system

Abstract

We provide the system. [Solution] Means for recognizing the user, Means for selecting the user's language, A means for analyzing the voice input from the user, A means for providing information based on the input voice, In addition to providing the aforementioned information, means of providing entertainment, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a modern multilingual environment, user guidance and customer service in public facilities such as airports and restaurants require multilingual support. However, limited human resources often cannot fully meet such needs. Also, it is important to provide entertainment so that users can comfortably spend their waiting and staying times, rather than just providing information, but there are limitations in doing this manually. Furthermore, since there is no system that integrates these functions, it is necessary to handle them individually, making efficient operation difficult.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides the following means: a system including means for recognizing a user, means for selecting the user's language, means for analyzing the input voice from the user, means for providing information based on the input voice, and means for providing entertainment in addition to the information provision. Specifically, a camera and a voice recognition device are used as the user recognition means, and a generative artificial intelligence model is used as the entertainment provision means. This enables multilingual support and automated entertainment provision, thereby improving user satisfaction.

[0006] "Means of recognizing a user" refers to system components that use cameras, voice recognition devices, etc., to detect a physically present user and recognize their presence.

[0007] "Means for selecting the user's language" refers to a system component that identifies the language the user speaks and automatically selects a corresponding language based on that language.

[0008] "Means for analyzing the voice input from the user" refers to a system component that analyzes the voice data emitted by the user, converts it into text data, and understands its content.

[0009] "Means for providing information based on the input voice" refers to a system component that acquires information requested by the user based on the analysis results of the input voice and provides it to the user in an appropriate format.

[0010] "Means of providing entertainment in addition to the aforementioned information provision" refers to system components that generate and provide content to make users' waiting or stay time more enjoyable, in addition to providing information.

[0011] A "camera" is a device used to acquire visual information, and is used to detect a user's face and movements.

[0012] A "speech recognition device" is a device or software used to convert speech into text data and understand its content.

[0013] "Generative artificial intelligence models" is a general term for machine learning algorithms and software that automatically generate new content based on input data.

[0014] A "system" is a collection of hardware and software that integrates these means and performs a series of processes. [Brief explanation of the drawing]

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

Mode for Carrying Out the Invention

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

[0017] First, the language used in the following description will be described.

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

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

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

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

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

[0023] [First Embodiment]

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

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

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

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

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

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

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

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0036] This invention relates to a system that recognizes a user, selects a language, analyzes input speech, and provides information and entertainment. The following describes the program processing of this system, and provides a detailed explanation of its embodiments with specific examples.

[0037] Program processing

[0038] User recognition

[0039] The device recognizes the user using a camera and voice recognition system. Specifically, the device detects when the user approaches the robot and confirms the user's presence using facial recognition technology. In addition, the voice recognition system captures the user's speech and initially identifies the language the user is speaking.

[0040] Language selection

[0041] Based on the language the user speaks, the device automatically selects the appropriate language. For example, if the user says "Hello," the device selects English and sends that information to the server. This ensures that the entire system is compatible with the user's chosen language.

[0042] Analysis of input audio

[0043] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server uses natural language processing technology to analyze the text data and clearly identify the information the user is seeking.

[0044] Providing information

[0045] The server retrieves the necessary information based on the user's request and sends it to the terminal in the appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information (e.g., "The flight to New York departs from Gate 32 at 14:45").

[0046] Entertainment provider

[0047] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model, this content is customized according to the user's interests and waiting time.

[0048] Specific example

[0049] Example 1: Airport reception

[0050] 1. The user approaches the robot and says, "Hello."

[0051] 2. The device recognizes the user and selects English using the voice recognition device.

[0052] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[0053] 4. The user replies, "I need information about my flight to New York."

[0054] 5. The device converts the audio to text and sends the text data to the server.

[0055] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0056] 7. The device communicates this information to the user.

[0057] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[0058] 9. The user responds, "I'd like to hear a joke."

[0059] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[0060] 11. The device delivers jokes to the user to entertain them.

[0061] Example 2: Restaurant reception

[0062] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[0063] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[0064] 3. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[0065] 4. The user answers, "There are 4 people."

[0066] 5. The device converts the audio to text and sends the text data to the server.

[0067] 6. The server parses the request, checks the table reservation status, generates information such as "A table for 4 people is available from 19:00," and sends it to the terminal.

[0068] 7. The device communicates this information to the user.

[0069] 8. The device then suggests games that can be enjoyed during the waiting time, and if the user selects one, it provides an AR puzzle game.

[0070] In this way, users, devices, and servers work together to realize the overall functionality and improve the user experience. This system enables efficient and effective service by providing automated customer service and entertainment in a multilingual environment.

[0071] The following describes the processing flow.

[0072] Step 1: User Recognition

[0073] The device uses a sensing sensor to detect when a user approaches.

[0074] The device's camera uses facial recognition technology to capture the user's face.

[0075] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0076] Step 2: Language Selection

[0077] The user says, "Please speak in English."

[0078] The device's voice recognition system analyzes this speech and selects "English" from its language database.

[0079] The terminal sends the language information it selected to the server.

[0080] Step 3: Confirming User Intent

[0081] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0082] The terminal uses this script to ask the user questions.

[0083] The user replies, "I need information about my flight to New York."

[0084] Step 4: Analysis of the voice and moon

[0085] The device's speech recognition system converts the user's speech into text data.

[0086] The terminal sends text data to the server.

[0087] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[0088] Step 5: Information Acquisition and Provision

[0089] The server accesses the flight information database based on the user's request.

[0090] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[0091] The server translates this information into English text and sends it to the terminal.

[0092] The device communicates the information it has acquired to the user.

[0093] Step 6: Entertainment Proposal

[0094] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0095] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0096] The user replies, "I'd like to hear a joke."

[0097] Step 7: Providing entertainment

[0098] The terminal sends the user's request to the server.

[0099] The server generates jokes using a generative artificial intelligence model.

[0100] The server generates a joke and sends it to the device.

[0101] The device delivers a joke to the user.

[0102] Step 8: Feedback and Closing

[0103] The device asks the user, "Do you need any further assistance?"

[0104] The user replies, "No, thank you."

[0105] The device concludes with "Have a great day!" and ends user support.

[0106] (Example 1)

[0107] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0108] Conventional voice interface systems have struggled to respond to individual user requests and have often been limited to specific languages ​​and situations. Furthermore, they have not adequately improved the user experience in terms of multilingual support and entertainment provision. This has made it difficult to provide efficient and effective services, especially in places used by multinational users (e.g., airports and tourist destinations). To solve these problems, a system is needed that can integrate user language recognition, information provision, and entertainment provision.

[0109] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0110] In this invention, the server includes means for the terminal to recognize a user using a camera and a speech recognition device, means for automatically selecting the language spoken by the user, means for converting the user's speech into text data using the speech recognition device and transmitting it to the server, means for analyzing the text data using natural language processing technology to obtain information requested by the user, means for transmitting the information to the terminal and providing it to the user, and means for providing entertainment in addition to the information using a generative artificial intelligence model. This enables multilingual support and allows for the provision of information and entertainment based on the individual requests of the user.

[0111] A "terminal" refers to a device used for direct interaction with a user, and is equipped with hardware including a camera and a voice recognition device.

[0112] A "camera" is a device used to capture images and is used to recognize the user's face and movements.

[0113] A "speech recognition device" is a device that converts speech into text data and is used to analyze a user's speech.

[0114] A "server" refers to a device or system for processing and storing data, and it plays a role in analyzing data using natural language processing technology and providing necessary information.

[0115] "Natural language processing technology" refers to techniques for analyzing text data and understanding human language. For example, it is used to analyze the meaning of text data and identify the information that the user is looking for.

[0116] A "generative artificial intelligence model" refers to artificial intelligence that has the ability to generate new content based on user input, and is used, for example, to generate entertainment content such as jokes and quizzes.

[0117] A "user" refers to a person who uses a system, obtaining information or enjoying entertainment through interaction with the system.

[0118] "Entertainment" refers to content that provides users with enjoyment and satisfaction, and can take the form of jokes, quizzes, music, and so on.

[0119] "Information provision" refers to the act of a server acquiring necessary information in response to a user's questions or requests and then transmitting that information to the user via their terminal.

[0120] Modes for carrying out the invention

[0121] This invention relates to a system that recognizes the user, selects a language, analyzes the input voice, provides information, and further provides entertainment. Specific embodiments of this system are described in detail below.

[0122] User recognition

[0123] The device recognizes the user using a camera and a speech recognition device. Specifically, the device detects when a user approaches and uses a camera (e.g., a typical webcam) to confirm the user's presence using facial recognition technology. It also uses a speech recognition device (e.g., Google® Speech-to-Text API) to capture the user's speech and identify the language the user is speaking.

[0124] Language selection

[0125] The device automatically selects a language based on the user's speech. For example, if the user says "Hello," the device selects English and sends this information to the server.

[0126] Analysis of input audio

[0127] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server analyzes the text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify the information the user is looking for.

[0128] Providing information

[0129] The server retrieves the necessary information from relevant databases based on the analysis results and sends it to the terminal in an appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information.

[0130] Entertainment provider

[0131] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model (e.g., GPT-3®), this content is customized according to the user's interests and waiting time.

[0132] Specific example

[0133] Example 1: Airport reception

[0134] 1. The user approaches the robot and says, "Hello."

[0135] 2. The device recognizes the user and selects English using the voice recognition device.

[0136] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[0137] 4. The user replies, "I need information about my flight to New York."

[0138] 5. The device converts the audio to text and sends the text data to the server.

[0139] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0140] 7. The device communicates this information to the user.

[0141] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[0142] 9. The user responds, "I'd like to hear a joke."

[0143] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[0144] 11. The device delivers jokes to the user to entertain them.

[0145] Example of a prompt

[0146] "Use a generative AI model to generate jokes appropriate to specific situations."

[0147] "To provide the flight information requested by the user, please refer to the flight information database."

[0148] As described above, the present invention enables efficient and effective service provision in locations used by multinational users, through the coordinated and effective operation of users, terminals, and servers.

[0149] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0150] Step 1:

[0151] The device recognizes the user.

[0152] Input: Camera video and audio data.

[0153] Processing: The device's camera detects an approaching person and uses facial recognition software (e.g., OpenCV or FaceNet) to recognize the user's face. Additionally, a speech recognition device captures the user's speech and obtains initial audio data.

[0154] Output: User's facial image data and initial voice data.

[0155] Specific actions:

[0156] The device's camera activates and captures images of the surroundings.

[0157] The device uses facial recognition software to analyze facial features and confirm the user's presence.

[0158] The speech recognition device captures the user's speech in real time and generates initial audio data.

[0159] Step 2:

[0160] The device selects the user's language.

[0161] Input: Initial audio data.

[0162] Processing: The speech recognition device analyzes the initial audio data to identify the language the user is speaking. The identified language information is converted into JSON format.

[0163] Output: JSON data including language information.

[0164] Specific actions:

[0165] The terminal identifies the spoken language from the analysis results of the speech recognition device, and for example, selects English from the utterance "Hello".

[0166] Convert language information to JSON format and generate data packets.

[0167] Step 3:

[0168] The device converts the user's spoken content into text data and sends it to the server.

[0169] Input: Detailed speech data of the user.

[0170] Processing: The speech recognition device converts the speech into text data and sends that text data to the server via the network.

[0171] Output: User's speech in text format.

[0172] Specific actions:

[0173] The terminal uses a voice recognition device to convert the user's specific request (e.g., "I need information about my flight to New York") into text data.

[0174] The text data is packaged into a packet and sent to the server.

[0175] Step 4:

[0176] The server analyzes the text data and retrieves the necessary information.

[0177] Input: Text data of the user's spoken content.

[0178] Processing: Analyze text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify user requests. Send queries to relevant databases.

[0179] Output: Informational data based on user requests.

[0180] Specific actions:

[0181] The server analyzes the received text data using a natural language processing engine.

[0182] The server, in response to the request, sends a query to a flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45".

[0183] Step 5:

[0184] The server formats the acquired information and sends it to the terminal.

[0185] Input: Acquired information data.

[0186] Processing: Format the information into an appropriate format (text or audio data) to convey it to the user, and send it to the terminal.

[0187] Output: Formatted informational data.

[0188] Specific actions:

[0189] The server formats the information into text format.

[0190] The formatted information is packaged into a packet and sent to the terminal.

[0191] Step 6:

[0192] The device provides information to the user.

[0193] Input: Formatted informational data.

[0194] Processing: Formatted information is converted into speech data using speech synthesis software and conveyed to the user.

[0195] Output: Information conveyed to the user.

[0196] Specific actions:

[0197] The device converts text data into speech using a speech synthesis device.

[0198] The system informs the user that "The flight to New York leaves from Gate 32 at 14:45."

[0199] Step 7:

[0200] The device suggests entertainment options to the user.

[0201] Input: User recognition information and request details obtained in the previous processing step.

[0202] Processing: Run an application that generates and suggests entertainment options (jokes, quizzes, music, etc.) to the user.

[0203] Output: Entertainment options presented to the user.

[0204] Specific actions:

[0205] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0206] The system presents customized options based on the user's interests and waiting time.

[0207] Step 8:

[0208] The server generates entertainment content and sends it to the device.

[0209] Input: The user's selected entertainment option.

[0210] Processing: Use a generative artificial intelligence model (e.g., GPT-3) to generate content based on user selections. Send the generated content to the device.

[0211] Output: Customized entertainment content.

[0212] Specific actions:

[0213] The device sends the user's selection (e.g., "I'd like to hear a joke") to the server.

[0214] The server prompts the AI ​​model with "Generate a joke for a traveler waiting for their flight" and sends the generated joke to the device.

[0215] Step 9:

[0216] The device provides users with generated entertainment content.

[0217] Input: Generated entertainment content.

[0218] Processing: Provide entertainment content to users in audio or other formats.

[0219] Output: Entertainment content provided to the user.

[0220] Specific actions:

[0221] The device converts the generated joke into speech using a speech synthesizer and delivers the joke, "Why don't scientists trust atoms? Because they make up everything!" to the user.

[0222] (Application Example 1)

[0223] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0224] In traditional brick-and-mortar stores, the challenges included providing customers with the information they needed quickly and efficiently, and improving customer waiting times and the overall experience. Furthermore, multilingual support was difficult, limiting service provision to foreign customers. Additionally, there was a lack of means to enhance customer satisfaction by providing appropriate entertainment.

[0225] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0226] In this invention, the server includes means for recognizing the user, means for selecting the user's language, means for analyzing the user's input voice, and means for interacting with customers in the store using smart glasses. This makes it possible to quickly provide the information that customers request and to provide information to foreign customers by supporting foreign languages. Furthermore, customer satisfaction can be improved by offering customers entertainment such as coupons and games.

[0227] A "user" is a person who uses a system to receive information and entertainment.

[0228] "Recognition" refers to identifying the presence and characteristics of a user using devices such as cameras and voice recognition systems.

[0229] "Language" refers to a means of communication used by users, and specifically to a particular natural language.

[0230] "Selection" refers to the automatic determination of the appropriate language based on the words spoken by the user.

[0231] "Input voice" refers to the voice data that a user emits to the system.

[0232] "Analysis" is the process of converting input audio into text data and understanding its content.

[0233] "Information provision" means conveying necessary data and knowledge based on user requests.

[0234] "Entertainment" refers to content such as jokes, games, and quizzes designed to entertain users.

[0235] "Smart glasses" are wearable devices that have the function of displaying visual information.

[0236] "Dialogue" is the process by which a system and a user exchange information through voice.

[0237] A "coupon" is an electronic or paper certificate that offers a discount on goods or services.

[0238] "Game" refers to a competition or activity conducted for entertainment purposes.

[0239] This invention is a system that recognizes the user, selects the appropriate language, analyzes the input voice, and provides information and entertainment. This system supports in-store interactions for the user using smart glasses.

[0240] System program

[0241] The system uses the following main hardware and software:

[0242] Hardware: Camera, voice recognition device, smart glasses

[0243] Software: Facial recognition technology, speech recognition (such as Google Speech Recognition API), natural language processing (NLP), generative artificial intelligence models

[0244] Program processing

[0245] 1. User Recognition: When a user enters a physical store, a camera recognizes the user's face and a voice recognition device captures the user's speech. Specifically, the camera uses facial recognition technology with HaarcascadeClassifier to confirm the user's presence.

[0246] 2. Language Selection: The system automatically selects a language based on the user's speech. Speech recognition software (such as the Google Speech Recognition API) is used to identify the language the user is speaking. This process ensures the entire system operates in the selected language.

[0247] 3. Analysis of Input Voice: The system analyzes the voice input provided by the user through the smart glasses. The input voice is converted into text data and sent to the server. The server uses natural language processing (NLP) technology to analyze the input text and identify the information the user is seeking.

[0248] 4. Information Provision: The server retrieves information according to the user's request and displays it to the user through smart glasses. For example, if the user says, "I want to know the size of this product," the server refers to the product database and sends the corresponding size information to the smart glasses.

[0249] 5. Entertainment Provision: After providing information, the server generates and suggests entertainment options (e.g., jokes, quizzes, games) to the user. Generative artificial intelligence models are used to customize content according to the user's interests and waiting time.

[0250] Specific example

[0251] Example 1: Providing services at a physical store

[0252] 1. The user enters a physical store and puts on the smart glasses.

[0253] 2. The camera recognizes the user, and the user speaks to the smart glasses saying, "Tell me about this product."

[0254] 3. The voice recognition device analyzes the user's speech and retrieves the relevant information from the product database.

[0255] 4. Information is displayed on the smart glasses and provided to the user.

[0256] 5. After providing information, the smart glasses will suggest to the user, "You have a coupon that can be used for your next purchase. Would you like to use it?"

[0257] Example of a prompt

[0258] "I'd like to know the size."

[0259] Prompt message:

[0260] Design a program that analyzes a user's voice when they use "smart glasses" to ask for product information, such as size, and then automatically provides that information. Additionally, the program should include a joke after providing the information.

[0261] Thus, the invention constructs a system in which the user, terminal, and server work together to greatly improve the user experience.

