System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting a user's voice; means for converting the user's voice into text data; means for analyzing the text data to understand a user's intention; means for acquiring location information; means for searching for and acquiring related data based on the location information; means for presenting the related data to the user; means for allowing the user to select the presented related data; and means for providing detailed information based on the selected data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's world, many applications are designed for specific purposes, creating the problem of users having to switch between different applications. For elderly users who are unfamiliar with smartphones and users who find using many apps stressful, switching between multiple applications to achieve their goals can be extremely difficult. The objective of this invention is to solve this problem by providing an environment in which users can simply and intuitively obtain the information they need and take action. [Means for solving the problem]

[0005] The present invention provides a system including: a means for inputting user speech; a means for converting the user speech into text data; a means for analyzing the text data to understand the user's intent; a means for acquiring location information; a means for searching for and acquiring related data based on the location information; a means for presenting the related data to the user; a means for allowing the user to select from the presented related data; and a means for providing detailed information based on the selected data. Specifically, when a user vocally inputs "I want to eat a delicious lunch," a speech recognition engine converts this into text, and an analysis engine interprets the user's intent. The system then acquires current location information and searches for and acquires information about nearby restaurants. The acquired restaurant information is presented to the user, and when the user selects a restaurant, route guidance to the selected restaurant and weather information are provided. In this way, users can obtain the information they need in a single system and take action smoothly without having to switch between multiple applications.

[0006] "User voice" refers to voice data uttered by a user, and this data is converted into text data during the voice recognition process.

[0007] "Text data" refers to character information converted by speech recognition means and is used for natural language processing.

[0008] "Natural language processing" is a technology that analyzes text data and understands its meaning and context, and is used to understand user intent.

[0009] "Location information" is data indicating the user's current location, and is obtained using technology such as GPS.

[0010] "Related data" is information that is searched based on the user's intent, and includes restaurant information, menus, reviews, weather information, and the like.

[0011] "Presenting" is the act of the system displaying or audibly announcing information to the user.

[0012] "Selection" is the act of the user specifying a particular option from a plurality of options presented.

[0013] "Detailed Information" is additional information related to the particular option selected by the user, including, for example, route directions and weather forecasts.

[0014] "Route guidance" is information showing the route from the user's current location to the destination, and is provided in the form of a map or text.

[0015] "Weather information" is data relating to current and future weather, and is information that users need when they go out. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. The specific operation of the system will be explained below in natural language.

[0038] System Overview

[0039] 1. User voice input and conversion

[0040] User: Speaks, "I want to eat a delicious lunch."

[0041] Device: Uses a microphone to capture the user's voice.

[0042] Device: Uses a speech recognition engine to convert speech into text data.

[0043] 2. Analyzing User Intent

[0044] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[0045] Device: Identify relevant categories and set search criteria.

[0046] 3. Obtaining location information

[0047] Terminal: Obtains the user's current location using a GPS module.

[0048] Device: Sends current location information to the server.

[0049] 4. Searching and retrieving relevant data

[0050] Server: Searches the database for nearby restaurant information based on the current location information.

[0051] Server: Collects data such as menus, reviews, and ratings for each relevant restaurant from an external API.

[0052] 5. Restaurant recommendations

[0053] Server: Selects highly rated restaurants based on collected data and generates a list.

[0054] Server: Sends the generated list to the terminal.

[0055] Terminal: Display to the user "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0056] 6. Your Choices and Details

[0057] User: Selects Restaurant B.

[0058] Terminal: Confirms the user's selection and sends the information to the server.

[0059] Server: Get detailed route guidance information and weather information for Restaurant B.

[0060] Server: Sends the acquired information to the terminal.

[0061] Terminal: Displays detailed route directions and weather information to the user.

[0062] Specific examples

[0063] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[0064] The above is an embodiment of the present invention.

[0065] The processing flow will be explained below.

[0066] Step 1: Enter user voice

[0067] User: Says, "I want to eat a delicious lunch."

[0068] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[0069] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[0070] Step 2: Analyzing the text data

[0071] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[0072] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[0073] Step 3: Obtaining location information

[0074] Device: Uses the GPS module to obtain the user's current location.

[0075] Device: Sends current location information to the server.

[0076] Step 4: Search for restaurant information

[0077] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0078] Server: Lists multiple candidate restaurants as search results.

[0079] Step 5: Get restaurant details

[0080] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0081] Server: Combines the collected information and sorts the restaurants by highest rating.

[0082] Step 6: Present the restaurant list

[0083] Server: Sends the consolidated restaurant list to the device.

[0084] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0085] Step 7: Selecting Users

[0086] User: Says, "Restaurant B is good."

[0087] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0088] Terminal: Parse the converted text and check the user's selections.

[0089] Step 8: Providing directions and weather information

[0090] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0091] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0092] Server: Obtains real-time weather information from an external weather API.

[0093] Server: Sends route guidance and weather information to the device.

[0094] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0095] Step 9: Final confirmation and guidance

[0096] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[0097] User: When ready, follow the instructions on the device to go to Restaurant B.

[0098] Example 1

[0099] 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."

[0100] Conventional information provision systems that use user voice have difficulty accurately understanding the user's intent and providing relevant information quickly and accurately. Even when providing information using location information, the system may not be able to present the most appropriate information for the user. Furthermore, when providing detailed information, the system may not be able to include the accurate information the user is looking for. It is necessary to solve these problems and provide more useful information to users.

[0101] 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.

[0102] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for the detailed information providing means to select related data based on an evaluation. This makes it possible to accurately understand the user's intention and quickly provide the most suitable related data for the user by utilizing the location information.

[0103] The "means for inputting user voice" is a function that allows a user to input voice into the system using a voice input device such as a microphone.

[0104] The "means for converting user voice into text data" is a function for converting voice data into text data using a voice recognition engine or the like.

[0105] "Means for analyzing text data to understand user intent" refers to a function that uses natural language processing technology to analyze and understand the content and intent of a user's speech from text data.

[0106] "Means for acquiring location information" refers to a function for acquiring the user's current location using a GPS module or other location measurement technology.

[0107] "Means for searching and obtaining related data based on location information" refers to a function that searches for and obtains related information from a database or external API based on the obtained location information.

[0108] The "means for presenting related data to the user" is a function for displaying the acquired related data on the user's terminal.

[0109] The "means for allowing the user to select the related data presented" is a function that allows the user to select desired information from the presented data.

[0110] The "means for providing detailed information based on selected data" is a function for obtaining and providing more detailed information to the user based on the data selected by the user.

[0111] The "means for the detailed information providing means to select related data based on evaluation" is a function that evaluates the collected related data and selects and provides data with high evaluations.

[0112] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. To implement the system, the following hardware and software are required:

[0113] Hardware

[0114] Device: Smartphone or tablet equipped with a microphone and GPS module

[0115] Server: Cloud server with database management system

[0116] software

[0117] Speech recognition engine: Google Speech-to-Text API

[0118] Natural language processing module: OpenAI's GPT-3

[0119] Database: MongoDB

[0120] External APIs: Yelp API, Google Maps API, and OpenWeatherMap API

[0121] This system operates in the following procedure.

[0122] 1. User voice input and conversion

[0123] The user uses the microphone on their smartphone to say, "I want to eat a delicious lunch." The device captures the user's voice using the microphone and converts it into text data using the Google Speech-to-Text API.

[0124] 2. Analyzing User Intent

[0125] The device then uses a natural language processing module to analyze the converted text and understand that the user is looking for a "delicious lunch." The analysis uses OpenAI's GPT-3 to extract related topics and keywords.

[0126] 3. Obtaining location information

[0127] The device acquires the user's current location using the GPS module and sends the acquired latitude and longitude to the server.

[0128] 4. Searching and retrieving relevant data

[0129] The server searches for nearby restaurant information from a database (MongoDB) based on the location information sent, and also collects data such as menus, reviews, and ratings for each related restaurant from an external API (Yelp API).

[0130] 5. Restaurant recommendations

[0131] The server selects highly rated restaurants based on the collected data and generates a list. The generated list is sent to the device, which then displays a message to the user saying, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0132] 6. Your Choices and Details

[0133] When the user selects Restaurant B, the device sends that information to the server. The server obtains detailed route guidance information to Restaurant B using the Google Maps API and weather information using the OpenWeatherMap API. The obtained information is sent to the device, and the device displays detailed route guidance and weather information to the user.

[0134] Specific examples

[0135] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[0136] Prompt Sentence Examples

[0137] By inputting the following prompt sentence into the generative AI model, information can be obtained to understand the overview of this system.

[0138] "When a user says they want to have a delicious lunch, explain how the speech recognition engine converts that information into text and then the natural language processing module analyzes it. Also explain how relevant restaurant information is searched for and presented."

[0139] The above is an embodiment of the present invention.

[0140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0141] Step 1:

[0142] The user speaks into the smartphone's microphone, saying, "I want to eat a delicious lunch."

[0143] Input: User voice

[0144] Output: Captured audio data

[0145] The device uses a microphone to capture the user's voice, and the voice signal is digitized by an audio input device.

[0146] Step 2:

[0147] The device sends the captured voice data to the Google Speech-to-Text API, which converts the voice data into text data.

[0148] Input: Captured audio data

[0149] Output: Converted text data

[0150] Specifically, code is executed to send the captured audio data to the API, and the returned text data is retrieved.

[0151] Step 3:

[0152] The device analyzes the converted text data using a natural language processing module (e.g., OpenAI's GPT-3) to understand the user's intent.

[0153] Input: Converted text data

[0154] Output: User intent

[0155] Text data is input into the AI ​​as a prompt, and keywords (e.g., "delicious," "lunch," "want to eat") are extracted from the response to identify the user's intent.

[0156] Step 4:

[0157] The terminal sets search conditions based on the extracted keywords.

[0158] Input: User intent

[0159] Output: Search criteria

[0160] As a specific example, if it turns out that the user is looking for a "delicious lunch," this is set as a search condition.

[0161] Step 5:

[0162] The terminal obtains the user's current location using a GPS module.

[0163] Input: None

[0164] Output: Latitude and longitude information

[0165] The code runs to activate the GPS sensor and obtain the current latitude and longitude.

[0166] Step 6:

[0167] The terminal transmits the acquired current location information to the server.

[0168] Input: Latitude and longitude information

[0169] Output: Transferred location information

[0170] For security reasons, data is sent to the server using the HTTPS protocol.

[0171] Step 7:

[0172] The server searches a database (e.g., MongoDB) for nearby restaurant information based on the received location information.

[0173] Input: Transferred current location information

[0174] Output: Nearby restaurant information

[0175] Create a query based on latitude and longitude to retrieve relevant restaurant data.

[0176] Step 8:

[0177] The server collects data such as menus, reviews, and ratings for each relevant restaurant from an external API (e.g., Yelp API).

[0178] Input: Nearby restaurant information

[0179] Output: Detailed restaurant information (menu, reviews, ratings, etc.)

[0180] Send a request to the Yelp API using the restaurant ID, and parse the returned JSON data to obtain information.

[0181] Step 9:

[0182] The server selects highly rated restaurants based on the collected data.

[0183] Input: Detailed restaurant information

[0184] Output: A list of top-rated restaurants

[0185] The reviews and rating scores of each restaurant are statistically analyzed to create a list of the top restaurants.

[0186] Step 10:

[0187] The server transmits the generated list to the terminal.

[0188] Input: Top-rated restaurant list

[0189] Output: Transferred restaurant list

[0190] Code is executed to send the generated list to the terminal.

[0191] Step 11:

[0192] The terminal displays to the user, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0193] Input: Transferred restaurant list

[0194] Output: Information presented to the user

[0195] The UI uses a list view to layout and display the list.

[0196] Step 12:

[0197] The user selects Restaurant B from the list.

[0198] Input: User's selection (Restaurant B)

[0199] Output: Selected restaurant information

[0200] When the user presses the selection button, the selection information is stored in the terminal.

[0201] Step 13:

[0202] The terminal transmits the user's selection to the server.

[0203] Input: Selected restaurant information

[0204] Output: Data sent to the server

[0205] Code is executed to send a request containing the ID of the selected restaurant.

[0206] Step 14:

[0207] The server retrieves detailed route guidance information to the selected restaurant using the Google Maps API and retrieves weather information using the OpenWeatherMap API.

[0208] Input: Data to send to the server

[0209] Output: Detailed route directions and weather information

[0210] Route guidance information is obtained using the Google Maps API, and weather information is obtained using the OpenWeatherMap API.

[0211] Step 15:

[0212] The server transmits the acquired information to the terminal.

[0213] Input: Detailed driving directions and weather information

[0214] Output: Data sent to the terminal

[0215] Code is executed to transmit the obtained information to the terminal.

[0216] Step 16:

[0217] The device displays detailed route directions and weather information to the user.

[0218] Input: Data to send to the terminal

[0219] Output: Displayed route and weather information

[0220] It uses a map view to display routes and provides weather information in a text view.

[0221] (Application example 1)

[0222] 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."

[0223] In recent years, security management has become increasingly important, but conventional systems have had difficulty obtaining and providing real-time security information based on voice input. Furthermore, when users check the security status of their home or office while away from home, they have had to use multiple applications and devices, which is inconvenient. There is a need to solve these problems and provide security information efficiently through a single system.

[0224] 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.

[0225] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, and means for cooperating with a security system to acquire a security status. This allows a user to obtain security information in real time using voice input, and to quickly check the security status of their home or office even when they are away from home.

[0226] "User speech" refers to instructions or requests that a user inputs by voice.

[0227] "Means" refers to a method or apparatus for accomplishing a particular function or purpose.

[0228] "Text data" refers to character string data converted from speech by speech recognition.

[0229] "Natural language processing" is a technology that analyzes text data to understand human language and perform appropriate processing.

[0230] "Location information" refers to data that indicates a user's current geographic location.

[0231] "Related data" refers to all information provided by the server based on the user's request and location information.

[0232] "Presenting to the user" means that the system displays information to the user visually or audibly.

[0233] "Making a choice" refers to the act of encouraging a user to select a specific option from the information provided.

[0234] "Detailed information" refers to supplemental and specific information provided based on the data selected by the user.

[0235] "Security system" refers to any information system that ensures safety in a specific area.

[0236] "Security status" means data that indicates the current security status of an area monitored by a security system.

[0237] The system of the present invention inputs user speech, analyzes the speech, and provides related information. How to implement this system will be described below.

[0238] System Configuration and Operation

[0239] 1. User voice input and conversion

[0240] User: Uses the smartphone microphone to say, "What is the security situation in my office?"

[0241] Terminal: A speech recognition engine (for example, the speech_recognition library) is used to convert user speech into text data.

[0242] 2. Analyzing User Intent

[0243] Terminal: Uses natural language processing techniques (e.g., generative AI models) to understand user intent from text data.

[0244] Terminal: In this case, it is understood that the user wants to check the "security status of the office."

[0245] 3. Obtaining location information

[0246] On the device: Use a GPS module (e.g., the geopy library) to get the user's current location.

[0247] 4. Searching and retrieving relevant data

[0248] Server: Based on the user's intent and location, the server retrieves relevant security data from the security system, including surveillance camera footage, alarm logs, and access history.

[0249] 5. Analyze relevant data and present it to the user

[0250] Server: Analyzes the acquired security data and evaluates the current security situation.

[0251] Server: For example, it evaluates the security status as "normal" or "an unconfirmed intrusion has occurred" and sends the result to the terminal.

[0252] Terminal: Presents the evaluation results to the user visually or audibly.

[0253] Hardware and software used

[0254] Speech recognition engine: speech_recognition library

[0255] GPS module: geopy library

[0256] Natural Language Processing Technology: Generative AI Model

[0257] Security data acquisition: Security system API (general name)

[0258] Device: Smartphone

[0259] Specific examples

[0260] For example, if a user asks their smartphone, "What's the security situation in the office?" during lunchtime, the system will use GPS to determine that the user is near the office, query the security system, and obtain the office's surveillance camera footage and alarm information. It will then notify the user that "The security situation is normal."

[0261] Prompt Sentence Examples

[0262] "Develop a security guard assistant app that can detect security situations through voice and provide relevant information. For example, when a user asks, 'What is the security situation in my office?' the app will check their current location, retrieve the latest information from the security system, and provide it to the user."

[0263] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0264] Step 1: Capturing Audio Input

[0265] The user uses the microphone on their smartphone to say, "Tell me about the security situation in the office." This voice input is captured by the microphone and sent to the smartphone as voice data.

[0266] Step 2: Convert audio data to text

[0267] The device converts the captured voice data into text data using a voice recognition engine (for example, the speech_recognition library). The input is voice data and the output is text data. Specifically, the device analyzes the voice data and converts it into words and sentences.

[0268] Step 3: Analyze user intent

[0269] The device uses natural language processing technology (e.g., a generative AI model) to understand the user's intent from the text data. The input is the text data, and the output is the information the user wants to know (in this case, "Office security status"). This involves analyzing the text data and extracting the user's intent from verbs, nouns, and adjectives.

[0270] Step 4: Obtaining location information

[0271] The device uses a GPS module (for example, the geopy library) to obtain the user's current location. The input is a signal from the GPS sensor, and the output is latitude and longitude coordinate data. Specifically, the device receives satellite signals from the GPS sensor and calculates the current location based on them.

[0272] Step 5: Find and retrieve relevant data

[0273] The server retrieves relevant security data from the security system based on the user's intent and location information. The input is the user's intent and location information, and the output is security data (surveillance camera footage, alarm logs, entry and exit history). The server calls the security system's API to retrieve the necessary data.

[0274] Step 6: Analyze security data

[0275] The server analyzes the acquired security data and evaluates the current security situation. The input is the security data, and the output is the evaluation result of the security situation (for example, "The security situation is normal" or "An unconfirmed intrusion has occurred"). Specifically, each piece of data is analyzed to check for any abnormalities.

[0276] Step 7: Present information to the user

[0277] The server sends the evaluation results to the terminal, which then presents them to the user. The input is the security status evaluation result, and the output is a notification message to the user. The terminal displays the notification message to the user visually or audibly. For example, it may display "Security status is normal" on the screen or read it aloud.

[0278] 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.

[0279] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide relevant information. It also has the ability to recognize the user's emotions and adjust the data presentation method based on the emotions. The following describes the specific operation of the system in natural language.

