text, Amazon Transcribe

[0451] Database management systems: MySQL, PostgreSQL

[0452] Sentiment analysis software: IBM Watson Tone Analyzer, Affectiva

[0453] Speech synthesis software: Google Cloud Text-to-Speech, Amazon Polly

[0454] Prompt Sentence Examples

[0455] "My baby cries at night, what should I do?"

[0456] "Today was the first time I walked."

[0457] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0458] This system makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

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

[0460] Step 1:

[0461] The user inputs questions or concerns about childcare by voice. For example, a question like, "My baby cries at night. What should I do?" The input voice is sent directly to the device.

[0462] Step 2:

[0463] The device records the user's voice and converts it into text data using speech recognition technology. The voice input is converted into text data using Google Cloud Speech-to-Text or Amazon Transcribe. The input is the user's voice data, and the output is text data. This process completes the step of converting voice into text information.

[0464] Step 3:

[0465] The terminal sends the converted text data to the server. The input is the converted text data, and the output is transmission to the server via an HTTP request. This process includes an operation of passing the text data to the server using a communication protocol.

[0466] Step 4:

[0467] The server receives the text data and executes a database query to find the appropriate advice. The input is the text data sent from the device, and the output is the searched advice data. Specifically, it uses an SQL query to search a database (such as MySQL or PostgreSQL) for parenting advice.

[0468] Step 5:

[0469] The server generates advice based on the search results and creates answer text. The input is advice data retrieved from the database, and the output is the generated answer text. Specifically, it creates appropriate advice sentences to provide to the user based on the search results.

[0470] Step 6:

[0471] The server sends the generated answer text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes advice based on that data. The input is the answer text and the user's emotion data, and the output is customized advice text. Emotion data is extracted using emotion analysis tools such as IBM Watson Tone Analyzer and Affectiva.

[0472] Step 7:

[0473] The emotion engine generates customized advice text based on the user's emotional state. The input is the emotion analysis result and the answer text, and the output is advice optimized for the user. Specific operations include adding relaxation techniques to advice for users who are feeling stressed.

[0474] Step 8:

[0475] The server sends the final customized advice to the terminal. The input is the customized advice text, and the output is an HTTP response to the terminal. This process includes passing the generated text to the terminal using a communication protocol.

[0476] Step 9:

[0477] The device converts the answer text into speech and responds to the user. The input is customized advice text, and the output is audio data. The text data is converted into audio data using Google Cloud Text-to-Speech or Amazon Polly, and the device responds to the user via audio.

[0478] Step 10:

[0479] The user listens to the audio advice played from the device. The input is the audio advice played from the device, and the output is the user's recognition and understanding. This step provides the user with the appropriate information to decide on their next action.

[0480] (Application example 2)

[0481] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0482] Parents raising children are prone to stress and fatigue, and often find it difficult to choose the right meal. In these circumstances, there is a demand for food delivery services that parents can easily access. However, conventional food delivery services are unable to provide individually optimized menus based on the user's emotional state, and are unable to fully increase user satisfaction. There is also a demand for meal suggestions that take into account the nutritional balance unique to parenting.

[0483] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, and means for analyzing the user's emotional state through emotion analysis and recommending an optimal menu based on the user's emotional state. This enables parents raising children to easily select an optimal food menu depending on their emotional state and child-rearing situation.

[0484] "User" refers to an individual or entity that uses the system.

[0485] "Audio input" is the process by which the system receives audio data recorded through a microphone.

[0486] "Text data" refers to data that has been converted from voice input into text information.

[0487] A "server" is a computer system that receives and processes requests from client devices over the Internet or a local network.

[0488] "Emotion analysis" is the process of determining a user's emotional state from their voice and text data.

[0489] "Childcare Information" refers to data related to childcare that a user provides to the system.

[0490] A "customized child-rearing guide" is advice and information that is optimized for each individual user based on accumulated child-rearing information.

[0491] A "food delivery service" is a service that delivers meals according to orders from users.

[0492] "Menu recommendation" is the process of suggesting the most suitable meal menu based on the user's emotional state and needs.

[0493] The present invention is a system that supports users in raising their children by proposing an optimal food menu based on the emotional state of the parent and providing a food delivery service. The system aims to reduce the burden on parents raising children by analyzing the user's voice input, understanding their emotional state, and then recommending an appropriate meal menu.

[0494] System configuration

[0495] The system includes the following components:

[0496] 1. User: The parent or guardian who uses the system.

[0497] 2. Terminal: A device, such as a smartphone or tablet, that receives voice input and sends data to a server.

[0498] 3. Server: A system that receives text data from users, performs sentiment analysis, and generates appropriate advice and information.

[0499] 4. Emotion engine: Software that analyzes the user's emotional state from their voice and text data.

[0500] Program processing explanation

[0501] Voice input and conversion

[0502] The user speaks to the device to request food delivery related to childcare. For example, "I'm tired today, so I'd like something easy to eat and nutritious." The device records this speech and converts it into text data using the speech_recognition library.

[0503] Sending and Receiving Data

[0504] The device sends the converted text data to the server, which receives it via an HTTP request. The received text data is then used for sentiment analysis.

[0505] Sentiment Analysis and Advice Generation

[0506] The server uses an emotion engine to analyze the user's emotional state based on the received text data. For emotion analysis, it uses a provisional package called text_to_emotion. Based on the results of this analysis, it determines the user's fatigue and stress levels and suggests the optimal meal menu. For menu recommendations, it uses a provisional package called menu_recommendation.

[0507] Voice advice provided

[0508] The server generates an optimal meal menu and sends the text data back to the device. The device converts this data into audio and plays it back to the user as advice. For example, the device might say, "The recommended nutritious menu is the fried shrimp set meal."

[0509] Hardware and software used

[0510] Hardware: Smartphones and tablets (microphones for voice recognition, communication modules for data transmission and reception)

[0511] software:

[0512] speech_recognition library: speech-to-text conversion

[0513] HTTP request: Sending and receiving text data

[0514] Provisional package text_to_emotion: Emotion analysis

[0515] Provisional package menu_recommendation: Menu recommendation

[0516] Specific examples

[0517] User: "I'm tired and want something to cheer me up."

[0518] Device: Converts speech to text and sends it to the server.

[0519] Server: Analyzes text data using an emotion engine to detect the user's level of fatigue.

[0520] Server: Use a menu recommendation package to select the best menu.

[0521] Device: A voice message will say, "The recommended nutritious menu item is the fried shrimp set meal."

[0522] Prompt statement

[0523] "Design an app that analyzes user emotions and provides the most appropriate food menu. The system should be able to suggest appropriate menu items based on the user's comments and the results of the emotion analysis."

[0524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0525] Step 1: The user voice-inputs their childcare-related food delivery request into the device. For example, they might say, "I'm tired today, so I'd like something easy to eat and nutritious." The voice data they input is then recorded.

[0526] Step 2: The device uses speech recognition technology to convert the recorded voice data into text data. Specifically, the speech-to-text conversion is performed using the speech_recognition library. The input is voice data, and the output is text data.

[0527] Step 3: The terminal uses an HTTP request to send the converted text data to the server. The input is the text data, and the output is an HTTP request to the server.

[0528] Step 4: The server receives the HTTP request and retrieves the text data. The received text data is prepared for analysis. The input is the text data in the HTTP request, and the output is the text data for analysis.

[0529] Step 5: The server uses the emotion engine to analyze the user's emotional state from the text data. Specifically, it uses a hypothetical package called text_to_emotion to perform emotion analysis. The input is text data, and the output is data indicating the user's emotional state.

[0530] Step 6: The server starts the process to generate an optimal food menu based on the emotional state. A hypothetical package, menu_recommendation, is used to recommend an appropriate menu based on the emotional data. The input is the data indicating the emotional state, and the output is the recommended menu.

[0531] Step 7: The server converts the generated menu into text data and sends an HTTP response to be sent to the terminal again. The input is the text data of the menu, and the output is the HTTP response.

[0532] Step 8: The terminal receives the HTTP response and obtains the text data of the menu that was sent. The input is the text data in the HTTP response, and the output is the text data to be displayed.

[0533] Step 9: The terminal converts the acquired menu text data into audio data and plays it back to the user. Specifically, the audio data is generated using text-to-speech conversion technology. The input is the text data to be displayed, and the output is audio data.

[0534] Step 10: The user listens to the audio advice played from the terminal and confirms the suggested meal menu. The input is audio data, and the output is information about the suggested menu.

[0535] This series of processes allows users to easily obtain optimal food menus that can reduce the burden of raising children.

[0536] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0537] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0538] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0539] [Second embodiment]

[0540] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0541] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0542] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0543] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0544] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0545] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0546] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0547] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0548] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0549] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0550] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0551] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0552] The present invention relates to a child-rearing support system that supports users' various child-rearing needs 24 hours a day, 365 days a year. This system provides appropriate advice and information by conducting voice dialogue with the user through a smart speaker or application and linking with a server. Specific embodiments are described below.

[0553] composition

[0554] The system mainly consists of the following components:

[0555] 1. User (Parent or Guardian)

[0556] 2. Device (smart speaker or device with application installed)

[0557] 3. Server

[0558] Program processing

[0559] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[0560] 2. The device records the voice input and converts it into text using speech recognition technology. This is the speech-to-text process.

[0561] 3. The device sends the converted text data to the server. Communication is usually via an HTTP request over the Internet.

[0562] 4. The server receives the text data and searches the database for appropriate advice or information. This is the database query process.

[0563] 5. The server generates advice and information based on the search results to answer the user's question. The generated text is organized as an answer.

[0564] 6. The server sends the generated answer text back to the device. This is done by sending an HTTP response.

[0565] 7. The device receives the response text and converts it back into speech using speech synthesis technology. This is the text-to-speech conversion process.

[0566] 8. The device will output a response to the user as a voice output. For example, "Possible causes of nighttime crying include loneliness or hunger. Try responding by cuddling your baby or giving him milk."

[0567] Specific examples

[0568] Case 1: Instant answers to questions

[0569] Scenario: A user asks a question about parenting.

[0570] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0571] Device: Converts speech to text and sends it to the server.

[0572] Server: Searches the database for corresponding countermeasure information and generates a response.

[0573] Terminal: Converts the answer into speech and conveys it to the user.

[0574] User: "To prevent diaper rash, it's important to change diapers frequently and keep the skin clean."

[0575] Case 2: Generating specialized parenting books

[0576] Scenario: A user records daily childcare information.

[0577] User: "Today was my first time walking."

[0578] Device: Converts speech to text and sends it to the server.

[0579] Server: Stores and analyzes data.

[0580] Server: Periodically generates a parenting guide based on the accumulated data.

[0581] Device: Notifies the user of updates to the parenting guide via voice.

[0582] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0583] Other Features

[0584] counseling

[0585] User: "I'm feeling stressed today. What should I do?"

[0586] Device: Converts speech to text and sends it to the server.

[0587] Server: Generates appropriate counseling and advice.

[0588] Terminal: Converts advice into voice and conveys it to the user.

[0589] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[0590] Data collection and sales

[0591] Server: Collects and anonymizes daily conversation data.

[0592] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[0593] In this way, the present invention can provide individual and optimal responses to the various childcare support needs of users.

[0594] The processing flow will be explained below.

[0595] Instant answers to your questions

[0596] Step 1:

[0597] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[0598] Step 2:

[0599] The device records the user's voice and converts it into text data using speech recognition technology, a process known as speech-to-text conversion.

[0600] Step 3:

[0601] The device sends the converted text data to the server, which is done using an HTTP request.

[0602] Step 4:

[0603] The server analyzes the received text data and searches the database for appropriate advice, which is a database query process.

[0604] Step 5:

[0605] The server generates advice based on the search results and writes answers in text format.

[0606] Step 6:

[0607] The server sends the generated answer text back to the device, by sending an HTTP response.

[0608] Step 7:

[0609] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[0610] Step 8:

[0611] The user listens to the audio advice played from the terminal.

[0612] Creation of specialized childcare books

[0613] Step 1:

[0614] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[0615] Step 2:

[0616] The device records the user's voice and converts it into text data using voice recognition technology.

[0617] Step 3:

[0618] The terminal transmits the converted text data to the server.

[0619] Step 4:

[0620] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[0621] Step 5:

[0622] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[0623] Step 6:

[0624] The server notifies the terminal of the generated child-rearing guide.

[0625] Step 7:

[0626] The device will notify the user of updates to the parenting guide via voice notification.

[0627] Step 8:

[0628] The user refers to the parenting guide provided and incorporates it into parenting.

[0629] Counselling and problem-solving

[0630] Step 1:

[0631] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[0632] Step 2:

[0633] The device records the user's voice and converts it into text data using voice recognition technology.

[0634] Step 3:

[0635] The terminal transmits the converted text data to the server.

[0636] Step 4:

[0637] The server receives the text data and searches the database for appropriate counseling and advice.

[0638] Step 5:

[0639] The server generates counseling advice based on the search results and creates answers in text format.

[0640] Step 6:

[0641] The server sends the generated answer text back to the terminal.

[0642] Step 7:

[0643] The terminal converts the answer text into speech and responds to the user.

[0644] Step 8:

[0645] The user listens to the audio advice played from the terminal and receives counseling.

[0646] Data collection and sales

[0647] Step 1:

[0648] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[0649] Step 2:

[0650] The server stores the anonymized data in a database.

[0651] Step 3:

[0652] The server periodically exports the data and sells it to product development companies.

[0653] Step 4:

[0654] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[0655] The above is a specific processing flow in the child-rearing support system.

[0656] Example 1

[0657] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0658] There is a demand for immediate and appropriate support for various questions and concerns about child-rearing. However, current systems only provide limited answers to users' questions and do not offer customized advice. Furthermore, there are issues with systems that do not adequately generate child-rearing guides tailored to each user's individual situation or provide appropriate counseling based on daily child-rearing records.

[0659] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0660] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching a database for corresponding advice or information to generate it, means for reconverting the generated advice or information from text to voice using a generative AI model and sending a reply to the user, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, thereby enabling the system to respond promptly and appropriately to the diverse child-rearing needs of users.

[0661] "User" refers to a parent or guardian who has questions or concerns about childcare.

[0662] "Voice input" refers to the act of a user providing voice data to a terminal.

[0663] "Text data" refers to character string data converted from voice input using voice recognition technology.

[0664] "Terminal" refers to a device that has the ability to record voice input and convert voice data into text data.

[0665] "Conversion means" refers to software or hardware for converting voice data into text data.

[0666] "Server" refers to a computer system that has the ability to process received text data, search a database for appropriate advice or information, and generate it.

[0667] "Generative AI model" refers to the artificial intelligence model used by the server to generate answers to users' questions.