[0262] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0263] Step 1:

[0264] The user enters a physical store and puts on smart glasses. The smart glasses activate, and the camera and voice recognition device begin operating. The input here is the activation of the smart glasses, and the output is the activation of the camera and voice recognition device.

[0265] Step 2:

[0266] The camera recognizes the user's face. When the user passes in front of the camera, the HaarcascadeClassifier is used to detect the face. If face recognition is successful, the information is saved as face feature data. The input here is the camera image, and the output is the recognized face feature data.

[0267] Step 3:

[0268] The speech recognition device captures the user's speech. When the user says, "What are the dimensions of this product?", the speech recognition device takes the audio and uses the Google Speech Recognition API to convert the audio data into text. In this case, the input is the user's voice, and the output is the converted text data.

[0269] Step 4:

[0270] Text data is sent to the server. The server receives this text data and performs analysis using natural language processing (NLP) techniques. Through this analysis, the server identifies the user's request (a request for product size information). The input here is text data, and the output is the analyzed request content.

[0271] Step 5:

[0272] The server refers to the product database and retrieves the relevant product information. Specifically, it executes a database search query and extracts the size information for the relevant product (e.g., a shirt). The input here is the parsed request content, and the output is the retrieved product size information.

[0273] Step 6:

[0274] The server sends the acquired information to the smart glasses. The smart glasses display this information to the user, informing them, "This product is size M." The input here is the acquired product size information, and the output is the information displayed on the smart glasses.

[0275] Step 7:

[0276] Following the provision of information, the server generates entertainment options using a generative artificial intelligence model. Specifically, based on the user's interests and waiting time, it generates content such as jokes and quizzes and sends it to the smart glasses. The input here is the user's interests and waiting time, and the output is the generated entertainment content.

[0277] Step 8:

[0278] The smart glasses propose entertainment options to the user. It makes a proposal in speech such as "There is a coupon that can be used at the next purchase. Do you want to use it?" The input here is the generated entertainment content, and the output is the content of the proposal conveyed to the user.

[0279] In this way, the system provides efficient and multilingual information and entertainment to the user through a series of processing steps.

[0280] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0281] The present invention relates to a system that combines an emotion engine for recognizing the user's emotion in addition to user recognition and language selection, analysis of input speech, information provision, and entertainment provision. The program and its processing of this system will be described in detail below.

[0282] Processing of the program

[0283] User recognition

[0284] The terminal uses a sensing sensor to detect that the user has approached. The camera of the terminal captures the user's face using face recognition technology, and the voice recognition device asks the user "Hello, in which language should I guide you?"

[0285] Language Selection

[0286] When the user says "Please in English", the voice recognition system of the terminal analyzes this voice and selects "English" from the language database. The terminal sends the selected language information to the server.

[0287] Emotion Recognition

[0288] The emotion engine of the terminal analyzes the voice and facial expression data of the user to identify the emotion. For example, it recognizes emotions such as "excitement", "uneasiness", "joy" from the user's voice tone and facial expression.

[0289] Confirmation of User Intent

[0290] The server generates an English question script "How can I assist you today?" and sends it to the terminal. The terminal uses this script to ask the user, and the user answers "I need information about my flight to New York".

[0291] Analysis of Voice Data

[0292] The voice recognition device of the terminal converts the user's speech into text data and sends the text data to the server. The server receives the sent text data and analyzes the user's intent using natural language processing technology.

[0293] Obtaining and Providing Information

[0294] The server refers to the flight information database based on the user's request and obtains specific information such as "The flight to New York leaves from Gate 32 at 14:45". The server formulates this information into a sentence in English and sends it to the terminal. The terminal conveys the obtained information to the user.

[0295] Entertainment Proposal and Emotion-based Customization

[0296] The server generates a script for an entertainment option (joke, quiz, music, etc.) and sends it to the device. The device then prompts the user with "Would you like to hear a joke or play a quick game while you wait?". If the user responds with "I'd like to hear a joke," the emotion engine generates an appropriate joke based on the user's current mood.

[0297] For example, if a user is feeling stressed, a lighthearted joke can be offered to help them relax. This emotionally-driven customization makes the user experience more personalized and increases satisfaction.

[0298] Specific example

[0299] Example 1: Application of emotion recognition at airport reception.

[0300] 1. The user approaches the robot and says, "Hello."

[0301] 2. The device recognizes the user and selects English using the voice recognition device.

[0302] 3. The device's emotion engine analyzes the user's voice and facial expressions to recognize "anxiety."

[0303] 4. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[0304] 5. The user replies, "I need information about my flight to New York."

[0305] 6. The device converts the audio to text and sends the text data to the server.

[0306] 7. The server analyzes the request, generates the information "The flight to New York leaves from Gate 32 at 14:45", and sends it to the terminal.

[0307] 8. After the terminal conveys this information to the user, it provides a joke to relax the user based on the emotion.

[0308] Example 2: Utilization of emotion recognition at the reception of a restaurant

[0309] 1. The user says to the robot in Japanese, "I want to reserve a table."

[0310] 2. The terminal recognizes the user and selects Japanese with the speech recognition device.

[0311] 3. The emotion engine of the terminal recognizes "joy" from the user's voice tone.

[0312] 4. The server generates a script to ask the user "How many people are there?", and sends it to the terminal.

[0313] 5. The user answers, "There are 4 people."

[0314] 6. The terminal converts the voice to text and sends the text data to the server.

[0315] 7. The server analyzes the request, generates the information "A table for 4 people can be used starting from 19:00", and sends it to the terminal.

[0316] 8. After the terminal conveys this information to the user, it proposes and provides entertainment (e.g., games) to enjoy according to the emotion.

[0317] In this way, the user, device, server, and emotion engine work together to realize the overall operation and improve the user experience. This system not only provides automated customer service and entertainment in a multilingual environment, but also delivers a more sophisticated service by responding to the user's emotions.

[0318] The following describes the processing flow.

[0319] Step 1: User Recognition

[0320] The device uses a proximity sensor to detect when a user approaches.

[0321] The device's camera captures the user's face, and facial recognition technology is used to confirm the user's presence.

[0322] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0323] Step 2: Language Selection

[0324] The user replies, "Please speak in English."

[0325] The device's voice recognition system analyzes the user's voice and selects "English" from its language database.

[0326] The terminal sends the language information it selected to the server.

[0327] Step 3: Emotion Recognition

[0328] The device's emotion engine analyzes the user's voice tone and facial expressions.

[0329] The device identifies the user's emotion as "anxiety."

[0330] Step 4: Confirming User Intent

[0331] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0332] The terminal uses this script to ask the user questions.

[0333] The user replies, "I need information about my flight to New York."

[0334] Step 5: Audio Data Analysis

[0335] The device's speech recognition system converts the user's speech into text data.

[0336] The terminal sends text data to the server.

[0337] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[0338] Step 6: Information Acquisition and Provision

[0339] The server accesses the flight information database based on the user's request.

[0340] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[0341] The server translates this information into English text and sends it to the terminal.

[0342] The device communicates the acquired information to the user. "Your flight to New York departs at 14:45 from Gate 32."

[0343] Step 7: Entertainment suggestions and emotionally-based customization

[0344] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0345] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0346] The user replies, "I'd like to hear a joke."

[0347] The terminal sends the user's request to the server.

[0348] The server uses a generative artificial intelligence model to generate lighthearted jokes to help the user relax based on their emotions (e.g., anxiety).

[0349] The server generates a joke and sends it to the device.

[0350] The device delivers a joke to the user.

[0351] Step 8: Feedback and Closing

[0352] The device asks the user, "Do you need any further assistance?"

[0353] The user replies, "No, thank you."

[0354] The device concludes with "Have a great day!" and ends user support.

[0355] (Example 2)

[0356] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0357] Traditional systems suffer from a lack of consideration for user emotions in language selection, information provision, and entertainment delivery, resulting in insufficient improvement in the quality of the user experience. Providing personalized services is particularly difficult for users in multilingual environments or those experiencing diverse emotional states. This can lead to decreased user satisfaction and reduced system usage.

[0358] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0359] In this invention, the server includes means for selecting the user's language, means for recognizing the user's emotions, and means for providing information. This enables the provision of personalized entertainment tailored to the user's emotional state.

[0360] "Means of recognizing users" refers to technologies that detect when a user approaches the system and identify the user using biometric information such as facial features and voice.

[0361] "Means for selecting the user's language" refers to technology that analyzes the appropriate language from the user's speech or input and sets the system's operation method and information provision method based on that language.

[0362] "Means for analyzing input speech" refers to technologies that acquire voice data spoken by a user and perform speech-to-text conversion or natural language processing to understand its content and intent.

[0363] "Means of providing information" refers to technologies that acquire appropriate information based on user input or requests and present that information to the user in an easily understandable way.

[0364] "Means of recognizing user emotions" refers to technologies that analyze the user's tone of voice, facial expressions, etc., to identify the user's current emotional state (excitement, anxiety, joy, etc.).

[0365] "Means of providing entertainment" refers to technologies that generate and provide entertainment content such as jokes, quizzes, and music in order to provide users with relaxation and enjoyment.

[0366] "Methods for customizing entertainment based on emotions" refers to technologies that select and provide optimal entertainment content by considering the user's emotional state.

[0367] This invention relates to a system that combines user recognition, language selection, input speech analysis, information provision, and entertainment provision with an emotion engine that recognizes the user's emotions. The following describes a specific form for implementing this system.

[0368] Hardware and software to be used

[0369] This system uses the following hardware and software:

[0370] Sensing sensor: Used to detect when a user approaches the device.

[0371] Camera: Captures the user's face using facial recognition technology (e.g., OpenCV or FaceNet).

[0372] Speech recognition device: A device for converting speech into text data (e.g., Google Speech-to-Text).

[0373] Emotion engine: Analyzes the user's voice tone and facial expressions to recognize emotions (e.g., Microsoft® Azure® Emotion API).

[0374] Server: Analyzes user intent using natural language processing technology (e.g., GPT-4®) and provides necessary information.

[0375] Flight information database: A database (e.g., SQLite, MySQL®) that stores information to respond to user requests.

[0376] Program details

[0377] User recognition

[0378] When a user approaches the device, the device's sensing sensors detect the user's proximity.

[0379] The device uses its camera and facial recognition technology to capture the user's face.

[0380] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0381] Language selection

[0382] The user replies, "Please speak in English."

[0383] The device analyzes this voice using its voice recognition system and selects "English" from its multilingual database.

[0384] The device sends the selected language information to the server.

[0385] emotion recognition

[0386] The device's emotion engine analyzes the user's voice and facial expressions to identify their emotions.

[0387] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[0388] Confirming user intent and providing information

[0389] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0390] The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[0391] The terminal's speech recognition device converts the user's speech into text data and sends it to the server.

[0392] The server uses natural language processing techniques to analyze the user's intent from the text data it receives.

[0393] Based on the user's request, the server consults the flight information database and retrieves the information "The flight to New York leaves from Gate 32 at 14:45".

[0394] The server generates information and sends it to the terminal, which then relays the information to the user.

[0395] Entertainment proposals and customization

[0396] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0397] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0398] The user replies, "I'd like to hear a joke."

[0399] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, it provides lighthearted jokes to help a stressed user relax.

[0400] Specific example

[0401] Airport reception

[0402] 1. The user approaches the robot and says, "Hello."

[0403] 2. The device detects approach using its sensors and recognizes faces using its cameras.

[0404] 3. The terminal asks, "In what language would you like us to guide you?"

[0405] 4. The user replies, "Please speak in English."

[0406] 5. The device analyzes the audio and notifies the server that it is in English.

[0407] 6. The device's emotion engine analyzes voice and facial expressions to recognize "anxiety."

[0408] 7. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[0409] 8. The user replies, "I need information about my flight to New York."

[0410] 9. The device converts the audio to text and sends it to the server.

[0411] 10. The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0412] 11. The device conveys information to the user.

[0413] 12. The device offers a lighthearted joke to alleviate user anxiety.

[0414] Examples of prompts for generative AI models

[0415] 1. To the emotion engine: "Identify the user's current emotion based on their voice tone and facial expression data."

[0416] 2. To a natural language processing system: "Please analyze this text data and understand the user's intent."

[0417] 3. In response to an entertainment suggestion: "Generate jokes to help users relax when they are feeling stressed."

[0418] In this way, a system can be realized in which the user, terminal, server, and emotion engine work together to improve the quality of service provided to the user.

[0419] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0420] Step 1: User Recognition

[0421] The user approaches the device.

[0422] Input: User approach.

[0423] The device's sensor detects the user's approach.

[0424] The device uses its camera to capture the user's face using facial recognition technology (e.g., OpenCV, FaceNet).

[0425] Input: User's face image.

[0426] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0427] Output: Face recognition results, language selection prompt.

[0428] Step 2: Language Selection

[0429] The user replies, "Please speak in English."

[0430] Input: User's voice.

[0431] The device analyzes this audio using its speech recognition system (e.g., Google Speech-to-Text) and selects "English" from its multilingual database.

[0432] The device sends the selected language information to the server.

[0433] Output: Language selection result (English), language information sent to the server.

[0434] Step 3: Emotion Recognition

[0435] The device's emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's voice and facial expressions.

[0436] Input: User's voice tone and facial expression data.

[0437] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[0438] Output: Emotion recognition result.

[0439] Step 4: Confirming User Intent

[0440] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0441] Input: Server entertainment planning.

[0442] The device asks the user a question.

[0443] The user replies, "I need information about my flight to New York."

[0444] Output: User request.

[0445] Step 5: Audio Data Analysis

[0446] The device's speech recognition system converts the user's speech into text data.

[0447] Input: User's spoken audio.

[0448] The terminal sends the generated text data to the server.

[0449] Output: Text data.

[0450] Step 6: Information Acquisition and Provision

[0451] The server analyzes the received text data using natural language processing techniques (e.g., GPT-4) to confirm the user's intent.

[0452] Input: Text data, natural language processing model.

[0453] The server accesses a flight information database (e.g., SQLite, MySQL) based on the user's request.

[0454] Output: Required information (flight information).

[0455] The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0456] Output: A message containing information.

[0457] Step 7: Information Dissemination

[0458] The device communicates the information it has acquired to the user.

[0459] Input: Flight information.

[0460] Output: Voice message.

[0461] Step 8: Entertainment Suggestions and Customization

[0462] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0463] Input: Server entertainment planning and sentiment information.

[0464] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0465] The user replies, "I'd like to hear a joke."

[0466] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, if the user is feeling stressed, it will provide lighthearted jokes to help them relax.

[0467] Output: Emotionally customized entertainment.

[0468] In this way, input, data processing, data calculation, and output are performed at each processing step, enabling personalized service for each user.

[0469] (Application Example 2)

[0470] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0471] Traditional automated dialogue systems struggle to take user emotions into account, resulting in a limited user experience. Furthermore, insufficient multilingual support makes it difficult to serve users who speak different languages. This makes it challenging to enhance user satisfaction, particularly in virtual stores where natural dialogue and high-quality information delivery are essential.

[0472] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0473] In this invention, the server includes means for recognizing a user, means for selecting the user's language, means for recognizing the user's emotions, means for providing information based on the input voice and emotions, and means for generating the entertainment using a generative artificial intelligence model. This enables the provision of personalized information and entertainment based on the user's emotions.

[0474] "Means of recognizing a user" refers to technologies that use cameras and voice recognition devices to detect and identify a user's face and voice.

[0475] "Means of selecting a language" refers to a technology that analyzes and selects the language used by the user via a speech recognition device.

[0476] "Methods for analyzing input speech" refer to technologies that convert voice input from a user into text data and understand its content.

[0477] "Means of recognizing emotions" refers to technologies that analyze a user's voice tone and facial expressions to identify the user's emotional state.

[0478] "Means of providing information" refers to technologies that search for relevant data based on user requests and provide that information to the user.

[0479] "Means of providing entertainment" refers to the technology that generates and delivers content that users can enjoy.

[0480] A "generative artificial intelligence model" is a technology that uses artificial intelligence algorithms to generate content tailored to the user.

[0481] A "prompt message" is an instruction message that is input into a generative artificial intelligence model to generate an appropriate response or content.

[0482] This invention relates to a system that combines means for recognizing emotions in user recognition, language selection, voice input analysis, information provision, and entertainment provision. The aim of this system is to improve the user experience in virtual stores.

[0483] 1. System Configuration

[0484] hardware

[0485] Camera: A device used to capture the user's face and perform facial recognition.

[0486] Speech recognition device: A device that captures the user's voice and performs language selection and speech analysis.

[0487] Server: A central device that processes and manages various types of data.

[0488] software

[0489] Face recognition technology: Uses ZaCV or similar face recognition technology.

[0490] Speech recognition technology: We use Google Speech-to-Text API and Amazon Transcribe.

[0491] Emotion recognition engine: Recognizes user emotions using Microsoft Azure Face API and other tools.

[0492] Natural language processing techniques: We use Google NLP API and spaCy.

[0493] Generative AI Models: Generative AI models such as OpenAI® GPT-3 are used.

[0494] 2. Data Calculation and Processing

[0495] User recognition and language selection

[0496] The device first uses a camera to capture the user's face and recognizes the user using facial recognition technology. Next, a voice recognition device captures the user's voice to determine which language to use. When the user responds to the question, "Hello, in what language would you like me to guide you?" with "English, please," the voice recognition technology analyzes the voice and selects the appropriate language.

[0497] emotion recognition

[0498] The device analyzes the user's voice tone and facial expressions to identify their emotions. For example, it can recognize emotions such as "joy" or "anxiety" from the user's voice tone and facial expressions. This process uses the Microsoft Azure Face API.

[0499] Providing information

[0500] The server receives a user request (e.g., "I am looking for a smart TV") and analyzes its content using natural language processing technology. It then retrieves the information the user is looking for from relevant databases, generates a specific response (e.g., "Here are the top 3 smart TVs available"), and sends it to the device.

[0501] Entertainment provider

[0502] The server uses a generative artificial intelligence model to generate entertainment options (e.g., jokes) based on the user's emotions. The terminal suggests these options, and if the user shows interest, it provides the generated entertainment content. For example, a user in a "relaxed" emotional state would be offered relaxing jokes.