[0280] System Overview

[0281] 1. User voice input and conversion

[0282] User: Says, "I want to eat a delicious lunch."

[0283] Device: Uses a microphone to capture the user's voice.

[0284] Device: Uses a speech recognition engine to convert speech into text data.

[0285] 2. Analyzing User Intent

[0286] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[0287] Device: Identify relevant categories and set search criteria.

[0288] 3. Obtaining location information

[0289] Terminal: Obtains the user's current location using a GPS module.

[0290] Device: Sends current location information to the server.

[0291] 4. Search for restaurant information

[0292] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0293] Server: Lists multiple candidate restaurants as search results.

[0294] 5. Get restaurant details

[0295] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0296] Server: Combines the collected information and sorts the restaurants by highest rating.

[0297] 6. Present a list of restaurants

[0298] Server: Sends the consolidated restaurant list to the device.

[0299] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0300] 7. Your Choices and Details

[0301] User: Says, "Restaurant B is good."

[0302] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0303] Terminal: Parse the converted text and check the user's selections.

[0304] 8. Providing route guidance and weather information

[0305] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0306] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0307] Server: Obtains real-time weather information from an external weather API.

[0308] Server: Sends route guidance and weather information to the device.

[0309] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0310] 9. Emotion Recognition with Emotion Engine

[0311] Terminal: The user's voice input is analyzed, and the emotion engine recognizes the user's emotions.

[0312] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device will quickly present information and provide guidance in a calm voice.

[0313] Specific examples

[0314] For example, if a user says "I want to eat a delicious lunch" at home, the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and weather information. Furthermore, the emotion engine recognizes the user's emotions and selects the appropriate information presentation method. This allows users to obtain all the information they need in one app and take action smoothly.

[0315] The above is an embodiment of the present invention.

[0316] The processing flow will be explained below.

[0317] Step 1: Enter user voice

[0318] User: Says, "I want to eat a delicious lunch."

[0319] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[0320] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[0321] Step 2: Analyzing the text data

[0322] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[0323] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[0324] Step 3: Obtaining location information

[0325] Terminal: Obtains the user's current location using a GPS module.

[0326] Device: Sends the acquired location information to the server.

[0327] Step 4: Search for restaurant information

[0328] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0329] Server: Lists multiple candidate restaurants as search results.

[0330] Step 5: Get restaurant details

[0331] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0332] Server: Combines the collected information and sorts the restaurants by highest rating.

[0333] Step 6: Present the restaurant list

[0334] Server: Sends the consolidated restaurant list to the device.

[0335] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0336] Step 7: Emotion Recognition with the Emotion Engine

[0337] Device: The emotion engine analyzes the user's voice input and recognizes the user's emotions. For example, it analyzes the tone, pitch, and speed of the user's voice to determine whether the user is excited or relaxed.

[0338] Step 8: Adjust information presentation based on emotions

[0339] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device displays information quickly and provides guidance in a calm voice. Conversely, if the user is relaxed, the device provides detailed explanations.

[0340] Step 9: Select User

[0341] User: Says, "Restaurant B is good."

[0342] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0343] Terminal: Parse the converted text and check the user's selections.

[0344] Step 10: Providing directions and weather information

[0345] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0346] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0347] Server: Obtains real-time weather information from an external weather API.

[0348] Server: Sends route guidance and weather information to the device.

[0349] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0350] Step 11: Final confirmation and guidance

[0351] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[0352] User: When ready, follow the instructions on the device to go to Restaurant B.

[0353] Example 2

[0354] 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."

[0355] While conventional speech recognition systems can convert a user's speech into text and understand their intent, they have the problem of being unable to consider the user's emotions when presenting information. This can result in inappropriate presentation of the information the user is looking for, or a poor user experience. In particular, when searching for restaurants or using navigation, it is important to provide the information users need quickly and appropriately, but conventional technologies fall short in this area.

[0356] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0357] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, means for performing emotion recognition, and means for adjusting the information presentation method based on the emotion recognition result. This enables appropriate and prompt information presentation taking the user's emotions into consideration, thereby improving the user experience.

[0358] A "means for inputting user voice" is a device or mechanism for capturing voice uttered by a user.

[0359] The "means for converting the user's voice into text data" refers to an algorithm or service that converts voice data into character string data.

[0360] The "means for analyzing the text data and understanding the user's intent" refers to a natural language processing technology or module for identifying the user's request or purpose from the text data.

[0361] "Means for obtaining location information" refers to a GPS module or other location identification technology for identifying the user's current location.

[0362] "Means for searching and acquiring relevant data based on the location information" refers to the process of searching for relevant information from a database or external API based on the acquired location information and collecting the necessary data.

[0363] "Means for presenting said relevant data to a user" refers to a mechanism or method for displaying collected information through a user interface.

[0364] The "means for allowing the user to select the related data presented" is a mechanism that provides an interaction for the user to make a selection from the presented information.

[0365] The "means for providing detailed information based on the selected data" is a process for collecting and displaying additional information related to the item selected by the user.

[0366] "Means for emotion recognition" refers to an algorithm or engine for recognizing the emotional state of a user from their voice or behavior.

[0367] The "means for adjusting the information presentation method based on the emotion recognition result" is a mechanism for changing the information presentation method according to the recognized emotion.

[0368] The present invention relates to a system that analyzes a user's voice input and provides relevant information based on the user's intentions and emotions. This system is realized by combining speech recognition technology that converts user speech into text, natural language processing technology, technology for acquiring location information, technology for searching related data, and technology for recognizing emotions.

[0369] Specifically, the following hardware and software are used:

[0370] 1. The device has a built-in microphone, GPS module, display, and speech recognition engine. The microphone is used to capture the user's voice, and the speech is converted into text data using a speech recognition engine (e.g., a speech recognition API). A specific example is the Google Cloud Speech-to-Text API.

[0371] 2. The device analyzes the text data using a natural language processing module (e.g., a natural language processing API) to understand the user's intent. A specific example is the Google Cloud Natural Language API.

[0372] 3. The device obtains the user's current location using a GPS module. The device sends the location information to the server. Based on this location information, the server searches for relevant data. The server searches for nearby restaurant information using a database or an external API (e.g., a restaurant search API). Specific examples include the Yelp API and Google Places API.

[0373] 4. The server collects detailed information about the restaurants (menus, reviews, ratings, etc.) found in the search results, integrates the information, sorts it by highest rating, and then sends the integrated information to the device.

[0374] 5. The device displays a list of restaurants for the user to select from, and provides an interface for the user to confirm their selection by voice input again.

[0375] 6. The device requests route guidance and weather information from the server based on the selected restaurant details. The server generates detailed route guidance and retrieves real-time weather information from an external weather API (e.g., a weather information API). Specific examples include Google Maps API and OpenWeatherMap API.

[0376] 7. The device analyzes the voice data using an emotion recognition engine (e.g., emotion recognition API) to recognize the user's emotions. A specific example is IBM Watson Tone Analyzer.

[0377] 8. The device adjusts the way it presents information based on the emotion recognition results. For example, if the user is excited, it will promptly present information and provide guidance in a calm voice.

[0378] Specific examples

[0379] For example, if a user says, "I want a delicious lunch," the device captures this with the microphone and converts it into text using the Google Cloud Speech-to-Text API. The text is then analyzed using the Google Cloud Natural Language API to identify the intent of "a delicious lunch." The device obtains its current location using GPS and searches for nearby restaurant information using the Yelp API. The server consolidates the collected restaurant details, sorts them by highest rating, and sends them to the device. If the user selects "Restaurant B is good" by voice, the device provides route guidance using the Google Maps API and retrieves and displays weather information from the OpenWeatherMap API. The device then uses IBM Watson Tone Analyzer to recognize the user's emotions and selects the optimal way to present information.

[0380] Prompt Sentence Examples

[0381] 1. "When a user says they want a delicious lunch, what prompts would you use to design a system that converts that speech to text and provides relevant restaurant information?"

[0382] 2. "Please provide a prompt to provide directions and weather information to a user-specified restaurant."

[0383] 3. "Generate a prompt for designing a system that uses an emotion engine to recognize a user's emotions and adjust the way information is presented based on the results."

[0384] The above is an embodiment of the present invention.

[0385] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0386] System program processing flow

[0387] Step 1: Input and convert user speech

[0388] The user says, "I want to eat a delicious lunch." The device captures this speech using the built-in microphone. The captured speech data is sent to a speech recognition engine such as the Google Cloud Speech-to-Text API and converted into text data. The input is the user's speech data, and the output is the text data obtained from the speech recognition engine.

[0389] Step 2: Analyze user intent

[0390] The device receives the converted text data, "I want to eat a delicious lunch." It then uses a natural language processing module, such as the Google Cloud Natural Language API, to analyze this text and identify the user's intent. In this case, it understands that the user's intent is "Find a restaurant that serves delicious lunch." The input is the text data, and the output is keywords related to the analyzed intent.

[0391] Step 3: Obtaining location information

[0392] The device uses a GPS module to obtain the user's current location. The location information (latitude and longitude) is sent to the server. The input is the location data obtained from the GPS module, and the output is the location information sent to the server.

[0393] Step 4: Search for restaurant information

[0394] Based on the received location information, the server searches for nearby restaurant information by requesting it from a database or an external API (e.g., Yelp API). Here, the server lists restaurants where you can have a delicious lunch based on the user's current location. The input is the location information and the user's intention, and the output is the list of restaurant information.

[0395] Step 5: Get restaurant details

[0396] The server collects detailed information (menus, reviews, ratings, etc.) about the listed restaurants using the Google Places API, etc. The detailed information is integrated and sorted in descending order of ratings. The input is a list of restaurant candidates, and the output is a list of restaurants with the integrated detailed information.

[0397] Step 6: Present the restaurant list

[0398] The server sends the integrated restaurant list to the terminal. The terminal displays the list to the user and asks, "I found restaurants A, B, and C. Which one do you want?" The input is the restaurant list from the server, and the output is the list display and voice guidance through the user interface.

[0399] Step 7: Select user and provide details

[0400] The user selects "Restaurant B is good." The device captures the voice again and converts it into text using a speech recognition engine. This text data is analyzed and the user's selection is confirmed. The input is the user's voice data, and the output is the text data of the selected restaurant.

[0401] Step 8: Providing directions and weather information

[0402] The device requests route guidance and weather information from the server based on the location of the selected restaurant. The server uses the Google Maps API to generate detailed driving directions and the OpenWeatherMap API to retrieve real-time weather information. These data are sent to the device. The input is the restaurant location data, and the output is route guidance and weather information, which the device displays to the user.

[0403] Step 9: Emotion Recognition with the Emotion Engine

[0404] The device analyzes the user's voice using an emotion recognition engine (for example, IBM Watson Tone Analyzer) to identify the user's emotion. Based on the emotion recognition results, the device adjusts the way information is presented. The input is voice data and analysis results, and the output is a method of presenting information according to the emotion. For example, if the user is excited, information is presented quickly and guidance is given in a calm voice.

[0405] (Application example 2)

[0406] 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."

[0407] Conventional voice recognition systems were able to convert a user's voice input into text data, analyze their intent, and provide relevant information. However, they lacked the ability to recognize the user's emotions and adjust the way information is presented based on that. Furthermore, there were issues with navigation in virtual stores and providing detailed product information, making it difficult to create an environment where users could comfortably shop. Furthermore, users often found it difficult to navigate within a store or select products, which could be stressful.

[0408] The identification process by the identification 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 inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for recognizing the user's emotions and adjusting the presentation method of the detailed information based on the emotions. This enables the provision of information that takes user emotions into consideration, thereby improving the shopping experience in the virtual store. Specifically, it is possible to change the speed and content of information presentation depending on emotions, providing an environment in which users can comfortably search for and select products.

[0409] The "means for inputting user voice" is a function for acquiring voice uttered by the user through an input device such as a microphone within the device.

[0410] The "means for converting the user's voice into text data" refers to a voice recognition engine or software that converts the acquired voice data into text format.

[0411] The "means for analyzing the text data and understanding the user's intention" is a technology that uses a natural language processing module based on the text data to analyze the user's intention and request.

[0412] "Means for obtaining location information" refers to a function for obtaining information about the user's current location using a GPS module or other location information services.

[0413] "Means for searching and acquiring related data based on the location information" refers to algorithms and database search techniques for searching and acquiring related data or information based on the acquired location information.

[0414] The "means for presenting the related data to the user" refers to a display device or interface that presents the searched and acquired data to the user visually, audibly, or in other ways.

[0415] The "means for allowing the user to select related data presented" refers to a technique for providing an interface or operating means that allows the user to select specific information from the displayed data.

[0416] "Means for providing detailed information based on the selected data" refers to functions and technologies for collecting detailed information related to the data selected by the user and providing it to the user.

[0417] "Means for recognizing the user's emotions and adjusting the way in which the detailed information is presented based on those emotions" refers to an algorithm or system that recognizes emotions from the user's voice, facial expressions, etc., and adjusts the way in which information is presented (speed, content, etc.) according to the user's emotional state.

[0418] "Virtual store navigation information" is information that provides route guidance, direction, location information, and the like that are necessary when a user moves within a virtual space.

[0419] The present invention is a system that adaptively processes everything from user voice input to providing detailed information based on the user's emotions. The system of the present invention is realized using various hardware and software components. The specific hardware and software used are shown below, and the operation of the system is explained.

[0420] Hardware and software used

[0421] Hardware: Smartphones, smart glasses, head-mounted displays

[0422] software:

[0423] Speech recognition engine: Uses the Google Speech-to-Text API to convert voice data into text.

[0424] Natural Language Processing: Use the Google Natural Language API to analyze the converted text data.

[0425] Emotion Recognition Engine: Uses IBM Watson Tone Analyzer to recognize user emotions.

[0426] Location information acquisition: Uses "Google Maps API" to acquire the user's current location.

[0427] Database: Uses "Firebase Firestore" to manage detailed information.

[0428] System Operation

[0429] User voice input

[0430] Users input voice commands using, for example, a smartphone, smart glasses, or a head-mounted display. The device's built-in microphone captures the voice and converts it into text data using a speech recognition engine.

[0431] Natural language processing and intent analysis

[0432] The converted text data is sent to a natural language processing module to analyze the user's intent, thereby understanding the specific information or service the user is seeking (e.g., searching for a product in a virtual store).

[0433] Acquiring location information and searching related data

[0434] The user's location information is acquired using a GPS module, and related data (e.g., location information of nearby products) is searched for. Based on the acquired location information and the user's intent, related data is searched for.

[0435] Data Presentation and User Selection

[0436] The retrieved related data is presented to the user, from which the user can select specific information, and based on the selected data, further detailed information is provided.

[0437] Emotion recognition and information provision coordination

[0438] The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotions, and adjusts how information is presented based on this analysis. For example, if the user is in a hurry, the system will present information more quickly.

[0439] Specific examples

[0440] Below are some specific examples for reference.

[0441] User Scenario

[0442] The user puts on the smart glasses and says, "I'm looking for a new smartphone at the virtual mall." The system converts this speech into text and analyzes the user's intent. Based on the analysis results, the system obtains information about the nearest smartphone store from the user's current location. Related products are presented to the user, providing detailed information. Further details, such as reviews, are displayed for the product selected by the user. The way information is presented is adjusted according to the user's emotions (excitement, impatience, etc.).

[0443] Prompt Sentence Examples

[0444] "If I want to easily get the information I need to optimize my system, how do I get started?"

[0445] These examples and prompts allow users to understand how the system is actually used and how information is presented. This invention allows users to easily obtain the information they need on the spot and respond appropriately according to their emotions.

[0446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0447] Step 1:

[0448] A user inputs voice using a smart device (smartphone, smart glasses, head-mounted display), and the input voice is captured by a microphone in the device.

[0449] Input: User speech (e.g., "I'm looking for a new phone at the virtual mall.")

[0450] Output: Audio data

[0451] Step 2:

[0452] The device receives the voice data and converts it into text data using a voice recognition engine (Google Speech-to-Text API).

[0453] Input: Audio data

[0454] Output: Text data (e.g., "Looking for a new smartphone at the virtual mall")

[0455] Step 3:

[0456] The device sends the converted text data to a natural language processing module (Google Natural Language API) to analyze the user's intent.

[0457] Input: Text data

[0458] Output: User intent (e.g., smartphone search)

[0459] Step 4:

[0460] The terminal obtains the user's current location information using a GPS module and acquires location information.

[0461] Input: None (location information is obtained internally by the system)

[0462] Output: Current location information (e.g. longitude and latitude)

[0463] Step 5:

[0464] Based on the current location information and the user's intent, the server searches and retrieves relevant data (e.g., nearby smartphone stores) from a database (Firebase Firestore).

[0465] Input: current location, user intent

[0466] Output: Related data (e.g., information on nearby smartphone stores)

[0467] Step 6:

[0468] The terminal presents the acquired related data to the user and prompts the user to make a selection.

[0469] Input: relevant data

[0470] Output: Presented data (e.g., smartphone sales area list)

[0471] Step 7:

[0472] The user selects specific information from the presented data, and the selected information is received by the device. The user's selection is made by voice or touch operation.

[0473] Input: User selection (e.g. "Select this phone")

[0474] Output: Selected data

[0475] Step 8:

[0476] Based on the selected data, the server collects more detailed information (e.g., reviews, stock status) from external APIs and sends it to the device.

[0477] Input: Selected data

[0478] Output: Detailed information (e.g. smartphone reviews, stock status)

[0479] Step 9:

[0480] The device analyzes the tone of the user's voice and recognizes the user's emotions using an emotion engine (IBM Watson Tone Analyzer).

[0481] Input: User voice data

[0482] Output: Emotion recognition result (e.g., excitement, impatience)

[0483] Step 10:

[0484] The device adjusts how detailed information is presented based on the emotion recognition results, for example, by presenting information more quickly if the user is excited.

[0485] Input: Emotion recognition results, detailed information

[0486] Output: Adjusted detailed information

[0487] In this way, the system based on the present invention can provide appropriate information based on the user's voice input, and further adjust the presentation method according to the user's emotions.

[0488] 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.

[0489] 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.

[0490] 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.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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).

[0498] 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.

[0499] 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.

[0500] 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.

[0501] 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.