[0668] "Speech synthesis technology" refers to technology that reconverts generated text data into voice data.

[0669] "Database" refers to an information resource that stores information related to childcare.

[0670] "Parenting Guide" refers to documents and data that provide individually customized advice and information based on a user's parenting information.

[0671] "Counseling" refers to the act of providing psychological support and advice to users regarding their worries and complaints.

[0672] "Anonymization" refers to a data processing method that renders a user's personal information unidentifiable.

[0673] "Product development companies" refer to companies that develop new products and services that meet market needs.

[0674] "Childcare support information" refers to advice and necessary information for questions and concerns about childcare.

[0675] MODE FOR CARRYING OUT THE INVENTION

[0676] The present invention is a system for responding to various childcare needs of users, and is highly convenient for users by providing support 24 hours a day, 365 days a year through voice input and responses. The system mainly consists of the following components: a user, a terminal, and a server.

[0677] Hardware and Software Examples

[0678] 1. User (Parent or Guardian):

[0679] Users input questions and concerns about childcare by voice.

[0680] 2. Device (smart speaker or device with application installed):

[0681] A device that receives voice input using a built-in microphone and speech recognition software, such as Google Speech-to-Text, and can also use Google Text-to-Speech as a speech synthesis technology.

[0682] 3. Server:

[0683] The server receives the text data, searches for appropriate information from a database, and generates answers for the user using SQL database queries and a generative AI model (e.g., OpenAI's GPT-3).

[0684] Example Details

[0685] Voice Input and Conversion Process

[0686] The user asks a question about childcare to the device: "My baby cries at night. What should I do?"

[0687] The device records the user's voice and converts it into text data using Google Speech-to-Text technology.

[0688] The device sends the converted text data to the server via the Internet, specifically via an HTTP request.

[0689] Data Processing and Information Retrieval

[0690] The server analyzes the HTTP request received from the terminal and extracts the text data.

[0691] The server uses a MySQL or PostgreSQL database to look up relevant childcare information.

[0692] After searching the database, a generative AI model (e.g., GPT-3) is used to generate a customized answer for the user.

[0693] Text retranslation and response

[0694] The server returns the generated response text data to the terminal as an HTTP response.

[0695] The text data received by the device is converted into speech using speech synthesis technology such as Google Text-to-Speech.

[0696] The device will then provide the user with a converted voice response: "Possible causes of nighttime crying include loneliness and hunger. Try cuddling your baby and offering them milk."

[0697] Specific use cases

[0698] For immediate answers to questions

[0699] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0700] Device: Converts speech to text and sends it to the server.

[0701] Server: Searches the database and uses a generative AI model to generate the answer, "To prevent diaper rash, it is important to change diapers frequently and keep the skin clean."

[0702] Terminal: Converts the answer into speech and conveys it to the user.

[0703] Prompt Sentence Examples

[0704] "My baby cries at night, what should I do?"

[0705] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0706] This system allows users to receive prompt and appropriate childcare support regardless of time or place.

[0707] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0708] Step 1:

[0709] The user speaks into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" This speech becomes the input.

[0710] Step 2:

[0711] The device uses a built-in microphone to record the user's voice. It then uses speech recognition technology (e.g., Google Speech-to-Text) to convert the recorded voice data into text data. This is the process by which voice input is converted into text data. The output is the converted text data. Specifically, the speech recognition software analyzes the voice waveform and generates the corresponding text.

[0712] Step 3:

[0713] The terminal sends the converted text data to the server. The text data is sent via the Internet using an HTTP request (POST method). The input is the converted text data, and the output is the HTTP request sent to the server.

[0714] Step 4:

[0715] The server receives an HTTP request sent from a terminal. The server extracts and analyzes text data from the HTTP request. The input is the HTTP request, and the output is the analyzed text data. Specifically, the server analyzes the body of the request and obtains the necessary information.

[0716] Step 5:

[0717] The server searches the database based on the parsed text data. The server uses an SQL query to retrieve childcare-related information from the database. In this process, the input is the parsed text data, and the output is information from the database as search results. Specifically, the server generates an SQL query and sends it to the database to retrieve information.

[0718] Step 6:

[0719] Based on the information the server retrieves from the database, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate answer to the user's question. In this process, the input is the database information of the search results, and the output is the generated answer text. The generative AI model generates text data using natural language processing techniques.

[0720] Step 7:

[0721] The server sends the generated answer text to the terminal as an HTTP response. In this process, the input is the generated answer text and the output is the HTTP response.

[0722] Step 8:

[0723] The response text received by the terminal as an HTTP response is converted into voice data using speech synthesis technology (e.g., Google Text-to-Speech). In this process, the input is the received response text, and the output is voice data. Specifically, the speech synthesis software converts the text into an audio file.

[0724] Step 9:

[0725] The terminal uses a device (such as a speaker) to play back the audio data and communicates the answer to the user. In this process, the input is audio data and the output is the played audio. Specifically, the terminal sends the audio data to the speaker and the audio is played back. This audio is then provided to the user.

[0726] (Application example 1)

[0727] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0728] Childcare is a time-consuming and labor-intensive task for parents and guardians, and meal preparation, among other daily tasks, often places an additional burden on them. Therefore, there is a need for a support system that can address the diverse needs of parents and guardians raising children. The present invention aims to provide a system that not only provides advice and information on childcare, but also suggests healthy foods and beverages to reduce the burden of meal preparation.

[0729] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0730] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and retrieving and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's childcare information and generating an individually customized childcare guide, and means for suggesting healthy foods and beverages when the user's question is related to diet, thereby enabling parents and guardians raising children to receive not only the childcare information and advice they need, but also specific suggestions for meal preparation.

[0731] "Voice input" is a means by which a user verbally asks questions or gives instructions and conveys them to the system.

[0732] "Text data" is voice input converted into text information, and the system uses this data for further information processing.

[0733] A "server" is a computer system that receives text data and generates appropriate advice and information.

[0734] "Speech-to-text" is the process of recognizing a user's voice input and converting it into written information.

[0735] "Advice or Information" refers to advice or knowledge provided in response to a user's parenting questions.

[0736] "Text-to-speech reconversion" is the process of converting the generated textual information back into speech and providing it audibly to the user.

[0737] "Childcare information" refers to records and data relating to the growth and development of a user's baby or child.

[0738] A "customized parenting guide" is a parenting instruction manual created to meet the needs of a particular user based on individual parenting information.

[0739] The "means for suggesting healthy food and drink options" is a means for presenting health-conscious food and drink options when the user's question is related to diet.

[0740] This invention relates to a child-rearing support system that provides 24-hour support to parents and guardians raising children. This system is primarily composed of a user (parent or guardian), a device (such as a smartphone or smart speaker), and a server. The entire system works in cooperation with each device and the server to provide appropriate advice and information to the user.

[0741] Program implementation and processing explanation

[0742] The system program is implemented using the following hardware and software. The speech_recognition library is used to receive voice input from the user as a signal and convert it into text data. This allows the device to accurately identify the user's voice input and convert it into text format. The converted text data is sent to the server using the requests library. After receiving the text data, the server is responsible for searching for and generating appropriate childcare information.

[0743] Server Processing

[0744] The server processes the received text data and queries a database. It generates appropriate advice and information and sends it back to the device. This process is typically achieved using a database management system (DBMS) and a natural language processing model (e.g., GPT-3). The generated text data is then sent back to the device using the requests library.

[0745] Terminal handling

[0746] The device receives the returned text data and converts it back into audio using the gTTS (Google Text-to-Speech) library, allowing the user to receive advice and information in audio format. If a question is related to diet, the server also generates healthy food and drink recommendations and presents them to the user via the device.

[0747] Specific examples

[0748] 1. Scenario 1: User asks a parenting question

[0749] User: "My baby cries at night, what should I do?"

[0750] Device: Converts voice input into text and sends it to the server.

[0751] Server: Searches and generates appropriate advice from a database.

[0752] Terminal: Converts advice into voice and responds to the user.

[0753] 2. Scenario 2: Asking a question about food

[0754] User: "What should we have for dinner tonight?"

[0755] Device: Converts voice input into text and sends it to the server.

[0756] Server: Generates advice suggesting healthy food and drink offerings.

[0757] Device: "Recommended delivery services offer healthy food and drinks."

[0758] Prompt Sentence Examples

[0759] "Parents are asking, 'What should we have for dinner tonight?' Generate answers that include healthy eating suggestions along with parenting advice."

[0760] This system allows parents and guardians to receive appropriate childcare advice 24 hours a day, 365 days a year, and also helps ease the burden of childcare by suggesting healthy options for dietary questions.

[0761] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0762] Step 1:

[0763] Users can voice-input questions or concerns about childcare via devices such as smartphones or smart speakers. For example, a question might be, "My baby cries at night. What should I do?"

[0764] Step 2:

[0765] The device records voice input and converts it to text data using speech recognition technology. Specifically, it uses the speech_recognition library to convert voice to text information. The input is voice data, and the output is the corresponding text data.

[0766] Step 3:

[0767] The terminal sends the converted text data to the server. Using the requests library, it sends an HTTP request over the Internet. The input is text data, and the output is an HTTP request.

[0768] Step 4:

[0769] The server receives the text data. The input received here is the HTTP request, which contains the text data. The server analyzes the received text data and extracts the necessary information.

[0770] Step 5:

[0771] The server uses a natural language processing model (e.g., GPT-3) to generate advice or information based on the text data. The input is the analyzed text data, and the output is the generated advice or information text data.

[0772] Step 6:

[0773] The server sends the generated advice and information back to the terminal, again using the requests library to send text data as an HTTP response. The input is the generated text data, and the output is the HTTP response.

[0774] Step 7:

[0775] The terminal receives the returned text data. The input is the HTTP response, and the text data is extracted from it.

[0776] Step 8:

[0777] The text data received by the terminal is converted back into speech using speech synthesis technology (for example, the gTTS library). The input is text data and the output is speech data.

[0778] Step 9:

[0779] The terminal plays back the audio data and provides advice and information to the user by voice. Specifically, it executes a playback command to play back the audio data. The input is the audio data, and the output is the played audio.

[0780] Through this series of steps, users can receive real-time parenting advice and information in audio format, as well as meal suggestions if the question is related to diet.

[0781] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0782] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[0783] composition

[0784] The system mainly consists of the following components:

[0785] 1. User (Parent or Guardian)

[0786] 2. Device (smart speaker or device with application installed)

[0787] 3. Server

[0788] 4. Emotion Engine

[0789] Program processing

[0790] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[0791] 2. The device records the user's voice and converts it into text using voice recognition technology. This is the voice-to-text process.

[0792] 3. The device sends the converted text data to the server using an HTTP request.

[0793] 4. The server receives the text data and searches the database for appropriate advice. This is a database query process.

[0794] 5. The server generates advice based on the search results and creates an answer text.

[0795] 6. The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[0796] 7. The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[0797] 8. The server sends the final customized advice to the device via an HTTP response.

[0798] 9. The device converts the answer text into speech and responds to the user. This is the text-to-speech conversion process.

[0799] 10. The user listens to the audio advice played from the device.

[0800] Specific examples

[0801] Case 1: Instant answers based on user questions

[0802] Scenario: A user asks a question about parenting.

[0803] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0804] Device: Converts speech to text and sends it to the server.

[0805] Server: Searches the database for corresponding countermeasure information and generates a response.

[0806] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[0807] Terminal: Converts the answer into speech and conveys it to the user.

[0808] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[0809] Case 2: Generating specialized parenting books

[0810] Scenario: A user logs daily childcare information.

[0811] User: "Today was my first time walking."

[0812] Device: Converts speech to text and sends it to the server.

[0813] Server: Stores and analyzes text data.

[0814] Emotion engine: Analyzes user emotion data and uses it for analysis.

[0815] Server: Generates an individually optimized parenting guide and notifies the device.

[0816] Device: Notify users of updates to the parenting guide via voice notification.

[0817] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0818] Other Features

[0819] counseling

[0820] User: "I'm stressed out today. What should I do?"

[0821] Device: Converts speech to text and sends it to the server.

[0822] Server: Searches for counseling information from a database and generates answers.

[0823] Emotion Engine: Analyzes the user's stress level from their voice and suggests ways to relax.

[0824] Terminal: Converts advice into voice and conveys it to the user.

[0825] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[0826] Data collection and sales

[0827] Server: Collects and anonymizes daily conversation data.

[0828] Emotion engine: Emotional data is collected and anonymized.

[0829] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[0830] In this way, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[0831] The processing flow will be explained below.

[0832] Embodiments of the invention combining emotion engines

[0833] Instant answers to your questions

[0834] Step 1:

[0835] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[0836] Step 2:

[0837] The device records the user's voice and converts it into text data using voice recognition technology. This is a voice-to-text conversion process.

[0838] Step 3:

[0839] The device sends the converted text data to the server, which is done using an HTTP request.

[0840] Step 4:

[0841] The server receives the text data and searches the database for appropriate advice, which is a database query process.

[0842] Step 5:

[0843] The server generates advice based on the search results and creates answer text.

[0844] Step 6:

[0845] The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[0846] Step 7:

[0847] The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[0848] Step 8:

[0849] The server sends the final customized advice to the device, which is done by sending an HTTP response.

[0850] Step 9:

[0851] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[0852] Step 10:

[0853] The user listens to the audio advice played from the terminal.

[0854] Creation of specialized childcare books

[0855] Step 1:

[0856] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[0857] Step 2:

[0858] The device records the user's voice and converts it into text data using voice recognition technology.

[0859] Step 3:

[0860] The terminal transmits the converted text data to the server.

[0861] Step 4:

[0862] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[0863] Step 5:

[0864] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[0865] Step 6:

[0866] The emotion engine generates parenting guides based on the user's parenting information, taking into account their emotional state. For example, if the user is happy, it will include many positive words.

[0867] Step 7:

[0868] The server notifies the terminal of the generated child-rearing guide.

[0869] Step 8:

[0870] The device will notify the user of updates to the parenting guide via voice notification.

[0871] Step 9:

[0872] The user refers to the parenting guide provided and incorporates it into parenting.

[0873] Counselling and problem-solving

[0874] Step 1:

[0875] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[0876] Step 2:

[0877] The device records the user's voice and converts it into text data using voice recognition technology.

[0878] Step 3:

[0879] The terminal transmits the converted text data to the server.

[0880] Step 4:

[0881] The server receives the text data and searches the database for appropriate counseling and advice.

[0882] Step 5:

[0883] The server generates counseling advice based on the search results and creates an answer text.

[0884] Step 6:

[0885] The server sends the generated answer text to the emotion engine, which analyzes the user's emotional state and customizes the advice accordingly.