[0503] Specific example

[0504] 1. The user accesses the virtual store. A camera recognizes the user, and a voice recognition device selects the language.

[0505] 2. Acquisition of text data: When the user asks "I am looking for a smart TV," speech recognition technology analyzes this and converts it into text.

[0506] 3. User emotion recognition: The emotion recognition engine recognizes "excitement" based on the user's voice and facial expressions.

[0507] 4. Information provision: The server generates information such as "Here are the top 3 smart TVs available" and provides it to the user through the terminal.

[0508] 5. Entertainment Suggestion: When the user is relaxed, the device will suggest, "Would you like to hear a joke?"

[0509] 6. Provide a joke: If the user answers "yes," the following joke will be provided: "Why don't scientists trust atoms? Because they make up everything!"

[0510] Example of a prompt

[0511] "A user has asked for information about smart TVs. Please provide the following information and a fun joke."

[0512] The user's emotional state is one of relaxation.

[0513] User question: I am looking for a smart TV.

[0514] Information provided: Here are the top 3 smart TVs available.

[0515] A funny joke: Why don't scientists trust atoms? Because they make up everything!

[0516] As described above, this system can improve the user experience in virtual stores by analyzing the user's voice and emotions and providing personalized information and entertainment.

[0517] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0518] Step 1:

[0519] The device uses a camera to capture the user's face. The input is video data captured by the camera, and the output is the user's face data identified via face recognition technology (OpenCV). Specifically, the camera captures the user's face in real time, and the face recognition algorithm analyzes this data to extract the user's facial features.

[0520] Step 2:

[0521] The device uses a speech recognition device to capture the user's voice and select a language. The input is voice data from the user, and the output is language data selected using speech recognition technology (Google Speech-to-Text API). Specifically, if the device asks the user, "Hello, in what language would you like me to guide you?", and the user replies, "English please," the speech recognition technology analyzes this voice and selects "English" as the language to use.

[0522] Step 3:

[0523] The device captures the user's voice tone and facial expression data and identifies emotions using an emotion recognition engine (Microsoft Azure Face API). The input is the user's voice and video data, and the output is analyzed emotion data (e.g., "excitement," "anxiety," "joy"). Specifically, it analyzes the user's voice tone and facial expressions in real time to identify their emotional state.

[0524] Step 4:

[0525] The server uses natural language processing technology (Google NLP API) to analyze user requests. The input is the user's utterance converted into text data by a speech recognition device, and the output is the analyzed user intent data. For example, if a user says "I need information about my flight to New York," this is analyzed to identify the intent "I am seeking flight information."

[0526] Step 5:

[0527] The server searches for and provides information based on the user's request. The input is the identified user's intent data, and the output is related information data (e.g., "The flight to New York leaves from Gate 32 at 14:45"). Specifically, the server accesses a flight information database, retrieves the necessary information, and formats it into text.

[0528] Step 6:

[0529] The server uses a generative artificial intelligence model (OpenAI GPT-3) to generate entertainment based on the user's emotions. The input is analyzed emotion data and user requests, and the output is generated entertainment content (e.g., jokes, music). Specifically, based on information that "the user wants to relax," the server generates jokes to help the user relax.

[0530] Step 7:

[0531] The terminal provides the user with generated information and entertainment content. The input is information data and entertainment content transmitted from the server, and the output is provided to the user in audio and video format. Specifically, the terminal will verbally announce the information, "The flight to New York leaves from Gate 32 at 14:45," and then suggest an entertainment option, "Would you like to hear a joke?"

[0532] As described above, each step works in conjunction to provide information and entertainment to users.

[0533] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0534] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0535] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0536] [Second Embodiment]

[0537] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0538] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0539] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0540] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0541] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0542] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0543] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0544] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0545] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0546] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0547] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0548] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0549] This invention relates to a system that recognizes a user, selects a language, analyzes input speech, and provides information and entertainment. The following describes the program processing of this system, and provides a detailed explanation of its embodiments with specific examples.

[0550] Program processing

[0551] User recognition

[0552] The device recognizes the user using a camera and voice recognition system. Specifically, the device detects when the user approaches the robot and confirms the user's presence using facial recognition technology. In addition, the voice recognition system captures the user's speech and initially identifies the language the user is speaking.

[0553] Language selection

[0554] Based on the language the user speaks, the device automatically selects the appropriate language. For example, if the user says "Hello," the device selects English and sends that information to the server. This ensures that the entire system is compatible with the user's chosen language.

[0555] Analysis of input audio

[0556] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server uses natural language processing technology to analyze the text data and clearly identify the information the user is seeking.

[0557] Providing information

[0558] The server retrieves the necessary information based on the user's request and sends it to the terminal in the appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information (e.g., "The flight to New York departs from Gate 32 at 14:45").

[0559] Entertainment provider

[0560] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model, this content is customized according to the user's interests and waiting time.

[0561] Specific example

[0562] Example 1: Airport reception

[0563] 1. The user approaches the robot and says, "Hello."

[0564] 2. The device recognizes the user and selects English using the voice recognition device.

[0565] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[0566] 4. The user replies, "I need information about my flight to New York."

[0567] 5. The device converts the audio to text and sends the text data to the server.

[0568] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0569] 7. The device communicates this information to the user.

[0570] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[0571] 9. The user responds, "I'd like to hear a joke."

[0572] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[0573] 11. The device delivers jokes to the user to entertain them.

[0574] Example 2: Restaurant reception

[0575] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[0576] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[0577] 3. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[0578] 4. The user answers, "There are 4 people."

[0579] 5. The device converts the audio to text and sends the text data to the server.

[0580] 6. The server parses the request, checks the table reservation status, generates information such as "A table for 4 people is available from 19:00," and sends it to the terminal.

[0581] 7. The device communicates this information to the user.

[0582] 8. The device then suggests games that can be enjoyed during the waiting time, and if the user selects one, it provides an AR puzzle game.

[0583] In this way, users, devices, and servers work together to realize the overall functionality and improve the user experience. This system enables efficient and effective service by providing automated customer service and entertainment in a multilingual environment.

[0584] The following describes the processing flow.

[0585] Step 1: User Recognition

[0586] The device uses a sensing sensor to detect when a user approaches.

[0587] The device's camera uses facial recognition technology to capture the user's face.

[0588] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0589] Step 2: Language Selection

[0590] The user says, "Please speak in English."

[0591] The device's voice recognition system analyzes this speech and selects "English" from its language database.

[0592] The terminal sends the language information it selected to the server.

[0593] Step 3: Confirming User Intent

[0594] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0595] The terminal uses this script to ask the user questions.

[0596] The user replies, "I need information about my flight to New York."

[0597] Step 4: Analysis of the voice and moon

[0598] The device's speech recognition system converts the user's speech into text data.

[0599] The terminal sends text data to the server.

[0600] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[0601] Step 5: Information Acquisition and Provision

[0602] The server accesses the flight information database based on the user's request.

[0603] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[0604] The server translates this information into English text and sends it to the terminal.

[0605] The device communicates the information it has acquired to the user.

[0606] Step 6: Entertainment Proposal

[0607] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0608] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0609] The user replies, "I'd like to hear a joke."

[0610] Step 7: Providing entertainment

[0611] The terminal sends the user's request to the server.

[0612] The server generates jokes using a generative artificial intelligence model.

[0613] The server generates a joke and sends it to the device.

[0614] The device delivers a joke to the user.

[0615] Step 8: Feedback and Closing

[0616] The device asks the user, "Do you need any further assistance?"

[0617] The user replies, "No, thank you."

[0618] The device concludes with "Have a great day!" and ends user support.

[0619] (Example 1)

[0620] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0621] Conventional voice interface systems have struggled to respond to individual user requests and have often been limited to specific languages ​​and situations. Furthermore, they have not adequately improved the user experience in terms of multilingual support and entertainment provision. This has made it difficult to provide efficient and effective services, especially in places used by multinational users (e.g., airports and tourist destinations). To solve these problems, a system is needed that can integrate user language recognition, information provision, and entertainment provision.

[0622] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0623] In this invention, the server includes means for the terminal to recognize a user using a camera and a speech recognition device, means for automatically selecting the language spoken by the user, means for converting the user's speech into text data using the speech recognition device and transmitting it to the server, means for analyzing the text data using natural language processing technology to obtain information requested by the user, means for transmitting the information to the terminal and providing it to the user, and means for providing entertainment in addition to the information using a generative artificial intelligence model. This enables multilingual support and allows for the provision of information and entertainment based on the individual requests of the user.

[0624] A "terminal" refers to a device used for direct interaction with a user, and is equipped with hardware including a camera and a voice recognition device.

[0625] A "camera" is a device used to capture images and is used to recognize the user's face and movements.

[0626] A "speech recognition device" is a device that converts speech into text data and is used to analyze a user's speech.

[0627] A "server" refers to a device or system for processing and storing data, and it plays a role in analyzing data using natural language processing technology and providing necessary information.

[0628] "Natural language processing technology" refers to techniques for analyzing text data and understanding human language. For example, it is used to analyze the meaning of text data and identify the information that the user is looking for.

[0629] A "generative artificial intelligence model" refers to artificial intelligence that has the ability to generate new content based on user input, and is used, for example, to generate entertainment content such as jokes and quizzes.

[0630] A "user" refers to a person who uses a system, obtaining information or enjoying entertainment through interaction with the system.

[0631] "Entertainment" refers to content that provides users with enjoyment and satisfaction, and can take the form of jokes, quizzes, music, and so on.

[0632] "Information provision" refers to the act of a server acquiring necessary information in response to a user's questions or requests and then transmitting that information to the user via their terminal.

[0633] Modes for carrying out the invention

[0634] This invention relates to a system that recognizes the user, selects a language, analyzes the input voice, provides information, and further provides entertainment. Specific embodiments of this system are described in detail below.

[0635] User recognition

[0636] The device recognizes the user using a camera and a voice recognition device. Specifically, the device detects when a user approaches and uses a camera (e.g., a typical webcam) to confirm the user's presence using facial recognition technology. It also uses a voice recognition device (e.g., Google Speech-to-Text API) to capture the user's speech and identify the language the user is speaking.

[0637] Language selection

[0638] The device automatically selects a language based on the user's speech. For example, if the user says "Hello," the device selects English and sends this information to the server.

[0639] Analysis of input audio

[0640] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server analyzes the text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify the information the user is looking for.

[0641] Providing information

[0642] The server retrieves the necessary information from relevant databases based on the analysis results and sends it to the terminal in an appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information.

[0643] Entertainment provider

[0644] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model (e.g., GPT-3), this content is customized according to the user's interests and waiting time.

[0645] Specific example

[0646] Example 1: Airport reception

[0647] 1. The user approaches the robot and says, "Hello."

[0648] 2. The device recognizes the user and selects English using the voice recognition device.

[0649] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[0650] 4. The user replies, "I need information about my flight to New York."

[0651] 5. The device converts the audio to text and sends the text data to the server.

[0652] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0653] 7. The device communicates this information to the user.

[0654] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[0655] 9. The user responds, "I'd like to hear a joke."

[0656] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[0657] 11. The device delivers jokes to the user to entertain them.

[0658] Example of a prompt

[0659] "Use a generative AI model to generate jokes appropriate to specific situations."

[0660] "To provide the flight information requested by the user, please refer to the flight information database."

[0661] As described above, the present invention enables efficient and effective service provision in locations used by multinational users, through the coordinated and effective operation of users, terminals, and servers.

[0662] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0663] Step 1:

[0664] The device recognizes the user.

[0665] Input: Camera video and audio data.

[0666] Processing: The device's camera detects an approaching person and uses facial recognition software (e.g., OpenCV or FaceNet) to recognize the user's face. Additionally, a speech recognition device captures the user's speech and obtains initial audio data.

[0667] Output: User's facial image data and initial voice data.

[0668] Specific actions:

[0669] The device's camera activates and captures images of the surroundings.

[0670] The device uses facial recognition software to analyze facial features and confirm the user's presence.

[0671] The speech recognition device captures the user's speech in real time and generates initial audio data.

[0672] Step 2:

[0673] The device selects the user's language.

[0674] Input: Initial audio data.

[0675] Processing: The speech recognition device analyzes the initial audio data to identify the language the user is speaking. The identified language information is converted into JSON format.

[0676] Output: JSON data including language information.

[0677] Specific actions:

[0678] The terminal identifies the spoken language from the analysis results of the speech recognition device, and for example, selects English from the utterance "Hello".

[0679] Convert language information to JSON format and generate data packets.

[0680] Step 3:

[0681] The device converts the user's spoken content into text data and sends it to the server.

[0682] Input: Detailed speech data of the user.

[0683] Processing: The speech recognition device converts the speech into text data and sends that text data to the server via the network.

[0684] Output: User's speech in text format.

[0685] Specific actions:

[0686] The terminal uses a voice recognition device to convert the user's specific request (e.g., "I need information about my flight to New York") into text data.

[0687] The text data is packaged into a packet and sent to the server.

[0688] Step 4:

[0689] The server analyzes the text data and retrieves the necessary information.

[0690] Input: Text data of the user's spoken content.

[0691] Processing: Analyze text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify user requests. Send queries to relevant databases.

[0692] Output: Informational data based on user requests.

[0693] Specific actions:

[0694] The server analyzes the received text data using a natural language processing engine.

[0695] The server, in response to the request, sends a query to a flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45".

[0696] Step 5:

[0697] The server formats the acquired information and sends it to the terminal.

[0698] Input: Acquired information data.

[0699] Processing: Format the information into an appropriate format (text or audio data) to convey it to the user, and send it to the terminal.

[0700] Output: Formatted informational data.

[0701] Specific actions:

[0702] The server formats the information into text format.

[0703] The formatted information is packaged into a packet and sent to the terminal.

[0704] Step 6:

[0705] The device provides information to the user.

[0706] Input: Formatted informational data.

[0707] Processing: Formatted information is converted into speech data using speech synthesis software and conveyed to the user.

[0708] Output: Information conveyed to the user.

[0709] Specific actions:

[0710] The device converts text data into speech using a speech synthesis device.

[0711] The system informs the user that "The flight to New York leaves from Gate 32 at 14:45."

[0712] Step 7:

[0713] The device suggests entertainment options to the user.

[0714] Input: User recognition information and request details obtained in the previous processing step.

[0715] Processing: Run an application that generates and suggests entertainment options (jokes, quizzes, music, etc.) to the user.

[0716] Output: Entertainment options presented to the user.

[0717] Specific actions:

[0718] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0719] The system presents customized options based on the user's interests and waiting time.

[0720] Step 8:

[0721] The server generates entertainment content and sends it to the device.

[0722] Input: The user's selected entertainment option.

[0723] Processing: Use a generative artificial intelligence model (e.g., GPT-3) to generate content based on user selections. Send the generated content to the device.

[0724] Output: Customized entertainment content.

[0725] Specific actions:

[0726] The device sends the user's selection (e.g., "I'd like to hear a joke") to the server.

[0727] The server prompts the AI ​​model with "Generate a joke for a traveler waiting for their flight" and sends the generated joke to the device.

[0728] Step 9:

[0729] The device provides users with generated entertainment content.

[0730] Input: Generated entertainment content.

[0731] Processing: Provide entertainment content to users in audio or other formats.

[0732] Output: Entertainment content provided to the user.

[0733] Specific actions:

[0734] The device converts the generated joke into speech using a speech synthesizer and delivers the joke, "Why don't scientists trust atoms? Because they make up everything!" to the user.

[0735] (Application Example 1)

[0736] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0737] In traditional brick-and-mortar stores, the challenges included providing customers with the information they needed quickly and efficiently, and improving customer waiting times and the overall experience. Furthermore, multilingual support was difficult, limiting service provision to foreign customers. Additionally, there was a lack of means to enhance customer satisfaction by providing appropriate entertainment.

[0738] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0739] In this invention, the server includes means for recognizing the user, means for selecting the user's language, means for analyzing the user's input voice, and means for interacting with customers in the store using smart glasses. This makes it possible to quickly provide the information that customers request and to provide information to foreign customers by supporting foreign languages. Furthermore, customer satisfaction can be improved by offering customers entertainment such as coupons and games.

[0740] A "user" is a person who uses a system to receive information and entertainment.

[0741] "Recognition" refers to identifying the presence and characteristics of a user using devices such as cameras and voice recognition systems.

[0742] "Language" refers to a means of communication used by users, and specifically to a particular natural language.

[0743] "Selection" refers to the automatic determination of the appropriate language based on the words spoken by the user.

[0744] "Input voice" refers to the voice data that a user emits to the system.

[0745] "Analysis" is the process of converting input audio into text data and understanding its content.

[0746] "Information provision" means conveying necessary data and knowledge based on user requests.

[0747] "Entertainment" refers to content such as jokes, games, and quizzes designed to entertain users.

[0748] "Smart glasses" are wearable devices that have the function of displaying visual information.

[0749] "Dialogue" is the process by which a system and a user exchange information through voice.

[0750] A "coupon" is an electronic or paper certificate that offers a discount on goods or services.

[0751] "Game" refers to a competition or activity conducted for entertainment purposes.

[0752] This invention is a system that recognizes the user, selects the appropriate language, analyzes the input voice, and provides information and entertainment. This system supports in-store interactions for the user using smart glasses.

[0753] System program

[0754] The system uses the following main hardware and software:

[0755] Hardware: Camera, voice recognition device, smart glasses

[0756] Software: Facial recognition technology, speech recognition (such as Google Speech Recognition API), natural language processing (NLP), generative artificial intelligence models

[0757] Program processing

[0758] 1. User Recognition: When a user enters a physical store, a camera recognizes the user's face and a voice recognition device captures the user's speech. Specifically, the camera uses facial recognition technology with HaarcascadeClassifier to confirm the user's presence.

[0759] 2. Language Selection: The system automatically selects a language based on the user's speech. Speech recognition software (such as the Google Speech Recognition API) is used to identify the language the user is speaking. This process ensures the entire system operates in the selected language.