[0502] 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.

[0503] 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."

[0504] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. The specific operation of the system will be explained below in natural language.

[0505] System Overview

[0506] 1. User voice input and conversion

[0507] User: Speaks, "I want to eat a delicious lunch."

[0508] Device: Uses a microphone to capture the user's voice.

[0509] Device: Uses a speech recognition engine to convert speech into text data.

[0510] 2. Analyzing User Intent

[0511] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[0512] Device: Identify relevant categories and set search criteria.

[0513] 3. Obtaining location information

[0514] Terminal: Obtains the user's current location using a GPS module.

[0515] Device: Sends current location information to the server.

[0516] 4. Searching and retrieving relevant data

[0517] Server: Searches the database for nearby restaurant information based on the current location information.

[0518] Server: Collects data such as menus, reviews, and ratings for each relevant restaurant from an external API.

[0519] 5. Restaurant recommendations

[0520] Server: Selects highly rated restaurants based on collected data and generates a list.

[0521] Server: Sends the generated list to the terminal.

[0522] Terminal: Display to the user "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0523] 6. Your Choices and Details

[0524] User: Selects Restaurant B.

[0525] Terminal: Confirms the user's selection and sends the information to the server.

[0526] Server: Get detailed route guidance information and weather information for Restaurant B.

[0527] Server: Sends the acquired information to the terminal.

[0528] Terminal: Displays detailed route directions and weather information to the user.

[0529] Specific examples

[0530] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[0531] The above is an embodiment of the present invention.

[0532] The processing flow will be explained below.

[0533] Step 1: Enter user voice

[0534] User: Says, "I want to eat a delicious lunch."

[0535] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[0536] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[0537] Step 2: Analyzing the text data

[0538] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[0539] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[0540] Step 3: Obtaining location information

[0541] Device: Uses the GPS module to obtain the user's current location.

[0542] Device: Sends current location information to the server.

[0543] Step 4: Search for restaurant information

[0544] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0545] Server: Lists multiple candidate restaurants as search results.

[0546] Step 5: Get restaurant details

[0547] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0548] Server: Combines the collected information and sorts the restaurants by highest rating.

[0549] Step 6: Present the restaurant list

[0550] Server: Sends the consolidated restaurant list to the device.

[0551] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0552] Step 7: Selecting Users

[0553] User: Says, "Restaurant B is good."

[0554] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0555] Terminal: Parse the converted text and check the user's selections.

[0556] Step 8: Providing directions and weather information

[0557] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0558] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0559] Server: Obtains real-time weather information from an external weather API.

[0560] Server: Sends route guidance and weather information to the device.

[0561] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0562] Step 9: Final confirmation and guidance

[0563] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[0564] User: When ready, follow the instructions on the device to go to Restaurant B.

[0565] Example 1

[0566] 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."

[0567] Conventional information provision systems that use user voice have difficulty accurately understanding the user's intent and providing relevant information quickly and accurately. Even when providing information using location information, the system may not be able to present the most appropriate information for the user. Furthermore, when providing detailed information, the system may not be able to include the accurate information the user is looking for. It is necessary to solve these problems and provide more useful information to users.

[0568] 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.

[0569] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for the detailed information providing means to select related data based on an evaluation. This makes it possible to accurately understand the user's intention and quickly provide the most suitable related data for the user by utilizing the location information.

[0570] The "means for inputting user voice" is a function that allows a user to input voice into the system using a voice input device such as a microphone.

[0571] The "means for converting user voice into text data" is a function for converting voice data into text data using a voice recognition engine or the like.

[0572] "Means for analyzing text data to understand user intent" refers to a function that uses natural language processing technology to analyze and understand the content and intent of a user's speech from text data.

[0573] "Means for acquiring location information" refers to a function for acquiring the user's current location using a GPS module or other location measurement technology.

[0574] "Means for searching and obtaining related data based on location information" refers to a function that searches for and obtains related information from a database or external API based on the obtained location information.

[0575] The "means for presenting related data to the user" is a function for displaying the acquired related data on the user's terminal.

[0576] The "means for allowing the user to select the related data presented" is a function that allows the user to select desired information from the presented data.

[0577] The "means for providing detailed information based on selected data" is a function for obtaining and providing more detailed information to the user based on the data selected by the user.

[0578] The "means for the detailed information providing means to select related data based on evaluation" is a function that evaluates the collected related data and selects and provides data with high evaluations.

[0579] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. To implement the system, the following hardware and software are required:

[0580] Hardware

[0581] Device: Smartphone or tablet equipped with a microphone and GPS module

[0582] Server: Cloud server with database management system

[0583] software

[0584] Speech recognition engine: Google Speech-to-Text API

[0585] Natural language processing module: OpenAI's GPT-3

[0586] Database: MongoDB

[0587] External APIs: Yelp API, Google Maps API, and OpenWeatherMap API

[0588] This system operates in the following procedure.

[0589] 1. User voice input and conversion

[0590] The user uses the microphone on their smartphone to say, "I want to eat a delicious lunch." The device captures the user's voice using the microphone and converts it into text data using the Google Speech-to-Text API.

[0591] 2. Analyzing User Intent

[0592] The device then uses a natural language processing module to analyze the converted text and understand that the user is looking for a "delicious lunch." The analysis uses OpenAI's GPT-3 to extract related topics and keywords.

[0593] 3. Obtaining location information

[0594] The device acquires the user's current location using the GPS module and sends the acquired latitude and longitude to the server.

[0595] 4. Searching and retrieving relevant data

[0596] The server searches for nearby restaurant information from a database (MongoDB) based on the location information sent, and also collects data such as menus, reviews, and ratings for each related restaurant from an external API (Yelp API).

[0597] 5. Restaurant recommendations

[0598] The server selects highly rated restaurants based on the collected data and generates a list. The generated list is sent to the device, which then displays a message to the user saying, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0599] 6. Your Choices and Details

[0600] When the user selects Restaurant B, the device sends that information to the server. The server obtains detailed route guidance information to Restaurant B using the Google Maps API and weather information using the OpenWeatherMap API. The obtained information is sent to the device, and the device displays detailed route guidance and weather information to the user.

[0601] Specific examples

[0602] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[0603] Prompt Sentence Examples

[0604] By inputting the following prompt sentence into the generative AI model, information can be obtained to understand the overview of this system.

[0605] "When a user says they want to have a delicious lunch, explain how the speech recognition engine converts that information into text and then the natural language processing module analyzes it. Also explain how relevant restaurant information is searched for and presented."

[0606] The above is an embodiment of the present invention.

[0607] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0608] Step 1:

[0609] The user speaks into the smartphone's microphone, saying, "I want to eat a delicious lunch."

[0610] Input: User voice

[0611] Output: Captured audio data

[0612] The device uses a microphone to capture the user's voice, and the voice signal is digitized by an audio input device.

[0613] Step 2:

[0614] The device sends the captured voice data to the Google Speech-to-Text API, which converts the voice data into text data.

[0615] Input: Captured audio data

[0616] Output: Converted text data

[0617] Specifically, code is executed to send the captured audio data to the API, and the returned text data is retrieved.

[0618] Step 3:

[0619] The device analyzes the converted text data using a natural language processing module (e.g., OpenAI's GPT-3) to understand the user's intent.

[0620] Input: Converted text data

[0621] Output: User intent

[0622] Text data is input into the AI ​​as a prompt, and keywords (e.g., "delicious," "lunch," "want to eat") are extracted from the response to identify the user's intent.

[0623] Step 4:

[0624] The terminal sets search conditions based on the extracted keywords.

[0625] Input: User intent

[0626] Output: Search criteria

[0627] As a specific example, if it turns out that the user is looking for a "delicious lunch," this is set as a search condition.

[0628] Step 5:

[0629] The terminal obtains the user's current location using a GPS module.

[0630] Input: None

[0631] Output: Latitude and longitude information

[0632] The code runs to activate the GPS sensor and obtain the current latitude and longitude.

[0633] Step 6:

[0634] The terminal transmits the acquired current location information to the server.

[0635] Input: Latitude and longitude information

[0636] Output: Transferred location information

[0637] For security reasons, data is sent to the server using the HTTPS protocol.

[0638] Step 7:

[0639] The server searches a database (e.g., MongoDB) for nearby restaurant information based on the received location information.

[0640] Input: Transferred current location information

[0641] Output: Nearby restaurant information

[0642] Create a query based on latitude and longitude to retrieve relevant restaurant data.

[0643] Step 8:

[0644] The server collects data such as menus, reviews, and ratings for each relevant restaurant from an external API (e.g., Yelp API).

[0645] Input: Nearby restaurant information

[0646] Output: Detailed restaurant information (menu, reviews, ratings, etc.)

[0647] Send a request to the Yelp API using the restaurant ID, and parse the returned JSON data to obtain information.

[0648] Step 9:

[0649] The server selects highly rated restaurants based on the collected data.

[0650] Input: Detailed restaurant information

[0651] Output: A list of top-rated restaurants

[0652] The reviews and rating scores of each restaurant are statistically analyzed to create a list of the top restaurants.

[0653] Step 10:

[0654] The server transmits the generated list to the terminal.

[0655] Input: Top-rated restaurant list

[0656] Output: Transferred restaurant list

[0657] Code is executed to send the generated list to the terminal.

[0658] Step 11:

[0659] The terminal displays to the user, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0660] Input: Transferred restaurant list

[0661] Output: Information presented to the user

[0662] The UI uses a list view to layout and display the list.

[0663] Step 12:

[0664] The user selects Restaurant B from the list.

[0665] Input: User's selection (Restaurant B)

[0666] Output: Selected restaurant information

[0667] When the user presses the selection button, the selection information is stored in the terminal.

[0668] Step 13:

[0669] The terminal transmits the user's selection to the server.

[0670] Input: Selected restaurant information

[0671] Output: Data sent to the server

[0672] Code is executed to send a request containing the ID of the selected restaurant.

[0673] Step 14:

[0674] The server retrieves detailed route guidance information to the selected restaurant using the Google Maps API and retrieves weather information using the OpenWeatherMap API.

[0675] Input: Data to send to the server

[0676] Output: Detailed route directions and weather information

[0677] Route guidance information is obtained using the Google Maps API, and weather information is obtained using the OpenWeatherMap API.

[0678] Step 15:

[0679] The server transmits the acquired information to the terminal.

[0680] Input: Detailed driving directions and weather information

[0681] Output: Data sent to the terminal

[0682] Code is executed to transmit the obtained information to the terminal.

[0683] Step 16:

[0684] The device displays detailed route directions and weather information to the user.

[0685] Input: Data to send to the terminal

[0686] Output: Displayed route and weather information

[0687] It uses a map view to display routes and provides weather information in a text view.

[0688] (Application example 1)

[0689] 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."

[0690] In recent years, security management has become increasingly important, but conventional systems have had difficulty obtaining and providing real-time security information based on voice input. Furthermore, when users check the security status of their home or office while away from home, they have had to use multiple applications and devices, which is inconvenient. There is a need to solve these problems and provide security information efficiently through a single system.

[0691] 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.

[0692] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, and means for cooperating with a security system to acquire a security status. This allows a user to obtain security information in real time using voice input, and to quickly check the security status of their home or office even when they are away from home.

[0693] "User speech" refers to instructions or requests that a user inputs by voice.

[0694] "Means" refers to a method or apparatus for accomplishing a particular function or purpose.

[0695] "Text data" refers to character string data converted from speech by speech recognition.

[0696] "Natural language processing" is a technology that analyzes text data to understand human language and perform appropriate processing.

[0697] "Location information" refers to data that indicates a user's current geographic location.

[0698] "Related data" refers to all information provided by the server based on the user's request and location information.

[0699] "Presenting to the user" means that the system displays information to the user visually or audibly.

[0700] "Making a choice" refers to the act of encouraging a user to select a specific option from the information provided.

[0701] "Detailed information" refers to supplemental and specific information provided based on the data selected by the user.

[0702] "Security system" refers to any information system that ensures safety in a specific area.

[0703] "Security status" means data that indicates the current security status of an area monitored by a security system.

[0704] The system of the present invention inputs user speech, analyzes the speech, and provides related information. How to implement this system will be described below.

[0705] System Configuration and Operation

[0706] 1. User voice input and conversion

[0707] User: Uses the smartphone microphone to say, "What is the security situation in my office?"

[0708] Terminal: A speech recognition engine (for example, the speech_recognition library) is used to convert user speech into text data.

[0709] 2. Analyzing User Intent

[0710] Terminal: Uses natural language processing techniques (e.g., generative AI models) to understand user intent from text data.

[0711] Terminal: In this case, it is understood that the user wants to check the "security status of the office."

[0712] 3. Obtaining location information

[0713] On the device: Use a GPS module (e.g., the geopy library) to get the user's current location.

[0714] 4. Searching and retrieving relevant data

[0715] Server: Based on the user's intent and location, the server retrieves relevant security data from the security system, including surveillance camera footage, alarm logs, and access history.

[0716] 5. Analyze relevant data and present it to the user

[0717] Server: Analyzes the acquired security data and evaluates the current security situation.

[0718] Server: For example, it evaluates the security status as "normal" or "an unconfirmed intrusion has occurred" and sends the result to the terminal.

[0719] Terminal: Presents the evaluation results to the user visually or audibly.

[0720] Hardware and software used

[0721] Speech recognition engine: speech_recognition library

[0722] GPS module: geopy library

[0723] Natural Language Processing Technology: Generative AI Model

[0724] Security data acquisition: Security system API (general name)

[0725] Device: Smartphone

[0726] Specific examples

[0727] For example, if a user asks their smartphone, "What's the security situation in the office?" during lunchtime, the system will use GPS to determine that the user is near the office, query the security system, and obtain the office's surveillance camera footage and alarm information. It will then notify the user that "The security situation is normal."

[0728] Prompt Sentence Examples

[0729] "Develop a security guard assistant app that can detect security situations through voice and provide relevant information. For example, when a user asks, 'What is the security situation in my office?' the app will check their current location, retrieve the latest information from the security system, and provide it to the user."

[0730] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0731] Step 1: Capturing Audio Input

[0732] The user uses the microphone on their smartphone to say, "Tell me about the security situation in the office." This voice input is captured by the microphone and sent to the smartphone as voice data.

[0733] Step 2: Convert audio data to text

[0734] The device converts the captured voice data into text data using a voice recognition engine (for example, the speech_recognition library). The input is voice data and the output is text data. Specifically, the device analyzes the voice data and converts it into words and sentences.

[0735] Step 3: Analyze user intent

[0736] The device uses natural language processing technology (e.g., a generative AI model) to understand the user's intent from the text data. The input is the text data, and the output is the information the user wants to know (in this case, "Office security status"). This involves analyzing the text data and extracting the user's intent from verbs, nouns, and adjectives.

[0737] Step 4: Obtaining location information

[0738] The device uses a GPS module (for example, the geopy library) to obtain the user's current location. The input is a signal from the GPS sensor, and the output is latitude and longitude coordinate data. Specifically, the device receives satellite signals from the GPS sensor and calculates the current location based on them.

[0739] Step 5: Find and retrieve relevant data

[0740] The server retrieves relevant security data from the security system based on the user's intent and location information. The input is the user's intent and location information, and the output is security data (surveillance camera footage, alarm logs, entry and exit history). The server calls the security system's API to retrieve the necessary data.

[0741] Step 6: Analyze security data

[0742] The server analyzes the acquired security data and evaluates the current security situation. The input is the security data, and the output is the evaluation result of the security situation (for example, "The security situation is normal" or "An unconfirmed intrusion has occurred"). Specifically, each piece of data is analyzed to check for any abnormalities.

[0743] Step 7: Present information to the user

[0744] The server sends the evaluation results to the terminal, which then presents them to the user. The input is the security status evaluation result, and the output is a notification message to the user. The terminal displays the notification message to the user visually or audibly. For example, it may display "Security status is normal" on the screen or read it aloud.

[0745] 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.

[0746] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide relevant information. It also has the ability to recognize the user's emotions and adjust the data presentation method based on the emotions. The following describes the specific operation of the system in natural language.

[0747] System Overview

[0748] 1. User voice input and conversion

[0749] User: Says, "I want to eat a delicious lunch."

[0750] Device: Uses a microphone to capture the user's voice.

[0751] Device: Uses a speech recognition engine to convert speech into text data.

[0752] 2. Analyzing User Intent

[0753] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[0754] Device: Identify relevant categories and set search criteria.

[0755] 3. Obtaining location information

[0756] Terminal: Obtains the user's current location using a GPS module.

[0757] Device: Sends current location information to the server.

[0758] 4. Search for restaurant information

[0759] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0760] Server: Lists multiple candidate restaurants as search results.

[0761] 5. Get restaurant details

[0762] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0763] Server: Combines the collected information and sorts the restaurants by highest rating.

[0764] 6. Present a list of restaurants

[0765] Server: Sends the consolidated restaurant list to the device.

[0766] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0767] 7. Your Choices and Details

[0768] User: Says, "Restaurant B is good."

[0769] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0770] Terminal: Parse the converted text and check the user's selections.

[0771] 8. Providing route guidance and weather information

[0772] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0773] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0774] Server: Obtains real-time weather information from an external weather API.

[0775] Server: Sends route guidance and weather information to the device.

[0776] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0777] 9. Emotion Recognition with Emotion Engine

[0778] Terminal: The user's voice input is analyzed, and the emotion engine recognizes the user's emotions.

[0779] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device will quickly present information and provide guidance in a calm voice.

[0780] Specific examples

[0781] For example, if a user says "I want to eat a delicious lunch" at home, the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and weather information. Furthermore, the emotion engine recognizes the user's emotions and selects the appropriate information presentation method. This allows users to obtain all the information they need in one app and take action smoothly.

[0782] The above is an embodiment of the present invention.

[0783] The processing flow will be explained below.

[0784] Step 1: Enter user voice

[0785] User: Says, "I want to eat a delicious lunch."

[0786] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[0787] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[0788] Step 2: Analyzing the text data

[0789] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[0790] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[0791] Step 3: Obtaining location information

[0792] Terminal: Obtains the user's current location using a GPS module.

[0793] Device: Sends the acquired location information to the server.

[0794] Step 4: Search for restaurant information

[0795] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[0796] Server: Lists multiple candidate restaurants as search results.