[0886] Step 7:

[0887] The emotion engine generates customized advice text that takes into account factors such as stress level.

[0888] Step 8:

[0889] The server sends the final advice to the terminal.

[0890] Step 9:

[0891] The device converts the advice into voice and conveys it to the user.

[0892] Step 10:

[0893] The user listens to the audio advice played from the terminal and receives counseling.

[0894] Data collection and sales

[0895] Step 1:

[0896] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[0897] Step 2:

[0898] The emotion engine also collects and anonymizes user emotion data, making it possible to obtain comprehensive data.

[0899] Step 3:

[0900] The server stores the anonymized data in a database.

[0901] Step 4:

[0902] The server periodically exports the data and sells it to product development companies.

[0903] Step 5:

[0904] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[0905] Through these steps, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[0906] Example 2

[0907] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0908] In modern society, childcare support needs to be provided quickly and accurately, 24 hours a day, 365 days a year. However, conventional systems only provide general advice without considering the user's psychological state, making it difficult to address individual needs. In addition, there is a lack of means to provide advice tailored to the user's emotional state, making it difficult to provide stress relief or appropriate counseling.

[0909] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the communication device, means for processing the text data received by the communication device and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and returning it to the user, means for extracting emotional data from the user's voice and customizing advice based on the emotional data, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide. This makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[0910] "Voice input" refers to a digital device receiving spoken words from a user as voice data.

[0911] "Text data" refers to data converted from voice input into a string of characters.

[0912] "Communication device" refers to a device that receives text data and interacts with a server to process it.

[0913] "Server" refers to a computer system capable of processing received data and generating and transmitting advice or information.

[0914] "Advice" refers to answers or recommendations provided to a user's questions or requests.

[0915] "Information" refers to knowledge and data provided in response to a user's request.

[0916] "Speech recognition" refers to the process of converting voice data into text data.

[0917] "Speech synthesis" refers to the process of converting text data into speech data.

[0918] "Emotion data" refers to data that represents an emotional state extracted from a user's voice.

[0919] "Customization" refers to tailoring advice and information to a user's specific situation and emotions.

[0920] "Storage" refers to storing data collected from users and making it available at a later time.

[0921] "Parenting Guide" refers to a document that compiles parenting advice and information provided to users.

[0922] "Anonymization" refers to the removal of personally identifiable information from collected data.

[0923] "Product development companies" refer to companies that use collected data to develop new products and services.

[0924] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[0925] Components

[0926] The system mainly consists of the following components:

[0927] 1. User (Parent or Guardian)

[0928] 2. Device (smart speaker or device with application installed)

[0929] 3. Server

[0930] 4. Emotion Engine

[0931] System Details

[0932] Voice to text conversion

[0933] Users speak into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" The device then records the user's voice and converts it into text data using voice recognition technologies such as Google Cloud Speech-to-Text and Amazon Transcribe.

[0934] Sending text data

[0935] The terminal sends the converted text data to the server using an HTTP request, which causes the text data to arrive at the server.

[0936] Database Queries and Advice Generation

[0937] The server searches a database for appropriate advice based on the received text data. Possible database management systems (DBMS) used are MySQL and PostgreSQL. The server executes a database query to extract the appropriate countermeasure. For example, in response to the question, "My baby cries at night. What should I do?", the server generates information about "the causes of night crying and what to do about it."

[0938] Sentiment Analysis and Customization

[0939] The server sends the generated advice text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes the advice based on that data. For example, if the user is feeling stressed, the advice will include relaxation tips.

[0940] Customized advice notifications

[0941] The server then sends the final, customized advice to the device, again via an HTTP response. The device then converts the advice into speech using Google Cloud Text-to-Speech or Amazon Polly, and delivers it to the user.

[0942] Specific examples

[0943] Case 1: Instant answers based on user questions

[0944] Scenario: A user asks a question about parenting.

[0945] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0946] Device: Converts speech to text and sends it to the server.

[0947] Server: Searches the database for corresponding countermeasure information and generates a response.

[0948] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[0949] Terminal: Converts the answer into speech and conveys it to the user.

[0950] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[0951] Case 2: Generating specialized parenting books

[0952] Scenario: A user logs daily childcare information.

[0953] User: "Today was my first time walking."

[0954] Device: Converts speech to text and sends it to the server.

[0955] Server: Stores and analyzes text data.

[0956] Emotion engine: Analyzes user emotion data and uses it for analysis.

[0957] Server: Generates an individually optimized parenting guide and notifies the device.

[0958] Device: Notify users of updates to the parenting guide via voice notification.

[0959] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[0960] Hardware and software used

[0961] Speech recognition software: Google Cloud Speech-to-Text, Amazon Transcribe

[0962] Database management systems: MySQL, PostgreSQL

[0963] Sentiment analysis software: IBM Watson Tone Analyzer, Affectiva

[0964] Speech synthesis software: Google Cloud Text-to-Speech, Amazon Polly

[0965] Prompt Sentence Examples

[0966] "My baby cries at night, what should I do?"

[0967] "Today was the first time I walked."

[0968] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[0969] This system makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[0970] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0971] Step 1:

[0972] The user inputs questions or concerns about childcare by voice. For example, a question like, "My baby cries at night. What should I do?" The input voice is sent directly to the device.

[0973] Step 2:

[0974] The device records the user's voice and converts it into text data using speech recognition technology. The voice input is converted into text data using Google Cloud Speech-to-Text or Amazon Transcribe. The input is the user's voice data, and the output is text data. This process completes the step of converting voice into text information.

[0975] Step 3:

[0976] The terminal sends the converted text data to the server. The input is the converted text data, and the output is transmission to the server via an HTTP request. This process includes an operation of passing the text data to the server using a communication protocol.

[0977] Step 4:

[0978] The server receives the text data and executes a database query to find the appropriate advice. The input is the text data sent from the device, and the output is the searched advice data. Specifically, it uses an SQL query to search a database (such as MySQL or PostgreSQL) for parenting advice.

[0979] Step 5:

[0980] The server generates advice based on the search results and creates answer text. The input is advice data retrieved from the database, and the output is the generated answer text. Specifically, it creates appropriate advice sentences to provide to the user based on the search results.

[0981] Step 6:

[0982] The server sends the generated answer text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes advice based on that data. The input is the answer text and the user's emotion data, and the output is customized advice text. Emotion data is extracted using emotion analysis tools such as IBM Watson Tone Analyzer and Affectiva.

[0983] Step 7:

[0984] The emotion engine generates customized advice text based on the user's emotional state. The input is the emotion analysis result and the answer text, and the output is advice optimized for the user. Specific operations include adding relaxation techniques to advice for users who are feeling stressed.

[0985] Step 8:

[0986] The server sends the final customized advice to the terminal. The input is the customized advice text, and the output is an HTTP response to the terminal. This process includes passing the generated text to the terminal using a communication protocol.

[0987] Step 9:

[0988] The device converts the answer text into speech and responds to the user. The input is customized advice text, and the output is audio data. The text data is converted into audio data using Google Cloud Text-to-Speech or Amazon Polly, and the device responds to the user via audio.

[0989] Step 10:

[0990] The user listens to the audio advice played from the device. The input is the audio advice played from the device, and the output is the user's recognition and understanding. This step provides the user with the appropriate information to decide on their next action.

[0991] (Application example 2)

[0992] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0993] Parents raising children are prone to stress and fatigue, and often find it difficult to choose the right meal. In these circumstances, there is a demand for food delivery services that parents can easily access. However, conventional food delivery services are unable to provide individually optimized menus based on the user's emotional state, and are unable to fully increase user satisfaction. There is also a demand for meal suggestions that take into account the nutritional balance unique to parenting.

[0994] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, and means for analyzing the user's emotional state through emotion analysis and recommending an optimal menu based on the user's emotional state. This enables parents raising children to easily select an optimal food menu depending on their emotional state and child-rearing situation.

[0995] "User" refers to an individual or entity that uses the system.

[0996] "Audio input" is the process by which the system receives audio data recorded through a microphone.

[0997] "Text data" refers to data that has been converted from voice input into text information.

[0998] A "server" is a computer system that receives and processes requests from client devices over the Internet or a local network.

[0999] "Emotion analysis" is the process of determining a user's emotional state from their voice and text data.

[1000] "Childcare Information" refers to data related to childcare that a user provides to the system.

[1001] A "customized child-rearing guide" is advice and information that is optimized for each individual user based on accumulated child-rearing information.

[1002] A "food delivery service" is a service that delivers meals according to orders from users.

[1003] "Menu recommendation" is the process of suggesting the most suitable meal menu based on the user's emotional state and needs.

[1004] The present invention is a system that supports users in raising their children by proposing an optimal food menu based on the emotional state of the parent and providing a food delivery service. The system aims to reduce the burden on parents raising children by analyzing the user's voice input, understanding their emotional state, and then recommending an appropriate meal menu.

[1005] System configuration

[1006] The system includes the following components:

[1007] 1. User: The parent or guardian who uses the system.

[1008] 2. Terminal: A device, such as a smartphone or tablet, that receives voice input and sends data to a server.

[1009] 3. Server: A system that receives text data from users, performs sentiment analysis, and generates appropriate advice and information.

[1010] 4. Emotion engine: Software that analyzes the user's emotional state from their voice and text data.

[1011] Program processing explanation

[1012] Voice input and conversion

[1013] The user speaks to the device to request food delivery related to childcare. For example, "I'm tired today, so I'd like something easy to eat and nutritious." The device records this speech and converts it into text data using the speech_recognition library.

[1014] Sending and Receiving Data

[1015] The device sends the converted text data to the server, which receives it via an HTTP request. The received text data is then used for sentiment analysis.

[1016] Sentiment Analysis and Advice Generation

[1017] The server uses an emotion engine to analyze the user's emotional state based on the received text data. For emotion analysis, it uses a provisional package called text_to_emotion. Based on the results of this analysis, it determines the user's fatigue and stress levels and suggests the optimal meal menu. For menu recommendations, it uses a provisional package called menu_recommendation.

[1018] Voice advice provided

[1019] The server generates an optimal meal menu and sends the text data back to the device. The device converts this data into audio and plays it back to the user as advice. For example, the device might say, "The recommended nutritious menu is the fried shrimp set meal."

[1020] Hardware and software used

[1021] Hardware: Smartphones and tablets (microphones for voice recognition, communication modules for data transmission and reception)

[1022] software:

[1023] speech_recognition library: speech-to-text conversion

[1024] HTTP request: Sending and receiving text data

[1025] Provisional package text_to_emotion: Emotion analysis

[1026] Provisional package menu_recommendation: Menu recommendation

[1027] Specific examples

[1028] User: "I'm tired and want something to cheer me up."

[1029] Device: Converts speech to text and sends it to the server.

[1030] Server: Analyzes text data using an emotion engine to detect the user's level of fatigue.

[1031] Server: Use a menu recommendation package to select the best menu.

[1032] Device: A voice message will say, "The recommended nutritious menu item is the fried shrimp set meal."

[1033] Prompt statement

[1034] "Design an app that analyzes user emotions and provides the most appropriate food menu. The system should be able to suggest appropriate menu items based on the user's comments and the results of the emotion analysis."

[1035] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1036] Step 1: The user voice-inputs their childcare-related food delivery request into the device. For example, they might say, "I'm tired today, so I'd like something easy to eat and nutritious." The voice data they input is then recorded.

[1037] Step 2: The device uses speech recognition technology to convert the recorded voice data into text data. Specifically, the speech-to-text conversion is performed using the speech_recognition library. The input is voice data, and the output is text data.

[1038] Step 3: The terminal uses an HTTP request to send the converted text data to the server. The input is the text data, and the output is an HTTP request to the server.

[1039] Step 4: The server receives the HTTP request and retrieves the text data. The received text data is prepared for analysis. The input is the text data in the HTTP request, and the output is the text data for analysis.

[1040] Step 5: The server uses the emotion engine to analyze the user's emotional state from the text data. Specifically, it uses a hypothetical package called text_to_emotion to perform emotion analysis. The input is text data, and the output is data indicating the user's emotional state.

[1041] Step 6: The server starts the process to generate an optimal food menu based on the emotional state. A hypothetical package, menu_recommendation, is used to recommend an appropriate menu based on the emotional data. The input is the data indicating the emotional state, and the output is the recommended menu.

[1042] Step 7: The server converts the generated menu into text data and sends an HTTP response to be sent to the terminal again. The input is the text data of the menu, and the output is the HTTP response.

[1043] Step 8: The terminal receives the HTTP response and obtains the text data of the menu that was sent. The input is the text data in the HTTP response, and the output is the text data to be displayed.

[1044] Step 9: The terminal converts the acquired menu text data into audio data and plays it back to the user. Specifically, the audio data is generated using text-to-speech conversion technology. The input is the text data to be displayed, and the output is audio data.

[1045] Step 10: The user listens to the audio advice played from the terminal and confirms the suggested meal menu. The input is audio data, and the output is information about the suggested menu.

[1046] This series of processes allows users to easily obtain optimal food menus that can reduce the burden of raising children.

[1047] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1048] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1049] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1050] [Third embodiment]

[1051] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1052] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1053] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1054] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1055] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1056] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1057] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1058] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1059] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1060] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1061] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1062] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1063] The present invention relates to a child-rearing support system that supports users' various child-rearing needs 24 hours a day, 365 days a year. This system provides appropriate advice and information by conducting voice dialogue with the user through a smart speaker or application and linking with a server. Specific embodiments are described below.

[1064] composition

[1065] The system mainly consists of the following components:

[1066] 1. User (Parent or Guardian)

[1067] 2. Device (smart speaker or device with application installed)

[1068] 3. Server

[1069] Program processing

[1070] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[1071] 2. The device records the voice input and converts it into text using speech recognition technology. This is the speech-to-text process.

[1072] 3. The device sends the converted text data to the server. Communication is usually via an HTTP request over the Internet.

[1073] 4. The server receives the text data and searches the database for appropriate advice or information. This is the database query process.

[1074] 5. The server generates advice and information based on the search results to answer the user's question. The generated text is organized as an answer.

[1075] 6. The server sends the generated answer text back to the device. This is done by sending an HTTP response.

[1076] 7. The device receives the response text and converts it back into speech using speech synthesis technology. This is the text-to-speech conversion process.

[1077] 8. The device will output a response to the user as a voice output. For example, "Possible causes of nighttime crying include loneliness or hunger. Try responding by cuddling your baby or giving him milk."

[1078] Specific examples

[1079] Case 1: Instant answers to questions

[1080] Scenario: A user asks a question about parenting.

[1081] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1082] Device: Converts speech to text and sends it to the server.