[0760] 3. Analysis of Input Voice: The system analyzes the voice input provided by the user through the smart glasses. The input voice is converted into text data and sent to the server. The server uses natural language processing (NLP) technology to analyze the input text and identify the information the user is seeking.

[0761] 4. Information Provision: The server retrieves information according to the user's request and displays it to the user through smart glasses. For example, if the user says, "I want to know the size of this product," the server refers to the product database and sends the corresponding size information to the smart glasses.

[0762] 5. Entertainment Provision: After providing information, the server generates and suggests entertainment options (e.g., jokes, quizzes, games) to the user. Generative artificial intelligence models are used to customize content according to the user's interests and waiting time.

[0763] Specific example

[0764] Example 1: Providing services at a physical store

[0765] 1. The user enters a physical store and puts on the smart glasses.

[0766] 2. The camera recognizes the user, and the user speaks to the smart glasses saying, "Tell me about this product."

[0767] 3. The voice recognition device analyzes the user's speech and retrieves the relevant information from the product database.

[0768] 4. Information is displayed on the smart glasses and provided to the user.

[0769] 5. After providing information, the smart glasses will suggest to the user, "You have a coupon that can be used for your next purchase. Would you like to use it?"

[0770] Example of a prompt

[0771] "I'd like to know the size."

[0772] Prompt message:

[0773] Design a program that analyzes a user's voice when they use "smart glasses" to ask for product information, such as size, and then automatically provides that information. Additionally, the program should include a joke after providing the information.

[0774] Thus, the invention constructs a system in which the user, terminal, and server work together to greatly improve the user experience.

[0775] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0776] Step 1:

[0777] The user enters a physical store and puts on smart glasses. The smart glasses activate, and the camera and voice recognition device begin operating. The input here is the activation of the smart glasses, and the output is the activation of the camera and voice recognition device.

[0778] Step 2:

[0779] The camera recognizes the user's face. When the user passes in front of the camera, the HaarcascadeClassifier is used to detect the face. If face recognition is successful, the information is saved as face feature data. The input here is the camera image, and the output is the recognized face feature data.

[0780] Step 3:

[0781] The speech recognition device captures the user's speech. When the user says, "What are the dimensions of this product?", the speech recognition device takes the audio and uses the Google Speech Recognition API to convert the audio data into text. In this case, the input is the user's voice, and the output is the converted text data.

[0782] Step 4:

[0783] Text data is sent to the server. The server receives this text data and performs analysis using natural language processing (NLP) techniques. Through this analysis, the server identifies the user's request (a request for product size information). The input here is text data, and the output is the analyzed request content.

[0784] Step 5:

[0785] The server refers to the product database and retrieves the relevant product information. Specifically, it executes a database search query and extracts the size information for the relevant product (e.g., a shirt). The input here is the parsed request content, and the output is the retrieved product size information.

[0786] Step 6:

[0787] The server sends the acquired information to the smart glasses. The smart glasses display this information to the user, informing them, "This product is size M." The input here is the acquired product size information, and the output is the information displayed on the smart glasses.

[0788] Step 7:

[0789] Following the information provision, the server generates entertainment options using a generative artificial intelligence model. Specifically, it generates content such as jokes and quizzes based on the user's interests and waiting time, and sends it to the smart glasses. Here, the input is the user's interests and waiting time, and the output is the generated entertainment content.

[0790] Step 8:

[0791] Smart glasses offer entertainment options to the user. They deliver suggestions via speech, such as, "We have a coupon you can use on your next purchase. Would you like to use it?" The input here is the generated entertainment content, and the output is the suggestions communicated to the user.

[0792] In this way, the system provides users with efficient, multilingual information and entertainment through a series of processing steps.

[0793] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0794] This invention relates to a system that combines user recognition and language selection, input speech analysis, information provision, entertainment provision, and an emotion engine that recognizes the user's emotions. The program and processing of this system are described in detail below.

[0795] Program processing

[0796] User recognition

[0797] The device uses a sensor to detect when a user approaches. The device's camera uses facial recognition technology to capture the user's face, and the voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0798] Language selection

[0799] When a user says "Please speak in English," the device's speech recognition system analyzes the speech and selects "English" from its language database. The device then sends the selected language information to the server.

[0800] emotion recognition

[0801] The device's emotion engine analyzes the user's voice and facial expression data to identify emotions. For example, it recognizes emotions such as "excitement," "anxiety," and "joy" from the user's voice tone and facial expressions.

[0802] Confirming User Intent

[0803] The server generates an English question script, "How can I assist you today?", and sends it to the terminal. The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[0804] Analysis of audio data

[0805] The terminal's speech recognition device converts the user's speech into text data and sends the text data to the server. The server receives the transmitted text data and analyzes the user's intent using natural language processing technology.

[0806] Information acquisition and provision

[0807] The server, based on the user's request, consults the flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45." The server then translates this information into English and sends it to the terminal. The terminal then communicates the retrieved information to the user.

[0808] Entertainment suggestions and emotion-based customization

[0809] The server generates a script for an entertainment option (joke, quiz, music, etc.) and sends it to the device. The device then prompts the user with "Would you like to hear a joke or play a quick game while you wait?". If the user responds with "I'd like to hear a joke," the emotion engine generates an appropriate joke based on the user's current mood.

[0810] For example, if a user is feeling stressed, a lighthearted joke can be offered to help them relax. This emotionally-driven customization makes the user experience more personalized and increases satisfaction.

[0811] Specific example

[0812] Example 1: Application of emotion recognition at airport reception.

[0813] 1. The user approaches the robot and says, "Hello."

[0814] 2. The device recognizes the user and selects English using the voice recognition device.

[0815] 3. The device's emotion engine analyzes the user's voice and facial expressions to recognize "anxiety."

[0816] 4. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[0817] 5. The user replies, "I need information about my flight to New York."

[0818] 6. The device converts the audio to text and sends the text data to the server.

[0819] 7. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0820] 8. After the device conveys this information to the user, it provides a joke to help the user relax based on their emotions.

[0821] Example 2: Application of emotion recognition at restaurant reception desks

[0822] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[0823] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[0824] 3. The device's emotion engine recognizes "joy" from the user's voice tone.

[0825] 4. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[0826] 5. The user answers, "There are 4 people."

[0827] 6. The device converts the audio to text and sends the text data to the server.

[0828] 7. The server analyzes the request and generates information stating, "A table for 4 people is available from 19:00," which it then sends to the terminal.

[0829] 8. After the device conveys this information to the user, it suggests and provides entertainment (e.g., games) to enjoy according to the user's emotions.

[0830] In this way, the user, device, server, and emotion engine work together to realize the overall operation and improve the user experience. This system not only provides automated customer service and entertainment in a multilingual environment, but also delivers a more sophisticated service by responding to the user's emotions.

[0831] The following describes the processing flow.

[0832] Step 1: User Recognition

[0833] The device uses a proximity sensor to detect when a user approaches.

[0834] The device's camera captures the user's face, and facial recognition technology is used to confirm the user's presence.

[0835] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0836] Step 2: Language Selection

[0837] The user replies, "Please speak in English."

[0838] The device's voice recognition system analyzes the user's voice and selects "English" from its language database.

[0839] The terminal sends the language information it selected to the server.

[0840] Step 3: Emotion Recognition

[0841] The device's emotion engine analyzes the user's voice tone and facial expressions.

[0842] The device identifies the user's emotion as "anxiety."

[0843] Step 4: Confirming User Intent

[0844] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0845] The terminal uses this script to ask the user questions.

[0846] The user replies, "I need information about my flight to New York."

[0847] Step 5: Audio Data Analysis

[0848] The device's speech recognition system converts the user's speech into text data.

[0849] The terminal sends text data to the server.

[0850] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[0851] Step 6: Information Acquisition and Provision

[0852] The server accesses the flight information database based on the user's request.

[0853] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[0854] The server translates this information into English text and sends it to the terminal.

[0855] The device communicates the acquired information to the user. "Your flight to New York departs at 14:45 from Gate 32."

[0856] Step 7: Entertainment suggestions and emotionally-based customization

[0857] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0858] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0859] The user replies, "I'd like to hear a joke."

[0860] The terminal sends the user's request to the server.

[0861] The server uses a generative artificial intelligence model to generate lighthearted jokes to help the user relax based on their emotions (e.g., anxiety).

[0862] The server generates a joke and sends it to the device.

[0863] The device delivers a joke to the user.

[0864] Step 8: Feedback and Closing

[0865] The device asks the user, "Do you need any further assistance?"

[0866] The user replies, "No, thank you."

[0867] The device concludes with "Have a great day!" and ends user support.

[0868] (Example 2)

[0869] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0870] Traditional systems suffer from a lack of consideration for user emotions in language selection, information provision, and entertainment delivery, resulting in insufficient improvement in the quality of the user experience. Providing personalized services is particularly difficult for users in multilingual environments or those experiencing diverse emotional states. This can lead to decreased user satisfaction and reduced system usage.

[0871] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0872] In this invention, the server includes means for selecting the user's language, means for recognizing the user's emotions, and means for providing information. This enables the provision of personalized entertainment tailored to the user's emotional state.

[0873] "Means of recognizing users" refers to technologies that detect when a user approaches the system and identify the user using biometric information such as facial features and voice.

[0874] "Means for selecting the user's language" refers to technology that analyzes the appropriate language from the user's speech or input and sets the system's operation method and information provision method based on that language.

[0875] "Means for analyzing input speech" refers to technologies that acquire voice data spoken by a user and perform speech-to-text conversion or natural language processing to understand its content and intent.

[0876] "Means of providing information" refers to technologies that acquire appropriate information based on user input or requests and present that information to the user in an easily understandable way.

[0877] "Means of recognizing user emotions" refers to technologies that analyze the user's tone of voice, facial expressions, etc., to identify the user's current emotional state (excitement, anxiety, joy, etc.).

[0878] "Means of providing entertainment" refers to technologies that generate and provide entertainment content such as jokes, quizzes, and music in order to provide users with relaxation and enjoyment.

[0879] "Methods for customizing entertainment based on emotions" refers to technologies that select and provide optimal entertainment content by considering the user's emotional state.

[0880] This invention relates to a system that combines user recognition, language selection, input speech analysis, information provision, and entertainment provision with an emotion engine that recognizes the user's emotions. The following describes a specific form for implementing this system.

[0881] Hardware and software to be used

[0882] This system uses the following hardware and software:

[0883] Sensing sensor: Used to detect when a user approaches the device.

[0884] Camera: Captures the user's face using facial recognition technology (e.g., OpenCV or FaceNet).

[0885] Speech recognition device: A device for converting speech into text data (e.g., Google Speech-to-Text).

[0886] Emotion engine: Analyzes the user's voice tone and facial expressions to recognize emotions (e.g., Microsoft Azure Emotion API).

[0887] Server: Analyzes user intent using natural language processing technology (e.g., GPT-4) and provides necessary information.

[0888] Flight information database: A database (e.g., SQLite, MySQL) that stores information to respond to user requests.

[0889] Program details

[0890] User recognition

[0891] When a user approaches the device, the device's sensing sensors detect the user's proximity.

[0892] The device uses its camera and facial recognition technology to capture the user's face.

[0893] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0894] Language selection

[0895] The user replies, "Please speak in English."

[0896] The device analyzes this voice using its voice recognition system and selects "English" from its multilingual database.

[0897] The device sends the selected language information to the server.

[0898] emotion recognition

[0899] The device's emotion engine analyzes the user's voice and facial expressions to identify their emotions.

[0900] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[0901] Confirming user intent and providing information

[0902] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0903] The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[0904] The terminal's speech recognition device converts the user's speech into text data and sends it to the server.

[0905] The server uses natural language processing techniques to analyze the user's intent from the text data it receives.

[0906] Based on the user's request, the server consults the flight information database and retrieves the information "The flight to New York leaves from Gate 32 at 14:45".

[0907] The server generates information and sends it to the terminal, which then relays the information to the user.

[0908] Entertainment proposals and customization

[0909] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0910] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0911] The user replies, "I'd like to hear a joke."

[0912] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, it provides lighthearted jokes to help a stressed user relax.

[0913] Specific example

[0914] Airport reception

[0915] 1. The user approaches the robot and says, "Hello."

[0916] 2. The device detects approach using its sensors and recognizes faces using its cameras.

[0917] 3. The terminal asks, "In what language would you like us to guide you?"

[0918] 4. The user replies, "Please speak in English."

[0919] 5. The device analyzes the audio and notifies the server that it is in English.

[0920] 6. The device's emotion engine analyzes voice and facial expressions to recognize "anxiety."

[0921] 7. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[0922] 8. The user replies, "I need information about my flight to New York."

[0923] 9. The device converts the audio to text and sends it to the server.

[0924] 10. The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0925] 11. The device conveys information to the user.

[0926] 12. The device offers a lighthearted joke to alleviate user anxiety.

[0927] Examples of prompts for generative AI models

[0928] 1. To the emotion engine: "Identify the user's current emotion based on their voice tone and facial expression data."

[0929] 2. To a natural language processing system: "Please analyze this text data and understand the user's intent."

[0930] 3. In response to an entertainment suggestion: "Generate jokes to help users relax when they are feeling stressed."

[0931] In this way, a system can be realized in which the user, terminal, server, and emotion engine work together to improve the quality of service provided to the user.

[0932] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0933] Step 1: User Recognition

[0934] The user approaches the device.

[0935] Input: User approach.

[0936] The device's sensor detects the user's approach.

[0937] The device uses its camera to capture the user's face using facial recognition technology (e.g., OpenCV, FaceNet).

[0938] Input: User's face image.

[0939] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[0940] Output: Face recognition results, language selection prompt.

[0941] Step 2: Language Selection

[0942] The user replies, "Please speak in English."

[0943] Input: User's voice.

[0944] The device analyzes this audio using its speech recognition system (e.g., Google Speech-to-Text) and selects "English" from its multilingual database.

[0945] The device sends the selected language information to the server.

[0946] Output: Language selection result (English), language information sent to the server.

[0947] Step 3: Emotion Recognition

[0948] The device's emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's voice and facial expressions.

[0949] Input: User's voice tone and facial expression data.

[0950] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[0951] Output: Emotion recognition result.

[0952] Step 4: Confirming User Intent

[0953] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[0954] Input: Server entertainment planning.

[0955] The device asks the user a question.

[0956] The user replies, "I need information about my flight to New York."

[0957] Output: User request.

[0958] Step 5: Audio Data Analysis

[0959] The device's speech recognition system converts the user's speech into text data.

[0960] Input: User's spoken audio.

[0961] The terminal sends the generated text data to the server.

[0962] Output: Text data.

[0963] Step 6: Information Acquisition and Provision

[0964] The server analyzes the received text data using natural language processing techniques (e.g., GPT-4) to confirm the user's intent.

[0965] Input: Text data, natural language processing model.

[0966] The server accesses a flight information database (e.g., SQLite, MySQL) based on the user's request.

[0967] Output: Required information (flight information).

[0968] The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[0969] Output: A message containing information.

[0970] Step 7: Information Dissemination

[0971] The device communicates the information it has acquired to the user.

[0972] Input: Flight information.

[0973] Output: Voice message.

[0974] Step 8: Entertainment Suggestions and Customization

[0975] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[0976] Input: Server entertainment planning and sentiment information.

[0977] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[0978] The user replies, "I'd like to hear a joke."

[0979] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, if the user is feeling stressed, it will provide lighthearted jokes to help them relax.

[0980] Output: Emotionally customized entertainment.

[0981] In this way, input, data processing, data calculation, and output are performed at each processing step, enabling personalized service for each user.

[0982] (Application Example 2)

[0983] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0984] Traditional automated dialogue systems struggle to take user emotions into account, resulting in a limited user experience. Furthermore, insufficient multilingual support makes it difficult to serve users who speak different languages. This makes it challenging to enhance user satisfaction, particularly in virtual stores where natural dialogue and high-quality information delivery are essential.

[0985] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0986] In this invention, the server includes means for recognizing a user, means for selecting the user's language, means for recognizing the user's emotions, means for providing information based on the input voice and emotions, and means for generating the entertainment using a generative artificial intelligence model. This enables the provision of personalized information and entertainment based on the user's emotions.

[0987] "Means of recognizing a user" refers to technologies that use cameras and voice recognition devices to detect and identify a user's face and voice.

[0988] "Means of selecting a language" refers to a technology that analyzes and selects the language used by the user via a speech recognition device.

[0989] "Methods for analyzing input speech" refer to technologies that convert voice input from a user into text data and understand its content.

[0990] "Means of recognizing emotions" refers to technologies that analyze a user's voice tone and facial expressions to identify the user's emotional state.

[0991] "Means of providing information" refers to technologies that search for relevant data based on user requests and provide that information to the user.

[0992] "Means of providing entertainment" refers to the technology that generates and delivers content that users can enjoy.

[0993] A "generative artificial intelligence model" is a technology that uses artificial intelligence algorithms to generate content tailored to the user.

[0994] A "prompt message" is an instruction message that is input into a generative artificial intelligence model to generate an appropriate response or content.

[0995] This invention relates to a system that combines means for recognizing emotions in user recognition, language selection, voice input analysis, information provision, and entertainment provision. The aim of this system is to improve the user experience in virtual stores.

[0996] 1. System Configuration

[0997] hardware

[0998] Camera: A device used to capture the user's face and perform facial recognition.

[0999] Speech recognition device: A device that captures the user's voice and performs language selection and speech analysis.

[1000] Server: A central device that processes and manages various types of data.

[1001] software

[1002] Face recognition technology: Uses ZaCV or similar face recognition technology.

[1003] Speech recognition technology: We use Google Speech-to-Text API and Amazon Transcribe.

[1004] Emotion recognition engine: Recognizes user emotions using Microsoft Azure Face API and other tools.

[1005] Natural language processing techniques: We use Google NLP API and spaCy.

[1006] Generative AI models: Generative AI models such as OpenAI GPT-3 are used.

[1007] 2. Data Calculation and Processing

[1008] User recognition and language selection

[1009] The device first uses a camera to capture the user's face and recognizes the user using facial recognition technology. Next, a voice recognition device captures the user's voice to determine which language to use. When the user responds to the question, "Hello, in what language would you like me to guide you?" with "English, please," the voice recognition technology analyzes the voice and selects the appropriate language.