[0797] Step 5: Get restaurant details

[0798] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[0799] Server: Combines the collected information and sorts the restaurants by highest rating.

[0800] Step 6: Present the restaurant list

[0801] Server: Sends the consolidated restaurant list to the device.

[0802] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[0803] Step 7: Emotion Recognition with the Emotion Engine

[0804] Device: The emotion engine analyzes the user's voice input and recognizes the user's emotions. For example, it analyzes the tone, pitch, and speed of the user's voice to determine whether the user is excited or relaxed.

[0805] Step 8: Adjust information presentation based on emotions

[0806] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device displays information quickly and provides guidance in a calm voice. Conversely, if the user is relaxed, the device provides detailed explanations.

[0807] Step 9: Select User

[0808] User: Says, "Restaurant B is good."

[0809] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[0810] Terminal: Parse the converted text and check the user's selections.

[0811] Step 10: Providing directions and weather information

[0812] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[0813] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[0814] Server: Obtains real-time weather information from an external weather API.

[0815] Server: Sends route guidance and weather information to the device.

[0816] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[0817] Step 11: Final confirmation and guidance

[0818] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[0819] User: When ready, follow the instructions on the device to go to Restaurant B.

[0820] Example 2

[0821] 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."

[0822] While conventional speech recognition systems can convert a user's speech into text and understand their intent, they have the problem of being unable to consider the user's emotions when presenting information. This can result in inappropriate presentation of the information the user is looking for, or a poor user experience. In particular, when searching for restaurants or using navigation, it is important to provide the information users need quickly and appropriately, but conventional technologies fall short in this area.

[0823] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0824] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, means for performing emotion recognition, and means for adjusting the information presentation method based on the emotion recognition result. This enables appropriate and prompt information presentation taking the user's emotions into consideration, thereby improving the user experience.

[0825] A "means for inputting user voice" is a device or mechanism for capturing voice uttered by a user.

[0826] The "means for converting the user's voice into text data" refers to an algorithm or service that converts voice data into character string data.

[0827] The "means for analyzing the text data and understanding the user's intent" refers to a natural language processing technology or module for identifying the user's request or purpose from the text data.

[0828] "Means for obtaining location information" refers to a GPS module or other location identification technology for identifying the user's current location.

[0829] "Means for searching and acquiring relevant data based on the location information" refers to the process of searching for relevant information from a database or external API based on the acquired location information and collecting the necessary data.

[0830] "Means for presenting said relevant data to a user" refers to a mechanism or method for displaying collected information through a user interface.

[0831] The "means for allowing the user to select the related data presented" is a mechanism that provides an interaction for the user to make a selection from the presented information.

[0832] The "means for providing detailed information based on the selected data" is a process for collecting and displaying additional information related to the item selected by the user.

[0833] "Means for emotion recognition" refers to an algorithm or engine for recognizing the emotional state of a user from their voice or behavior.

[0834] The "means for adjusting the information presentation method based on the emotion recognition result" is a mechanism for changing the information presentation method according to the recognized emotion.

[0835] The present invention relates to a system that analyzes a user's voice input and provides relevant information based on the user's intentions and emotions. This system is realized by combining speech recognition technology that converts user speech into text, natural language processing technology, technology for acquiring location information, technology for searching related data, and technology for recognizing emotions.

[0836] Specifically, the following hardware and software are used:

[0837] 1. The device has a built-in microphone, GPS module, display, and speech recognition engine. The microphone is used to capture the user's voice, and the speech is converted into text data using a speech recognition engine (e.g., a speech recognition API). A specific example is the Google Cloud Speech-to-Text API.

[0838] 2. The device analyzes the text data using a natural language processing module (e.g., a natural language processing API) to understand the user's intent. A specific example is the Google Cloud Natural Language API.

[0839] 3. The device obtains the user's current location using a GPS module. The device sends the location information to the server. Based on this location information, the server searches for relevant data. The server searches for nearby restaurant information using a database or an external API (e.g., a restaurant search API). Specific examples include the Yelp API and Google Places API.

[0840] 4. The server collects detailed information about the restaurants (menus, reviews, ratings, etc.) found in the search results, integrates the information, sorts it by highest rating, and then sends the integrated information to the device.

[0841] 5. The device displays a list of restaurants for the user to select from, and provides an interface for the user to confirm their selection by voice input again.

[0842] 6. The device requests route guidance and weather information from the server based on the selected restaurant details. The server generates detailed route guidance and retrieves real-time weather information from an external weather API (e.g., a weather information API). Specific examples include Google Maps API and OpenWeatherMap API.

[0843] 7. The device analyzes the voice data using an emotion recognition engine (e.g., emotion recognition API) to recognize the user's emotions. A specific example is IBM Watson Tone Analyzer.

[0844] 8. The device adjusts the way it presents information based on the emotion recognition results. For example, if the user is excited, it will promptly present information and provide guidance in a calm voice.

[0845] Specific examples

[0846] For example, if a user says, "I want a delicious lunch," the device captures this with the microphone and converts it into text using the Google Cloud Speech-to-Text API. The text is then analyzed using the Google Cloud Natural Language API to identify the intent of "a delicious lunch." The device obtains its current location using GPS and searches for nearby restaurant information using the Yelp API. The server consolidates the collected restaurant details, sorts them by highest rating, and sends them to the device. If the user selects "Restaurant B is good" by voice, the device provides route guidance using the Google Maps API and retrieves and displays weather information from the OpenWeatherMap API. The device then uses IBM Watson Tone Analyzer to recognize the user's emotions and selects the optimal way to present information.

[0847] Prompt Sentence Examples

[0848] 1. "When a user says they want a delicious lunch, what prompts would you use to design a system that converts that speech to text and provides relevant restaurant information?"

[0849] 2. "Please provide a prompt to provide directions and weather information to a user-specified restaurant."

[0850] 3. "Generate a prompt for designing a system that uses an emotion engine to recognize a user's emotions and adjust the way information is presented based on the results."

[0851] The above is an embodiment of the present invention.

[0852] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0853] System program processing flow

[0854] Step 1: Input and convert user speech

[0855] The user says, "I want to eat a delicious lunch." The device captures this speech using the built-in microphone. The captured speech data is sent to a speech recognition engine such as the Google Cloud Speech-to-Text API and converted into text data. The input is the user's speech data, and the output is the text data obtained from the speech recognition engine.

[0856] Step 2: Analyze user intent

[0857] The device receives the converted text data, "I want to eat a delicious lunch." It then uses a natural language processing module, such as the Google Cloud Natural Language API, to analyze this text and identify the user's intent. In this case, it understands that the user's intent is "Find a restaurant that serves delicious lunch." The input is the text data, and the output is keywords related to the analyzed intent.

[0858] Step 3: Obtaining location information

[0859] The device uses a GPS module to obtain the user's current location. The location information (latitude and longitude) is sent to the server. The input is the location data obtained from the GPS module, and the output is the location information sent to the server.

[0860] Step 4: Search for restaurant information

[0861] Based on the received location information, the server searches for nearby restaurant information by requesting it from a database or an external API (e.g., Yelp API). Here, the server lists restaurants where you can have a delicious lunch based on the user's current location. The input is the location information and the user's intention, and the output is the list of restaurant information.

[0862] Step 5: Get restaurant details

[0863] The server collects detailed information (menus, reviews, ratings, etc.) about the listed restaurants using the Google Places API, etc. The detailed information is integrated and sorted in descending order of ratings. The input is a list of restaurant candidates, and the output is a list of restaurants with the integrated detailed information.

[0864] Step 6: Present the restaurant list

[0865] The server sends the integrated restaurant list to the terminal. The terminal displays the list to the user and asks, "I found restaurants A, B, and C. Which one do you want?" The input is the restaurant list from the server, and the output is the list display and voice guidance through the user interface.

[0866] Step 7: Select user and provide details

[0867] The user selects "Restaurant B is good." The device captures the voice again and converts it into text using a speech recognition engine. This text data is analyzed and the user's selection is confirmed. The input is the user's voice data, and the output is the text data of the selected restaurant.

[0868] Step 8: Providing directions and weather information

[0869] The device requests route guidance and weather information from the server based on the location of the selected restaurant. The server uses the Google Maps API to generate detailed driving directions and the OpenWeatherMap API to retrieve real-time weather information. These data are sent to the device. The input is the restaurant location data, and the output is route guidance and weather information, which the device displays to the user.

[0870] Step 9: Emotion Recognition with the Emotion Engine

[0871] The device analyzes the user's voice using an emotion recognition engine (for example, IBM Watson Tone Analyzer) to identify the user's emotion. Based on the emotion recognition results, the device adjusts the way information is presented. The input is voice data and analysis results, and the output is a method of presenting information according to the emotion. For example, if the user is excited, information is presented quickly and guidance is given in a calm voice.

[0872] (Application example 2)

[0873] 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."

[0874] Conventional voice recognition systems were able to convert a user's voice input into text data, analyze their intent, and provide relevant information. However, they lacked the ability to recognize the user's emotions and adjust the way information is presented based on that. Furthermore, there were issues with navigation in virtual stores and providing detailed product information, making it difficult to create an environment where users could comfortably shop. Furthermore, users often found it difficult to navigate within a store or select products, which could be stressful.

[0875] The identification process by the identification 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 inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for recognizing the user's emotions and adjusting the presentation method of the detailed information based on the emotions. This enables the provision of information that takes user emotions into consideration, thereby improving the shopping experience in the virtual store. Specifically, it is possible to change the speed and content of information presentation depending on emotions, providing an environment in which users can comfortably search for and select products.

[0876] The "means for inputting user voice" is a function for acquiring voice uttered by the user through an input device such as a microphone within the device.

[0877] The "means for converting the user's voice into text data" refers to a voice recognition engine or software that converts the acquired voice data into text format.

[0878] The "means for analyzing the text data and understanding the user's intention" is a technology that uses a natural language processing module based on the text data to analyze the user's intention and request.

[0879] "Means for obtaining location information" refers to a function for obtaining information about the user's current location using a GPS module or other location information services.

[0880] "Means for searching and acquiring related data based on the location information" refers to algorithms and database search techniques for searching and acquiring related data or information based on the acquired location information.

[0881] The "means for presenting the related data to the user" refers to a display device or interface that presents the searched and acquired data to the user visually, audibly, or in other ways.

[0882] The "means for allowing the user to select related data presented" refers to a technique for providing an interface or operating means that allows the user to select specific information from the displayed data.

[0883] "Means for providing detailed information based on the selected data" refers to functions and technologies for collecting detailed information related to the data selected by the user and providing it to the user.

[0884] "Means for recognizing the user's emotions and adjusting the way in which the detailed information is presented based on those emotions" refers to an algorithm or system that recognizes emotions from the user's voice, facial expressions, etc., and adjusts the way in which information is presented (speed, content, etc.) according to the user's emotional state.

[0885] "Virtual store navigation information" is information that provides route guidance, direction, location information, and the like that are necessary when a user moves within a virtual space.

[0886] The present invention is a system that adaptively processes everything from user voice input to providing detailed information based on the user's emotions. The system of the present invention is realized using various hardware and software components. The specific hardware and software used are shown below, and the operation of the system is explained.

[0887] Hardware and software used

[0888] Hardware: Smartphones, smart glasses, head-mounted displays

[0889] software:

[0890] Speech recognition engine: Uses the Google Speech-to-Text API to convert voice data into text.

[0891] Natural Language Processing: Use the Google Natural Language API to analyze the converted text data.

[0892] Emotion Recognition Engine: Uses IBM Watson Tone Analyzer to recognize user emotions.

[0893] Location information acquisition: Uses "Google Maps API" to acquire the user's current location.

[0894] Database: Uses "Firebase Firestore" to manage detailed information.

[0895] System Operation

[0896] User voice input

[0897] Users input voice commands using, for example, a smartphone, smart glasses, or a head-mounted display. The device's built-in microphone captures the voice and converts it into text data using a speech recognition engine.

[0898] Natural language processing and intent analysis

[0899] The converted text data is sent to a natural language processing module to analyze the user's intent, thereby understanding the specific information or service the user is seeking (e.g., searching for a product in a virtual store).

[0900] Acquiring location information and searching related data

[0901] The user's location information is acquired using a GPS module, and related data (e.g., location information of nearby products) is searched for. Based on the acquired location information and the user's intent, related data is searched for.

[0902] Data Presentation and User Selection

[0903] The retrieved related data is presented to the user, from which the user can select specific information, and based on the selected data, further detailed information is provided.

[0904] Emotion recognition and information provision coordination

[0905] The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotions, and adjusts how information is presented based on this analysis. For example, if the user is in a hurry, the system will present information more quickly.

[0906] Specific examples

[0907] Below are some specific examples for reference.

[0908] User Scenario

[0909] The user puts on the smart glasses and says, "I'm looking for a new smartphone at the virtual mall." The system converts this speech into text and analyzes the user's intent. Based on the analysis results, the system obtains information about the nearest smartphone store from the user's current location. Related products are presented to the user, providing detailed information. Further details, such as reviews, are displayed for the product selected by the user. The way information is presented is adjusted according to the user's emotions (excitement, impatience, etc.).

[0910] Prompt Sentence Examples

[0911] "If I want to easily get the information I need to optimize my system, how do I get started?"

[0912] These examples and prompts allow users to understand how the system is actually used and how information is presented. This invention allows users to easily obtain the information they need on the spot and respond appropriately according to their emotions.

[0913] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0914] Step 1:

[0915] A user inputs voice using a smart device (smartphone, smart glasses, head-mounted display), and the input voice is captured by a microphone in the device.

[0916] Input: User speech (e.g., "I'm looking for a new phone at the virtual mall.")

[0917] Output: Audio data

[0918] Step 2:

[0919] The device receives the voice data and converts it into text data using a voice recognition engine (Google Speech-to-Text API).

[0920] Input: Audio data

[0921] Output: Text data (e.g., "Looking for a new smartphone at the virtual mall")

[0922] Step 3:

[0923] The device sends the converted text data to a natural language processing module (Google Natural Language API) to analyze the user's intent.

[0924] Input: Text data

[0925] Output: User intent (e.g., smartphone search)

[0926] Step 4:

[0927] The terminal obtains the user's current location information using a GPS module and acquires location information.

[0928] Input: None (location information is obtained internally by the system)

[0929] Output: Current location information (e.g. longitude and latitude)

[0930] Step 5:

[0931] Based on the current location information and the user's intent, the server searches and retrieves relevant data (e.g., nearby smartphone stores) from a database (Firebase Firestore).

[0932] Input: current location, user intent

[0933] Output: Related data (e.g., information on nearby smartphone stores)

[0934] Step 6:

[0935] The terminal presents the acquired related data to the user and prompts the user to make a selection.

[0936] Input: relevant data

[0937] Output: Presented data (e.g., smartphone sales area list)

[0938] Step 7:

[0939] The user selects specific information from the presented data, and the selected information is received by the device. The user's selection is made by voice or touch operation.

[0940] Input: User selection (e.g. "Select this phone")

[0941] Output: Selected data

[0942] Step 8:

[0943] Based on the selected data, the server collects more detailed information (e.g., reviews, stock status) from external APIs and sends it to the device.

[0944] Input: Selected data

[0945] Output: Detailed information (e.g. smartphone reviews, stock status)

[0946] Step 9:

[0947] The device analyzes the tone of the user's voice and recognizes the user's emotions using an emotion engine (IBM Watson Tone Analyzer).

[0948] Input: User voice data

[0949] Output: Emotion recognition result (e.g., excitement, impatience)

[0950] Step 10:

[0951] The device adjusts how detailed information is presented based on the emotion recognition results, for example, by presenting information more quickly if the user is excited.

[0952] Input: Emotion recognition results, detailed information

[0953] Output: Adjusted detailed information

[0954] In this way, the system based on the present invention can provide appropriate information based on the user's voice input, and further adjust the presentation method according to the user's emotions.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] [Third embodiment]

[0959] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0960] 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.

[0961] 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).

[0962] 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.

[0963] 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.

[0964] 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).

[0965] 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.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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."

[0971] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. The specific operation of the system will be explained below in natural language.

[0972] System Overview

[0973] 1. User voice input and conversion

[0974] User: Speaks, "I want to eat a delicious lunch."

[0975] Device: Uses a microphone to capture the user's voice.

[0976] Device: Uses a speech recognition engine to convert speech into text data.

[0977] 2. Analyzing User Intent

[0978] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[0979] Device: Identify relevant categories and set search criteria.

[0980] 3. Obtaining location information

[0981] Terminal: Obtains the user's current location using a GPS module.

[0982] Device: Sends current location information to the server.

[0983] 4. Searching and retrieving relevant data

[0984] Server: Searches the database for nearby restaurant information based on the current location information.

[0985] Server: Collects data such as menus, reviews, and ratings for each relevant restaurant from an external API.

[0986] 5. Restaurant recommendations

[0987] Server: Selects highly rated restaurants based on collected data and generates a list.

[0988] Server: Sends the generated list to the terminal.

[0989] Terminal: Display to the user "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[0990] 6. Your Choices and Details

[0991] User: Selects Restaurant B.

[0992] Terminal: Confirms the user's selection and sends the information to the server.

[0993] Server: Get detailed route guidance information and weather information for Restaurant B.

[0994] Server: Sends the acquired information to the terminal.

[0995] Terminal: Displays detailed route directions and weather information to the user.

[0996] Specific examples

[0997] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[0998] The above is an embodiment of the present invention.

[0999] The processing flow will be explained below.

[1000] Step 1: Enter user voice

[1001] User: Says, "I want to eat a delicious lunch."

[1002] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[1003] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[1004] Step 2: Analyzing the text data

[1005] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[1006] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[1007] Step 3: Obtaining location information

[1008] Device: Uses the GPS module to obtain the user's current location.

[1009] Device: Sends current location information to the server.

[1010] Step 4: Search for restaurant information

[1011] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1012] Server: Lists multiple candidate restaurants as search results.

[1013] Step 5: Get restaurant details

[1014] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1015] Server: Combines the collected information and sorts the restaurants by highest rating.

[1016] Step 6: Present the restaurant list

[1017] Server: Sends the consolidated restaurant list to the device.

[1018] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1019] Step 7: Selecting Users

[1020] User: Says, "Restaurant B is good."