[1083] Server: Searches the database for corresponding countermeasure information and generates a response.

[1084] Terminal: Converts the answer into speech and conveys it to the user.

[1085] User: "To prevent diaper rash, it's important to change diapers frequently and keep the skin clean."

[1086] Case 2: Generating specialized parenting books

[1087] Scenario: A user records daily childcare information.

[1088] User: "Today was my first time walking."

[1089] Device: Converts speech to text and sends it to the server.

[1090] Server: Stores and analyzes data.

[1091] Server: Periodically generates a parenting guide based on the accumulated data.

[1092] Device: Notifies the user of updates to the parenting guide via voice.

[1093] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1094] Other Features

[1095] counseling

[1096] User: "I'm feeling stressed today. What should I do?"

[1097] Device: Converts speech to text and sends it to the server.

[1098] Server: Generates appropriate counseling and advice.

[1099] Terminal: Converts advice into voice and conveys it to the user.

[1100] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[1101] Data collection and sales

[1102] Server: Collects and anonymizes daily conversation data.

[1103] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[1104] In this way, the present invention can provide individual and optimal responses to the various childcare support needs of users.

[1105] The processing flow will be explained below.

[1106] Instant answers to your questions

[1107] Step 1:

[1108] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[1109] Step 2:

[1110] The device records the user's voice and converts it into text data using speech recognition technology, a process known as speech-to-text conversion.

[1111] Step 3:

[1112] The device sends the converted text data to the server, which is done using an HTTP request.

[1113] Step 4:

[1114] The server analyzes the received text data and searches the database for appropriate advice, which is a database query process.

[1115] Step 5:

[1116] The server generates advice based on the search results and writes answers in text format.

[1117] Step 6:

[1118] The server sends the generated answer text back to the device, by sending an HTTP response.

[1119] Step 7:

[1120] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[1121] Step 8:

[1122] The user listens to the audio advice played from the terminal.

[1123] Creation of specialized childcare books

[1124] Step 1:

[1125] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[1126] Step 2:

[1127] The device records the user's voice and converts it into text data using voice recognition technology.

[1128] Step 3:

[1129] The terminal transmits the converted text data to the server.

[1130] Step 4:

[1131] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[1132] Step 5:

[1133] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[1134] Step 6:

[1135] The server notifies the terminal of the generated child-rearing guide.

[1136] Step 7:

[1137] The device will notify the user of updates to the parenting guide via voice notification.

[1138] Step 8:

[1139] The user refers to the parenting guide provided and incorporates it into parenting.

[1140] Counselling and problem-solving

[1141] Step 1:

[1142] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[1143] Step 2:

[1144] The device records the user's voice and converts it into text data using voice recognition technology.

[1145] Step 3:

[1146] The terminal transmits the converted text data to the server.

[1147] Step 4:

[1148] The server receives the text data and searches the database for appropriate counseling and advice.

[1149] Step 5:

[1150] The server generates counseling advice based on the search results and creates answers in text format.

[1151] Step 6:

[1152] The server sends the generated answer text back to the terminal.

[1153] Step 7:

[1154] The terminal converts the answer text into speech and responds to the user.

[1155] Step 8:

[1156] The user listens to the audio advice played from the terminal and receives counseling.

[1157] Data collection and sales

[1158] Step 1:

[1159] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[1160] Step 2:

[1161] The server stores the anonymized data in a database.

[1162] Step 3:

[1163] The server periodically exports the data and sells it to product development companies.

[1164] Step 4:

[1165] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[1166] The above is a specific processing flow in the child-rearing support system.

[1167] Example 1

[1168] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1169] There is a demand for immediate and appropriate support for various questions and concerns about child-rearing. However, current systems only provide limited answers to users' questions and do not offer customized advice. Furthermore, there are issues with systems that do not adequately generate child-rearing guides tailored to each user's individual situation or provide appropriate counseling based on daily child-rearing records.

[1170] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1171] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching a database for corresponding advice or information to generate it, means for reconverting the generated advice or information from text to voice using a generative AI model and sending a reply to the user, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, thereby enabling the system to respond promptly and appropriately to the diverse child-rearing needs of users.

[1172] "User" refers to a parent or guardian who has questions or concerns about childcare.

[1173] "Voice input" refers to the act of a user providing voice data to a terminal.

[1174] "Text data" refers to character string data converted from voice input using voice recognition technology.

[1175] "Terminal" refers to a device that has the ability to record voice input and convert voice data into text data.

[1176] "Conversion means" refers to software or hardware for converting voice data into text data.

[1177] "Server" refers to a computer system that has the ability to process received text data, search a database for appropriate advice or information, and generate it.

[1178] "Generative AI model" refers to the artificial intelligence model used by the server to generate answers to users' questions.

[1179] "Speech synthesis technology" refers to technology that reconverts generated text data into voice data.

[1180] "Database" refers to an information resource that stores information related to childcare.

[1181] "Parenting Guide" refers to documents and data that provide individually customized advice and information based on a user's parenting information.

[1182] "Counseling" refers to the act of providing psychological support and advice to users regarding their worries and complaints.

[1183] "Anonymization" refers to a data processing method that renders a user's personal information unidentifiable.

[1184] "Product development companies" refer to companies that develop new products and services that meet market needs.

[1185] "Childcare support information" refers to advice and necessary information for questions and concerns about childcare.

[1186] MODE FOR CARRYING OUT THE INVENTION

[1187] The present invention is a system for responding to various childcare needs of users, and is highly convenient for users by providing support 24 hours a day, 365 days a year through voice input and responses. The system mainly consists of the following components: a user, a terminal, and a server.

[1188] Hardware and Software Examples

[1189] 1. User (Parent or Guardian):

[1190] Users input questions and concerns about childcare by voice.

[1191] 2. Device (smart speaker or device with application installed):

[1192] A device that receives voice input using a built-in microphone and speech recognition software, such as Google Speech-to-Text, and can also use Google Text-to-Speech as a speech synthesis technology.

[1193] 3. Server:

[1194] The server receives the text data, searches for appropriate information from a database, and generates answers for the user using SQL database queries and a generative AI model (e.g., OpenAI's GPT-3).

[1195] Example Details

[1196] Voice Input and Conversion Process

[1197] The user asks a question about childcare to the device: "My baby cries at night. What should I do?"

[1198] The device records the user's voice and converts it into text data using Google Speech-to-Text technology.

[1199] The device sends the converted text data to the server via the Internet, specifically via an HTTP request.

[1200] Data Processing and Information Retrieval

[1201] The server analyzes the HTTP request received from the terminal and extracts the text data.

[1202] The server uses a MySQL or PostgreSQL database to look up relevant childcare information.

[1203] After searching the database, a generative AI model (e.g., GPT-3) is used to generate a customized answer for the user.

[1204] Text retranslation and response

[1205] The server returns the generated response text data to the terminal as an HTTP response.

[1206] The text data received by the device is converted into speech using speech synthesis technology such as Google Text-to-Speech.

[1207] The device will then provide the user with a converted voice response: "Possible causes of nighttime crying include loneliness and hunger. Try cuddling your baby and offering them milk."

[1208] Specific use cases

[1209] For immediate answers to questions

[1210] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1211] Device: Converts speech to text and sends it to the server.

[1212] Server: Searches the database and uses a generative AI model to generate the answer, "To prevent diaper rash, it is important to change diapers frequently and keep the skin clean."

[1213] Terminal: Converts the answer into speech and conveys it to the user.

[1214] Prompt Sentence Examples

[1215] "My baby cries at night, what should I do?"

[1216] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1217] This system allows users to receive prompt and appropriate childcare support regardless of time or place.

[1218] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1219] Step 1:

[1220] The user speaks into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" This speech becomes the input.

[1221] Step 2:

[1222] The device uses a built-in microphone to record the user's voice. It then uses speech recognition technology (e.g., Google Speech-to-Text) to convert the recorded voice data into text data. This is the process by which voice input is converted into text data. The output is the converted text data. Specifically, the speech recognition software analyzes the voice waveform and generates the corresponding text.

[1223] Step 3:

[1224] The terminal sends the converted text data to the server. The text data is sent via the Internet using an HTTP request (POST method). The input is the converted text data, and the output is the HTTP request sent to the server.

[1225] Step 4:

[1226] The server receives an HTTP request sent from a terminal. The server extracts and analyzes text data from the HTTP request. The input is the HTTP request, and the output is the analyzed text data. Specifically, the server analyzes the body of the request and obtains the necessary information.

[1227] Step 5:

[1228] The server searches the database based on the parsed text data. The server uses an SQL query to retrieve childcare-related information from the database. In this process, the input is the parsed text data, and the output is information from the database as search results. Specifically, the server generates an SQL query and sends it to the database to retrieve information.

[1229] Step 6:

[1230] Based on the information the server retrieves from the database, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate answer to the user's question. In this process, the input is the database information of the search results, and the output is the generated answer text. The generative AI model generates text data using natural language processing techniques.

[1231] Step 7:

[1232] The server sends the generated answer text to the terminal as an HTTP response. In this process, the input is the generated answer text and the output is the HTTP response.

[1233] Step 8:

[1234] The response text received by the terminal as an HTTP response is converted into voice data using speech synthesis technology (e.g., Google Text-to-Speech). In this process, the input is the received response text, and the output is voice data. Specifically, the speech synthesis software converts the text into an audio file.

[1235] Step 9:

[1236] The terminal uses a device (such as a speaker) to play back the audio data and communicates the answer to the user. In this process, the input is audio data and the output is the played audio. Specifically, the terminal sends the audio data to the speaker and the audio is played back. This audio is then provided to the user.

[1237] (Application example 1)

[1238] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1239] Childcare is a time-consuming and labor-intensive task for parents and guardians, and meal preparation, among other daily tasks, often places an additional burden on them. Therefore, there is a need for a support system that can address the diverse needs of parents and guardians raising children. The present invention aims to provide a system that not only provides advice and information on childcare, but also suggests healthy foods and beverages to reduce the burden of meal preparation.

[1240] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1241] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and retrieving and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's childcare information and generating an individually customized childcare guide, and means for suggesting healthy foods and beverages when the user's question is related to diet, thereby enabling parents and guardians raising children to receive not only the childcare information and advice they need, but also specific suggestions for meal preparation.

[1242] "Voice input" is a means by which a user verbally asks questions or gives instructions and conveys them to the system.

[1243] "Text data" is voice input converted into text information, and the system uses this data for further information processing.

[1244] A "server" is a computer system that receives text data and generates appropriate advice and information.

[1245] "Speech-to-text" is the process of recognizing a user's voice input and converting it into written information.

[1246] "Advice or Information" refers to advice or knowledge provided in response to a user's parenting questions.

[1247] "Text-to-speech reconversion" is the process of converting the generated textual information back into speech and providing it audibly to the user.

[1248] "Childcare information" refers to records and data relating to the growth and development of a user's baby or child.

[1249] A "customized parenting guide" is a parenting instruction manual created to meet the needs of a particular user based on individual parenting information.

[1250] The "means for suggesting healthy food and drink options" is a means for presenting health-conscious food and drink options when the user's question is related to diet.

[1251] This invention relates to a child-rearing support system that provides 24-hour support to parents and guardians raising children. This system is primarily composed of a user (parent or guardian), a device (such as a smartphone or smart speaker), and a server. The entire system works in cooperation with each device and the server to provide appropriate advice and information to the user.

[1252] Program implementation and processing explanation

[1253] The system program is implemented using the following hardware and software. The speech_recognition library is used to receive voice input from the user as a signal and convert it into text data. This allows the device to accurately identify the user's voice input and convert it into text format. The converted text data is sent to the server using the requests library. After receiving the text data, the server is responsible for searching for and generating appropriate childcare information.

[1254] Server Processing

[1255] The server processes the received text data and queries a database. It generates appropriate advice and information and sends it back to the device. This process is typically achieved using a database management system (DBMS) and a natural language processing model (e.g., GPT-3). The generated text data is then sent back to the device using the requests library.

[1256] Terminal handling

[1257] The device receives the returned text data and converts it back into audio using the gTTS (Google Text-to-Speech) library, allowing the user to receive advice and information in audio format. If a question is related to diet, the server also generates healthy food and drink recommendations and presents them to the user via the device.

[1258] Specific examples

[1259] 1. Scenario 1: User asks a parenting question

[1260] User: "My baby cries at night, what should I do?"

[1261] Device: Converts voice input into text and sends it to the server.

[1262] Server: Searches and generates appropriate advice from a database.

[1263] Terminal: Converts advice into voice and responds to the user.

[1264] 2. Scenario 2: Asking a question about food

[1265] User: "What should we have for dinner tonight?"

[1266] Device: Converts voice input into text and sends it to the server.

[1267] Server: Generates advice suggesting healthy food and drink offerings.

[1268] Device: "Recommended delivery services offer healthy food and drinks."

[1269] Prompt Sentence Examples

[1270] "Parents are asking, 'What should we have for dinner tonight?' Generate answers that include healthy eating suggestions along with parenting advice."

[1271] This system allows parents and guardians to receive appropriate childcare advice 24 hours a day, 365 days a year, and also helps ease the burden of childcare by suggesting healthy options for dietary questions.

[1272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1273] Step 1:

[1274] Users can voice-input questions or concerns about childcare via devices such as smartphones or smart speakers. For example, a question might be, "My baby cries at night. What should I do?"

[1275] Step 2:

[1276] The device records voice input and converts it to text data using speech recognition technology. Specifically, it uses the speech_recognition library to convert voice to text information. The input is voice data, and the output is the corresponding text data.

[1277] Step 3:

[1278] The terminal sends the converted text data to the server. Using the requests library, it sends an HTTP request over the Internet. The input is text data, and the output is an HTTP request.

[1279] Step 4:

[1280] The server receives the text data. The input received here is the HTTP request, which contains the text data. The server analyzes the received text data and extracts the necessary information.

[1281] Step 5:

[1282] The server uses a natural language processing model (e.g., GPT-3) to generate advice or information based on the text data. The input is the analyzed text data, and the output is the generated advice or information text data.

[1283] Step 6:

[1284] The server sends the generated advice and information back to the terminal, again using the requests library to send text data as an HTTP response. The input is the generated text data, and the output is the HTTP response.

[1285] Step 7:

[1286] The terminal receives the returned text data. The input is the HTTP response, and the text data is extracted from it.

[1287] Step 8:

[1288] The text data received by the terminal is converted back into speech using speech synthesis technology (for example, the gTTS library). The input is text data and the output is speech data.

[1289] Step 9:

[1290] The terminal plays back the audio data and provides advice and information to the user by voice. Specifically, it executes a playback command to play back the audio data. The input is the audio data, and the output is the played audio.