[1010] emotion recognition

[1011] The device analyzes the user's voice tone and facial expressions to identify their emotions. For example, it can recognize emotions such as "joy" or "anxiety" from the user's voice tone and facial expressions. This process uses the Microsoft Azure Face API.

[1012] Providing information

[1013] The server receives a user request (e.g., "I am looking for a smart TV") and analyzes its content using natural language processing technology. It then retrieves the information the user is looking for from relevant databases, generates a specific response (e.g., "Here are the top 3 smart TVs available"), and sends it to the device.

[1014] Entertainment provider

[1015] The server uses a generative artificial intelligence model to generate entertainment options (e.g., jokes) based on the user's emotions. The terminal suggests these options, and if the user shows interest, it provides the generated entertainment content. For example, a user in a "relaxed" emotional state would be offered relaxing jokes.

[1016] Specific example

[1017] 1. The user accesses the virtual store. A camera recognizes the user, and a voice recognition device selects the language.

[1018] 2. Acquisition of text data: When the user asks "I am looking for a smart TV," speech recognition technology analyzes this and converts it into text.

[1019] 3. User emotion recognition: The emotion recognition engine recognizes "excitement" based on the user's voice and facial expressions.

[1020] 4. Information provision: The server generates information such as "Here are the top 3 smart TVs available" and provides it to the user through the terminal.

[1021] 5. Entertainment Suggestion: When the user is relaxed, the device will suggest, "Would you like to hear a joke?"

[1022] 6. Provide a joke: If the user answers "yes," the following joke will be provided: "Why don't scientists trust atoms? Because they make up everything!"

[1023] Example of a prompt

[1024] "A user has asked for information about smart TVs. Please provide the following information and a fun joke."

[1025] The user's emotional state is one of relaxation.

[1026] User question: I am looking for a smart TV.

[1027] Information provided: Here are the top 3 smart TVs available.

[1028] A funny joke: Why don't scientists trust atoms? Because they make up everything!

[1029] As described above, this system can improve the user experience in virtual stores by analyzing the user's voice and emotions and providing personalized information and entertainment.

[1030] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1031] Step 1:

[1032] The device uses a camera to capture the user's face. The input is video data captured by the camera, and the output is the user's face data identified via face recognition technology (OpenCV). Specifically, the camera captures the user's face in real time, and the face recognition algorithm analyzes this data to extract the user's facial features.

[1033] Step 2:

[1034] The device uses a speech recognition device to capture the user's voice and select a language. The input is voice data from the user, and the output is language data selected using speech recognition technology (Google Speech-to-Text API). Specifically, if the device asks the user, "Hello, in what language would you like me to guide you?", and the user replies, "English please," the speech recognition technology analyzes this voice and selects "English" as the language to use.

[1035] Step 3:

[1036] The device captures the user's voice tone and facial expression data and identifies emotions using an emotion recognition engine (Microsoft Azure Face API). The input is the user's voice and video data, and the output is analyzed emotion data (e.g., "excitement," "anxiety," "joy"). Specifically, it analyzes the user's voice tone and facial expressions in real time to identify their emotional state.

[1037] Step 4:

[1038] The server uses natural language processing technology (Google NLP API) to analyze user requests. The input is the user's utterance converted into text data by a speech recognition device, and the output is the analyzed user intent data. For example, if a user says "I need information about my flight to New York," this is analyzed to identify the intent "I am seeking flight information."

[1039] Step 5:

[1040] The server searches for and provides information based on the user's request. The input is the identified user's intent data, and the output is related information data (e.g., "The flight to New York leaves from Gate 32 at 14:45"). Specifically, the server accesses a flight information database, retrieves the necessary information, and formats it into text.

[1041] Step 6:

[1042] The server uses a generative artificial intelligence model (OpenAI GPT-3) to generate entertainment based on the user's emotions. The input is analyzed emotion data and user requests, and the output is generated entertainment content (e.g., jokes, music). Specifically, based on information that "the user wants to relax," the server generates jokes to help the user relax.

[1043] Step 7:

[1044] The terminal provides the user with generated information and entertainment content. The input is information data and entertainment content transmitted from the server, and the output is provided to the user in audio and video format. Specifically, the terminal will verbally announce the information, "The flight to New York leaves from Gate 32 at 14:45," and then suggest an entertainment option, "Would you like to hear a joke?"

[1045] As described above, each step works in conjunction to provide information and entertainment to users.

[1046] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1047] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1048] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[1049] [Third Embodiment]

[1050] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1051] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1052] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1053] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[1054] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1055] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1056] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1057] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1058] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1059] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1060] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1061] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[1062] This invention relates to a system that recognizes a user, selects a language, analyzes input speech, and provides information and entertainment. The following describes the program processing of this system, and provides a detailed explanation of its embodiments with specific examples.

[1063] Program processing

[1064] User recognition

[1065] The device recognizes the user using a camera and voice recognition system. Specifically, the device detects when the user approaches the robot and confirms the user's presence using facial recognition technology. In addition, the voice recognition system captures the user's speech and initially identifies the language the user is speaking.

[1066] Language selection

[1067] Based on the language the user speaks, the device automatically selects the appropriate language. For example, if the user says "Hello," the device selects English and sends that information to the server. This ensures that the entire system is compatible with the user's chosen language.

[1068] Analysis of input audio

[1069] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server uses natural language processing technology to analyze the text data and clearly identify the information the user is seeking.

[1070] Providing information

[1071] The server retrieves the necessary information based on the user's request and sends it to the terminal in the appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information (e.g., "The flight to New York departs from Gate 32 at 14:45").

[1072] Entertainment provider

[1073] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model, this content is customized according to the user's interests and waiting time.

[1074] Specific example

[1075] Example 1: Airport reception

[1076] 1. The user approaches the robot and says, "Hello."

[1077] 2. The device recognizes the user and selects English using the voice recognition device.

[1078] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[1079] 4. The user replies, "I need information about my flight to New York."

[1080] 5. The device converts the audio to text and sends the text data to the server.

[1081] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1082] 7. The device communicates this information to the user.

[1083] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[1084] 9. The user responds, "I'd like to hear a joke."

[1085] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[1086] 11. The device delivers jokes to the user to entertain them.

[1087] Example 2: Restaurant reception

[1088] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[1089] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[1090] 3. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[1091] 4. The user answers, "There are 4 people."

[1092] 5. The device converts the audio to text and sends the text data to the server.

[1093] 6. The server parses the request, checks the table reservation status, generates information such as "A table for 4 people is available from 19:00," and sends it to the terminal.

[1094] 7. The device communicates this information to the user.

[1095] 8. The device then suggests games that can be enjoyed during the waiting time, and if the user selects one, it provides an AR puzzle game.

[1096] In this way, users, devices, and servers work together to realize the overall functionality and improve the user experience. This system enables efficient and effective service by providing automated customer service and entertainment in a multilingual environment.

[1097] The following describes the processing flow.

[1098] Step 1: User Recognition

[1099] The device uses a sensing sensor to detect when a user approaches.

[1100] The device's camera uses facial recognition technology to capture the user's face.

[1101] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1102] Step 2: Language Selection

[1103] The user says, "Please speak in English."

[1104] The device's voice recognition system analyzes this speech and selects "English" from its language database.

[1105] The terminal sends the language information it selected to the server.

[1106] Step 3: Confirming User Intent

[1107] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1108] The terminal uses this script to ask the user questions.

[1109] The user replies, "I need information about my flight to New York."

[1110] Step 4: Analysis of the voice and moon

[1111] The device's speech recognition system converts the user's speech into text data.

[1112] The terminal sends text data to the server.

[1113] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[1114] Step 5: Information Acquisition and Provision

[1115] The server accesses the flight information database based on the user's request.

[1116] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[1117] The server translates this information into English text and sends it to the terminal.

[1118] The device communicates the information it has acquired to the user.

[1119] Step 6: Entertainment Proposal

[1120] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1121] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1122] The user replies, "I'd like to hear a joke."

[1123] Step 7: Providing entertainment

[1124] The terminal sends the user's request to the server.

[1125] The server generates jokes using a generative artificial intelligence model.

[1126] The server generates a joke and sends it to the device.

[1127] The device delivers a joke to the user.

[1128] Step 8: Feedback and Closing

[1129] The device asks the user, "Do you need any further assistance?"

[1130] The user replies, "No, thank you."

[1131] The device concludes with "Have a great day!" and ends user support.

[1132] (Example 1)

[1133] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1134] Conventional voice interface systems have struggled to respond to individual user requests and have often been limited to specific languages ​​and situations. Furthermore, they have not adequately improved the user experience in terms of multilingual support and entertainment provision. This has made it difficult to provide efficient and effective services, especially in places used by multinational users (e.g., airports and tourist destinations). To solve these problems, a system is needed that can integrate user language recognition, information provision, and entertainment provision.

[1135] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1136] In this invention, the server includes means for the terminal to recognize a user using a camera and a speech recognition device, means for automatically selecting the language spoken by the user, means for converting the user's speech into text data using the speech recognition device and transmitting it to the server, means for analyzing the text data using natural language processing technology to obtain information requested by the user, means for transmitting the information to the terminal and providing it to the user, and means for providing entertainment in addition to the information using a generative artificial intelligence model. This enables multilingual support and allows for the provision of information and entertainment based on the individual requests of the user.

[1137] A "terminal" refers to a device used for direct interaction with a user, and is equipped with hardware including a camera and a voice recognition device.

[1138] A "camera" is a device used to capture images and is used to recognize the user's face and movements.

[1139] A "speech recognition device" is a device that converts speech into text data and is used to analyze a user's speech.

[1140] A "server" refers to a device or system for processing and storing data, and it plays a role in analyzing data using natural language processing technology and providing necessary information.

[1141] "Natural language processing technology" refers to techniques for analyzing text data and understanding human language. For example, it is used to analyze the meaning of text data and identify the information that the user is looking for.

[1142] A "generative artificial intelligence model" refers to artificial intelligence that has the ability to generate new content based on user input, and is used, for example, to generate entertainment content such as jokes and quizzes.

[1143] A "user" refers to a person who uses a system, obtaining information or enjoying entertainment through interaction with the system.

[1144] "Entertainment" refers to content that provides users with enjoyment and satisfaction, and can take the form of jokes, quizzes, music, and so on.

[1145] "Information provision" refers to the act of a server acquiring necessary information in response to a user's questions or requests and then transmitting that information to the user via their terminal.

[1146] Modes for carrying out the invention

[1147] This invention relates to a system that recognizes the user, selects a language, analyzes the input voice, provides information, and further provides entertainment. Specific embodiments of this system are described in detail below.

[1148] User recognition

[1149] The device recognizes the user using a camera and a voice recognition device. Specifically, the device detects when a user approaches and uses a camera (e.g., a typical webcam) to confirm the user's presence using facial recognition technology. It also uses a voice recognition device (e.g., Google Speech-to-Text API) to capture the user's speech and identify the language the user is speaking.

[1150] Language selection

[1151] The device automatically selects a language based on the user's speech. For example, if the user says "Hello," the device selects English and sends this information to the server.

[1152] Analysis of input audio

[1153] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server analyzes the text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify the information the user is looking for.

[1154] Providing information

[1155] The server retrieves the necessary information from relevant databases based on the analysis results and sends it to the terminal in an appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information.

[1156] Entertainment provider

[1157] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model (e.g., GPT-3), this content is customized according to the user's interests and waiting time.

[1158] Specific example

[1159] Example 1: Airport reception

[1160] 1. The user approaches the robot and says, "Hello."

[1161] 2. The device recognizes the user and selects English using the voice recognition device.

[1162] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[1163] 4. The user replies, "I need information about my flight to New York."

[1164] 5. The device converts the audio to text and sends the text data to the server.

[1165] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1166] 7. The device communicates this information to the user.

[1167] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[1168] 9. The user responds, "I'd like to hear a joke."

[1169] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[1170] 11. The device delivers jokes to the user to entertain them.

[1171] Example of a prompt

[1172] "Use a generative AI model to generate jokes appropriate to specific situations."

[1173] "To provide the flight information requested by the user, please refer to the flight information database."

[1174] As described above, the present invention enables efficient and effective service provision in locations used by multinational users, through the coordinated and effective operation of users, terminals, and servers.

[1175] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1176] Step 1:

[1177] The device recognizes the user.

[1178] Input: Camera video and audio data.

[1179] Processing: The device's camera detects an approaching person and uses facial recognition software (e.g., OpenCV or FaceNet) to recognize the user's face. Additionally, a speech recognition device captures the user's speech and obtains initial audio data.

[1180] Output: User's facial image data and initial voice data.

[1181] Specific actions:

[1182] The device's camera activates and captures images of the surroundings.

[1183] The device uses facial recognition software to analyze facial features and confirm the user's presence.

[1184] The speech recognition device captures the user's speech in real time and generates initial audio data.

[1185] Step 2:

[1186] The device selects the user's language.

[1187] Input: Initial audio data.

[1188] Processing: The speech recognition device analyzes the initial audio data to identify the language the user is speaking. The identified language information is converted into JSON format.

[1189] Output: JSON data including language information.

[1190] Specific actions:

[1191] The terminal identifies the spoken language from the analysis results of the speech recognition device, and for example, selects English from the utterance "Hello".

[1192] Convert language information to JSON format and generate data packets.

[1193] Step 3:

[1194] The device converts the user's spoken content into text data and sends it to the server.

[1195] Input: Detailed speech data of the user.

[1196] Processing: The speech recognition device converts the speech into text data and sends that text data to the server via the network.

[1197] Output: User's speech in text format.

[1198] Specific actions:

[1199] The terminal uses a voice recognition device to convert the user's specific request (e.g., "I need information about my flight to New York") into text data.

[1200] The text data is packaged into a packet and sent to the server.

[1201] Step 4:

[1202] The server analyzes the text data and retrieves the necessary information.

[1203] Input: Text data of the user's spoken content.

[1204] Processing: Analyze text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify user requests. Send queries to relevant databases.

[1205] Output: Informational data based on user requests.

[1206] Specific actions:

[1207] The server analyzes the received text data using a natural language processing engine.

[1208] The server, in response to the request, sends a query to a flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45".

[1209] Step 5:

[1210] The server formats the acquired information and sends it to the terminal.

[1211] Input: Acquired information data.

[1212] Processing: Format the information into an appropriate format (text or audio data) to convey it to the user, and send it to the terminal.

[1213] Output: Formatted informational data.

[1214] Specific actions:

[1215] The server formats the information into text format.

[1216] The formatted information is packaged into a packet and sent to the terminal.

[1217] Step 6:

[1218] The device provides information to the user.

[1219] Input: Formatted informational data.

[1220] Processing: Formatted information is converted into speech data using speech synthesis software and conveyed to the user.

[1221] Output: Information conveyed to the user.

[1222] Specific actions:

[1223] The device converts text data into speech using a speech synthesis device.

[1224] The system informs the user that "The flight to New York leaves from Gate 32 at 14:45."

[1225] Step 7:

[1226] The device suggests entertainment options to the user.

[1227] Input: User recognition information and request details obtained in the previous processing step.

[1228] Processing: Run an application that generates and suggests entertainment options (jokes, quizzes, music, etc.) to the user.

[1229] Output: Entertainment options presented to the user.

[1230] Specific actions:

[1231] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1232] The system presents customized options based on the user's interests and waiting time.

[1233] Step 8:

[1234] The server generates entertainment content and sends it to the device.

[1235] Input: The user's selected entertainment option.

[1236] Processing: Use a generative artificial intelligence model (e.g., GPT-3) to generate content based on user selections. Send the generated content to the device.

[1237] Output: Customized entertainment content.

[1238] Specific actions:

[1239] The device sends the user's selection (e.g., "I'd like to hear a joke") to the server.

[1240] The server prompts the AI ​​model with "Generate a joke for a traveler waiting for their flight" and sends the generated joke to the device.

[1241] Step 9:

[1242] The device provides users with generated entertainment content.

[1243] Input: Generated entertainment content.

[1244] Processing: Provide entertainment content to users in audio or other formats.

[1245] Output: Entertainment content provided to the user.

[1246] Specific actions:

[1247] The device converts the generated joke into speech using a speech synthesizer and delivers the joke, "Why don't scientists trust atoms? Because they make up everything!" to the user.

[1248] (Application Example 1)

[1249] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1250] In traditional brick-and-mortar stores, the challenges included providing customers with the information they needed quickly and efficiently, and improving customer waiting times and the overall experience. Furthermore, multilingual support was difficult, limiting service provision to foreign customers. Additionally, there was a lack of means to enhance customer satisfaction by providing appropriate entertainment.

[1251] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1252] In this invention, the server includes means for recognizing the user, means for selecting the user's language, means for analyzing the user's input voice, and means for interacting with customers in the store using smart glasses. This makes it possible to quickly provide the information that customers request and to provide information to foreign customers by supporting foreign languages. Furthermore, customer satisfaction can be improved by offering customers entertainment such as coupons and games.

[1253] A "user" is a person who uses a system to receive information and entertainment.

[1254] "Recognition" refers to identifying the presence and characteristics of a user using devices such as cameras and voice recognition systems.

[1255] "Language" refers to a means of communication used by users, and specifically to a particular natural language.

[1256] "Selection" refers to the automatic determination of the appropriate language based on the words spoken by the user.

[1257] "Input voice" refers to the voice data that a user emits to the system.

[1258] "Analysis" is the process of converting input audio into text data and understanding its content.

[1259] "Information provision" means conveying necessary data and knowledge based on user requests.

[1260] "Entertainment" refers to content such as jokes, games, and quizzes designed to entertain users.

[1261] "Smart glasses" are wearable devices that have the function of displaying visual information.

[1262] "Dialogue" is the process by which a system and a user exchange information through voice.

[1263] A "coupon" is an electronic or paper certificate that offers a discount on goods or services.

[1264] "Game" refers to a competition or activity conducted for entertainment purposes.