[1021] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1022] Terminal: Parse the converted text and check the user's selections.

[1023] Step 8: Providing directions and weather information

[1024] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1025] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1026] Server: Obtains real-time weather information from an external weather API.

[1027] Server: Sends route guidance and weather information to the device.

[1028] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1029] Step 9: Final confirmation and guidance

[1030] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[1031] User: When ready, follow the instructions on the device to go to Restaurant B.

[1032] Example 1

[1033] 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."

[1034] Conventional information provision systems that use user voice have difficulty accurately understanding the user's intent and providing relevant information quickly and accurately. Even when providing information using location information, the system may not be able to present the most appropriate information for the user. Furthermore, when providing detailed information, the system may not be able to include the accurate information the user is looking for. It is necessary to solve these problems and provide more useful information to users.

[1035] 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.

[1036] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for the detailed information providing means to select related data based on an evaluation. This makes it possible to accurately understand the user's intention and quickly provide the most suitable related data for the user by utilizing the location information.

[1037] The "means for inputting user voice" is a function that allows a user to input voice into the system using a voice input device such as a microphone.

[1038] The "means for converting user voice into text data" is a function for converting voice data into text data using a voice recognition engine or the like.

[1039] "Means for analyzing text data to understand user intent" refers to a function that uses natural language processing technology to analyze and understand the content and intent of a user's speech from text data.

[1040] "Means for acquiring location information" refers to a function for acquiring the user's current location using a GPS module or other location measurement technology.

[1041] "Means for searching and obtaining related data based on location information" refers to a function that searches for and obtains related information from a database or external API based on the obtained location information.

[1042] The "means for presenting related data to the user" is a function for displaying the acquired related data on the user's terminal.

[1043] The "means for allowing the user to select the related data presented" is a function that allows the user to select desired information from the presented data.

[1044] The "means for providing detailed information based on selected data" is a function for obtaining and providing more detailed information to the user based on the data selected by the user.

[1045] The "means for the detailed information providing means to select related data based on evaluation" is a function that evaluates the collected related data and selects and provides data with high evaluations.

[1046] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. To implement the system, the following hardware and software are required:

[1047] Hardware

[1048] Device: Smartphone or tablet equipped with a microphone and GPS module

[1049] Server: Cloud server with database management system

[1050] software

[1051] Speech recognition engine: Google Speech-to-Text API

[1052] Natural language processing module: OpenAI's GPT-3

[1053] Database: MongoDB

[1054] External APIs: Yelp API, Google Maps API, and OpenWeatherMap API

[1055] This system operates in the following procedure.

[1056] 1. User voice input and conversion

[1057] The user uses the microphone on their smartphone to say, "I want to eat a delicious lunch." The device captures the user's voice using the microphone and converts it into text data using the Google Speech-to-Text API.

[1058] 2. Analyzing User Intent

[1059] The device then uses a natural language processing module to analyze the converted text and understand that the user is looking for a "delicious lunch." The analysis uses OpenAI's GPT-3 to extract related topics and keywords.

[1060] 3. Obtaining location information

[1061] The device acquires the user's current location using the GPS module and sends the acquired latitude and longitude to the server.

[1062] 4. Searching and retrieving relevant data

[1063] The server searches for nearby restaurant information from a database (MongoDB) based on the location information sent, and also collects data such as menus, reviews, and ratings for each related restaurant from an external API (Yelp API).

[1064] 5. Restaurant recommendations

[1065] The server selects highly rated restaurants based on the collected data and generates a list. The generated list is sent to the device, which then displays a message to the user saying, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[1066] 6. Your Choices and Details

[1067] When the user selects Restaurant B, the device sends that information to the server. The server obtains detailed route guidance information to Restaurant B using the Google Maps API and weather information using the OpenWeatherMap API. The obtained information is sent to the device, and the device displays detailed route guidance and weather information to the user.

[1068] Specific examples

[1069] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[1070] Prompt Sentence Examples

[1071] By inputting the following prompt sentence into the generative AI model, information can be obtained to understand the overview of this system.

[1072] "When a user says they want to have a delicious lunch, explain how the speech recognition engine converts that information into text and then the natural language processing module analyzes it. Also explain how relevant restaurant information is searched for and presented."

[1073] The above is an embodiment of the present invention.

[1074] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1075] Step 1:

[1076] The user speaks into the smartphone's microphone, saying, "I want to eat a delicious lunch."

[1077] Input: User voice

[1078] Output: Captured audio data

[1079] The device uses a microphone to capture the user's voice, and the voice signal is digitized by an audio input device.

[1080] Step 2:

[1081] The device sends the captured voice data to the Google Speech-to-Text API, which converts the voice data into text data.

[1082] Input: Captured audio data

[1083] Output: Converted text data

[1084] Specifically, code is executed to send the captured audio data to the API, and the returned text data is retrieved.

[1085] Step 3:

[1086] The device analyzes the converted text data using a natural language processing module (e.g., OpenAI's GPT-3) to understand the user's intent.

[1087] Input: Converted text data

[1088] Output: User intent

[1089] Text data is input into the AI ​​as a prompt, and keywords (e.g., "delicious," "lunch," "want to eat") are extracted from the response to identify the user's intent.

[1090] Step 4:

[1091] The terminal sets search conditions based on the extracted keywords.

[1092] Input: User intent

[1093] Output: Search criteria

[1094] As a specific example, if it turns out that the user is looking for a "delicious lunch," this is set as a search condition.

[1095] Step 5:

[1096] The terminal obtains the user's current location using a GPS module.

[1097] Input: None

[1098] Output: Latitude and longitude information

[1099] The code runs to activate the GPS sensor and obtain the current latitude and longitude.

[1100] Step 6:

[1101] The terminal transmits the acquired current location information to the server.

[1102] Input: Latitude and longitude information

[1103] Output: Transferred location information

[1104] For security reasons, data is sent to the server using the HTTPS protocol.

[1105] Step 7:

[1106] The server searches a database (e.g., MongoDB) for nearby restaurant information based on the received location information.

[1107] Input: Transferred current location information

[1108] Output: Nearby restaurant information

[1109] Create a query based on latitude and longitude to retrieve relevant restaurant data.

[1110] Step 8:

[1111] The server collects data such as menus, reviews, and ratings for each relevant restaurant from an external API (e.g., Yelp API).

[1112] Input: Nearby restaurant information

[1113] Output: Detailed restaurant information (menu, reviews, ratings, etc.)

[1114] Send a request to the Yelp API using the restaurant ID, and parse the returned JSON data to obtain information.

[1115] Step 9:

[1116] The server selects highly rated restaurants based on the collected data.

[1117] Input: Detailed restaurant information

[1118] Output: A list of top-rated restaurants

[1119] The reviews and rating scores of each restaurant are statistically analyzed to create a list of the top restaurants.

[1120] Step 10:

[1121] The server transmits the generated list to the terminal.

[1122] Input: Top-rated restaurant list

[1123] Output: Transferred restaurant list

[1124] Code is executed to send the generated list to the terminal.

[1125] Step 11:

[1126] The terminal displays to the user, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[1127] Input: Transferred restaurant list

[1128] Output: Information presented to the user

[1129] The UI uses a list view to layout and display the list.

[1130] Step 12:

[1131] The user selects Restaurant B from the list.

[1132] Input: User's selection (Restaurant B)

[1133] Output: Selected restaurant information

[1134] When the user presses the selection button, the selection information is stored in the terminal.

[1135] Step 13:

[1136] The terminal transmits the user's selection to the server.

[1137] Input: Selected restaurant information

[1138] Output: Data sent to the server

[1139] Code is executed to send a request containing the ID of the selected restaurant.

[1140] Step 14:

[1141] The server retrieves detailed route guidance information to the selected restaurant using the Google Maps API and retrieves weather information using the OpenWeatherMap API.

[1142] Input: Data to send to the server

[1143] Output: Detailed route directions and weather information

[1144] Route guidance information is obtained using the Google Maps API, and weather information is obtained using the OpenWeatherMap API.

[1145] Step 15:

[1146] The server transmits the acquired information to the terminal.

[1147] Input: Detailed driving directions and weather information

[1148] Output: Data sent to the terminal

[1149] Code is executed to transmit the obtained information to the terminal.

[1150] Step 16:

[1151] The device displays detailed route directions and weather information to the user.

[1152] Input: Data to send to the terminal

[1153] Output: Displayed route and weather information

[1154] It uses a map view to display routes and provides weather information in a text view.

[1155] (Application example 1)

[1156] 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."

[1157] In recent years, security management has become increasingly important, but conventional systems have had difficulty obtaining and providing real-time security information based on voice input. Furthermore, when users check the security status of their home or office while away from home, they have had to use multiple applications and devices, which is inconvenient. There is a need to solve these problems and provide security information efficiently through a single system.

[1158] 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.

[1159] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, and means for cooperating with a security system to acquire a security status. This allows a user to obtain security information in real time using voice input, and to quickly check the security status of their home or office even when they are away from home.

[1160] "User speech" refers to instructions or requests that a user inputs by voice.

[1161] "Means" refers to a method or apparatus for accomplishing a particular function or purpose.

[1162] "Text data" refers to character string data converted from speech by speech recognition.

[1163] "Natural language processing" is a technology that analyzes text data to understand human language and perform appropriate processing.

[1164] "Location information" refers to data that indicates a user's current geographic location.

[1165] "Related data" refers to all information provided by the server based on the user's request and location information.

[1166] "Presenting to the user" means that the system displays information to the user visually or audibly.

[1167] "Making a choice" refers to the act of encouraging a user to select a specific option from the information provided.

[1168] "Detailed information" refers to supplemental and specific information provided based on the data selected by the user.

[1169] "Security system" refers to any information system that ensures safety in a specific area.

[1170] "Security status" means data that indicates the current security status of an area monitored by a security system.

[1171] The system of the present invention inputs user speech, analyzes the speech, and provides related information. How to implement this system will be described below.

[1172] System Configuration and Operation

[1173] 1. User voice input and conversion

[1174] User: Uses the smartphone microphone to say, "What is the security situation in my office?"

[1175] Terminal: A speech recognition engine (for example, the speech_recognition library) is used to convert user speech into text data.

[1176] 2. Analyzing User Intent

[1177] Terminal: Uses natural language processing techniques (e.g., generative AI models) to understand user intent from text data.

[1178] Terminal: In this case, it is understood that the user wants to check the "security status of the office."

[1179] 3. Obtaining location information

[1180] On the device: Use a GPS module (e.g., the geopy library) to get the user's current location.

[1181] 4. Searching and retrieving relevant data

[1182] Server: Based on the user's intent and location, the server retrieves relevant security data from the security system, including surveillance camera footage, alarm logs, and access history.

[1183] 5. Analyze relevant data and present it to the user

[1184] Server: Analyzes the acquired security data and evaluates the current security situation.

[1185] Server: For example, it evaluates the security status as "normal" or "an unconfirmed intrusion has occurred" and sends the result to the terminal.

[1186] Terminal: Presents the evaluation results to the user visually or audibly.

[1187] Hardware and software used

[1188] Speech recognition engine: speech_recognition library

[1189] GPS module: geopy library

[1190] Natural Language Processing Technology: Generative AI Model

[1191] Security data acquisition: Security system API (general name)

[1192] Device: Smartphone

[1193] Specific examples

[1194] For example, if a user asks their smartphone, "What's the security situation in the office?" during lunchtime, the system will use GPS to determine that the user is near the office, query the security system, and obtain the office's surveillance camera footage and alarm information. It will then notify the user that "The security situation is normal."

[1195] Prompt Sentence Examples

[1196] "Develop a security guard assistant app that can detect security situations through voice and provide relevant information. For example, when a user asks, 'What is the security situation in my office?' the app will check their current location, retrieve the latest information from the security system, and provide it to the user."

[1197] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1198] Step 1: Capturing Audio Input

[1199] The user uses the microphone on their smartphone to say, "Tell me about the security situation in the office." This voice input is captured by the microphone and sent to the smartphone as voice data.

[1200] Step 2: Convert audio data to text

[1201] The device converts the captured voice data into text data using a voice recognition engine (for example, the speech_recognition library). The input is voice data and the output is text data. Specifically, the device analyzes the voice data and converts it into words and sentences.

[1202] Step 3: Analyze user intent

[1203] The device uses natural language processing technology (e.g., a generative AI model) to understand the user's intent from the text data. The input is the text data, and the output is the information the user wants to know (in this case, "Office security status"). This involves analyzing the text data and extracting the user's intent from verbs, nouns, and adjectives.

[1204] Step 4: Obtaining location information

[1205] The device uses a GPS module (for example, the geopy library) to obtain the user's current location. The input is a signal from the GPS sensor, and the output is latitude and longitude coordinate data. Specifically, the device receives satellite signals from the GPS sensor and calculates the current location based on them.

[1206] Step 5: Find and retrieve relevant data

[1207] The server retrieves relevant security data from the security system based on the user's intent and location information. The input is the user's intent and location information, and the output is security data (surveillance camera footage, alarm logs, entry and exit history). The server calls the security system's API to retrieve the necessary data.

[1208] Step 6: Analyze security data

[1209] The server analyzes the acquired security data and evaluates the current security situation. The input is the security data, and the output is the evaluation result of the security situation (for example, "The security situation is normal" or "An unconfirmed intrusion has occurred"). Specifically, each piece of data is analyzed to check for any abnormalities.

[1210] Step 7: Present information to the user

[1211] The server sends the evaluation results to the terminal, which then presents them to the user. The input is the security status evaluation result, and the output is a notification message to the user. The terminal displays the notification message to the user visually or audibly. For example, it may display "Security status is normal" on the screen or read it aloud.

[1212] 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.

[1213] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide relevant information. It also has the ability to recognize the user's emotions and adjust the data presentation method based on the emotions. The following describes the specific operation of the system in natural language.

[1214] System Overview

[1215] 1. User voice input and conversion

[1216] User: Says, "I want to eat a delicious lunch."

[1217] Device: Uses a microphone to capture the user's voice.

[1218] Device: Uses a speech recognition engine to convert speech into text data.

[1219] 2. Analyzing User Intent

[1220] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[1221] Device: Identify relevant categories and set search criteria.

[1222] 3. Obtaining location information

[1223] Terminal: Obtains the user's current location using a GPS module.

[1224] Device: Sends current location information to the server.

[1225] 4. Search for restaurant information

[1226] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1227] Server: Lists multiple candidate restaurants as search results.

[1228] 5. Get restaurant details

[1229] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1230] Server: Combines the collected information and sorts the restaurants by highest rating.

[1231] 6. Present a list of restaurants

[1232] Server: Sends the consolidated restaurant list to the device.

[1233] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1234] 7. Your Choices and Details

[1235] User: Says, "Restaurant B is good."

[1236] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1237] Terminal: Parse the converted text and check the user's selections.

[1238] 8. Providing route guidance and weather information

[1239] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1240] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1241] Server: Obtains real-time weather information from an external weather API.

[1242] Server: Sends route guidance and weather information to the device.

[1243] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1244] 9. Emotion Recognition with Emotion Engine

[1245] Terminal: The user's voice input is analyzed, and the emotion engine recognizes the user's emotions.

[1246] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device will quickly present information and provide guidance in a calm voice.

[1247] Specific examples

[1248] For example, if a user says "I want to eat a delicious lunch" at home, the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and weather information. Furthermore, the emotion engine recognizes the user's emotions and selects the appropriate information presentation method. This allows users to obtain all the information they need in one app and take action smoothly.

[1249] The above is an embodiment of the present invention.

[1250] The processing flow will be explained below.

[1251] Step 1: Enter user voice

[1252] User: Says, "I want to eat a delicious lunch."

[1253] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[1254] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[1255] Step 2: Analyzing the text data

[1256] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[1257] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[1258] Step 3: Obtaining location information

[1259] Terminal: Obtains the user's current location using a GPS module.

[1260] Device: Sends the acquired location information to the server.

[1261] Step 4: Search for restaurant information

[1262] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1263] Server: Lists multiple candidate restaurants as search results.

[1264] Step 5: Get restaurant details

[1265] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1266] Server: Combines the collected information and sorts the restaurants by highest rating.

[1267] Step 6: Present the restaurant list

[1268] Server: Sends the consolidated restaurant list to the device.

[1269] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1270] Step 7: Emotion Recognition with the Emotion Engine

[1271] Device: The emotion engine analyzes the user's voice input and recognizes the user's emotions. For example, it analyzes the tone, pitch, and speed of the user's voice to determine whether the user is excited or relaxed.

[1272] Step 8: Adjust information presentation based on emotions

[1273] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device displays information quickly and provides guidance in a calm voice. Conversely, if the user is relaxed, the device provides detailed explanations.

[1274] Step 9: Select User

[1275] User: Says, "Restaurant B is good."

[1276] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1277] Terminal: Parse the converted text and check the user's selections.

[1278] Step 10: Providing directions and weather information

[1279] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1280] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1281] Server: Obtains real-time weather information from an external weather API.

[1282] Server: Sends route guidance and weather information to the device.

[1283] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1284] Step 11: Final confirmation and guidance

[1285] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[1286] User: When ready, follow the instructions on the device to go to Restaurant B.

[1287] Example 2

[1288] 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."

[1289] While conventional speech recognition systems can convert a user's speech into text and understand their intent, they have the problem of being unable to consider the user's emotions when presenting information. This can result in inappropriate presentation of the information the user is looking for, or a poor user experience. In particular, when searching for restaurants or using navigation, it is important to provide the information users need quickly and appropriately, but conventional technologies fall short in this area.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1291] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, means for performing emotion recognition, and means for adjusting the information presentation method based on the emotion recognition result. This enables appropriate and prompt information presentation taking the user's emotions into consideration, thereby improving the user experience.

[1292] A "means for inputting user voice" is a device or mechanism for capturing voice uttered by a user.

[1293] The "means for converting the user's voice into text data" refers to an algorithm or service that converts voice data into character string data.

[1294] The "means for analyzing the text data and understanding the user's intent" refers to a natural language processing technology or module for identifying the user's request or purpose from the text data.

[1295] "Means for obtaining location information" refers to a GPS module or other location identification technology for identifying the user's current location.