[1291] Through this series of steps, users can receive real-time parenting advice and information in audio format, as well as meal suggestions if the question is related to diet.

[1292] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1293] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[1294] composition

[1295] The system mainly consists of the following components:

[1296] 1. User (Parent or Guardian)

[1297] 2. Device (smart speaker or device with application installed)

[1298] 3. Server

[1299] 4. Emotion Engine

[1300] Program processing

[1301] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[1302] 2. The device records the user's voice and converts it into text using voice recognition technology. This is the voice-to-text process.

[1303] 3. The device sends the converted text data to the server using an HTTP request.

[1304] 4. The server receives the text data and searches the database for appropriate advice. This is a database query process.

[1305] 5. The server generates advice based on the search results and creates an answer text.

[1306] 6. The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[1307] 7. The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[1308] 8. The server sends the final customized advice to the device via an HTTP response.

[1309] 9. The device converts the answer text into speech and responds to the user. This is the text-to-speech conversion process.

[1310] 10. The user listens to the audio advice played from the device.

[1311] Specific examples

[1312] Case 1: Instant answers based on user questions

[1313] Scenario: A user asks a question about parenting.

[1314] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1315] Device: Converts speech to text and sends it to the server.

[1316] Server: Searches the database for corresponding countermeasure information and generates a response.

[1317] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[1318] Terminal: Converts the answer into speech and conveys it to the user.

[1319] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[1320] Case 2: Generating specialized parenting books

[1321] Scenario: A user logs daily childcare information.

[1322] User: "Today was my first time walking."

[1323] Device: Converts speech to text and sends it to the server.

[1324] Server: Stores and analyzes text data.

[1325] Emotion engine: Analyzes user emotion data and uses it for analysis.

[1326] Server: Generates an individually optimized parenting guide and notifies the device.

[1327] Device: Notify users of updates to the parenting guide via voice notification.

[1328] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1329] Other Features

[1330] counseling

[1331] User: "I'm stressed out today. What should I do?"

[1332] Device: Converts speech to text and sends it to the server.

[1333] Server: Searches for counseling information from a database and generates answers.

[1334] Emotion Engine: Analyzes the user's stress level from their voice and suggests ways to relax.

[1335] Terminal: Converts advice into voice and conveys it to the user.

[1336] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[1337] Data collection and sales

[1338] Server: Collects and anonymizes daily conversation data.

[1339] Emotion engine: Emotional data is collected and anonymized.

[1340] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[1341] In this way, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[1342] The processing flow will be explained below.

[1343] Embodiments of the invention combining emotion engines

[1344] Instant answers to your questions

[1345] Step 1:

[1346] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[1347] Step 2:

[1348] The device records the user's voice and converts it into text data using voice recognition technology. This is a voice-to-text conversion process.

[1349] Step 3:

[1350] The device sends the converted text data to the server, which is done using an HTTP request.

[1351] Step 4:

[1352] The server receives the text data and searches the database for appropriate advice, which is a database query process.

[1353] Step 5:

[1354] The server generates advice based on the search results and creates answer text.

[1355] Step 6:

[1356] The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[1357] Step 7:

[1358] The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[1359] Step 8:

[1360] The server sends the final customized advice to the device, which is done by sending an HTTP response.

[1361] Step 9:

[1362] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[1363] Step 10:

[1364] The user listens to the audio advice played from the terminal.

[1365] Creation of specialized childcare books

[1366] Step 1:

[1367] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[1368] Step 2:

[1369] The device records the user's voice and converts it into text data using voice recognition technology.

[1370] Step 3:

[1371] The terminal transmits the converted text data to the server.

[1372] Step 4:

[1373] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[1374] Step 5:

[1375] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[1376] Step 6:

[1377] The emotion engine generates parenting guides based on the user's parenting information, taking into account their emotional state. For example, if the user is happy, it will include many positive words.

[1378] Step 7:

[1379] The server notifies the terminal of the generated child-rearing guide.

[1380] Step 8:

[1381] The device will notify the user of updates to the parenting guide via voice notification.

[1382] Step 9:

[1383] The user refers to the parenting guide provided and incorporates it into parenting.

[1384] Counselling and problem-solving

[1385] Step 1:

[1386] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[1387] Step 2:

[1388] The device records the user's voice and converts it into text data using voice recognition technology.

[1389] Step 3:

[1390] The terminal transmits the converted text data to the server.

[1391] Step 4:

[1392] The server receives the text data and searches the database for appropriate counseling and advice.

[1393] Step 5:

[1394] The server generates counseling advice based on the search results and creates an answer text.

[1395] Step 6:

[1396] The server sends the generated answer text to the emotion engine, which analyzes the user's emotional state and customizes the advice accordingly.

[1397] Step 7:

[1398] The emotion engine generates customized advice text that takes into account factors such as stress level.

[1399] Step 8:

[1400] The server sends the final advice to the terminal.

[1401] Step 9:

[1402] The device converts the advice into voice and conveys it to the user.

[1403] Step 10:

[1404] The user listens to the audio advice played from the terminal and receives counseling.

[1405] Data collection and sales

[1406] Step 1:

[1407] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[1408] Step 2:

[1409] The emotion engine also collects and anonymizes user emotion data, making it possible to obtain comprehensive data.

[1410] Step 3:

[1411] The server stores the anonymized data in a database.

[1412] Step 4:

[1413] The server periodically exports the data and sells it to product development companies.

[1414] Step 5:

[1415] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[1416] Through these steps, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[1417] Example 2

[1418] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1419] In modern society, childcare support needs to be provided quickly and accurately, 24 hours a day, 365 days a year. However, conventional systems only provide general advice without considering the user's psychological state, making it difficult to address individual needs. In addition, there is a lack of means to provide advice tailored to the user's emotional state, making it difficult to provide stress relief or appropriate counseling.

[1420] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the communication device, means for processing the text data received by the communication device and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and returning it to the user, means for extracting emotional data from the user's voice and customizing advice based on the emotional data, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide. This makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[1421] "Voice input" refers to a digital device receiving spoken words from a user as voice data.

[1422] "Text data" refers to data converted from voice input into a string of characters.

[1423] "Communication device" refers to a device that receives text data and interacts with a server to process it.

[1424] "Server" refers to a computer system capable of processing received data and generating and transmitting advice or information.

[1425] "Advice" refers to answers or recommendations provided to a user's questions or requests.

[1426] "Information" refers to knowledge and data provided in response to a user's request.

[1427] "Speech recognition" refers to the process of converting voice data into text data.

[1428] "Speech synthesis" refers to the process of converting text data into speech data.

[1429] "Emotion data" refers to data that represents an emotional state extracted from a user's voice.

[1430] "Customization" refers to tailoring advice and information to a user's specific situation and emotions.

[1431] "Storage" refers to storing data collected from users and making it available at a later time.

[1432] "Parenting Guide" refers to a document that compiles parenting advice and information provided to users.

[1433] "Anonymization" refers to the removal of personally identifiable information from collected data.

[1434] "Product development companies" refer to companies that use collected data to develop new products and services.

[1435] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[1436] Components

[1437] The system mainly consists of the following components:

[1438] 1. User (Parent or Guardian)

[1439] 2. Device (smart speaker or device with application installed)

[1440] 3. Server

[1441] 4. Emotion Engine

[1442] System Details

[1443] Voice to text conversion

[1444] Users speak into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" The device then records the user's voice and converts it into text data using voice recognition technologies such as Google Cloud Speech-to-Text and Amazon Transcribe.

[1445] Sending text data

[1446] The terminal sends the converted text data to the server using an HTTP request, which causes the text data to arrive at the server.

[1447] Database Queries and Advice Generation

[1448] The server searches a database for appropriate advice based on the received text data. Possible database management systems (DBMS) used are MySQL and PostgreSQL. The server executes a database query to extract the appropriate countermeasure. For example, in response to the question, "My baby cries at night. What should I do?", the server generates information about "the causes of night crying and what to do about it."

[1449] Sentiment Analysis and Customization

[1450] The server sends the generated advice text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes the advice based on that data. For example, if the user is feeling stressed, the advice will include relaxation tips.

[1451] Customized advice notifications

[1452] The server then sends the final, customized advice to the device, again via an HTTP response. The device then converts the advice into speech using Google Cloud Text-to-Speech or Amazon Polly, and delivers it to the user.

[1453] Specific examples

[1454] Case 1: Instant answers based on user questions

[1455] Scenario: A user asks a question about parenting.

[1456] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1457] Device: Converts speech to text and sends it to the server.

[1458] Server: Searches the database for corresponding countermeasure information and generates a response.

[1459] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[1460] Terminal: Converts the answer into speech and conveys it to the user.

[1461] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[1462] Case 2: Generating specialized parenting books

[1463] Scenario: A user logs daily childcare information.

[1464] User: "Today was my first time walking."

[1465] Device: Converts speech to text and sends it to the server.

[1466] Server: Stores and analyzes text data.

[1467] Emotion engine: Analyzes user emotion data and uses it for analysis.

[1468] Server: Generates an individually optimized parenting guide and notifies the device.

[1469] Device: Notify users of updates to the parenting guide via voice notification.

[1470] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1471] Hardware and software used

[1472] Speech recognition software: Google Cloud Speech-to-Text, Amazon Transcribe

[1473] Database management systems: MySQL, PostgreSQL

[1474] Sentiment analysis software: IBM Watson Tone Analyzer, Affectiva

[1475] Speech synthesis software: Google Cloud Text-to-Speech, Amazon Polly

[1476] Prompt Sentence Examples

[1477] "My baby cries at night, what should I do?"

[1478] "Today was the first time I walked."

[1479] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1480] This system makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[1481] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1482] Step 1:

[1483] The user inputs questions or concerns about childcare by voice. For example, a question like, "My baby cries at night. What should I do?" The input voice is sent directly to the device.

[1484] Step 2:

[1485] The device records the user's voice and converts it into text data using speech recognition technology. The voice input is converted into text data using Google Cloud Speech-to-Text or Amazon Transcribe. The input is the user's voice data, and the output is text data. This process completes the step of converting voice into text information.

[1486] Step 3:

[1487] The terminal sends the converted text data to the server. The input is the converted text data, and the output is transmission to the server via an HTTP request. This process includes an operation of passing the text data to the server using a communication protocol.

[1488] Step 4:

[1489] The server receives the text data and executes a database query to find the appropriate advice. The input is the text data sent from the device, and the output is the searched advice data. Specifically, it uses an SQL query to search a database (such as MySQL or PostgreSQL) for parenting advice.

[1490] Step 5:

[1491] The server generates advice based on the search results and creates answer text. The input is advice data retrieved from the database, and the output is the generated answer text. Specifically, it creates appropriate advice sentences to provide to the user based on the search results.

[1492] Step 6:

[1493] The server sends the generated answer text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes advice based on that data. The input is the answer text and the user's emotion data, and the output is customized advice text. Emotion data is extracted using emotion analysis tools such as IBM Watson Tone Analyzer and Affectiva.

[1494] Step 7:

[1495] The emotion engine generates customized advice text based on the user's emotional state. The input is the emotion analysis result and the answer text, and the output is advice optimized for the user. Specific operations include adding relaxation techniques to advice for users who are feeling stressed.

[1496] Step 8:

[1497] The server sends the final customized advice to the terminal. The input is the customized advice text, and the output is an HTTP response to the terminal. This process includes passing the generated text to the terminal using a communication protocol.

[1498] Step 9:

[1499] The device converts the answer text into speech and responds to the user. The input is customized advice text, and the output is audio data. The text data is converted into audio data using Google Cloud Text-to-Speech or Amazon Polly, and the device responds to the user via audio.

[1500] Step 10:

[1501] The user listens to the audio advice played from the device. The input is the audio advice played from the device, and the output is the user's recognition and understanding. This step provides the user with the appropriate information to decide on their next action.

[1502] (Application example 2)

[1503] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1504] Parents raising children are prone to stress and fatigue, and often find it difficult to choose the right meal. In these circumstances, there is a demand for food delivery services that parents can easily access. However, conventional food delivery services are unable to provide individually optimized menus based on the user's emotional state, and are unable to fully increase user satisfaction. There is also a demand for meal suggestions that take into account the nutritional balance unique to parenting.

[1505] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, and means for analyzing the user's emotional state through emotion analysis and recommending an optimal menu based on the user's emotional state. This enables parents raising children to easily select an optimal food menu depending on their emotional state and child-rearing situation.

[1506] "User" refers to an individual or entity that uses the system.

[1507] "Audio input" is the process by which the system receives audio data recorded through a microphone.

[1508] "Text data" refers to data that has been converted from voice input into text information.

[1509] A "server" is a computer system that receives and processes requests from client devices over the Internet or a local network.

[1510] "Emotion analysis" is the process of determining a user's emotional state from their voice and text data.

[1511] "Childcare Information" refers to data related to childcare that a user provides to the system.

[1512] A "customized child-rearing guide" is advice and information that is optimized for each individual user based on accumulated child-rearing information.

[1513] A "food delivery service" is a service that delivers meals according to orders from users.

[1514] "Menu recommendation" is the process of suggesting the most suitable meal menu based on the user's emotional state and needs.

[1515] The present invention is a system that supports users in raising their children by proposing an optimal food menu based on the emotional state of the parent and providing a food delivery service. The system aims to reduce the burden on parents raising children by analyzing the user's voice input, understanding their emotional state, and then recommending an appropriate meal menu.

[1516] System configuration

[1517] The system includes the following components:

[1518] 1. User: The parent or guardian who uses the system.

[1519] 2. Terminal: A device, such as a smartphone or tablet, that receives voice input and sends data to a server.

[1520] 3. Server: A system that receives text data from users, performs sentiment analysis, and generates appropriate advice and information.

[1521] 4. Emotion engine: Software that analyzes the user's emotional state from their voice and text data.

[1522] Program processing explanation

[1523] Voice input and conversion

[1524] The user speaks to the device to request food delivery related to childcare. For example, "I'm tired today, so I'd like something easy to eat and nutritious." The device records this speech and converts it into text data using the speech_recognition library.

[1525] Sending and Receiving Data

[1526] The device sends the converted text data to the server, which receives it via an HTTP request. The received text data is then used for sentiment analysis.

[1527] Sentiment Analysis and Advice Generation

[1528] The server uses an emotion engine to analyze the user's emotional state based on the received text data. For emotion analysis, it uses a provisional package called text_to_emotion. Based on the results of this analysis, it determines the user's fatigue and stress levels and suggests the optimal meal menu. For menu recommendations, it uses a provisional package called menu_recommendation.