[1265] This invention is a system that recognizes the user, selects the appropriate language, analyzes the input voice, and provides information and entertainment. This system supports in-store interactions for the user using smart glasses.

[1266] System program

[1267] The system uses the following main hardware and software:

[1268] Hardware: Camera, voice recognition device, smart glasses

[1269] Software: Facial recognition technology, speech recognition (such as Google Speech Recognition API), natural language processing (NLP), generative artificial intelligence models

[1270] Program processing

[1271] 1. User Recognition: When a user enters a physical store, a camera recognizes the user's face and a voice recognition device captures the user's speech. Specifically, the camera uses facial recognition technology with HaarcascadeClassifier to confirm the user's presence.

[1272] 2. Language Selection: The system automatically selects a language based on the user's speech. Speech recognition software (such as the Google Speech Recognition API) is used to identify the language the user is speaking. This process ensures the entire system operates in the selected language.

[1273] 3. Analysis of Input Voice: The system analyzes the voice input provided by the user through the smart glasses. The input voice is converted into text data and sent to the server. The server uses natural language processing (NLP) technology to analyze the input text and identify the information the user is seeking.

[1274] 4. Information Provision: The server retrieves information according to the user's request and displays it to the user through smart glasses. For example, if the user says, "I want to know the size of this product," the server refers to the product database and sends the corresponding size information to the smart glasses.

[1275] 5. Entertainment Provision: After providing information, the server generates and suggests entertainment options (e.g., jokes, quizzes, games) to the user. Generative artificial intelligence models are used to customize content according to the user's interests and waiting time.

[1276] Specific example

[1277] Example 1: Providing services at a physical store

[1278] 1. The user enters a physical store and puts on the smart glasses.

[1279] 2. The camera recognizes the user, and the user speaks to the smart glasses saying, "Tell me about this product."

[1280] 3. The voice recognition device analyzes the user's speech and retrieves the relevant information from the product database.

[1281] 4. Information is displayed on the smart glasses and provided to the user.

[1282] 5. After providing information, the smart glasses will suggest to the user, "You have a coupon that can be used for your next purchase. Would you like to use it?"

[1283] Example of a prompt

[1284] "I'd like to know the size."

[1285] Prompt message:

[1286] Design a program that analyzes a user's voice when they use "smart glasses" to ask for product information, such as size, and then automatically provides that information. Additionally, the program should include a joke after providing the information.

[1287] Thus, the invention constructs a system in which the user, terminal, and server work together to greatly improve the user experience.

[1288] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1289] Step 1:

[1290] The user enters a physical store and puts on smart glasses. The smart glasses activate, and the camera and voice recognition device begin operating. The input here is the activation of the smart glasses, and the output is the activation of the camera and voice recognition device.

[1291] Step 2:

[1292] The camera recognizes the user's face. When the user passes in front of the camera, the HaarcascadeClassifier is used to detect the face. If face recognition is successful, the information is saved as face feature data. The input here is the camera image, and the output is the recognized face feature data.

[1293] Step 3:

[1294] The speech recognition device captures the user's speech. When the user says, "What are the dimensions of this product?", the speech recognition device takes the audio and uses the Google Speech Recognition API to convert the audio data into text. In this case, the input is the user's voice, and the output is the converted text data.

[1295] Step 4:

[1296] Text data is sent to the server. The server receives this text data and performs analysis using natural language processing (NLP) techniques. Through this analysis, the server identifies the user's request (a request for product size information). The input here is text data, and the output is the analyzed request content.

[1297] Step 5:

[1298] The server refers to the product database and retrieves the relevant product information. Specifically, it executes a database search query and extracts the size information for the relevant product (e.g., a shirt). The input here is the parsed request content, and the output is the retrieved product size information.

[1299] Step 6:

[1300] The server sends the acquired information to the smart glasses. The smart glasses display this information to the user, informing them, "This product is size M." The input here is the acquired product size information, and the output is the information displayed on the smart glasses.

[1301] Step 7:

[1302] Following the information provision, the server generates entertainment options using a generative artificial intelligence model. Specifically, it generates content such as jokes and quizzes based on the user's interests and waiting time, and sends it to the smart glasses. Here, the input is the user's interests and waiting time, and the output is the generated entertainment content.

[1303] Step 8:

[1304] Smart glasses offer entertainment options to the user. They deliver suggestions via speech, such as, "We have a coupon you can use on your next purchase. Would you like to use it?" The input here is the generated entertainment content, and the output is the suggestions communicated to the user.

[1305] In this way, the system provides users with efficient, multilingual information and entertainment through a series of processing steps.

[1306] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1307] This invention relates to a system that combines user recognition and language selection, input speech analysis, information provision, entertainment provision, and an emotion engine that recognizes the user's emotions. The program and processing of this system are described in detail below.

[1308] Program processing

[1309] User recognition

[1310] The device uses a sensor to detect when a user approaches. The device's camera uses facial recognition technology to capture the user's face, and the voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1311] Language selection

[1312] When a user says "Please speak in English," the device's speech recognition system analyzes the speech and selects "English" from its language database. The device then sends the selected language information to the server.

[1313] emotion recognition

[1314] The device's emotion engine analyzes the user's voice and facial expression data to identify emotions. For example, it recognizes emotions such as "excitement," "anxiety," and "joy" from the user's voice tone and facial expressions.

[1315] Confirming User Intent

[1316] The server generates an English question script, "How can I assist you today?", and sends it to the terminal. The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[1317] Analysis of audio data

[1318] The terminal's speech recognition device converts the user's speech into text data and sends the text data to the server. The server receives the transmitted text data and analyzes the user's intent using natural language processing technology.

[1319] Information acquisition and provision

[1320] The server, based on the user's request, consults the flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45." The server then translates this information into English and sends it to the terminal. The terminal then communicates the retrieved information to the user.

[1321] Entertainment suggestions and emotion-based customization

[1322] The server generates a script for an entertainment option (joke, quiz, music, etc.) and sends it to the device. The device then prompts the user with "Would you like to hear a joke or play a quick game while you wait?". If the user responds with "I'd like to hear a joke," the emotion engine generates an appropriate joke based on the user's current mood.

[1323] For example, if a user is feeling stressed, a lighthearted joke can be offered to help them relax. This emotionally-driven customization makes the user experience more personalized and increases satisfaction.

[1324] Specific example

[1325] Example 1: Application of emotion recognition at airport reception.

[1326] 1. The user approaches the robot and says, "Hello."

[1327] 2. The device recognizes the user and selects English using the voice recognition device.

[1328] 3. The device's emotion engine analyzes the user's voice and facial expressions to recognize "anxiety."

[1329] 4. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[1330] 5. The user replies, "I need information about my flight to New York."

[1331] 6. The device converts the audio to text and sends the text data to the server.

[1332] 7. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1333] 8. After the device conveys this information to the user, it provides a joke to help the user relax based on their emotions.

[1334] Example 2: Application of emotion recognition at restaurant reception desks

[1335] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[1336] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[1337] 3. The device's emotion engine recognizes "joy" from the user's voice tone.

[1338] 4. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[1339] 5. The user answers, "There are 4 people."

[1340] 6. The device converts the audio to text and sends the text data to the server.

[1341] 7. The server analyzes the request and generates information stating, "A table for 4 people is available from 19:00," which it then sends to the terminal.

[1342] 8. After the device conveys this information to the user, it suggests and provides entertainment (e.g., games) to enjoy according to the user's emotions.

[1343] In this way, the user, device, server, and emotion engine work together to realize the overall operation and improve the user experience. This system not only provides automated customer service and entertainment in a multilingual environment, but also delivers a more sophisticated service by responding to the user's emotions.

[1344] The following describes the processing flow.

[1345] Step 1: User Recognition

[1346] The device uses a proximity sensor to detect when a user approaches.

[1347] The device's camera captures the user's face, and facial recognition technology is used to confirm the user's presence.

[1348] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1349] Step 2: Language Selection

[1350] The user replies, "Please speak in English."

[1351] The device's voice recognition system analyzes the user's voice and selects "English" from its language database.

[1352] The terminal sends the language information it selected to the server.

[1353] Step 3: Emotion Recognition

[1354] The device's emotion engine analyzes the user's voice tone and facial expressions.

[1355] The device identifies the user's emotion as "anxiety."

[1356] Step 4: Confirming User Intent

[1357] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1358] The terminal uses this script to ask the user questions.

[1359] The user replies, "I need information about my flight to New York."

[1360] Step 5: Audio Data Analysis

[1361] The device's speech recognition system converts the user's speech into text data.

[1362] The terminal sends text data to the server.

[1363] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[1364] Step 6: Information Acquisition and Provision

[1365] The server accesses the flight information database based on the user's request.

[1366] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[1367] The server translates this information into English text and sends it to the terminal.

[1368] The device communicates the acquired information to the user. "Your flight to New York departs at 14:45 from Gate 32."

[1369] Step 7: Entertainment suggestions and emotionally-based customization

[1370] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1371] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1372] The user replies, "I'd like to hear a joke."

[1373] The terminal sends the user's request to the server.

[1374] The server uses a generative artificial intelligence model to generate lighthearted jokes to help the user relax based on their emotions (e.g., anxiety).

[1375] The server generates a joke and sends it to the device.

[1376] The device delivers a joke to the user.

[1377] Step 8: Feedback and Closing

[1378] The device asks the user, "Do you need any further assistance?"

[1379] The user replies, "No, thank you."

[1380] The device concludes with "Have a great day!" and ends user support.

[1381] (Example 2)

[1382] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1383] Traditional systems suffer from a lack of consideration for user emotions in language selection, information provision, and entertainment delivery, resulting in insufficient improvement in the quality of the user experience. Providing personalized services is particularly difficult for users in multilingual environments or those experiencing diverse emotional states. This can lead to decreased user satisfaction and reduced system usage.

[1384] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1385] In this invention, the server includes means for selecting the user's language, means for recognizing the user's emotions, and means for providing information. This enables the provision of personalized entertainment tailored to the user's emotional state.

[1386] "Means of recognizing users" refers to technologies that detect when a user approaches the system and identify the user using biometric information such as facial features and voice.

[1387] "Means for selecting the user's language" refers to technology that analyzes the appropriate language from the user's speech or input and sets the system's operation method and information provision method based on that language.

[1388] "Means for analyzing input speech" refers to technologies that acquire voice data spoken by a user and perform speech-to-text conversion or natural language processing to understand its content and intent.

[1389] "Means of providing information" refers to technologies that acquire appropriate information based on user input or requests and present that information to the user in an easily understandable way.

[1390] "Means of recognizing user emotions" refers to technologies that analyze the user's tone of voice, facial expressions, etc., to identify the user's current emotional state (excitement, anxiety, joy, etc.).

[1391] "Means of providing entertainment" refers to technologies that generate and provide entertainment content such as jokes, quizzes, and music in order to provide users with relaxation and enjoyment.

[1392] "Methods for customizing entertainment based on emotions" refers to technologies that select and provide optimal entertainment content by considering the user's emotional state.

[1393] This invention relates to a system that combines user recognition, language selection, input speech analysis, information provision, and entertainment provision with an emotion engine that recognizes the user's emotions. The following describes a specific form for implementing this system.

[1394] Hardware and software to be used

[1395] This system uses the following hardware and software:

[1396] Sensing sensor: Used to detect when a user approaches the device.

[1397] Camera: Captures the user's face using facial recognition technology (e.g., OpenCV or FaceNet).

[1398] Speech recognition device: A device for converting speech into text data (e.g., Google Speech-to-Text).

[1399] Emotion engine: Analyzes the user's voice tone and facial expressions to recognize emotions (e.g., Microsoft Azure Emotion API).

[1400] Server: Analyzes user intent using natural language processing technology (e.g., GPT-4) and provides necessary information.

[1401] Flight information database: A database (e.g., SQLite, MySQL) that stores information to respond to user requests.

[1402] Program details

[1403] User recognition

[1404] When a user approaches the device, the device's sensing sensors detect the user's proximity.

[1405] The device uses its camera and facial recognition technology to capture the user's face.

[1406] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1407] Language selection

[1408] The user replies, "Please speak in English."

[1409] The device analyzes this voice using its voice recognition system and selects "English" from its multilingual database.

[1410] The device sends the selected language information to the server.

[1411] emotion recognition

[1412] The device's emotion engine analyzes the user's voice and facial expressions to identify their emotions.

[1413] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[1414] Confirming user intent and providing information

[1415] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1416] The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[1417] The terminal's speech recognition device converts the user's speech into text data and sends it to the server.

[1418] The server uses natural language processing techniques to analyze the user's intent from the text data it receives.

[1419] Based on the user's request, the server consults the flight information database and retrieves the information "The flight to New York leaves from Gate 32 at 14:45".

[1420] The server generates information and sends it to the terminal, which then relays the information to the user.

[1421] Entertainment proposals and customization

[1422] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1423] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1424] The user replies, "I'd like to hear a joke."

[1425] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, it provides lighthearted jokes to help a stressed user relax.

[1426] Specific example

[1427] Airport reception

[1428] 1. The user approaches the robot and says, "Hello."

[1429] 2. The device detects approach using its sensors and recognizes faces using its cameras.

[1430] 3. The terminal asks, "In what language would you like us to guide you?"

[1431] 4. The user replies, "Please speak in English."

[1432] 5. The device analyzes the audio and notifies the server that it is in English.

[1433] 6. The device's emotion engine analyzes voice and facial expressions to recognize "anxiety."

[1434] 7. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[1435] 8. The user replies, "I need information about my flight to New York."

[1436] 9. The device converts the audio to text and sends it to the server.

[1437] 10. The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1438] 11. The device conveys information to the user.

[1439] 12. The device offers a lighthearted joke to alleviate user anxiety.

[1440] Examples of prompts for generative AI models

[1441] 1. To the emotion engine: "Identify the user's current emotion based on their voice tone and facial expression data."

[1442] 2. To a natural language processing system: "Please analyze this text data and understand the user's intent."

[1443] 3. In response to an entertainment suggestion: "Generate jokes to help users relax when they are feeling stressed."

[1444] In this way, a system can be realized in which the user, terminal, server, and emotion engine work together to improve the quality of service provided to the user.

[1445] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1446] Step 1: User Recognition

[1447] The user approaches the device.

[1448] Input: User approach.

[1449] The device's sensor detects the user's approach.

[1450] The device uses its camera to capture the user's face using facial recognition technology (e.g., OpenCV, FaceNet).

[1451] Input: User's face image.

[1452] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1453] Output: Face recognition results, language selection prompt.

[1454] Step 2: Language Selection

[1455] The user replies, "Please speak in English."

[1456] Input: User's voice.

[1457] The device analyzes this audio using its speech recognition system (e.g., Google Speech-to-Text) and selects "English" from its multilingual database.

[1458] The device sends the selected language information to the server.

[1459] Output: Language selection result (English), language information sent to the server.

[1460] Step 3: Emotion Recognition

[1461] The device's emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's voice and facial expressions.

[1462] Input: User's voice tone and facial expression data.

[1463] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[1464] Output: Emotion recognition result.

[1465] Step 4: Confirming User Intent

[1466] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1467] Input: Server entertainment planning.

[1468] The device asks the user a question.

[1469] The user replies, "I need information about my flight to New York."

[1470] Output: User request.

[1471] Step 5: Audio Data Analysis

[1472] The device's speech recognition system converts the user's speech into text data.

[1473] Input: User's spoken audio.

[1474] The terminal sends the generated text data to the server.

[1475] Output: Text data.

[1476] Step 6: Information Acquisition and Provision

[1477] The server analyzes the received text data using natural language processing techniques (e.g., GPT-4) to confirm the user's intent.

[1478] Input: Text data, natural language processing model.

[1479] The server accesses a flight information database (e.g., SQLite, MySQL) based on the user's request.

[1480] Output: Required information (flight information).

[1481] The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1482] Output: A message containing information.

[1483] Step 7: Information Dissemination

[1484] The device communicates the information it has acquired to the user.

[1485] Input: Flight information.

[1486] Output: Voice message.

[1487] Step 8: Entertainment Suggestions and Customization

[1488] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1489] Input: Server entertainment planning and sentiment information.

[1490] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1491] The user replies, "I'd like to hear a joke."

[1492] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, if the user is feeling stressed, it will provide lighthearted jokes to help them relax.

[1493] Output: Emotionally customized entertainment.

[1494] In this way, input, data processing, data calculation, and output are performed at each processing step, enabling personalized service for each user.

[1495] (Application Example 2)

[1496] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1497] Traditional automated dialogue systems struggle to take user emotions into account, resulting in a limited user experience. Furthermore, insufficient multilingual support makes it difficult to serve users who speak different languages. This makes it challenging to enhance user satisfaction, particularly in virtual stores where natural dialogue and high-quality information delivery are essential.

[1498] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1499] In this invention, the server includes means for recognizing a user, means for selecting the user's language, means for recognizing the user's emotions, means for providing information based on the input voice and emotions, and means for generating the entertainment using a generative artificial intelligence model. This enables the provision of personalized information and entertainment based on the user's emotions.

[1500] "Means of recognizing a user" refers to technologies that use cameras and voice recognition devices to detect and identify a user's face and voice.

[1501] "Means of selecting a language" refers to a technology that analyzes and selects the language used by the user via a speech recognition device.

[1502] "Methods for analyzing input speech" refer to technologies that convert voice input from a user into text data and understand its content.

[1503] "Means of recognizing emotions" refers to technologies that analyze a user's voice tone and facial expressions to identify the user's emotional state.

[1504] "Means of providing information" refers to technologies that search for relevant data based on user requests and provide that information to the user.

[1505] "Means of providing entertainment" refers to the technology that generates and delivers content that users can enjoy.

[1506] A "generative artificial intelligence model" is a technology that uses artificial intelligence algorithms to generate content tailored to the user.

[1507] A "prompt message" is an instruction message that is input into a generative artificial intelligence model to generate an appropriate response or content.

[1508] This invention relates to a system that combines means for recognizing emotions in user recognition, language selection, voice input analysis, information provision, and entertainment provision. The aim of this system is to improve the user experience in virtual stores.

[1509] 1. System Configuration

[1510] hardware

[1511] Camera: A device used to capture the user's face and perform facial recognition.