[1296] "Means for searching and acquiring relevant data based on the location information" refers to the process of searching for relevant information from a database or external API based on the acquired location information and collecting the necessary data.

[1297] "Means for presenting said relevant data to a user" refers to a mechanism or method for displaying collected information through a user interface.

[1298] The "means for allowing the user to select the related data presented" is a mechanism that provides an interaction for the user to make a selection from the presented information.

[1299] The "means for providing detailed information based on the selected data" is a process for collecting and displaying additional information related to the item selected by the user.

[1300] "Means for emotion recognition" refers to an algorithm or engine for recognizing the emotional state of a user from their voice or behavior.

[1301] The "means for adjusting the information presentation method based on the emotion recognition result" is a mechanism for changing the information presentation method according to the recognized emotion.

[1302] The present invention relates to a system that analyzes a user's voice input and provides relevant information based on the user's intentions and emotions. This system is realized by combining speech recognition technology that converts user speech into text, natural language processing technology, technology for acquiring location information, technology for searching related data, and technology for recognizing emotions.

[1303] Specifically, the following hardware and software are used:

[1304] 1. The device has a built-in microphone, GPS module, display, and speech recognition engine. The microphone is used to capture the user's voice, and the speech is converted into text data using a speech recognition engine (e.g., a speech recognition API). A specific example is the Google Cloud Speech-to-Text API.

[1305] 2. The device analyzes the text data using a natural language processing module (e.g., a natural language processing API) to understand the user's intent. A specific example is the Google Cloud Natural Language API.

[1306] 3. The device obtains the user's current location using a GPS module. The device sends the location information to the server. Based on this location information, the server searches for relevant data. The server searches for nearby restaurant information using a database or an external API (e.g., a restaurant search API). Specific examples include the Yelp API and Google Places API.

[1307] 4. The server collects detailed information about the restaurants (menus, reviews, ratings, etc.) found in the search results, integrates the information, sorts it by highest rating, and then sends the integrated information to the device.

[1308] 5. The device displays a list of restaurants for the user to select from, and provides an interface for the user to confirm their selection by voice input again.

[1309] 6. The device requests route guidance and weather information from the server based on the selected restaurant details. The server generates detailed route guidance and retrieves real-time weather information from an external weather API (e.g., a weather information API). Specific examples include Google Maps API and OpenWeatherMap API.

[1310] 7. The device analyzes the voice data using an emotion recognition engine (e.g., emotion recognition API) to recognize the user's emotions. A specific example is IBM Watson Tone Analyzer.

[1311] 8. The device adjusts the way it presents information based on the emotion recognition results. For example, if the user is excited, it will promptly present information and provide guidance in a calm voice.

[1312] Specific examples

[1313] For example, if a user says, "I want a delicious lunch," the device captures this with the microphone and converts it into text using the Google Cloud Speech-to-Text API. The text is then analyzed using the Google Cloud Natural Language API to identify the intent of "a delicious lunch." The device obtains its current location using GPS and searches for nearby restaurant information using the Yelp API. The server consolidates the collected restaurant details, sorts them by highest rating, and sends them to the device. If the user selects "Restaurant B is good" by voice, the device provides route guidance using the Google Maps API and retrieves and displays weather information from the OpenWeatherMap API. The device then uses IBM Watson Tone Analyzer to recognize the user's emotions and selects the optimal way to present information.

[1314] Prompt Sentence Examples

[1315] 1. "When a user says they want a delicious lunch, what prompts would you use to design a system that converts that speech to text and provides relevant restaurant information?"

[1316] 2. "Please provide a prompt to provide directions and weather information to a user-specified restaurant."

[1317] 3. "Generate a prompt for designing a system that uses an emotion engine to recognize a user's emotions and adjust the way information is presented based on the results."

[1318] The above is an embodiment of the present invention.

[1319] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1320] System program processing flow

[1321] Step 1: Input and convert user speech

[1322] The user says, "I want to eat a delicious lunch." The device captures this speech using the built-in microphone. The captured speech data is sent to a speech recognition engine such as the Google Cloud Speech-to-Text API and converted into text data. The input is the user's speech data, and the output is the text data obtained from the speech recognition engine.

[1323] Step 2: Analyze user intent

[1324] The device receives the converted text data, "I want to eat a delicious lunch." It then uses a natural language processing module, such as the Google Cloud Natural Language API, to analyze this text and identify the user's intent. In this case, it understands that the user's intent is "Find a restaurant that serves delicious lunch." The input is the text data, and the output is keywords related to the analyzed intent.

[1325] Step 3: Obtaining location information

[1326] The device uses a GPS module to obtain the user's current location. The location information (latitude and longitude) is sent to the server. The input is the location data obtained from the GPS module, and the output is the location information sent to the server.

[1327] Step 4: Search for restaurant information

[1328] Based on the received location information, the server searches for nearby restaurant information by requesting it from a database or an external API (e.g., Yelp API). Here, the server lists restaurants where you can have a delicious lunch based on the user's current location. The input is the location information and the user's intention, and the output is the list of restaurant information.

[1329] Step 5: Get restaurant details

[1330] The server collects detailed information (menus, reviews, ratings, etc.) about the listed restaurants using the Google Places API, etc. The detailed information is integrated and sorted in descending order of ratings. The input is a list of restaurant candidates, and the output is a list of restaurants with the integrated detailed information.

[1331] Step 6: Present the restaurant list

[1332] The server sends the integrated restaurant list to the terminal. The terminal displays the list to the user and asks, "I found restaurants A, B, and C. Which one do you want?" The input is the restaurant list from the server, and the output is the list display and voice guidance through the user interface.

[1333] Step 7: Select user and provide details

[1334] The user selects "Restaurant B is good." The device captures the voice again and converts it into text using a speech recognition engine. This text data is analyzed and the user's selection is confirmed. The input is the user's voice data, and the output is the text data of the selected restaurant.

[1335] Step 8: Providing directions and weather information

[1336] The device requests route guidance and weather information from the server based on the location of the selected restaurant. The server uses the Google Maps API to generate detailed driving directions and the OpenWeatherMap API to retrieve real-time weather information. These data are sent to the device. The input is the restaurant location data, and the output is route guidance and weather information, which the device displays to the user.

[1337] Step 9: Emotion Recognition with the Emotion Engine

[1338] The device analyzes the user's voice using an emotion recognition engine (for example, IBM Watson Tone Analyzer) to identify the user's emotion. Based on the emotion recognition results, the device adjusts the way information is presented. The input is voice data and analysis results, and the output is a method of presenting information according to the emotion. For example, if the user is excited, information is presented quickly and guidance is given in a calm voice.

[1339] (Application example 2)

[1340] 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."

[1341] Conventional voice recognition systems were able to convert a user's voice input into text data, analyze their intent, and provide relevant information. However, they lacked the ability to recognize the user's emotions and adjust the way information is presented based on that. Furthermore, there were issues with navigation in virtual stores and providing detailed product information, making it difficult to create an environment where users could comfortably shop. Furthermore, users often found it difficult to navigate within a store or select products, which could be stressful.

[1342] The identification process by the identification 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 inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for recognizing the user's emotions and adjusting the presentation method of the detailed information based on the emotions. This enables the provision of information that takes user emotions into consideration, thereby improving the shopping experience in the virtual store. Specifically, it is possible to change the speed and content of information presentation depending on emotions, providing an environment in which users can comfortably search for and select products.

[1343] The "means for inputting user voice" is a function for acquiring voice uttered by the user through an input device such as a microphone within the device.

[1344] The "means for converting the user's voice into text data" refers to a voice recognition engine or software that converts the acquired voice data into text format.

[1345] The "means for analyzing the text data and understanding the user's intention" is a technology that uses a natural language processing module based on the text data to analyze the user's intention and request.

[1346] "Means for obtaining location information" refers to a function for obtaining information about the user's current location using a GPS module or other location information services.

[1347] "Means for searching and acquiring related data based on the location information" refers to algorithms and database search techniques for searching and acquiring related data or information based on the acquired location information.

[1348] The "means for presenting the related data to the user" refers to a display device or interface that presents the searched and acquired data to the user visually, audibly, or in other ways.

[1349] The "means for allowing the user to select related data presented" refers to a technique for providing an interface or operating means that allows the user to select specific information from the displayed data.

[1350] "Means for providing detailed information based on the selected data" refers to functions and technologies for collecting detailed information related to the data selected by the user and providing it to the user.

[1351] "Means for recognizing the user's emotions and adjusting the way in which the detailed information is presented based on those emotions" refers to an algorithm or system that recognizes emotions from the user's voice, facial expressions, etc., and adjusts the way in which information is presented (speed, content, etc.) according to the user's emotional state.

[1352] "Virtual store navigation information" is information that provides route guidance, direction, location information, and the like that are necessary when a user moves within a virtual space.

[1353] The present invention is a system that adaptively processes everything from user voice input to providing detailed information based on the user's emotions. The system of the present invention is realized using various hardware and software components. The specific hardware and software used are shown below, and the operation of the system is explained.

[1354] Hardware and software used

[1355] Hardware: Smartphones, smart glasses, head-mounted displays

[1356] software:

[1357] Speech recognition engine: Uses the Google Speech-to-Text API to convert voice data into text.

[1358] Natural Language Processing: Use the Google Natural Language API to analyze the converted text data.

[1359] Emotion Recognition Engine: Uses IBM Watson Tone Analyzer to recognize user emotions.

[1360] Location information acquisition: Uses "Google Maps API" to acquire the user's current location.

[1361] Database: Uses "Firebase Firestore" to manage detailed information.

[1362] System Operation

[1363] User voice input

[1364] Users input voice commands using, for example, a smartphone, smart glasses, or a head-mounted display. The device's built-in microphone captures the voice and converts it into text data using a speech recognition engine.

[1365] Natural language processing and intent analysis

[1366] The converted text data is sent to a natural language processing module to analyze the user's intent, thereby understanding the specific information or service the user is seeking (e.g., searching for a product in a virtual store).

[1367] Acquiring location information and searching related data

[1368] The user's location information is acquired using a GPS module, and related data (e.g., location information of nearby products) is searched for. Based on the acquired location information and the user's intent, related data is searched for.

[1369] Data Presentation and User Selection

[1370] The retrieved related data is presented to the user, from which the user can select specific information, and based on the selected data, further detailed information is provided.

[1371] Emotion recognition and information provision coordination

[1372] The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotions, and adjusts how information is presented based on this analysis. For example, if the user is in a hurry, the system will present information more quickly.

[1373] Specific examples

[1374] Below are some specific examples for reference.

[1375] User Scenario

[1376] The user puts on the smart glasses and says, "I'm looking for a new smartphone at the virtual mall." The system converts this speech into text and analyzes the user's intent. Based on the analysis results, the system obtains information about the nearest smartphone store from the user's current location. Related products are presented to the user, providing detailed information. Further details, such as reviews, are displayed for the product selected by the user. The way information is presented is adjusted according to the user's emotions (excitement, impatience, etc.).

[1377] Prompt Sentence Examples

[1378] "If I want to easily get the information I need to optimize my system, how do I get started?"

[1379] These examples and prompts allow users to understand how the system is actually used and how information is presented. This invention allows users to easily obtain the information they need on the spot and respond appropriately according to their emotions.

[1380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1381] Step 1:

[1382] A user inputs voice using a smart device (smartphone, smart glasses, head-mounted display), and the input voice is captured by a microphone in the device.

[1383] Input: User speech (e.g., "I'm looking for a new phone at the virtual mall.")

[1384] Output: Audio data

[1385] Step 2:

[1386] The device receives the voice data and converts it into text data using a voice recognition engine (Google Speech-to-Text API).

[1387] Input: Audio data

[1388] Output: Text data (e.g., "Looking for a new smartphone at the virtual mall")

[1389] Step 3:

[1390] The device sends the converted text data to a natural language processing module (Google Natural Language API) to analyze the user's intent.

[1391] Input: Text data

[1392] Output: User intent (e.g., smartphone search)

[1393] Step 4:

[1394] The terminal obtains the user's current location information using a GPS module and acquires location information.

[1395] Input: None (location information is obtained internally by the system)

[1396] Output: Current location information (e.g. longitude and latitude)

[1397] Step 5:

[1398] Based on the current location information and the user's intent, the server searches and retrieves relevant data (e.g., nearby smartphone stores) from a database (Firebase Firestore).

[1399] Input: current location, user intent

[1400] Output: Related data (e.g., information on nearby smartphone stores)

[1401] Step 6:

[1402] The terminal presents the acquired related data to the user and prompts the user to make a selection.

[1403] Input: relevant data

[1404] Output: Presented data (e.g., smartphone sales area list)

[1405] Step 7:

[1406] The user selects specific information from the presented data, and the selected information is received by the device. The user's selection is made by voice or touch operation.

[1407] Input: User selection (e.g. "Select this phone")

[1408] Output: Selected data

[1409] Step 8:

[1410] Based on the selected data, the server collects more detailed information (e.g., reviews, stock status) from external APIs and sends it to the device.

[1411] Input: Selected data

[1412] Output: Detailed information (e.g. smartphone reviews, stock status)

[1413] Step 9:

[1414] The device analyzes the tone of the user's voice and recognizes the user's emotions using an emotion engine (IBM Watson Tone Analyzer).

[1415] Input: User voice data

[1416] Output: Emotion recognition result (e.g., excitement, impatience)

[1417] Step 10:

[1418] The device adjusts how detailed information is presented based on the emotion recognition results, for example, by presenting information more quickly if the user is excited.

[1419] Input: Emotion recognition results, detailed information

[1420] Output: Adjusted detailed information

[1421] In this way, the system based on the present invention can provide appropriate information based on the user's voice input, and further adjust the presentation method according to the user's emotions.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] [Fourth embodiment]

[1426] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1427] 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.

[1428] 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).

[1429] 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.

[1430] 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.

[1431] 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).

[1432] 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.

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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."

[1439] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. The specific operation of the system will be explained below in natural language.

[1440] System Overview

[1441] 1. User voice input and conversion

[1442] User: Speaks, "I want to eat a delicious lunch."

[1443] Device: Uses a microphone to capture the user's voice.

[1444] Device: Uses a speech recognition engine to convert speech into text data.

[1445] 2. Analyzing User Intent

[1446] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[1447] Device: Identify relevant categories and set search criteria.

[1448] 3. Obtaining location information

[1449] Terminal: Obtains the user's current location using a GPS module.

[1450] Device: Sends current location information to the server.

[1451] 4. Searching and retrieving relevant data

[1452] Server: Searches the database for nearby restaurant information based on the current location information.

[1453] Server: Collects data such as menus, reviews, and ratings for each relevant restaurant from an external API.

[1454] 5. Restaurant recommendations

[1455] Server: Selects highly rated restaurants based on collected data and generates a list.

[1456] Server: Sends the generated list to the terminal.

[1457] Terminal: Display to the user "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[1458] 6. Your Choices and Details

[1459] User: Selects Restaurant B.

[1460] Terminal: Confirms the user's selection and sends the information to the server.

[1461] Server: Get detailed route guidance information and weather information for Restaurant B.

[1462] Server: Sends the acquired information to the terminal.

[1463] Terminal: Displays detailed route directions and weather information to the user.

[1464] Specific examples

[1465] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[1466] The above is an embodiment of the present invention.

[1467] The processing flow will be explained below.

[1468] Step 1: Enter user voice

[1469] User: Says, "I want to eat a delicious lunch."

[1470] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[1471] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[1472] Step 2: Analyzing the text data

[1473] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[1474] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[1475] Step 3: Obtaining location information

[1476] Device: Uses the GPS module to obtain the user's current location.

[1477] Device: Sends current location information to the server.

[1478] Step 4: Search for restaurant information

[1479] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1480] Server: Lists multiple candidate restaurants as search results.

[1481] Step 5: Get restaurant details

[1482] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1483] Server: Combines the collected information and sorts the restaurants by highest rating.

[1484] Step 6: Present the restaurant list

[1485] Server: Sends the consolidated restaurant list to the device.

[1486] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1487] Step 7: Selecting Users

[1488] User: Says, "Restaurant B is good."

[1489] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1490] Terminal: Parse the converted text and check the user's selections.

[1491] Step 8: Providing directions and weather information

[1492] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1493] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1494] Server: Obtains real-time weather information from an external weather API.

[1495] Server: Sends route guidance and weather information to the device.

[1496] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1497] Step 9: Final confirmation and guidance

[1498] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[1499] User: When ready, follow the instructions on the device to go to Restaurant B.

[1500] Example 1

[1501] 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."

[1502] Conventional information provision systems that use user voice have difficulty accurately understanding the user's intent and providing relevant information quickly and accurately. Even when providing information using location information, the system may not be able to present the most appropriate information for the user. Furthermore, when providing detailed information, the system may not be able to include the accurate information the user is looking for. It is necessary to solve these problems and provide more useful information to users.

[1503] 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.

[1504] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for the detailed information providing means to select related data based on an evaluation. This makes it possible to accurately understand the user's intention and quickly provide the most suitable related data for the user by utilizing the location information.

[1505] The "means for inputting user voice" is a function that allows a user to input voice into the system using a voice input device such as a microphone.

[1506] The "means for converting user voice into text data" is a function for converting voice data into text data using a voice recognition engine or the like.

[1507] "Means for analyzing text data to understand user intent" refers to a function that uses natural language processing technology to analyze and understand the content and intent of a user's speech from text data.

[1508] "Means for acquiring location information" refers to a function for acquiring the user's current location using a GPS module or other location measurement technology.

[1509] "Means for searching and obtaining related data based on location information" refers to a function that searches for and obtains related information from a database or external API based on the obtained location information.

[1510] The "means for presenting related data to the user" is a function for displaying the acquired related data on the user's terminal.

[1511] The "means for allowing the user to select the related data presented" is a function that allows the user to select desired information from the presented data.

[1512] The "means for providing detailed information based on selected data" is a function for obtaining and providing more detailed information to the user based on the data selected by the user.

[1513] The "means for the detailed information providing means to select related data based on evaluation" is a function that evaluates the collected related data and selects and provides data with high evaluations.