[1529] Voice advice provided

[1530] The server generates an optimal meal menu and sends the text data back to the device. The device converts this data into audio and plays it back to the user as advice. For example, the device might say, "The recommended nutritious menu is the fried shrimp set meal."

[1531] Hardware and software used

[1532] Hardware: Smartphones and tablets (microphones for voice recognition, communication modules for data transmission and reception)

[1533] software:

[1534] speech_recognition library: speech-to-text conversion

[1535] HTTP request: Sending and receiving text data

[1536] Provisional package text_to_emotion: Emotion analysis

[1537] Provisional package menu_recommendation: Menu recommendation

[1538] Specific examples

[1539] User: "I'm tired and want something to cheer me up."

[1540] Device: Converts speech to text and sends it to the server.

[1541] Server: Analyzes text data using an emotion engine to detect the user's level of fatigue.

[1542] Server: Use a menu recommendation package to select the best menu.

[1543] Device: A voice message will say, "The recommended nutritious menu item is the fried shrimp set meal."

[1544] Prompt statement

[1545] "Design an app that analyzes user emotions and provides the most appropriate food menu. The system should be able to suggest appropriate menu items based on the user's comments and the results of the emotion analysis."

[1546] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1547] Step 1: The user voice-inputs their childcare-related food delivery request into the device. For example, they might say, "I'm tired today, so I'd like something easy to eat and nutritious." The voice data they input is then recorded.

[1548] Step 2: The device uses speech recognition technology to convert the recorded voice data into text data. Specifically, the speech-to-text conversion is performed using the speech_recognition library. The input is voice data, and the output is text data.

[1549] Step 3: The terminal uses an HTTP request to send the converted text data to the server. The input is the text data, and the output is an HTTP request to the server.

[1550] Step 4: The server receives the HTTP request and retrieves the text data. The received text data is prepared for analysis. The input is the text data in the HTTP request, and the output is the text data for analysis.

[1551] Step 5: The server uses the emotion engine to analyze the user's emotional state from the text data. Specifically, it uses a hypothetical package called text_to_emotion to perform emotion analysis. The input is text data, and the output is data indicating the user's emotional state.

[1552] Step 6: The server starts the process to generate an optimal food menu based on the emotional state. A hypothetical package, menu_recommendation, is used to recommend an appropriate menu based on the emotional data. The input is the data indicating the emotional state, and the output is the recommended menu.

[1553] Step 7: The server converts the generated menu into text data and sends an HTTP response to be sent to the terminal again. The input is the text data of the menu, and the output is the HTTP response.

[1554] Step 8: The terminal receives the HTTP response and obtains the text data of the menu that was sent. The input is the text data in the HTTP response, and the output is the text data to be displayed.

[1555] Step 9: The terminal converts the acquired menu text data into audio data and plays it back to the user. Specifically, the audio data is generated using text-to-speech conversion technology. The input is the text data to be displayed, and the output is audio data.

[1556] Step 10: The user listens to the audio advice played from the terminal and confirms the suggested meal menu. The input is audio data, and the output is information about the suggested menu.

[1557] This series of processes allows users to easily obtain optimal food menus that can reduce the burden of raising children.

[1558] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1559] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1560] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1561] [Fourth embodiment]

[1562] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1563] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1564] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1565] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1566] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1567] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1568] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1569] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1570] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1571] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1572] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1573] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1574] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1575] The present invention relates to a child-rearing support system that supports users' various child-rearing needs 24 hours a day, 365 days a year. This system provides appropriate advice and information by conducting voice dialogue with the user through a smart speaker or application and linking with a server. Specific embodiments are described below.

[1576] composition

[1577] The system mainly consists of the following components:

[1578] 1. User (Parent or Guardian)

[1579] 2. Device (smart speaker or device with application installed)

[1580] 3. Server

[1581] Program processing

[1582] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[1583] 2. The device records the voice input and converts it into text using speech recognition technology. This is the speech-to-text process.

[1584] 3. The device sends the converted text data to the server. Communication is usually via an HTTP request over the Internet.

[1585] 4. The server receives the text data and searches the database for appropriate advice or information. This is the database query process.

[1586] 5. The server generates advice and information based on the search results to answer the user's question. The generated text is organized as an answer.

[1587] 6. The server sends the generated answer text back to the device. This is done by sending an HTTP response.

[1588] 7. The device receives the response text and converts it back into speech using speech synthesis technology. This is the text-to-speech conversion process.

[1589] 8. The device will output a response to the user as a voice output. For example, "Possible causes of nighttime crying include loneliness or hunger. Try responding by cuddling your baby or giving him milk."

[1590] Specific examples

[1591] Case 1: Instant answers to questions

[1592] Scenario: A user asks a question about parenting.

[1593] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1594] Device: Converts speech to text and sends it to the server.

[1595] Server: Searches the database for corresponding countermeasure information and generates a response.

[1596] Terminal: Converts the answer into speech and conveys it to the user.

[1597] User: "To prevent diaper rash, it's important to change diapers frequently and keep the skin clean."

[1598] Case 2: Generating specialized parenting books

[1599] Scenario: A user records daily childcare information.

[1600] User: "Today was my first time walking."

[1601] Device: Converts speech to text and sends it to the server.

[1602] Server: Stores and analyzes data.

[1603] Server: Periodically generates a parenting guide based on the accumulated data.

[1604] Device: Notifies the user of updates to the parenting guide via voice.

[1605] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1606] Other Features

[1607] counseling

[1608] User: "I'm feeling stressed today. What should I do?"

[1609] Device: Converts speech to text and sends it to the server.

[1610] Server: Generates appropriate counseling and advice.

[1611] Terminal: Converts advice into voice and conveys it to the user.

[1612] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[1613] Data collection and sales

[1614] Server: Collects and anonymizes daily conversation data.

[1615] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[1616] In this way, the present invention can provide individual and optimal responses to the various childcare support needs of users.

[1617] The processing flow will be explained below.

[1618] Instant answers to your questions

[1619] Step 1:

[1620] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[1621] Step 2:

[1622] The device records the user's voice and converts it into text data using speech recognition technology, a process known as speech-to-text conversion.

[1623] Step 3:

[1624] The device sends the converted text data to the server, which is done using an HTTP request.

[1625] Step 4:

[1626] The server analyzes the received text data and searches the database for appropriate advice, which is a database query process.

[1627] Step 5:

[1628] The server generates advice based on the search results and writes answers in text format.

[1629] Step 6:

[1630] The server sends the generated answer text back to the device, by sending an HTTP response.

[1631] Step 7:

[1632] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[1633] Step 8:

[1634] The user listens to the audio advice played from the terminal.

[1635] Creation of specialized childcare books

[1636] Step 1:

[1637] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[1638] Step 2:

[1639] The device records the user's voice and converts it into text data using voice recognition technology.

[1640] Step 3:

[1641] The terminal transmits the converted text data to the server.

[1642] Step 4:

[1643] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[1644] Step 5:

[1645] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[1646] Step 6:

[1647] The server notifies the terminal of the generated child-rearing guide.

[1648] Step 7:

[1649] The device will notify the user of updates to the parenting guide via voice notification.

[1650] Step 8:

[1651] The user refers to the parenting guide provided and incorporates it into parenting.

[1652] Counselling and problem-solving

[1653] Step 1:

[1654] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[1655] Step 2:

[1656] The device records the user's voice and converts it into text data using voice recognition technology.

[1657] Step 3:

[1658] The terminal transmits the converted text data to the server.

[1659] Step 4:

[1660] The server receives the text data and searches the database for appropriate counseling and advice.

[1661] Step 5:

[1662] The server generates counseling advice based on the search results and creates answers in text format.

[1663] Step 6:

[1664] The server sends the generated answer text back to the terminal.

[1665] Step 7:

[1666] The terminal converts the answer text into speech and responds to the user.

[1667] Step 8:

[1668] The user listens to the audio advice played from the terminal and receives counseling.

[1669] Data collection and sales

[1670] Step 1:

[1671] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[1672] Step 2:

[1673] The server stores the anonymized data in a database.

[1674] Step 3:

[1675] The server periodically exports the data and sells it to product development companies.

[1676] Step 4:

[1677] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[1678] The above is a specific processing flow in the child-rearing support system.

[1679] Example 1

[1680] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1681] There is a demand for immediate and appropriate support for various questions and concerns about child-rearing. However, current systems only provide limited answers to users' questions and do not offer customized advice. Furthermore, there are issues with systems that do not adequately generate child-rearing guides tailored to each user's individual situation or provide appropriate counseling based on daily child-rearing records.

[1682] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1683] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching a database for corresponding advice or information to generate it, means for reconverting the generated advice or information from text to voice using a generative AI model and sending a reply to the user, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, thereby enabling the system to respond promptly and appropriately to the diverse child-rearing needs of users.

[1684] "User" refers to a parent or guardian who has questions or concerns about childcare.

[1685] "Voice input" refers to the act of a user providing voice data to a terminal.

[1686] "Text data" refers to character string data converted from voice input using voice recognition technology.

[1687] "Terminal" refers to a device that has the ability to record voice input and convert voice data into text data.

[1688] "Conversion means" refers to software or hardware for converting voice data into text data.

[1689] "Server" refers to a computer system that has the ability to process received text data, search a database for appropriate advice or information, and generate it.

[1690] "Generative AI model" refers to the artificial intelligence model used by the server to generate answers to users' questions.

[1691] "Speech synthesis technology" refers to technology that reconverts generated text data into voice data.

[1692] "Database" refers to an information resource that stores information related to childcare.

[1693] "Parenting Guide" refers to documents and data that provide individually customized advice and information based on a user's parenting information.

[1694] "Counseling" refers to the act of providing psychological support and advice to users regarding their worries and complaints.

[1695] "Anonymization" refers to a data processing method that renders a user's personal information unidentifiable.

[1696] "Product development companies" refer to companies that develop new products and services that meet market needs.

[1697] "Childcare support information" refers to advice and necessary information for questions and concerns about childcare.

[1698] MODE FOR CARRYING OUT THE INVENTION

[1699] The present invention is a system for responding to various childcare needs of users, and is highly convenient for users by providing support 24 hours a day, 365 days a year through voice input and responses. The system mainly consists of the following components: a user, a terminal, and a server.

[1700] Hardware and Software Examples

[1701] 1. User (Parent or Guardian):

[1702] Users input questions and concerns about childcare by voice.

[1703] 2. Device (smart speaker or device with application installed):

[1704] A device that receives voice input using a built-in microphone and speech recognition software, such as Google Speech-to-Text, and can also use Google Text-to-Speech as a speech synthesis technology.

[1705] 3. Server:

[1706] The server receives the text data, searches for appropriate information from a database, and generates answers for the user using SQL database queries and a generative AI model (e.g., OpenAI's GPT-3).

[1707] Example Details

[1708] Voice Input and Conversion Process

[1709] The user asks a question about childcare to the device: "My baby cries at night. What should I do?"

[1710] The device records the user's voice and converts it into text data using Google Speech-to-Text technology.

[1711] The device sends the converted text data to the server via the Internet, specifically via an HTTP request.

[1712] Data Processing and Information Retrieval

[1713] The server analyzes the HTTP request received from the terminal and extracts the text data.

[1714] The server uses a MySQL or PostgreSQL database to look up relevant childcare information.

[1715] After searching the database, a generative AI model (e.g., GPT-3) is used to generate a customized answer for the user.

[1716] Text retranslation and response

[1717] The server returns the generated response text data to the terminal as an HTTP response.

[1718] The text data received by the device is converted into speech using speech synthesis technology such as Google Text-to-Speech.

[1719] The device will then provide the user with a converted voice response: "Possible causes of nighttime crying include loneliness and hunger. Try cuddling your baby and offering them milk."

[1720] Specific use cases

[1721] For immediate answers to questions

[1722] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1723] Device: Converts speech to text and sends it to the server.

[1724] Server: Searches the database and uses a generative AI model to generate the answer, "To prevent diaper rash, it is important to change diapers frequently and keep the skin clean."

[1725] Terminal: Converts the answer into speech and conveys it to the user.

[1726] Prompt Sentence Examples

[1727] "My baby cries at night, what should I do?"

[1728] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1729] This system allows users to receive prompt and appropriate childcare support regardless of time or place.

[1730] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1731] Step 1:

[1732] The user speaks into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" This speech becomes the input.

[1733] Step 2:

[1734] The device uses a built-in microphone to record the user's voice. It then uses speech recognition technology (e.g., Google Speech-to-Text) to convert the recorded voice data into text data. This is the process by which voice input is converted into text data. The output is the converted text data. Specifically, the speech recognition software analyzes the voice waveform and generates the corresponding text.

[1735] Step 3:

[1736] The terminal sends the converted text data to the server. The text data is sent via the Internet using an HTTP request (POST method). The input is the converted text data, and the output is the HTTP request sent to the server.

[1737] Step 4:

[1738] The server receives an HTTP request sent from a terminal. The server extracts and analyzes text data from the HTTP request. The input is the HTTP request, and the output is the analyzed text data. Specifically, the server analyzes the body of the request and obtains the necessary information.

[1739] Step 5:

[1740] The server searches the database based on the parsed text data. The server uses an SQL query to retrieve childcare-related information from the database. In this process, the input is the parsed text data, and the output is information from the database as search results. Specifically, the server generates an SQL query and sends it to the database to retrieve information.

[1741] Step 6:

[1742] Based on the information the server retrieves from the database, it uses a generative AI model (e.g., OpenAI's GPT-3) to generate an appropriate answer to the user's question. In this process, the input is the database information of the search results, and the output is the generated answer text. The generative AI model generates text data using natural language processing techniques.

[1743] Step 7:

[1744] The server sends the generated answer text to the terminal as an HTTP response. In this process, the input is the generated answer text and the output is the HTTP response.

[1745] Step 8:

[1746] The response text received by the terminal as an HTTP response is converted into voice data using speech synthesis technology (e.g., Google Text-to-Speech). In this process, the input is the received response text, and the output is voice data. Specifically, the speech synthesis software converts the text into an audio file.

[1747] Step 9:

[1748] The terminal uses a device (such as a speaker) to play back the audio data and communicates the answer to the user. In this process, the input is audio data and the output is the played audio. Specifically, the terminal sends the audio data to the speaker and the audio is played back. This audio is then provided to the user.

[1749] (Application example 1)

[1750] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1751] Childcare is a time-consuming and labor-intensive task for parents and guardians, and meal preparation, among other daily tasks, often places an additional burden on them. Therefore, there is a need for a support system that can address the diverse needs of parents and guardians raising children. The present invention aims to provide a system that not only provides advice and information on childcare, but also suggests healthy foods and beverages to reduce the burden of meal preparation.