[1512] Speech recognition device: A device that captures the user's voice and performs language selection and speech analysis.

[1513] Server: A central device that processes and manages various types of data.

[1514] software

[1515] Face recognition technology: Uses ZaCV or similar face recognition technology.

[1516] Speech recognition technology: We use Google Speech-to-Text API and Amazon Transcribe.

[1517] Emotion recognition engine: Recognizes user emotions using Microsoft Azure Face API and other tools.

[1518] Natural language processing techniques: We use Google NLP API and spaCy.

[1519] Generative AI models: Generative AI models such as OpenAI GPT-3 are used.

[1520] 2. Data Calculation and Processing

[1521] User recognition and language selection

[1522] The device first uses a camera to capture the user's face and recognizes the user using facial recognition technology. Next, a voice recognition device captures the user's voice to determine which language to use. When the user responds to the question, "Hello, in what language would you like me to guide you?" with "English, please," the voice recognition technology analyzes the voice and selects the appropriate language.

[1523] emotion recognition

[1524] The device analyzes the user's voice tone and facial expressions to identify their emotions. For example, it can recognize emotions such as "joy" or "anxiety" from the user's voice tone and facial expressions. This process uses the Microsoft Azure Face API.

[1525] Providing information

[1526] The server receives a user request (e.g., "I am looking for a smart TV") and analyzes its content using natural language processing technology. It then retrieves the information the user is looking for from relevant databases, generates a specific response (e.g., "Here are the top 3 smart TVs available"), and sends it to the device.

[1527] Entertainment provider

[1528] The server uses a generative artificial intelligence model to generate entertainment options (e.g., jokes) based on the user's emotions. The terminal suggests these options, and if the user shows interest, it provides the generated entertainment content. For example, a user in a "relaxed" emotional state would be offered relaxing jokes.

[1529] Specific example

[1530] 1. The user accesses the virtual store. A camera recognizes the user, and a voice recognition device selects the language.

[1531] 2. Acquisition of text data: When the user asks "I am looking for a smart TV," speech recognition technology analyzes this and converts it into text.

[1532] 3. User emotion recognition: The emotion recognition engine recognizes "excitement" based on the user's voice and facial expressions.

[1533] 4. Information provision: The server generates information such as "Here are the top 3 smart TVs available" and provides it to the user through the terminal.

[1534] 5. Entertainment Suggestion: When the user is relaxed, the device will suggest, "Would you like to hear a joke?"

[1535] 6. Provide a joke: If the user answers "yes," the following joke will be provided: "Why don't scientists trust atoms? Because they make up everything!"

[1536] Example of a prompt

[1537] "A user has asked for information about smart TVs. Please provide the following information and a fun joke."

[1538] The user's emotional state is one of relaxation.

[1539] User question: I am looking for a smart TV.

[1540] Information provided: Here are the top 3 smart TVs available.

[1541] A funny joke: Why don't scientists trust atoms? Because they make up everything!

[1542] As described above, this system can improve the user experience in virtual stores by analyzing the user's voice and emotions and providing personalized information and entertainment.

[1543] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1544] Step 1:

[1545] The device uses a camera to capture the user's face. The input is video data captured by the camera, and the output is the user's face data identified via face recognition technology (OpenCV). Specifically, the camera captures the user's face in real time, and the face recognition algorithm analyzes this data to extract the user's facial features.

[1546] Step 2:

[1547] The device uses a speech recognition device to capture the user's voice and select a language. The input is voice data from the user, and the output is language data selected using speech recognition technology (Google Speech-to-Text API). Specifically, if the device asks the user, "Hello, in what language would you like me to guide you?", and the user replies, "English please," the speech recognition technology analyzes this voice and selects "English" as the language to use.

[1548] Step 3:

[1549] The device captures the user's voice tone and facial expression data and identifies emotions using an emotion recognition engine (Microsoft Azure Face API). The input is the user's voice and video data, and the output is analyzed emotion data (e.g., "excitement," "anxiety," "joy"). Specifically, it analyzes the user's voice tone and facial expressions in real time to identify their emotional state.

[1550] Step 4:

[1551] The server uses natural language processing technology (Google NLP API) to analyze user requests. The input is the user's utterance converted into text data by a speech recognition device, and the output is the analyzed user intent data. For example, if a user says "I need information about my flight to New York," this is analyzed to identify the intent "I am seeking flight information."

[1552] Step 5:

[1553] The server searches for and provides information based on the user's request. The input is the identified user's intent data, and the output is related information data (e.g., "The flight to New York leaves from Gate 32 at 14:45"). Specifically, the server accesses a flight information database, retrieves the necessary information, and formats it into text.

[1554] Step 6:

[1555] The server uses a generative artificial intelligence model (OpenAI GPT-3) to generate entertainment based on the user's emotions. The input is analyzed emotion data and user requests, and the output is generated entertainment content (e.g., jokes, music). Specifically, based on information that "the user wants to relax," the server generates jokes to help the user relax.

[1556] Step 7:

[1557] The terminal provides the user with generated information and entertainment content. The input is information data and entertainment content transmitted from the server, and the output is provided to the user in audio and video format. Specifically, the terminal will verbally announce the information, "The flight to New York leaves from Gate 32 at 14:45," and then suggest an entertainment option, "Would you like to hear a joke?"

[1558] As described above, each step works in conjunction to provide information and entertainment to users.

[1559] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1560] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1561] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1562] [Fourth Embodiment]

[1563] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1564] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1565] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1566] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1567] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1568] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1569] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1570] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1571] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1572] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1573] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1574] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1575] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1576] This invention relates to a system that recognizes a user, selects a language, analyzes input speech, and provides information and entertainment. The following describes the program processing of this system, and provides a detailed explanation of its embodiments with specific examples.

[1577] Program processing

[1578] User recognition

[1579] The device recognizes the user using a camera and voice recognition system. Specifically, the device detects when the user approaches the robot and confirms the user's presence using facial recognition technology. In addition, the voice recognition system captures the user's speech and initially identifies the language the user is speaking.

[1580] Language selection

[1581] Based on the language the user speaks, the device automatically selects the appropriate language. For example, if the user says "Hello," the device selects English and sends that information to the server. This ensures that the entire system is compatible with the user's chosen language.

[1582] Analysis of input audio

[1583] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server uses natural language processing technology to analyze the text data and clearly identify the information the user is seeking.

[1584] Providing information

[1585] The server retrieves the necessary information based on the user's request and sends it to the terminal in the appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information (e.g., "The flight to New York departs from Gate 32 at 14:45").

[1586] Entertainment provider

[1587] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model, this content is customized according to the user's interests and waiting time.

[1588] Specific example

[1589] Example 1: Airport reception

[1590] 1. The user approaches the robot and says, "Hello."

[1591] 2. The device recognizes the user and selects English using the voice recognition device.

[1592] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[1593] 4. The user replies, "I need information about my flight to New York."

[1594] 5. The device converts the audio to text and sends the text data to the server.

[1595] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1596] 7. The device communicates this information to the user.

[1597] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[1598] 9. The user responds, "I'd like to hear a joke."

[1599] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[1600] 11. The device delivers jokes to the user to entertain them.

[1601] Example 2: Restaurant reception

[1602] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[1603] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[1604] 3. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[1605] 4. The user answers, "There are 4 people."

[1606] 5. The device converts the audio to text and sends the text data to the server.

[1607] 6. The server parses the request, checks the table reservation status, generates information such as "A table for 4 people is available from 19:00," and sends it to the terminal.

[1608] 7. The device communicates this information to the user.

[1609] 8. The device then suggests games that can be enjoyed during the waiting time, and if the user selects one, it provides an AR puzzle game.

[1610] In this way, users, devices, and servers work together to realize the overall functionality and improve the user experience. This system enables efficient and effective service by providing automated customer service and entertainment in a multilingual environment.

[1611] The following describes the processing flow.

[1612] Step 1: User Recognition

[1613] The device uses a sensing sensor to detect when a user approaches.

[1614] The device's camera uses facial recognition technology to capture the user's face.

[1615] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1616] Step 2: Language Selection

[1617] The user says, "Please speak in English."

[1618] The device's voice recognition system analyzes this speech and selects "English" from its language database.

[1619] The terminal sends the language information it selected to the server.

[1620] Step 3: Confirming User Intent

[1621] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1622] The terminal uses this script to ask the user questions.

[1623] The user replies, "I need information about my flight to New York."

[1624] Step 4: Analysis of the voice and moon

[1625] The device's speech recognition system converts the user's speech into text data.

[1626] The terminal sends text data to the server.

[1627] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[1628] Step 5: Information Acquisition and Provision

[1629] The server accesses the flight information database based on the user's request.

[1630] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[1631] The server translates this information into English text and sends it to the terminal.

[1632] The device communicates the information it has acquired to the user.

[1633] Step 6: Entertainment Proposal

[1634] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1635] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1636] The user replies, "I'd like to hear a joke."

[1637] Step 7: Providing entertainment

[1638] The terminal sends the user's request to the server.

[1639] The server generates jokes using a generative artificial intelligence model.

[1640] The server generates a joke and sends it to the device.

[1641] The device delivers a joke to the user.

[1642] Step 8: Feedback and Closing

[1643] The device asks the user, "Do you need any further assistance?"

[1644] The user replies, "No, thank you."

[1645] The device concludes with "Have a great day!" and ends user support.

[1646] (Example 1)

[1647] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1648] Conventional voice interface systems have struggled to respond to individual user requests and have often been limited to specific languages ​​and situations. Furthermore, they have not adequately improved the user experience in terms of multilingual support and entertainment provision. This has made it difficult to provide efficient and effective services, especially in places used by multinational users (e.g., airports and tourist destinations). To solve these problems, a system is needed that can integrate user language recognition, information provision, and entertainment provision.

[1649] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1650] In this invention, the server includes means for the terminal to recognize a user using a camera and a speech recognition device, means for automatically selecting the language spoken by the user, means for converting the user's speech into text data using the speech recognition device and transmitting it to the server, means for analyzing the text data using natural language processing technology to obtain information requested by the user, means for transmitting the information to the terminal and providing it to the user, and means for providing entertainment in addition to the information using a generative artificial intelligence model. This enables multilingual support and allows for the provision of information and entertainment based on the individual requests of the user.

[1651] A "terminal" refers to a device used for direct interaction with a user, and is equipped with hardware including a camera and a voice recognition device.

[1652] A "camera" is a device used to capture images and is used to recognize the user's face and movements.

[1653] A "speech recognition device" is a device that converts speech into text data and is used to analyze a user's speech.

[1654] A "server" refers to a device or system for processing and storing data, and it plays a role in analyzing data using natural language processing technology and providing necessary information.

[1655] "Natural language processing technology" refers to techniques for analyzing text data and understanding human language. For example, it is used to analyze the meaning of text data and identify the information that the user is looking for.

[1656] A "generative artificial intelligence model" refers to artificial intelligence that has the ability to generate new content based on user input, and is used, for example, to generate entertainment content such as jokes and quizzes.

[1657] A "user" refers to a person who uses a system, obtaining information or enjoying entertainment through interaction with the system.

[1658] "Entertainment" refers to content that provides users with enjoyment and satisfaction, and can take the form of jokes, quizzes, music, and so on.

[1659] "Information provision" refers to the act of a server acquiring necessary information in response to a user's questions or requests and then transmitting that information to the user via their terminal.

[1660] Modes for carrying out the invention

[1661] This invention relates to a system that recognizes the user, selects a language, analyzes the input voice, provides information, and further provides entertainment. Specific embodiments of this system are described in detail below.

[1662] User recognition

[1663] The device recognizes the user using a camera and a voice recognition device. Specifically, the device detects when a user approaches and uses a camera (e.g., a typical webcam) to confirm the user's presence using facial recognition technology. It also uses a voice recognition device (e.g., Google Speech-to-Text API) to capture the user's speech and identify the language the user is speaking.

[1664] Language selection

[1665] The device automatically selects a language based on the user's speech. For example, if the user says "Hello," the device selects English and sends this information to the server.

[1666] Analysis of input audio

[1667] The speech recognition device converts the user's spoken content into text data and sends that text data to the server. The server analyzes the text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify the information the user is looking for.

[1668] Providing information

[1669] The server retrieves the necessary information from relevant databases based on the analysis results and sends it to the terminal in an appropriate format. For example, if a user says, "I want to know the flight information for New York," the server will refer to the flight information database and provide specific information.

[1670] Entertainment provider

[1671] Following the provision of information, the server generates and delivers entertainment to the user. The terminal suggests entertainment options (jokes, quizzes, music, etc.) to the user and provides appropriate content according to the user's selection. By utilizing a generative artificial intelligence model (e.g., GPT-3), this content is customized according to the user's interests and waiting time.

[1672] Specific example

[1673] Example 1: Airport reception

[1674] 1. The user approaches the robot and says, "Hello."

[1675] 2. The device recognizes the user and selects English using the voice recognition device.

[1676] 3. The server generates a script that asks the user, "How can I assist you today?" and sends it to the terminal.

[1677] 4. The user replies, "I need information about my flight to New York."

[1678] 5. The device converts the audio to text and sends the text data to the server.

[1679] 6. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1680] 7. The device communicates this information to the user.

[1681] 8. After the information has been shared, the device will suggest, "Would you like to hear a joke or play a quick game while you wait?"

[1682] 9. The user responds, "I'd like to hear a joke."

[1683] 10. The device sends this request to the server, which generates a joke and sends it back to the device.

[1684] 11. The device delivers jokes to the user to entertain them.

[1685] Example of a prompt

[1686] "Use a generative AI model to generate jokes appropriate to specific situations."

[1687] "To provide the flight information requested by the user, please refer to the flight information database."

[1688] As described above, the present invention enables efficient and effective service provision in locations used by multinational users, through the coordinated and effective operation of users, terminals, and servers.

[1689] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1690] Step 1:

[1691] The device recognizes the user.

[1692] Input: Camera video and audio data.

[1693] Processing: The device's camera detects an approaching person and uses facial recognition software (e.g., OpenCV or FaceNet) to recognize the user's face. Additionally, a speech recognition device captures the user's speech and obtains initial audio data.

[1694] Output: User's facial image data and initial voice data.

[1695] Specific actions:

[1696] The device's camera activates and captures images of the surroundings.

[1697] The device uses facial recognition software to analyze facial features and confirm the user's presence.

[1698] The speech recognition device captures the user's speech in real time and generates initial audio data.

[1699] Step 2:

[1700] The device selects the user's language.

[1701] Input: Initial audio data.

[1702] Processing: The speech recognition device analyzes the initial audio data to identify the language the user is speaking. The identified language information is converted into JSON format.

[1703] Output: JSON data including language information.

[1704] Specific actions:

[1705] The terminal identifies the spoken language from the analysis results of the speech recognition device, and for example, selects English from the utterance "Hello".

[1706] Convert language information to JSON format and generate data packets.

[1707] Step 3:

[1708] The device converts the user's spoken content into text data and sends it to the server.

[1709] Input: Detailed speech data of the user.

[1710] Processing: The speech recognition device converts the speech into text data and sends that text data to the server via the network.

[1711] Output: User's speech in text format.

[1712] Specific actions:

[1713] The terminal uses a voice recognition device to convert the user's specific request (e.g., "I need information about my flight to New York") into text data.

[1714] The text data is packaged into a packet and sent to the server.

[1715] Step 4:

[1716] The server analyzes the text data and retrieves the necessary information.

[1717] Input: Text data of the user's spoken content.

[1718] Processing: Analyze text data using natural language processing techniques (e.g., spaCy or Transformer models) to identify user requests. Send queries to relevant databases.

[1719] Output: Informational data based on user requests.

[1720] Specific actions:

[1721] The server analyzes the received text data using a natural language processing engine.

[1722] The server, in response to the request, sends a query to a flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45".

[1723] Step 5:

[1724] The server formats the acquired information and sends it to the terminal.

[1725] Input: Acquired information data.

[1726] Processing: Format the information into an appropriate format (text or audio data) to convey it to the user, and send it to the terminal.

[1727] Output: Formatted informational data.

[1728] Specific actions:

[1729] The server formats the information into text format.

[1730] The formatted information is packaged into a packet and sent to the terminal.

[1731] Step 6:

[1732] The device provides information to the user.

[1733] Input: Formatted informational data.

[1734] Processing: Formatted information is converted into speech data using speech synthesis software and conveyed to the user.

[1735] Output: Information conveyed to the user.

[1736] Specific actions:

[1737] The device converts text data into speech using a speech synthesis device.

[1738] The system informs the user that "The flight to New York leaves from Gate 32 at 14:45."

[1739] Step 7:

[1740] The device suggests entertainment options to the user.

[1741] Input: User recognition information and request details obtained in the previous processing step.

[1742] Processing: Run an application that generates and suggests entertainment options (jokes, quizzes, music, etc.) to the user.

[1743] Output: Entertainment options presented to the user.

[1744] Specific actions:

[1745] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1746] The system presents customized options based on the user's interests and waiting time.

[1747] Step 8:

[1748] The server generates entertainment content and sends it to the device.

[1749] Input: The user's selected entertainment option.

[1750] Processing: Use a generative artificial intelligence model (e.g., GPT-3) to generate content based on user selections. Send the generated content to the device.

[1751] Output: Customized entertainment content.

[1752] Specific actions:

[1753] The device sends the user's selection (e.g., "I'd like to hear a joke") to the server.

[1754] The server prompts the AI ​​model with "Generate a joke for a traveler waiting for their flight" and sends the generated joke to the device.

[1755] Step 9:

[1756] The device provides users with generated entertainment content.

[1757] Input: Generated entertainment content.

[1758] Processing: Provide entertainment content to users in audio or other formats.

[1759] Output: Entertainment content provided to the user.

[1760] Specific actions:

[1761] The device converts the generated joke into speech using a speech synthesizer and delivers the joke, "Why don't scientists trust atoms? Because they make up everything!" to the user.