[1514] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide related information. To implement the system, the following hardware and software are required:

[1515] Hardware

[1516] Device: Smartphone or tablet equipped with a microphone and GPS module

[1517] Server: Cloud server with database management system

[1518] software

[1519] Speech recognition engine: Google Speech-to-Text API

[1520] Natural language processing module: OpenAI's GPT-3

[1521] Database: MongoDB

[1522] External APIs: Yelp API, Google Maps API, and OpenWeatherMap API

[1523] This system operates in the following procedure.

[1524] 1. User voice input and conversion

[1525] The user uses the microphone on their smartphone to say, "I want to eat a delicious lunch." The device captures the user's voice using the microphone and converts it into text data using the Google Speech-to-Text API.

[1526] 2. Analyzing User Intent

[1527] The device then uses a natural language processing module to analyze the converted text and understand that the user is looking for a "delicious lunch." The analysis uses OpenAI's GPT-3 to extract related topics and keywords.

[1528] 3. Obtaining location information

[1529] The device acquires the user's current location using the GPS module and sends the acquired latitude and longitude to the server.

[1530] 4. Searching and retrieving relevant data

[1531] The server searches for nearby restaurant information from a database (MongoDB) based on the location information sent, and also collects data such as menus, reviews, and ratings for each related restaurant from an external API (Yelp API).

[1532] 5. Restaurant recommendations

[1533] The server selects highly rated restaurants based on the collected data and generates a list. The generated list is sent to the device, which then displays a message to the user saying, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[1534] 6. Your Choices and Details

[1535] When the user selects Restaurant B, the device sends that information to the server. The server obtains detailed route guidance information to Restaurant B using the Google Maps API and weather information using the OpenWeatherMap API. The obtained information is sent to the device, and the device displays detailed route guidance and weather information to the user.

[1536] Specific examples

[1537] For example, if a user says, "I want to eat a delicious lunch," the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and simultaneously displays weather information, allowing the user to obtain all the necessary information in one app and take action smoothly.

[1538] Prompt Sentence Examples

[1539] By inputting the following prompt sentence into the generative AI model, information can be obtained to understand the overview of this system.

[1540] "When a user says they want to have a delicious lunch, explain how the speech recognition engine converts that information into text and then the natural language processing module analyzes it. Also explain how relevant restaurant information is searched for and presented."

[1541] The above is an embodiment of the present invention.

[1542] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1543] Step 1:

[1544] The user speaks into the smartphone's microphone, saying, "I want to eat a delicious lunch."

[1545] Input: User voice

[1546] Output: Captured audio data

[1547] The device uses a microphone to capture the user's voice, and the voice signal is digitized by an audio input device.

[1548] Step 2:

[1549] The device sends the captured voice data to the Google Speech-to-Text API, which converts the voice data into text data.

[1550] Input: Captured audio data

[1551] Output: Converted text data

[1552] Specifically, code is executed to send the captured audio data to the API, and the returned text data is retrieved.

[1553] Step 3:

[1554] The device analyzes the converted text data using a natural language processing module (e.g., OpenAI's GPT-3) to understand the user's intent.

[1555] Input: Converted text data

[1556] Output: User intent

[1557] Text data is input into the AI ​​as a prompt, and keywords (e.g., "delicious," "lunch," "want to eat") are extracted from the response to identify the user's intent.

[1558] Step 4:

[1559] The terminal sets search conditions based on the extracted keywords.

[1560] Input: User intent

[1561] Output: Search criteria

[1562] As a specific example, if it turns out that the user is looking for a "delicious lunch," this is set as a search condition.

[1563] Step 5:

[1564] The terminal obtains the user's current location using a GPS module.

[1565] Input: None

[1566] Output: Latitude and longitude information

[1567] The code runs to activate the GPS sensor and obtain the current latitude and longitude.

[1568] Step 6:

[1569] The terminal transmits the acquired current location information to the server.

[1570] Input: Latitude and longitude information

[1571] Output: Transferred location information

[1572] For security reasons, data is sent to the server using the HTTPS protocol.

[1573] Step 7:

[1574] The server searches a database (e.g., MongoDB) for nearby restaurant information based on the received location information.

[1575] Input: Transferred current location information

[1576] Output: Nearby restaurant information

[1577] Create a query based on latitude and longitude to retrieve relevant restaurant data.

[1578] Step 8:

[1579] The server collects data such as menus, reviews, and ratings for each relevant restaurant from an external API (e.g., Yelp API).

[1580] Input: Nearby restaurant information

[1581] Output: Detailed restaurant information (menu, reviews, ratings, etc.)

[1582] Send a request to the Yelp API using the restaurant ID, and parse the returned JSON data to obtain information.

[1583] Step 9:

[1584] The server selects highly rated restaurants based on the collected data.

[1585] Input: Detailed restaurant information

[1586] Output: A list of top-rated restaurants

[1587] The reviews and rating scores of each restaurant are statistically analyzed to create a list of the top restaurants.

[1588] Step 10:

[1589] The server transmits the generated list to the terminal.

[1590] Input: Top-rated restaurant list

[1591] Output: Transferred restaurant list

[1592] Code is executed to send the generated list to the terminal.

[1593] Step 11:

[1594] The terminal displays to the user, "Restaurant A, Restaurant B, and Restaurant C have been found. Which one would you like?"

[1595] Input: Transferred restaurant list

[1596] Output: Information presented to the user

[1597] The UI uses a list view to layout and display the list.

[1598] Step 12:

[1599] The user selects Restaurant B from the list.

[1600] Input: User's selection (Restaurant B)

[1601] Output: Selected restaurant information

[1602] When the user presses the selection button, the selection information is stored in the terminal.

[1603] Step 13:

[1604] The terminal transmits the user's selection to the server.

[1605] Input: Selected restaurant information

[1606] Output: Data sent to the server

[1607] Code is executed to send a request containing the ID of the selected restaurant.

[1608] Step 14:

[1609] The server retrieves detailed route guidance information to the selected restaurant using the Google Maps API and retrieves weather information using the OpenWeatherMap API.

[1610] Input: Data to send to the server

[1611] Output: Detailed route directions and weather information

[1612] Route guidance information is obtained using the Google Maps API, and weather information is obtained using the OpenWeatherMap API.

[1613] Step 15:

[1614] The server transmits the acquired information to the terminal.

[1615] Input: Detailed driving directions and weather information

[1616] Output: Data sent to the terminal

[1617] Code is executed to transmit the obtained information to the terminal.

[1618] Step 16:

[1619] The device displays detailed route directions and weather information to the user.

[1620] Input: Data to send to the terminal

[1621] Output: Displayed route and weather information

[1622] It uses a map view to display routes and provides weather information in a text view.

[1623] (Application example 1)

[1624] 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."

[1625] In recent years, security management has become increasingly important, but conventional systems have had difficulty obtaining and providing real-time security information based on voice input. Furthermore, when users check the security status of their home or office while away from home, they have had to use multiple applications and devices, which is inconvenient. There is a need to solve these problems and provide security information efficiently through a single system.

[1626] 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.

[1627] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, and means for cooperating with a security system to acquire a security status. This allows a user to obtain security information in real time using voice input, and to quickly check the security status of their home or office even when they are away from home.

[1628] "User speech" refers to instructions or requests that a user inputs by voice.

[1629] "Means" refers to a method or apparatus for accomplishing a particular function or purpose.

[1630] "Text data" refers to character string data converted from speech by speech recognition.

[1631] "Natural language processing" is a technology that analyzes text data to understand human language and perform appropriate processing.

[1632] "Location information" refers to data that indicates a user's current geographic location.

[1633] "Related data" refers to all information provided by the server based on the user's request and location information.

[1634] "Presenting to the user" means that the system displays information to the user visually or audibly.

[1635] "Making a choice" refers to the act of encouraging a user to select a specific option from the information provided.

[1636] "Detailed information" refers to supplemental and specific information provided based on the data selected by the user.

[1637] "Security system" refers to any information system that ensures safety in a specific area.

[1638] "Security status" means data that indicates the current security status of an area monitored by a security system.

[1639] The system of the present invention inputs user speech, analyzes the speech, and provides related information. How to implement this system will be described below.

[1640] System Configuration and Operation

[1641] 1. User voice input and conversion

[1642] User: Uses the smartphone microphone to say, "What is the security situation in my office?"

[1643] Terminal: A speech recognition engine (for example, the speech_recognition library) is used to convert user speech into text data.

[1644] 2. Analyzing User Intent

[1645] Terminal: Uses natural language processing techniques (e.g., generative AI models) to understand user intent from text data.

[1646] Terminal: In this case, it is understood that the user wants to check the "security status of the office."

[1647] 3. Obtaining location information

[1648] On the device: Use a GPS module (e.g., the geopy library) to get the user's current location.

[1649] 4. Searching and retrieving relevant data

[1650] Server: Based on the user's intent and location, the server retrieves relevant security data from the security system, including surveillance camera footage, alarm logs, and access history.

[1651] 5. Analyze relevant data and present it to the user

[1652] Server: Analyzes the acquired security data and evaluates the current security situation.

[1653] Server: For example, it evaluates the security status as "normal" or "an unconfirmed intrusion has occurred" and sends the result to the terminal.

[1654] Terminal: Presents the evaluation results to the user visually or audibly.

[1655] Hardware and software used

[1656] Speech recognition engine: speech_recognition library

[1657] GPS module: geopy library

[1658] Natural Language Processing Technology: Generative AI Model

[1659] Security data acquisition: Security system API (general name)

[1660] Device: Smartphone

[1661] Specific examples

[1662] For example, if a user asks their smartphone, "What's the security situation in the office?" during lunchtime, the system will use GPS to determine that the user is near the office, query the security system, and obtain the office's surveillance camera footage and alarm information. It will then notify the user that "The security situation is normal."

[1663] Prompt Sentence Examples

[1664] "Develop a security guard assistant app that can detect security situations through voice and provide relevant information. For example, when a user asks, 'What is the security situation in my office?' the app will check their current location, retrieve the latest information from the security system, and provide it to the user."

[1665] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1666] Step 1: Capturing Audio Input

[1667] The user uses the microphone on their smartphone to say, "Tell me about the security situation in the office." This voice input is captured by the microphone and sent to the smartphone as voice data.

[1668] Step 2: Convert audio data to text

[1669] The device converts the captured voice data into text data using a voice recognition engine (for example, the speech_recognition library). The input is voice data and the output is text data. Specifically, the device analyzes the voice data and converts it into words and sentences.

[1670] Step 3: Analyze user intent

[1671] The device uses natural language processing technology (e.g., a generative AI model) to understand the user's intent from the text data. The input is the text data, and the output is the information the user wants to know (in this case, "Office security status"). This involves analyzing the text data and extracting the user's intent from verbs, nouns, and adjectives.

[1672] Step 4: Obtaining location information

[1673] The device uses a GPS module (for example, the geopy library) to obtain the user's current location. The input is a signal from the GPS sensor, and the output is latitude and longitude coordinate data. Specifically, the device receives satellite signals from the GPS sensor and calculates the current location based on them.

[1674] Step 5: Find and retrieve relevant data

[1675] The server retrieves relevant security data from the security system based on the user's intent and location information. The input is the user's intent and location information, and the output is security data (surveillance camera footage, alarm logs, entry and exit history). The server calls the security system's API to retrieve the necessary data.

[1676] Step 6: Analyze security data

[1677] The server analyzes the acquired security data and evaluates the current security situation. The input is the security data, and the output is the evaluation result of the security situation (for example, "The security situation is normal" or "An unconfirmed intrusion has occurred"). Specifically, each piece of data is analyzed to check for any abnormalities.

[1678] Step 7: Present information to the user

[1679] The server sends the evaluation results to the terminal, which then presents them to the user. The input is the security status evaluation result, and the output is a notification message to the user. The terminal displays the notification message to the user visually or audibly. For example, it may display "Security status is normal" on the screen or read it aloud.

[1680] 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.

[1681] The system of the present invention inputs user speech, analyzes the speech, and performs a series of processes to provide relevant information. It also has the ability to recognize the user's emotions and adjust the data presentation method based on the emotions. The following describes the specific operation of the system in natural language.

[1682] System Overview

[1683] 1. User voice input and conversion

[1684] User: Says, "I want to eat a delicious lunch."

[1685] Device: Uses a microphone to capture the user's voice.

[1686] Device: Uses a speech recognition engine to convert speech into text data.

[1687] 2. Analyzing User Intent

[1688] Terminal: The text data is analyzed using a natural language processing module to understand that the user is looking for a "delicious lunch."

[1689] Device: Identify relevant categories and set search criteria.

[1690] 3. Obtaining location information

[1691] Terminal: Obtains the user's current location using a GPS module.

[1692] Device: Sends current location information to the server.

[1693] 4. Search for restaurant information

[1694] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1695] Server: Lists multiple candidate restaurants as search results.

[1696] 5. Get restaurant details

[1697] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1698] Server: Combines the collected information and sorts the restaurants by highest rating.

[1699] 6. Present a list of restaurants

[1700] Server: Sends the consolidated restaurant list to the device.

[1701] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1702] 7. Your Choices and Details

[1703] User: Says, "Restaurant B is good."

[1704] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1705] Terminal: Parse the converted text and check the user's selections.

[1706] 8. Providing route guidance and weather information

[1707] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1708] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1709] Server: Obtains real-time weather information from an external weather API.

[1710] Server: Sends route guidance and weather information to the device.

[1711] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1712] 9. Emotion Recognition with Emotion Engine

[1713] Terminal: The user's voice input is analyzed, and the emotion engine recognizes the user's emotions.

[1714] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device will quickly present information and provide guidance in a calm voice.

[1715] Specific examples

[1716] For example, if a user says "I want to eat a delicious lunch" at home, the device converts this into text data and analyzes the user's intent. Next, it obtains the user's current location and searches for highly rated restaurants in the area. The server collects detailed information, including menu information and reviews, and presents recommended restaurants to the user based on the ratings. Once the user selects a restaurant, the device provides route guidance to the restaurant and weather information. Furthermore, the emotion engine recognizes the user's emotions and selects the appropriate information presentation method. This allows users to obtain all the information they need in one app and take action smoothly.

[1717] The above is an embodiment of the present invention.

[1718] The processing flow will be explained below.

[1719] Step 1: Enter user voice

[1720] User: Says, "I want to eat a delicious lunch."

[1721] Device: Captures the user's voice through a microphone and sends it to a speech recognition engine.

[1722] Device: The speech recognition engine converts the speech into text data, generating the text "I want to eat a delicious lunch."

[1723] Step 2: Analyzing the text data

[1724] Device: The natural language processing module analyzes the text data and understands the user's intent. Specifically, it analyzes the request "I want to eat a delicious lunch" and identifies restaurant search criteria.

[1725] Device: Set restaurant search conditions (e.g., delicious lunch, current time) as the analysis results.

[1726] Step 3: Obtaining location information

[1727] Terminal: Obtains the user's current location using a GPS module.

[1728] Device: Sends the acquired location information to the server.

[1729] Step 4: Search for restaurant information

[1730] Server: Based on the user's current location, the server searches a database for nearby restaurants that serve delicious lunch.

[1731] Server: Lists multiple candidate restaurants as search results.

[1732] Step 5: Get restaurant details

[1733] Server: For each listed restaurant, collect details such as menu, reviews, and ratings from an external API.

[1734] Server: Combines the collected information and sorts the restaurants by highest rating.

[1735] Step 6: Present the restaurant list

[1736] Server: Sends the consolidated restaurant list to the device.

[1737] Terminal: Show the user the list and ask, "I found Restaurant A, Restaurant B, and Restaurant C. Which one is better?"

[1738] Step 7: Emotion Recognition with the Emotion Engine

[1739] Device: The emotion engine analyzes the user's voice input and recognizes the user's emotions. For example, it analyzes the tone, pitch, and speed of the user's voice to determine whether the user is excited or relaxed.

[1740] Step 8: Adjust information presentation based on emotions

[1741] Device: Based on the emotion recognition results, the device adjusts the way information is presented. For example, if the user is excited, the device displays information quickly and provides guidance in a calm voice. Conversely, if the user is relaxed, the device provides detailed explanations.

[1742] Step 9: Select User

[1743] User: Says, "Restaurant B is good."

[1744] Device: Captures the user's voice and sends it to a speech recognition engine to convert it into text.

[1745] Terminal: Parse the converted text and check the user's selections.

[1746] Step 10: Providing directions and weather information

[1747] Terminal: Sends a request for route guidance to the server based on the location of the selected restaurant B.

[1748] Server: Works with the map database to generate detailed directions from the user's current location to Restaurant B.

[1749] Server: Obtains real-time weather information from an external weather API.

[1750] Server: Sends route guidance and weather information to the device.

[1751] Device: Shows the user detailed route directions with a map and displays weather information such as "rain expected."

[1752] Step 11: Final confirmation and guidance

[1753] Terminal: "Here are the directions to Restaurant B. Rain is expected. Are you ready?" confirms with the user.

[1754] User: When ready, follow the instructions on the device to go to Restaurant B.

[1755] Example 2

[1756] 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."

[1757] While conventional speech recognition systems can convert a user's speech into text and understand their intent, they have the problem of being unable to consider the user's emotions when presenting information. This can result in inappropriate presentation of the information the user is looking for, or a poor user experience. In particular, when searching for restaurants or using navigation, it is important to provide the information users need quickly and appropriately, but conventional technologies fall short in this area.

[1758] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1759] In this invention, the server includes means for inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select from the presented related data, means for providing detailed information based on the selected data, means for performing emotion recognition, and means for adjusting the information presentation method based on the emotion recognition result. This enables appropriate and prompt information presentation taking the user's emotions into consideration, thereby improving the user experience.

[1760] A "means for inputting user voice" is a device or mechanism for capturing voice uttered by a user.

[1761] The "means for converting the user's voice into text data" refers to an algorithm or service that converts voice data into character string data.

[1762] The "means for analyzing the text data and understanding the user's intent" refers to a natural language processing technology or module for identifying the user's request or purpose from the text data.

[1763] "Means for obtaining location information" refers to a GPS module or other location identification technology for identifying the user's current location.

[1764] "Means for searching and acquiring relevant data based on the location information" refers to the process of searching for relevant information from a database or external API based on the acquired location information and collecting the necessary data.

[1765] "Means for presenting said relevant data to a user" refers to a mechanism or method for displaying collected information through a user interface.

[1766] The "means for allowing the user to select the related data presented" is a mechanism that provides an interaction for the user to make a selection from the presented information.