[1752] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1753] In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and retrieving and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's childcare information and generating an individually customized childcare guide, and means for suggesting healthy foods and beverages when the user's question is related to diet, thereby enabling parents and guardians raising children to receive not only the childcare information and advice they need, but also specific suggestions for meal preparation.

[1754] "Voice input" is a means by which a user verbally asks questions or gives instructions and conveys them to the system.

[1755] "Text data" is voice input converted into text information, and the system uses this data for further information processing.

[1756] A "server" is a computer system that receives text data and generates appropriate advice and information.

[1757] "Speech-to-text" is the process of recognizing a user's voice input and converting it into written information.

[1758] "Advice or Information" refers to advice or knowledge provided in response to a user's parenting questions.

[1759] "Text-to-speech reconversion" is the process of converting the generated textual information back into speech and providing it audibly to the user.

[1760] "Childcare information" refers to records and data relating to the growth and development of a user's baby or child.

[1761] A "customized parenting guide" is a parenting instruction manual created to meet the needs of a particular user based on individual parenting information.

[1762] The "means for suggesting healthy food and drink options" is a means for presenting health-conscious food and drink options when the user's question is related to diet.

[1763] This invention relates to a child-rearing support system that provides 24-hour support to parents and guardians raising children. This system is primarily composed of a user (parent or guardian), a device (such as a smartphone or smart speaker), and a server. The entire system works in cooperation with each device and the server to provide appropriate advice and information to the user.

[1764] Program implementation and processing explanation

[1765] The system program is implemented using the following hardware and software. The speech_recognition library is used to receive voice input from the user as a signal and convert it into text data. This allows the device to accurately identify the user's voice input and convert it into text format. The converted text data is sent to the server using the requests library. After receiving the text data, the server is responsible for searching for and generating appropriate childcare information.

[1766] Server Processing

[1767] The server processes the received text data and queries a database. It generates appropriate advice and information and sends it back to the device. This process is typically achieved using a database management system (DBMS) and a natural language processing model (e.g., GPT-3). The generated text data is then sent back to the device using the requests library.

[1768] Terminal handling

[1769] The device receives the returned text data and converts it back into audio using the gTTS (Google Text-to-Speech) library, allowing the user to receive advice and information in audio format. If a question is related to diet, the server also generates healthy food and drink recommendations and presents them to the user via the device.

[1770] Specific examples

[1771] 1. Scenario 1: User asks a parenting question

[1772] User: "My baby cries at night, what should I do?"

[1773] Device: Converts voice input into text and sends it to the server.

[1774] Server: Searches and generates appropriate advice from a database.

[1775] Terminal: Converts advice into voice and responds to the user.

[1776] 2. Scenario 2: Asking a question about food

[1777] User: "What should we have for dinner tonight?"

[1778] Device: Converts voice input into text and sends it to the server.

[1779] Server: Generates advice suggesting healthy food and drink offerings.

[1780] Device: "Recommended delivery services offer healthy food and drinks."

[1781] Prompt Sentence Examples

[1782] "Parents are asking, 'What should we have for dinner tonight?' Generate answers that include healthy eating suggestions along with parenting advice."

[1783] This system allows parents and guardians to receive appropriate childcare advice 24 hours a day, 365 days a year, and also helps ease the burden of childcare by suggesting healthy options for dietary questions.

[1784] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1785] Step 1:

[1786] Users can voice-input questions or concerns about childcare via devices such as smartphones or smart speakers. For example, a question might be, "My baby cries at night. What should I do?"

[1787] Step 2:

[1788] The device records voice input and converts it to text data using speech recognition technology. Specifically, it uses the speech_recognition library to convert voice to text information. The input is voice data, and the output is the corresponding text data.

[1789] Step 3:

[1790] The terminal sends the converted text data to the server. Using the requests library, it sends an HTTP request over the Internet. The input is text data, and the output is an HTTP request.

[1791] Step 4:

[1792] The server receives the text data. The input received here is the HTTP request, which contains the text data. The server analyzes the received text data and extracts the necessary information.

[1793] Step 5:

[1794] The server uses a natural language processing model (e.g., GPT-3) to generate advice or information based on the text data. The input is the analyzed text data, and the output is the generated advice or information text data.

[1795] Step 6:

[1796] The server sends the generated advice and information back to the terminal, again using the requests library to send text data as an HTTP response. The input is the generated text data, and the output is the HTTP response.

[1797] Step 7:

[1798] The terminal receives the returned text data. The input is the HTTP response, and the text data is extracted from it.

[1799] Step 8:

[1800] The text data received by the terminal is converted back into speech using speech synthesis technology (for example, the gTTS library). The input is text data and the output is speech data.

[1801] Step 9:

[1802] The terminal plays back the audio data and provides advice and information to the user by voice. Specifically, it executes a playback command to play back the audio data. The input is the audio data, and the output is the played audio.

[1803] Through this series of steps, users can receive real-time parenting advice and information in audio format, as well as meal suggestions if the question is related to diet.

[1804] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1805] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[1806] composition

[1807] The system mainly consists of the following components:

[1808] 1. User (Parent or Guardian)

[1809] 2. Device (smart speaker or device with application installed)

[1810] 3. Server

[1811] 4. Emotion Engine

[1812] Program processing

[1813] 1. The user speaks into the device to ask a question or express a concern about childcare. For example, "My baby cries at night. What should I do?"

[1814] 2. The device records the user's voice and converts it into text using voice recognition technology. This is the voice-to-text process.

[1815] 3. The device sends the converted text data to the server using an HTTP request.

[1816] 4. The server receives the text data and searches the database for appropriate advice. This is a database query process.

[1817] 5. The server generates advice based on the search results and creates an answer text.

[1818] 6. The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[1819] 7. The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[1820] 8. The server sends the final customized advice to the device via an HTTP response.

[1821] 9. The device converts the answer text into speech and responds to the user. This is the text-to-speech conversion process.

[1822] 10. The user listens to the audio advice played from the device.

[1823] Specific examples

[1824] Case 1: Instant answers based on user questions

[1825] Scenario: A user asks a question about parenting.

[1826] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1827] Device: Converts speech to text and sends it to the server.

[1828] Server: Searches the database for corresponding countermeasure information and generates a response.

[1829] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[1830] Terminal: Converts the answer into speech and conveys it to the user.

[1831] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[1832] Case 2: Generating specialized parenting books

[1833] Scenario: A user logs daily childcare information.

[1834] User: "Today was my first time walking."

[1835] Device: Converts speech to text and sends it to the server.

[1836] Server: Stores and analyzes text data.

[1837] Emotion engine: Analyzes user emotion data and uses it for analysis.

[1838] Server: Generates an individually optimized parenting guide and notifies the device.

[1839] Device: Notify users of updates to the parenting guide via voice notification.

[1840] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1841] Other Features

[1842] counseling

[1843] User: "I'm stressed out today. What should I do?"

[1844] Device: Converts speech to text and sends it to the server.

[1845] Server: Searches for counseling information from a database and generates answers.

[1846] Emotion Engine: Analyzes the user's stress level from their voice and suggests ways to relax.

[1847] Terminal: Converts advice into voice and conveys it to the user.

[1848] User: "To relieve stress, I recommend taking short breaks and doing some light exercise."

[1849] Data collection and sales

[1850] Server: Collects and anonymizes daily conversation data.

[1851] Emotion engine: Emotional data is collected and anonymized.

[1852] Server: Sells data to product development companies to raise funds to further improve the accuracy of childcare support information.

[1853] In this way, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[1854] The processing flow will be explained below.

[1855] Embodiments of the invention combining emotion engines

[1856] Instant answers to your questions

[1857] Step 1:

[1858] Users can voice-input questions or concerns about childcare into the device. For example, "My baby cries at night. What should I do?"

[1859] Step 2:

[1860] The device records the user's voice and converts it into text data using voice recognition technology. This is a voice-to-text conversion process.

[1861] Step 3:

[1862] The device sends the converted text data to the server, which is done using an HTTP request.

[1863] Step 4:

[1864] The server receives the text data and searches the database for appropriate advice, which is a database query process.

[1865] Step 5:

[1866] The server generates advice based on the search results and creates answer text.

[1867] Step 6:

[1868] The server sends the generated answer text to the emotion engine, which customizes advice based on the emotion data extracted from the user's voice. This is the emotion analysis process.

[1869] Step 7:

[1870] The emotion engine generates customized advice text based on the user's emotional state. For example, if the user is feeling stressed, it will add corresponding relaxation techniques.

[1871] Step 8:

[1872] The server sends the final customized advice to the device, which is done by sending an HTTP response.

[1873] Step 9:

[1874] The terminal converts the answer text into speech and responds to the user. This is a text-to-speech conversion process.

[1875] Step 10:

[1876] The user listens to the audio advice played from the terminal.

[1877] Creation of specialized childcare books

[1878] Step 1:

[1879] The user speaks into the device to input daily childcare information and records of the child's growth. For example, "Today, my child walked for the first time."

[1880] Step 2:

[1881] The device records the user's voice and converts it into text data using voice recognition technology.

[1882] Step 3:

[1883] The terminal transmits the converted text data to the server.

[1884] Step 4:

[1885] The server receives the text data and stores it in a separate childcare database. This is a database insertion process.

[1886] Step 5:

[1887] The server periodically analyzes the accumulated childcare data and generates an individually optimized childcare guide, which is a data analysis and report generation process.

[1888] Step 6:

[1889] The emotion engine generates parenting guides based on the user's parenting information, taking into account their emotional state. For example, if the user is happy, it will include many positive words.

[1890] Step 7:

[1891] The server notifies the terminal of the generated child-rearing guide.

[1892] Step 8:

[1893] The device will notify the user of updates to the parenting guide via voice notification.

[1894] Step 9:

[1895] The user refers to the parenting guide provided and incorporates it into parenting.

[1896] Counselling and problem-solving

[1897] Step 1:

[1898] The user speaks their worries or complaints into the device. For example, "I'm very tired today."

[1899] Step 2:

[1900] The device records the user's voice and converts it into text data using voice recognition technology.

[1901] Step 3:

[1902] The terminal transmits the converted text data to the server.

[1903] Step 4:

[1904] The server receives the text data and searches the database for appropriate counseling and advice.

[1905] Step 5:

[1906] The server generates counseling advice based on the search results and creates an answer text.

[1907] Step 6:

[1908] The server sends the generated answer text to the emotion engine, which analyzes the user's emotional state and customizes the advice accordingly.

[1909] Step 7:

[1910] The emotion engine generates customized advice text that takes into account factors such as stress level.

[1911] Step 8:

[1912] The server sends the final advice to the terminal.

[1913] Step 9:

[1914] The device converts the advice into voice and conveys it to the user.

[1915] Step 10:

[1916] The user listens to the audio advice played from the terminal and receives counseling.

[1917] Data collection and sales

[1918] Step 1:

[1919] The server anonymizes and collects daily conversation data with the user. This is data anonymization processing.

[1920] Step 2:

[1921] The emotion engine also collects and anonymizes user emotion data, making it possible to obtain comprehensive data.

[1922] Step 3:

[1923] The server stores the anonymized data in a database.

[1924] Step 4:

[1925] The server periodically exports the data and sells it to product development companies.

[1926] Step 5:

[1927] The revenue the server receives from sales is used to fund system maintenance and accuracy improvements.

[1928] Through these steps, the present invention can provide an individualized and optimal response that takes into account the user's emotional state, thereby providing more advanced childcare support.

[1929] Example 2

[1930] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1931] In modern society, childcare support needs to be provided quickly and accurately, 24 hours a day, 365 days a year. However, conventional systems only provide general advice without considering the user's psychological state, making it difficult to address individual needs. In addition, there is a lack of means to provide advice tailored to the user's emotional state, making it difficult to provide stress relief or appropriate counseling.

[1932] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the communication device, means for processing the text data received by the communication device and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and returning it to the user, means for extracting emotional data from the user's voice and customizing advice based on the emotional data, and means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide. This makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[1933] "Voice input" refers to a digital device receiving spoken words from a user as voice data.

[1934] "Text data" refers to data converted from voice input into a string of characters.

[1935] "Communication device" refers to a device that receives text data and interacts with a server to process it.

[1936] "Server" refers to a computer system capable of processing received data and generating and transmitting advice or information.

[1937] "Advice" refers to answers or recommendations provided to a user's questions or requests.

[1938] "Information" refers to knowledge and data provided in response to a user's request.

[1939] "Speech recognition" refers to the process of converting voice data into text data.

[1940] "Speech synthesis" refers to the process of converting text data into speech data.

[1941] "Emotion data" refers to data that represents an emotional state extracted from a user's voice.

[1942] "Customization" refers to tailoring advice and information to a user's specific situation and emotions.

[1943] "Storage" refers to storing data collected from users and making it available at a later time.

[1944] "Parenting Guide" refers to a document that compiles parenting advice and information provided to users.

[1945] "Anonymization" refers to the removal of personally identifiable information from collected data.

[1946] "Product development companies" refer to companies that use collected data to develop new products and services.

[1947] This invention relates to a child-rearing support system that supports users' diverse child-rearing needs 24 hours a day, 365 days a year, and provides more individually optimized advice and information by combining it with an emotion engine that recognizes the user's emotions. This system provides appropriate advice and information by engaging in voice dialogue with the user through a smart speaker or application and linking with a server. The emotion engine also analyzes the user's emotional state and responds appropriately according to that state.

[1948] Components

[1949] The system mainly consists of the following components:

[1950] 1. User (Parent or Guardian)

[1951] 2. Device (smart speaker or device with application installed)

[1952] 3. Server

[1953] 4. Emotion Engine

[1954] System Details

[1955] Voice to text conversion

[1956] Users speak into the device to ask questions or express concerns about childcare. For example, they might ask, "My baby cries at night. What should I do?" The device then records the user's voice and converts it into text data using voice recognition technologies such as Google Cloud Speech-to-Text and Amazon Transcribe.

[1957] Sending text data

[1958] The terminal sends the converted text data to the server using an HTTP request, which causes the text data to arrive at the server.

[1959] Database Queries and Advice Generation

[1960] The server searches a database for appropriate advice based on the received text data. Possible database management systems (DBMS) used are MySQL and PostgreSQL. The server executes a database query to extract the appropriate countermeasure. For example, in response to the question, "My baby cries at night. What should I do?", the server generates information about "the causes of night crying and what to do about it."

[1961] Sentiment Analysis and Customization

[1962] The server sends the generated advice text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes the advice based on that data. For example, if the user is feeling stressed, the advice will include relaxation tips.

[1963] Customized advice notifications

[1964] The server then sends the final, customized advice to the device, again via an HTTP response. The device then converts the advice into speech using Google Cloud Text-to-Speech or Amazon Polly, and delivers it to the user.

[1965] Specific examples

[1966] Case 1: Instant answers based on user questions

[1967] Scenario: A user asks a question about parenting.

[1968] User: "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1969] Device: Converts speech to text and sends it to the server.

[1970] Server: Searches the database for corresponding countermeasure information and generates a response.

[1971] Emotion engine: Recognizes emotions from the user's voice and adds stress-relieving elements to the answer.

[1972] Terminal: Converts the answer into speech and conveys it to the user.

[1973] User: "To prevent diaper rash, it's important to change diapers frequently and keep the baby's skin clean. It's also important to be relaxed when interacting with your baby."

[1974] Case 2: Generating specialized parenting books

[1975] Scenario: A user logs daily childcare information.

[1976] User: "Today was my first time walking."

[1977] Device: Converts speech to text and sends it to the server.

[1978] Server: Stores and analyzes text data.

[1979] Emotion engine: Analyzes user emotion data and uses it for analysis.

[1980] Server: Generates an individually optimized parenting guide and notifies the device.

[1981] Device: Notify users of updates to the parenting guide via voice notification.

[1982] User: "This week's Parenting Guide has been updated with new advice on training your baby to walk."

[1983] Hardware and software used

[1984] Speech recognition software: Google Cloud Speech-to-Text, Amazon Transcribe

[1985] Database management systems: MySQL, PostgreSQL

[1986] Sentiment analysis software: IBM Watson Tone Analyzer, Affectiva

[1987] Speech synthesis software: Google Cloud Text-to-Speech, Amazon Polly

[1988] Prompt Sentence Examples

[1989] "My baby cries at night, what should I do?"

[1990] "Today was the first time I walked."

[1991] "My baby has a terrible diaper rash. Is there anything I can do about it?"

[1992] This system makes it possible to provide individually optimized advice and information that reflects the user's emotional state.

[1993] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1994] Step 1:

[1995] The user inputs questions or concerns about childcare by voice. For example, a question like, "My baby cries at night. What should I do?" The input voice is sent directly to the device.

[1996] Step 2:

[1997] The device records the user's voice and converts it into text data using speech recognition technology. The voice input is converted into text data using Google Cloud Speech-to-Text or Amazon Transcribe. The input is the user's voice data, and the output is text data. This process completes the step of converting voice into text information.

[1998] Step 3:

[1999] The terminal sends the converted text data to the server. The input is the converted text data, and the output is transmission to the server via an HTTP request. This process includes an operation of passing the text data to the server using a communication protocol.

[2000] Step 4:

[2001] The server receives the text data and executes a database query to find the appropriate advice. The input is the text data sent from the device, and the output is the searched advice data. Specifically, it uses an SQL query to search a database (such as MySQL or PostgreSQL) for parenting advice.

[2002] Step 5:

[2003] The server generates advice based on the search results and creates answer text. The input is advice data retrieved from the database, and the output is the generated answer text. Specifically, it creates appropriate advice sentences to provide to the user based on the search results.

[2004] Step 6:

[2005] The server sends the generated answer text to the emotion engine, which analyzes the emotion data extracted from the user's voice and customizes advice based on that data. The input is the answer text and the user's emotion data, and the output is customized advice text. Emotion data is extracted using emotion analysis tools such as IBM Watson Tone Analyzer and Affectiva.

[2006] Step 7:

[2007] The emotion engine generates customized advice text based on the user's emotional state. The input is the emotion analysis result and the answer text, and the output is advice optimized for the user. Specific operations include adding relaxation techniques to advice for users who are feeling stressed.

[2008] Step 8:

[2009] The server sends the final customized advice to the terminal. The input is the customized advice text, and the output is an HTTP response to the terminal. This process includes passing the generated text to the terminal using a communication protocol.

[2010] Step 9:

[2011] The device converts the answer text into speech and responds to the user. The input is customized advice text, and the output is audio data. The text data is converted into audio data using Google Cloud Text-to-Speech or Amazon Polly, and the device responds to the user via audio.

[2012] Step 10:

[2013] The user listens to the audio advice played from the device. The input is the audio advice played from the device, and the output is the user's recognition and understanding. This step provides the user with the appropriate information to decide on their next action.

[2014] (Application example 2)

[2015] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2016] Parents raising children are prone to stress and fatigue, and often find it difficult to choose the right meal. In these circumstances, there is a demand for food delivery services that parents can easily access. However, conventional food delivery services are unable to provide individually optimized menus based on the user's emotional state, and are unable to fully increase user satisfaction. There is also a demand for meal suggestions that take into account the nutritional balance unique to parenting.

[2017] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for converting voice input from the user into text data, means for transmitting the converted text data to the server, means for processing the text data received by the server and searching for and generating corresponding advice or information, means for reconverting the generated advice or information from text to voice and sending a reply to the user, means for accumulating the user's child-rearing information and generating an individually customized child-rearing guide, and means for analyzing the user's emotional state through emotion analysis and recommending an optimal menu based on the user's emotional state. This enables parents raising children to easily select an optimal food menu depending on their emotional state and child-rearing situation.

[2018] "User" refers to an individual or entity that uses the system.

[2019] "Audio input" is the process by which the system receives audio data recorded through a microphone.

[2020] "Text data" refers to data that has been converted from voice input into text information.

[2021] A "server" is a computer system that receives and processes requests from client devices over the Internet or a local network.

[2022] "Emotion analysis" is the process of determining a user's emotional state from their voice and text data.

[2023] "Childcare Information" refers to data related to childcare that a user provides to the system.

[2024] A "customized child-rearing guide" is advice and information that is optimized for each individual user based on accumulated child-rearing information.

[2025] A "food delivery service" is a service that delivers meals according to orders from users.

[2026] "Menu recommendation" is the process of suggesting the most suitable meal menu based on the user's emotional state and needs.

[2027] The present invention is a system that supports users in raising their children by proposing an optimal food menu based on the emotional state of the parent and providing a food delivery service. The system aims to reduce the burden on parents raising children by analyzing the user's voice input, understanding their emotional state, and then recommending an appropriate meal menu.

[2028] System configuration

[2029] The system includes the following components:

[2030] 1. User: The parent or guardian who uses the system.

[2031] 2. Terminal: A device, such as a smartphone or tablet, that receives voice input and sends data to a server.

[2032] 3. Server: A system that receives text data from users, performs sentiment analysis, and generates appropriate advice and information.

[2033] 4. Emotion engine: Software that analyzes the user's emotional state from their voice and text data.

[2034] Program processing explanation

[2035] Voice input and conversion

[2036] The user speaks to the device to request food delivery related to childcare. For example, "I'm tired today, so I'd like something easy to eat and nutritious." The device records this speech and converts it into text data using the speech_recognition library.

[2037] Sending and Receiving Data

[2038] The device sends the converted text data to the server, which receives it via an HTTP request. The received text data is then used for sentiment analysis.

[2039] Sentiment Analysis and Advice Generation

[2040] The server uses an emotion engine to analyze the user's emotional state based on the received text data. For emotion analysis, it uses a provisional package called text_to_emotion. Based on the results of this analysis, it determines the user's fatigue and stress levels and suggests the optimal meal menu. For menu recommendations, it uses a provisional package called menu_recommendation.

[2041] Voice advice provided

[2042] The server generates an optimal meal menu and sends the text data back to the device. The device converts this data into audio and plays it back to the user as advice. For example, the device might say, "The recommended nutritious menu is the fried shrimp set meal."

[2043] Hardware and software used

[2044] Hardware: Smartphones and tablets (microphones for voice recognition, communication modules for data transmission and reception)

[2045] software:

[2046] speech_recognition library: speech-to-text conversion

[2047] HTTP request: Sending and receiving text data

[2048] Provisional package text_to_emotion: Emotion analysis

[2049] Provisional package menu_recommendation: Menu recommendation

[2050] Specific examples

[2051] User: "I'm tired and want something to cheer me up."

[2052] Device: Converts speech to text and sends it to the server.

[2053] Server: Analyzes text data using an emotion engine to detect the user's level of fatigue.

[2054] Server: Use a menu recommendation package to select the best menu.

[2055] Device: A voice message will say, "The recommended nutritious menu item is the fried shrimp set meal."

[2056] Prompt statement

[2057] "Design an app that analyzes user emotions and provides the most appropriate food menu. The system should be able to suggest appropriate menu items based on the user's comments and the results of the emotion analysis."

[2058] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2059] Step 1: The user voice-inputs their childcare-related food delivery request into the device. For example, they might say, "I'm tired today, so I'd like something easy to eat and nutritious." The voice data they input is then recorded.

[2060] Step 2: The device uses speech recognition technology to convert the recorded voice data into text data. Specifically, the speech-to-text conversion is performed using the speech_recognition library. The input is voice data, and the output is text data.

[2061] Step 3: The terminal uses an HTTP request to send the converted text data to the server. The input is the text data, and the output is an HTTP request to the server.

[2062] Step 4: The server receives the HTTP request and retrieves the text data. The received text data is prepared for analysis. The input is the text data in the HTTP request, and the output is the text data for analysis.

[2063] Step 5: The server uses the emotion engine to analyze the user's emotional state from the text data. Specifically, it uses a hypothetical package called text_to_emotion to perform emotion analysis. The input is text data, and the output is data indicating the user's emotional state.

[2064] Step 6: The server starts the process to generate an optimal food menu based on the emotional state. A hypothetical package, menu_recommendation, is used to recommend an appropriate menu based on the emotional data. The input is the data indicating the emotional state, and the output is the recommended menu.

[2065] Step 7: The server converts the generated menu into text data and sends an HTTP response to be sent to the terminal again. The input is the text data of the menu, and the output is the HTTP response.

[2066] Step 8: The terminal receives the HTTP response and obtains the text data of the menu that was sent. The input is the text data in the HTTP response, and the output is the text data to be displayed.

[2067] Step 9: The terminal converts the acquired menu text data into audio data and plays it back to the user. Specifically, the audio data is generated using text-to-speech conversion technology. The input is the text data to be displayed, and the output is audio data.

[2068] Step 10: The user listens to the audio advice played from the terminal and confirms the suggested meal menu. The input is audio data, and the output is information about the suggested menu.

[2069] This series of processes allows users to easily obtain optimal food menus that can reduce the burden of raising children.

[2070] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[2071] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2072] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2073] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2074] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2075] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2076] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2077] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2078] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2079] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2080] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2081] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2082] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2083] 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.

[2084] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2085] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2086] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2087] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2088] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2089] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2090] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2091] The following is further disclosed regarding the above embodiment.

[2092] (Claim 1)

[2093] means for converting voice input from a user into text data;

[2094] means for transmitting the converted text data to a server;

[2095] means for the server to process the received text data and retrieve and generate corresponding advice or information;

[2096] means for converting the generated advice or information back from text to speech and replying to the user;

[2097] A means for accumulating childcare information of a user and generating an individually customized childcare guide;

[2098] A system including:

[2099] (Claim 2)

[2100] 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the same.

[2101] (Claim 3)

[2102] The system according to claim 1, further comprising a means for anonymizing and collecting user input data, and further improving the accuracy of childcare support information by selling the data to product development companies.

[2103] "Example 1"

[2104] (Claim 1)

[2105] means for converting voice input from a user into text data;

[2106] means for transmitting the converted text data to a server;

[2107] means for processing the received text data by the server and retrieving and generating corresponding advice or information from a database;

[2108] a means for converting the generated advice or information from text to speech using a generative AI model and replying to the user;

[2109] A means for accumulating childcare information of a user and generating an individually customized childcare guide;

[2110] A system including:

[2111] (Claim 2)

[2112] 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the same.

[2113] (Claim 3)

[2114] The system according to claim 1, further comprising a means for anonymizing and collecting user input data, and further improving the accuracy of childcare support information by selling the data to product development companies.

[2115] "Application Example 1"

[2116] (Claim 1)

[2117] means for converting voice input from a user into text data;

[2118] means for transmitting the converted text data to a server;

[2119] means for the server to process the received text data and retrieve and generate corresponding advice or information;

[2120] means for converting the generated advice or information back from text to speech and replying to the user;

[2121] A means for accumulating childcare information of a user and generating an individually customized childcare guide;

[2122] means for suggesting healthy food and drink offerings when a user's question is diet-related;

[2123] A system including:

[2124] (Claim 2)

[2125] 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the same.

[2126] (Claim 3)

[2127] The system according to claim 1, further comprising a means for anonymizing and collecting user input data, and further improving the accuracy of childcare support information by selling the data to product development companies.

[2128] "Example 2: Combining Emotion Engines"

[2129] (Claim 1)

[2130] means for converting voice input from a user into text data;

[2131] means for transmitting the converted text data to a communication device;

[2132] means for processing the text data received by the communication device to retrieve and generate corresponding advice or information;

[2133] means for converting the generated advice or information back from text to speech and replying to the user;

[2134] means for extracting emotion data from the user's speech and customizing advice based on the emotion data;

[2135] A means for accumulating childcare information of a user and generating an individually customized childcare guide;

[2136] A system including:

[2137] (Claim 2)

[2138] 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the same.

[2139] (Claim 3)

[2140] The system according to claim 1, further comprising a means for anonymizing and collecting user input data, and further improving the accuracy of childcare support information by selling the data to product development companies.

[2141] "Application example 2 when combining emotion engines"

[2142] (Claim 1)

[2143] means for converting voice input from a user into text data;

[2144] means for transmitting the converted text data to a server;

[2145] means for the server to process the received text data and retrieve and generate corresponding advice or information;

[2146] means for converting the generated advice or information back from text to speech and replying to the user;

[2147] A means for accumulating childcare information of a user and generating an individually customized childcare guide;

[2148] A means for analyzing the emotional state of a user through emotion analysis and recommending an optimal menu based on the emotional state of the user;

[2149] A system including:

[2150] (Claim 2)

[2151] 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the same.

[2152] (Claim 3)

[2153] The system according to claim 1, further comprising a means for anonymizing and collecting user input data, and further improving the accuracy of childcare support information by selling the data to product development companies. [Explanation of symbols]

[2154] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for converting voice input from a user into text data; means for transmitting the converted text data to a server; means for the server to process the received text data and retrieve and generate corresponding advice or information; means for converting the generated advice or information back from text to speech and replying to the user; A means for accumulating childcare information of a user and generating an individually customized childcare guide; A system including:

2. 2. The system according to claim 1, further comprising means for receiving the user's worries and complaints by voice input and providing appropriate counseling and advice regarding the worries and complaints.

3. 2. The system according to claim 1, further comprising means for anonymizing and collecting user input data, and further improving the accuracy of the childcare support information by selling the data to product development companies.

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