[1767] The "means for providing detailed information based on the selected data" is a process for collecting and displaying additional information related to the item selected by the user.

[1768] "Means for emotion recognition" refers to an algorithm or engine for recognizing the emotional state of a user from their voice or behavior.

[1769] The "means for adjusting the information presentation method based on the emotion recognition result" is a mechanism for changing the information presentation method according to the recognized emotion.

[1770] The present invention relates to a system that analyzes a user's voice input and provides relevant information based on the user's intentions and emotions. This system is realized by combining speech recognition technology that converts user speech into text, natural language processing technology, technology for acquiring location information, technology for searching related data, and technology for recognizing emotions.

[1771] Specifically, the following hardware and software are used:

[1772] 1. The device has a built-in microphone, GPS module, display, and speech recognition engine. The microphone is used to capture the user's voice, and the speech is converted into text data using a speech recognition engine (e.g., a speech recognition API). A specific example is the Google Cloud Speech-to-Text API.

[1773] 2. The device analyzes the text data using a natural language processing module (e.g., a natural language processing API) to understand the user's intent. A specific example is the Google Cloud Natural Language API.

[1774] 3. The device obtains the user's current location using a GPS module. The device sends the location information to the server. Based on this location information, the server searches for relevant data. The server searches for nearby restaurant information using a database or an external API (e.g., a restaurant search API). Specific examples include the Yelp API and Google Places API.

[1775] 4. The server collects detailed information about the restaurants (menus, reviews, ratings, etc.) found in the search results, integrates the information, sorts it by highest rating, and then sends the integrated information to the device.

[1776] 5. The device displays a list of restaurants for the user to select from, and provides an interface for the user to confirm their selection by voice input again.

[1777] 6. The device requests route guidance and weather information from the server based on the selected restaurant details. The server generates detailed route guidance and retrieves real-time weather information from an external weather API (e.g., a weather information API). Specific examples include Google Maps API and OpenWeatherMap API.

[1778] 7. The device analyzes the voice data using an emotion recognition engine (e.g., emotion recognition API) to recognize the user's emotions. A specific example is IBM Watson Tone Analyzer.

[1779] 8. The device adjusts the way it presents information based on the emotion recognition results. For example, if the user is excited, it will promptly present information and provide guidance in a calm voice.

[1780] Specific examples

[1781] For example, if a user says, "I want a delicious lunch," the device captures this with the microphone and converts it into text using the Google Cloud Speech-to-Text API. The text is then analyzed using the Google Cloud Natural Language API to identify the intent of "a delicious lunch." The device obtains its current location using GPS and searches for nearby restaurant information using the Yelp API. The server consolidates the collected restaurant details, sorts them by highest rating, and sends them to the device. If the user selects "Restaurant B is good" by voice, the device provides route guidance using the Google Maps API and retrieves and displays weather information from the OpenWeatherMap API. The device then uses IBM Watson Tone Analyzer to recognize the user's emotions and selects the optimal way to present information.

[1782] Prompt Sentence Examples

[1783] 1. "When a user says they want a delicious lunch, what prompts would you use to design a system that converts that speech to text and provides relevant restaurant information?"

[1784] 2. "Please provide a prompt to provide directions and weather information to a user-specified restaurant."

[1785] 3. "Generate a prompt for designing a system that uses an emotion engine to recognize a user's emotions and adjust the way information is presented based on the results."

[1786] The above is an embodiment of the present invention.

[1787] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1788] System program processing flow

[1789] Step 1: Input and convert user speech

[1790] The user says, "I want to eat a delicious lunch." The device captures this speech using the built-in microphone. The captured speech data is sent to a speech recognition engine such as the Google Cloud Speech-to-Text API and converted into text data. The input is the user's speech data, and the output is the text data obtained from the speech recognition engine.

[1791] Step 2: Analyze user intent

[1792] The device receives the converted text data, "I want to eat a delicious lunch." It then uses a natural language processing module, such as the Google Cloud Natural Language API, to analyze this text and identify the user's intent. In this case, it understands that the user's intent is "Find a restaurant that serves delicious lunch." The input is the text data, and the output is keywords related to the analyzed intent.

[1793] Step 3: Obtaining location information

[1794] The device uses a GPS module to obtain the user's current location. The location information (latitude and longitude) is sent to the server. The input is the location data obtained from the GPS module, and the output is the location information sent to the server.

[1795] Step 4: Search for restaurant information

[1796] Based on the received location information, the server searches for nearby restaurant information by requesting it from a database or an external API (e.g., Yelp API). Here, the server lists restaurants where you can have a delicious lunch based on the user's current location. The input is the location information and the user's intention, and the output is the list of restaurant information.

[1797] Step 5: Get restaurant details

[1798] The server collects detailed information (menus, reviews, ratings, etc.) about the listed restaurants using the Google Places API, etc. The detailed information is integrated and sorted in descending order of ratings. The input is a list of restaurant candidates, and the output is a list of restaurants with the integrated detailed information.

[1799] Step 6: Present the restaurant list

[1800] The server sends the integrated restaurant list to the terminal. The terminal displays the list to the user and asks, "I found restaurants A, B, and C. Which one do you want?" The input is the restaurant list from the server, and the output is the list display and voice guidance through the user interface.

[1801] Step 7: Select user and provide details

[1802] The user selects "Restaurant B is good." The device captures the voice again and converts it into text using a speech recognition engine. This text data is analyzed and the user's selection is confirmed. The input is the user's voice data, and the output is the text data of the selected restaurant.

[1803] Step 8: Providing directions and weather information

[1804] The device requests route guidance and weather information from the server based on the location of the selected restaurant. The server uses the Google Maps API to generate detailed driving directions and the OpenWeatherMap API to retrieve real-time weather information. These data are sent to the device. The input is the restaurant location data, and the output is route guidance and weather information, which the device displays to the user.

[1805] Step 9: Emotion Recognition with the Emotion Engine

[1806] The device analyzes the user's voice using an emotion recognition engine (for example, IBM Watson Tone Analyzer) to identify the user's emotion. Based on the emotion recognition results, the device adjusts the way information is presented. The input is voice data and analysis results, and the output is a method of presenting information according to the emotion. For example, if the user is excited, information is presented quickly and guidance is given in a calm voice.

[1807] (Application example 2)

[1808] 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."

[1809] Conventional voice recognition systems were able to convert a user's voice input into text data, analyze their intent, and provide relevant information. However, they lacked the ability to recognize the user's emotions and adjust the way information is presented based on that. Furthermore, there were issues with navigation in virtual stores and providing detailed product information, making it difficult to create an environment where users could comfortably shop. Furthermore, users often found it difficult to navigate within a store or select products, which could be stressful.

[1810] The identification process by the identification 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 inputting user voice, means for converting the user voice into text data, means for analyzing the text data to understand the user's intention, means for acquiring location information, means for searching for and acquiring related data based on the location information, means for presenting the related data to the user, means for allowing the user to select the presented related data, means for providing detailed information based on the selected data, and means for recognizing the user's emotions and adjusting the presentation method of the detailed information based on the emotions. This enables the provision of information that takes user emotions into consideration, thereby improving the shopping experience in the virtual store. Specifically, it is possible to change the speed and content of information presentation depending on emotions, providing an environment in which users can comfortably search for and select products.

[1811] The "means for inputting user voice" is a function for acquiring voice uttered by the user through an input device such as a microphone within the device.

[1812] The "means for converting the user's voice into text data" refers to a voice recognition engine or software that converts the acquired voice data into text format.

[1813] The "means for analyzing the text data and understanding the user's intention" is a technology that uses a natural language processing module based on the text data to analyze the user's intention and request.

[1814] "Means for obtaining location information" refers to a function for obtaining information about the user's current location using a GPS module or other location information services.

[1815] "Means for searching and acquiring related data based on the location information" refers to algorithms and database search techniques for searching and acquiring related data or information based on the acquired location information.

[1816] The "means for presenting the related data to the user" refers to a display device or interface that presents the searched and acquired data to the user visually, audibly, or in other ways.

[1817] The "means for allowing the user to select related data presented" refers to a technique for providing an interface or operating means that allows the user to select specific information from the displayed data.

[1818] "Means for providing detailed information based on the selected data" refers to functions and technologies for collecting detailed information related to the data selected by the user and providing it to the user.

[1819] "Means for recognizing the user's emotions and adjusting the way in which the detailed information is presented based on those emotions" refers to an algorithm or system that recognizes emotions from the user's voice, facial expressions, etc., and adjusts the way in which information is presented (speed, content, etc.) according to the user's emotional state.

[1820] "Virtual store navigation information" is information that provides route guidance, direction, location information, and the like that are necessary when a user moves within a virtual space.

[1821] The present invention is a system that adaptively processes everything from user voice input to providing detailed information based on the user's emotions. The system of the present invention is realized using various hardware and software components. The specific hardware and software used are shown below, and the operation of the system is explained.

[1822] Hardware and software used

[1823] Hardware: Smartphones, smart glasses, head-mounted displays

[1824] software:

[1825] Speech recognition engine: Uses the Google Speech-to-Text API to convert voice data into text.

[1826] Natural Language Processing: Use the Google Natural Language API to analyze the converted text data.

[1827] Emotion Recognition Engine: Uses IBM Watson Tone Analyzer to recognize user emotions.

[1828] Location information acquisition: Uses "Google Maps API" to acquire the user's current location.

[1829] Database: Uses "Firebase Firestore" to manage detailed information.

[1830] System Operation

[1831] User voice input

[1832] Users input voice commands using, for example, a smartphone, smart glasses, or a head-mounted display. The device's built-in microphone captures the voice and converts it into text data using a speech recognition engine.

[1833] Natural language processing and intent analysis

[1834] The converted text data is sent to a natural language processing module to analyze the user's intent, thereby understanding the specific information or service the user is seeking (e.g., searching for a product in a virtual store).

[1835] Acquiring location information and searching related data

[1836] The user's location information is acquired using a GPS module, and related data (e.g., location information of nearby products) is searched for. Based on the acquired location information and the user's intent, related data is searched for.

[1837] Data Presentation and User Selection

[1838] The retrieved related data is presented to the user, from which the user can select specific information, and based on the selected data, further detailed information is provided.

[1839] Emotion recognition and information provision coordination

[1840] The emotion engine analyzes the user's tone of voice and facial expressions to identify their emotions, and adjusts how information is presented based on this analysis. For example, if the user is in a hurry, the system will present information more quickly.

[1841] Specific examples

[1842] Below are some specific examples for reference.

[1843] User Scenario

[1844] The user puts on the smart glasses and says, "I'm looking for a new smartphone at the virtual mall." The system converts this speech into text and analyzes the user's intent. Based on the analysis results, the system obtains information about the nearest smartphone store from the user's current location. Related products are presented to the user, providing detailed information. Further details, such as reviews, are displayed for the product selected by the user. The way information is presented is adjusted according to the user's emotions (excitement, impatience, etc.).

[1845] Prompt Sentence Examples

[1846] "If I want to easily get the information I need to optimize my system, how do I get started?"

[1847] These examples and prompts allow users to understand how the system is actually used and how information is presented. This invention allows users to easily obtain the information they need on the spot and respond appropriately according to their emotions.

[1848] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1849] Step 1:

[1850] A user inputs voice using a smart device (smartphone, smart glasses, head-mounted display), and the input voice is captured by a microphone in the device.

[1851] Input: User speech (e.g., "I'm looking for a new phone at the virtual mall.")

[1852] Output: Audio data

[1853] Step 2:

[1854] The device receives the voice data and converts it into text data using a voice recognition engine (Google Speech-to-Text API).

[1855] Input: Audio data

[1856] Output: Text data (e.g., "Looking for a new smartphone at the virtual mall")

[1857] Step 3:

[1858] The device sends the converted text data to a natural language processing module (Google Natural Language API) to analyze the user's intent.

[1859] Input: Text data

[1860] Output: User intent (e.g., smartphone search)

[1861] Step 4:

[1862] The terminal obtains the user's current location information using a GPS module and acquires location information.

[1863] Input: None (location information is obtained internally by the system)

[1864] Output: Current location information (e.g. longitude and latitude)

[1865] Step 5:

[1866] Based on the current location information and the user's intent, the server searches and retrieves relevant data (e.g., nearby smartphone stores) from a database (Firebase Firestore).

[1867] Input: current location, user intent

[1868] Output: Related data (e.g., information on nearby smartphone stores)

[1869] Step 6:

[1870] The terminal presents the acquired related data to the user and prompts the user to make a selection.

[1871] Input: relevant data

[1872] Output: Presented data (e.g., smartphone sales area list)

[1873] Step 7:

[1874] The user selects specific information from the presented data, and the selected information is received by the device. The user's selection is made by voice or touch operation.

[1875] Input: User selection (e.g. "Select this phone")

[1876] Output: Selected data

[1877] Step 8:

[1878] Based on the selected data, the server collects more detailed information (e.g., reviews, stock status) from external APIs and sends it to the device.

[1879] Input: Selected data

[1880] Output: Detailed information (e.g. smartphone reviews, stock status)

[1881] Step 9:

[1882] The device analyzes the tone of the user's voice and recognizes the user's emotions using an emotion engine (IBM Watson Tone Analyzer).

[1883] Input: User voice data

[1884] Output: Emotion recognition result (e.g., excitement, impatience)

[1885] Step 10:

[1886] The device adjusts how detailed information is presented based on the emotion recognition results, for example, by presenting information more quickly if the user is excited.

[1887] Input: Emotion recognition results, detailed information

[1888] Output: Adjusted detailed information

[1889] In this way, the system based on the present invention can provide appropriate information based on the user's voice input, and further adjust the presentation method according to the user's emotions.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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.

[1894] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1895] 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.

[1896] 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).

[1897] 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.

[1898] 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."

[1899] 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.

[1900] 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).

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] 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.

[1909] 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.

[1910] 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.

[1911] The following is further disclosed regarding the above embodiment.

[1912] (Claim 1)

[1913] a means for inputting user speech;

[1914] means for converting the user's voice into text data;

[1915] means for analyzing the text data to understand the user's intent;

[1916] A means for acquiring location information;

[1917] means for searching and acquiring related data based on the location information;

[1918] means for presenting the related data to a user;

[1919] means for allowing the user to select the presented related data;

[1920] means for providing detailed information based on the selected data;

[1921] A system including:

[1922] (Claim 2)

[1923] 2. The system of claim 1, wherein the detailed information providing means includes weather information.

[1924] (Claim 3)

[1925] 2. The system according to claim 1, wherein the detailed information providing means includes route guidance information.

[1926] "Example 1"

[1927] (Claim 1)

[1928] a means for inputting user speech;

[1929] means for converting the user's voice into text data;

[1930] means for analyzing the text data to understand the user's intent;

[1931] A means for acquiring location information;

[1932] means for searching and acquiring related data based on the location information;

[1933] means for presenting the related data to a user;

[1934] means for allowing the user to select the presented related data;

[1935] means for providing detailed information based on the selected data;

[1936] a means for selecting related data based on the evaluation by the detailed information providing means;

[1937] A system including:

[1938] (Claim 2)

[1939] 2. The system of claim 1, wherein the detailed information providing means includes weather information.

[1940] (Claim 3)

[1941] 2. The system according to claim 1, wherein the detailed information providing means includes route guidance information.

[1942] "Application Example 1"

[1943] (Claim 1)

[1944] a means for inputting user speech;

[1945] means for converting the user's voice into text data;

[1946] means for analyzing the text data to understand the user's intent;

[1947] A means for acquiring location information;

[1948] means for searching and acquiring related data based on the location information;

[1949] means for presenting the related data to a user;

[1950] means for allowing the user to select the presented related data;

[1951] means for providing detailed information based on the selected data;

[1952] A means for linking with a security system and acquiring a security status;

[1953] A system including:

[1954] (Claim 2)

[1955] 2. The system of claim 1, wherein the detailed information providing means includes weather information.

[1956] (Claim 3)

[1957] 2. The system according to claim 1, wherein the detailed information providing means includes route guidance information.

[1958] "Example 2: Combining Emotion Engines"

[1959] (Claim 1)

[1960] a means for inputting user speech;

[1961] means for converting the user's voice into text data;

[1962] means for analyzing the text data to understand the user's intent;

[1963] A means for acquiring location information;

[1964] means for searching and acquiring related data based on the location information;

[1965] means for presenting the related data to a user;

[1966] means for allowing the user to select the presented related data;

[1967] means for providing detailed information based on the selected data;

[1968] a means for performing emotion recognition;

[1969] a means for adjusting an information presentation method based on the emotion recognition result;

[1970] A system including:

[1971] (Claim 2)

[1972] 2. The system of claim 1, wherein the detailed information providing means includes weather information.

[1973] (Claim 3)

[1974] 2. The system according to claim 1, wherein the detailed information providing means includes route guidance information.

[1975] "Application example 2 when combining emotion engines"

[1976] (Claim 1)

[1977] a means for inputting user speech;

[1978] means for converting the user's voice into text data;

[1979] means for analyzing the text data to understand the user's intent;

[1980] A means for acquiring location information;

[1981] means for searching and acquiring related data based on the location information;

[1982] means for presenting the related data to a user;

[1983] means for allowing the user to select the presented related data;

[1984] means for providing detailed information based on the selected data;

[1985] means for recognizing a user's emotion and adjusting the presentation method of the detailed information based on the emotion;

[1986] A system including:

[1987] (Claim 2)

[1988] 2. The system of claim 1, wherein the detailed information providing means includes weather information.

[1989] (Claim 3)

[1990] 2. The system according to claim 1, wherein the detailed information providing means includes route guidance information.

[1991] (Claim 4)

[1992] 2. The system according to claim 1, wherein the detailed information providing means includes navigation information for a virtual store. [Explanation of symbols]

[1993] 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. a means for inputting user speech; means for converting the user's voice into text data; means for analyzing the text data to understand the user's intent; A means for acquiring location information; means for searching and acquiring related data based on the location information; means for presenting the related data to a user; means for allowing the user to select the presented related data; means for providing detailed information based on the selected data; A system including:

2. 2. The system of claim 1, wherein said detailed information providing means includes weather information.

3. 2. The system of claim 1, wherein said detailed information providing means includes route guidance information.

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