[1762] (Application Example 1)

[1763] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1764] In traditional brick-and-mortar stores, the challenges included providing customers with the information they needed quickly and efficiently, and improving customer waiting times and the overall experience. Furthermore, multilingual support was difficult, limiting service provision to foreign customers. Additionally, there was a lack of means to enhance customer satisfaction by providing appropriate entertainment.

[1765] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1766] In this invention, the server includes means for recognizing the user, means for selecting the user's language, means for analyzing the user's input voice, and means for interacting with customers in the store using smart glasses. This makes it possible to quickly provide the information that customers request and to provide information to foreign customers by supporting foreign languages. Furthermore, customer satisfaction can be improved by offering customers entertainment such as coupons and games.

[1767] A "user" is a person who uses a system to receive information and entertainment.

[1768] "Recognition" refers to identifying the presence and characteristics of a user using devices such as cameras and voice recognition systems.

[1769] "Language" refers to a means of communication used by users, and specifically to a particular natural language.

[1770] "Selection" refers to the automatic determination of the appropriate language based on the words spoken by the user.

[1771] "Input voice" refers to the voice data that a user emits to the system.

[1772] "Analysis" is the process of converting input audio into text data and understanding its content.

[1773] "Information provision" means conveying necessary data and knowledge based on user requests.

[1774] "Entertainment" refers to content such as jokes, games, and quizzes designed to entertain users.

[1775] "Smart glasses" are wearable devices that have the function of displaying visual information.

[1776] "Dialogue" is the process by which a system and a user exchange information through voice.

[1777] A "coupon" is an electronic or paper certificate that offers a discount on goods or services.

[1778] "Game" refers to a competition or activity conducted for entertainment purposes.

[1779] This invention is a system that recognizes the user, selects the appropriate language, analyzes the input voice, and provides information and entertainment. This system supports in-store interactions for the user using smart glasses.

[1780] System program

[1781] The system uses the following main hardware and software:

[1782] Hardware: Camera, voice recognition device, smart glasses

[1783] Software: Facial recognition technology, speech recognition (such as Google Speech Recognition API), natural language processing (NLP), generative artificial intelligence models

[1784] Program processing

[1785] 1. User Recognition: When a user enters a physical store, a camera recognizes the user's face and a voice recognition device captures the user's speech. Specifically, the camera uses facial recognition technology with HaarcascadeClassifier to confirm the user's presence.

[1786] 2. Language Selection: The system automatically selects a language based on the user's speech. Speech recognition software (such as the Google Speech Recognition API) is used to identify the language the user is speaking. This process ensures the entire system operates in the selected language.

[1787] 3. Analysis of Input Voice: The system analyzes the voice input provided by the user through the smart glasses. The input voice is converted into text data and sent to the server. The server uses natural language processing (NLP) technology to analyze the input text and identify the information the user is seeking.

[1788] 4. Information Provision: The server retrieves information according to the user's request and displays it to the user through smart glasses. For example, if the user says, "I want to know the size of this product," the server refers to the product database and sends the corresponding size information to the smart glasses.

[1789] 5. Entertainment Provision: After providing information, the server generates and suggests entertainment options (e.g., jokes, quizzes, games) to the user. Generative artificial intelligence models are used to customize content according to the user's interests and waiting time.

[1790] Specific example

[1791] Example 1: Providing services at a physical store

[1792] 1. The user enters a physical store and puts on the smart glasses.

[1793] 2. The camera recognizes the user, and the user speaks to the smart glasses saying, "Tell me about this product."

[1794] 3. The voice recognition device analyzes the user's speech and retrieves the relevant information from the product database.

[1795] 4. Information is displayed on the smart glasses and provided to the user.

[1796] 5. After providing information, the smart glasses will suggest to the user, "You have a coupon that can be used for your next purchase. Would you like to use it?"

[1797] Example of a prompt

[1798] "I'd like to know the size."

[1799] Prompt message:

[1800] Design a program that analyzes a user's voice when they use "smart glasses" to ask for product information, such as size, and then automatically provides that information. Additionally, the program should include a joke after providing the information.

[1801] Thus, the invention constructs a system in which the user, terminal, and server work together to greatly improve the user experience.

[1802] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1803] Step 1:

[1804] The user enters a physical store and puts on smart glasses. The smart glasses activate, and the camera and voice recognition device begin operating. The input here is the activation of the smart glasses, and the output is the activation of the camera and voice recognition device.

[1805] Step 2:

[1806] The camera recognizes the user's face. When the user passes in front of the camera, the HaarcascadeClassifier is used to detect the face. If face recognition is successful, the information is saved as face feature data. The input here is the camera image, and the output is the recognized face feature data.

[1807] Step 3:

[1808] The speech recognition device captures the user's speech. When the user says, "What are the dimensions of this product?", the speech recognition device takes the audio and uses the Google Speech Recognition API to convert the audio data into text. In this case, the input is the user's voice, and the output is the converted text data.

[1809] Step 4:

[1810] Text data is sent to the server. The server receives this text data and performs analysis using natural language processing (NLP) techniques. Through this analysis, the server identifies the user's request (a request for product size information). The input here is text data, and the output is the analyzed request content.

[1811] Step 5:

[1812] The server refers to the product database and retrieves the relevant product information. Specifically, it executes a database search query and extracts the size information for the relevant product (e.g., a shirt). The input here is the parsed request content, and the output is the retrieved product size information.

[1813] Step 6:

[1814] The server sends the acquired information to the smart glasses. The smart glasses display this information to the user, informing them, "This product is size M." The input here is the acquired product size information, and the output is the information displayed on the smart glasses.

[1815] Step 7:

[1816] Following the information provision, the server generates entertainment options using a generative artificial intelligence model. Specifically, it generates content such as jokes and quizzes based on the user's interests and waiting time, and sends it to the smart glasses. Here, the input is the user's interests and waiting time, and the output is the generated entertainment content.

[1817] Step 8:

[1818] Smart glasses offer entertainment options to the user. They deliver suggestions via speech, such as, "We have a coupon you can use on your next purchase. Would you like to use it?" The input here is the generated entertainment content, and the output is the suggestions communicated to the user.

[1819] In this way, the system provides users with efficient, multilingual information and entertainment through a series of processing steps.

[1820] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1821] This invention relates to a system that combines user recognition and language selection, input speech analysis, information provision, entertainment provision, and an emotion engine that recognizes the user's emotions. The program and processing of this system are described in detail below.

[1822] Program processing

[1823] User recognition

[1824] The device uses a sensor to detect when a user approaches. The device's camera uses facial recognition technology to capture the user's face, and the voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1825] Language selection

[1826] When a user says "Please speak in English," the device's speech recognition system analyzes the speech and selects "English" from its language database. The device then sends the selected language information to the server.

[1827] emotion recognition

[1828] The device's emotion engine analyzes the user's voice and facial expression data to identify emotions. For example, it recognizes emotions such as "excitement," "anxiety," and "joy" from the user's voice tone and facial expressions.

[1829] Confirming User Intent

[1830] The server generates an English question script, "How can I assist you today?", and sends it to the terminal. The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[1831] Analysis of audio data

[1832] The terminal's speech recognition device converts the user's speech into text data and sends the text data to the server. The server receives the transmitted text data and analyzes the user's intent using natural language processing technology.

[1833] Information acquisition and provision

[1834] The server, based on the user's request, consults the flight information database and retrieves specific information such as "The flight to New York leaves from Gate 32 at 14:45." The server then translates this information into English and sends it to the terminal. The terminal then communicates the retrieved information to the user.

[1835] Entertainment suggestions and emotion-based customization

[1836] The server generates a script for an entertainment option (joke, quiz, music, etc.) and sends it to the device. The device then prompts the user with "Would you like to hear a joke or play a quick game while you wait?". If the user responds with "I'd like to hear a joke," the emotion engine generates an appropriate joke based on the user's current mood.

[1837] For example, if a user is feeling stressed, a lighthearted joke can be offered to help them relax. This emotionally-driven customization makes the user experience more personalized and increases satisfaction.

[1838] Specific example

[1839] Example 1: Application of emotion recognition at airport reception.

[1840] 1. The user approaches the robot and says, "Hello."

[1841] 2. The device recognizes the user and selects English using the voice recognition device.

[1842] 3. The device's emotion engine analyzes the user's voice and facial expressions to recognize "anxiety."

[1843] 4. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[1844] 5. The user replies, "I need information about my flight to New York."

[1845] 6. The device converts the audio to text and sends the text data to the server.

[1846] 7. The server parses the request and generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1847] 8. After the device conveys this information to the user, it provides a joke to help the user relax based on their emotions.

[1848] Example 2: Application of emotion recognition at restaurant reception desks

[1849] 1. The user says to the robot in Japanese, "I would like to reserve a table."

[1850] 2. The device recognizes the user and selects Japanese using the voice recognition device.

[1851] 3. The device's emotion engine recognizes "joy" from the user's voice tone.

[1852] 4. The server generates a script that asks the user, "How many people are in your party?" and sends it to the terminal.

[1853] 5. The user answers, "There are 4 people."

[1854] 6. The device converts the audio to text and sends the text data to the server.

[1855] 7. The server analyzes the request and generates information stating, "A table for 4 people is available from 19:00," which it then sends to the terminal.

[1856] 8. After the device conveys this information to the user, it suggests and provides entertainment (e.g., games) to enjoy according to the user's emotions.

[1857] In this way, the user, device, server, and emotion engine work together to realize the overall operation and improve the user experience. This system not only provides automated customer service and entertainment in a multilingual environment, but also delivers a more sophisticated service by responding to the user's emotions.

[1858] The following describes the processing flow.

[1859] Step 1: User Recognition

[1860] The device uses a proximity sensor to detect when a user approaches.

[1861] The device's camera captures the user's face, and facial recognition technology is used to confirm the user's presence.

[1862] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1863] Step 2: Language Selection

[1864] The user replies, "Please speak in English."

[1865] The device's voice recognition system analyzes the user's voice and selects "English" from its language database.

[1866] The terminal sends the language information it selected to the server.

[1867] Step 3: Emotion Recognition

[1868] The device's emotion engine analyzes the user's voice tone and facial expressions.

[1869] The device identifies the user's emotion as "anxiety."

[1870] Step 4: Confirming User Intent

[1871] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1872] The terminal uses this script to ask the user questions.

[1873] The user replies, "I need information about my flight to New York."

[1874] Step 5: Audio Data Analysis

[1875] The device's speech recognition system converts the user's speech into text data.

[1876] The terminal sends text data to the server.

[1877] The server receives the transmitted text data and uses natural language processing techniques to analyze the user's intent.

[1878] Step 6: Information Acquisition and Provision

[1879] The server accesses the flight information database based on the user's request.

[1880] The server retrieves specific information: "The flight to New York leaves from Gate 32 at 14:45."

[1881] The server translates this information into English text and sends it to the terminal.

[1882] The device communicates the acquired information to the user. "Your flight to New York departs at 14:45 from Gate 32."

[1883] Step 7: Entertainment suggestions and emotionally-based customization

[1884] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1885] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1886] The user replies, "I'd like to hear a joke."

[1887] The terminal sends the user's request to the server.

[1888] The server uses a generative artificial intelligence model to generate lighthearted jokes to help the user relax based on their emotions (e.g., anxiety).

[1889] The server generates a joke and sends it to the device.

[1890] The device delivers a joke to the user.

[1891] Step 8: Feedback and Closing

[1892] The device asks the user, "Do you need any further assistance?"

[1893] The user replies, "No, thank you."

[1894] The device concludes with "Have a great day!" and ends user support.

[1895] (Example 2)

[1896] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1897] Traditional systems suffer from a lack of consideration for user emotions in language selection, information provision, and entertainment delivery, resulting in insufficient improvement in the quality of the user experience. Providing personalized services is particularly difficult for users in multilingual environments or those experiencing diverse emotional states. This can lead to decreased user satisfaction and reduced system usage.

[1898] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1899] In this invention, the server includes means for selecting the user's language, means for recognizing the user's emotions, and means for providing information. This enables the provision of personalized entertainment tailored to the user's emotional state.

[1900] "Means of recognizing users" refers to technologies that detect when a user approaches the system and identify the user using biometric information such as facial features and voice.

[1901] "Means for selecting the user's language" refers to technology that analyzes the appropriate language from the user's speech or input and sets the system's operation method and information provision method based on that language.

[1902] "Means for analyzing input speech" refers to technologies that acquire voice data spoken by a user and perform speech-to-text conversion or natural language processing to understand its content and intent.

[1903] "Means of providing information" refers to technologies that acquire appropriate information based on user input or requests and present that information to the user in an easily understandable way.

[1904] "Means of recognizing user emotions" refers to technologies that analyze the user's tone of voice, facial expressions, etc., to identify the user's current emotional state (excitement, anxiety, joy, etc.).

[1905] "Means of providing entertainment" refers to technologies that generate and provide entertainment content such as jokes, quizzes, and music in order to provide users with relaxation and enjoyment.

[1906] "Methods for customizing entertainment based on emotions" refers to technologies that select and provide optimal entertainment content by considering the user's emotional state.

[1907] This invention relates to a system that combines user recognition, language selection, input speech analysis, information provision, and entertainment provision with an emotion engine that recognizes the user's emotions. The following describes a specific form for implementing this system.

[1908] Hardware and software to be used

[1909] This system uses the following hardware and software:

[1910] Sensing sensor: Used to detect when a user approaches the device.

[1911] Camera: Captures the user's face using facial recognition technology (e.g., OpenCV or FaceNet).

[1912] Speech recognition device: A device for converting speech into text data (e.g., Google Speech-to-Text).

[1913] Emotion engine: Analyzes the user's voice tone and facial expressions to recognize emotions (e.g., Microsoft Azure Emotion API).

[1914] Server: Analyzes user intent using natural language processing technology (e.g., GPT-4) and provides necessary information.

[1915] Flight information database: A database (e.g., SQLite, MySQL) that stores information to respond to user requests.

[1916] Program details

[1917] User recognition

[1918] When a user approaches the device, the device's sensing sensors detect the user's proximity.

[1919] The device uses its camera and facial recognition technology to capture the user's face.

[1920] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1921] Language selection

[1922] The user replies, "Please speak in English."

[1923] The device analyzes this voice using its voice recognition system and selects "English" from its multilingual database.

[1924] The device sends the selected language information to the server.

[1925] emotion recognition

[1926] The device's emotion engine analyzes the user's voice and facial expressions to identify their emotions.

[1927] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[1928] Confirming user intent and providing information

[1929] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1930] The terminal uses this script to ask the user a question, and the user replies, "I need information about my flight to New York."

[1931] The terminal's speech recognition device converts the user's speech into text data and sends it to the server.

[1932] The server uses natural language processing techniques to analyze the user's intent from the text data it receives.

[1933] Based on the user's request, the server consults the flight information database and retrieves the information "The flight to New York leaves from Gate 32 at 14:45".

[1934] The server generates information and sends it to the terminal, which then relays the information to the user.

[1935] Entertainment proposals and customization

[1936] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[1937] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[1938] The user replies, "I'd like to hear a joke."

[1939] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, it provides lighthearted jokes to help a stressed user relax.

[1940] Specific example

[1941] Airport reception

[1942] 1. The user approaches the robot and says, "Hello."

[1943] 2. The device detects approach using its sensors and recognizes faces using its cameras.

[1944] 3. The terminal asks, "In what language would you like us to guide you?"

[1945] 4. The user replies, "Please speak in English."

[1946] 5. The device analyzes the audio and notifies the server that it is in English.

[1947] 6. The device's emotion engine analyzes voice and facial expressions to recognize "anxiety."

[1948] 7. The server generates a script that asks "How can I assist you today?" and sends it to the terminal.

[1949] 8. The user replies, "I need information about my flight to New York."

[1950] 9. The device converts the audio to text and sends it to the server.

[1951] 10. The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1952] 11. The device conveys information to the user.

[1953] 12. The device offers a lighthearted joke to alleviate user anxiety.

[1954] Examples of prompts for generative AI models

[1955] 1. To the emotion engine: "Identify the user's current emotion based on their voice tone and facial expression data."

[1956] 2. To a natural language processing system: "Please analyze this text data and understand the user's intent."

[1957] 3. In response to an entertainment suggestion: "Generate jokes to help users relax when they are feeling stressed."

[1958] In this way, a system can be realized in which the user, terminal, server, and emotion engine work together to improve the quality of service provided to the user.

[1959] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1960] Step 1: User Recognition

[1961] The user approaches the device.

[1962] Input: User approach.

[1963] The device's sensor detects the user's approach.

[1964] The device uses its camera to capture the user's face using facial recognition technology (e.g., OpenCV, FaceNet).

[1965] Input: User's face image.

[1966] The terminal's voice recognition device asks the user, "Hello, in what language would you like me to guide you?"

[1967] Output: Face recognition results, language selection prompt.

[1968] Step 2: Language Selection

[1969] The user replies, "Please speak in English."

[1970] Input: User's voice.

[1971] The device analyzes this audio using its speech recognition system (e.g., Google Speech-to-Text) and selects "English" from its multilingual database.

[1972] The device sends the selected language information to the server.

[1973] Output: Language selection result (English), language information sent to the server.

[1974] Step 3: Emotion Recognition

[1975] The device's emotion engine (e.g., Microsoft Azure Emotion API) analyzes the user's voice and facial expressions.

[1976] Input: User's voice tone and facial expression data.

[1977] The device identifies the user's emotions from categories such as "excitement," "anxiety," and "joy."

[1978] Output: Emotion recognition result.

[1979] Step 4: Confirming User Intent

[1980] The server generates an English question script, "How can I assist you today?", and sends it to the terminal.

[1981] Input: Server entertainment planning.

[1982] The device asks the user a question.

[1983] The user replies, "I need information about my flight to New York."

[1984] Output: User request.

[1985] Step 5: Audio Data Analysis

[1986] The device's speech recognition system converts the user's speech into text data.

[1987] Input: User's spoken audio.

[1988] The terminal sends the generated text data to the server.

[1989] Output: Text data.

[1990] Step 6: Information Acquisition and Provision

[1991] The server analyzes the received text data using natural language processing techniques (e.g., GPT-4) to confirm the user's intent.

[1992] Input: Text data, natural language processing model.

[1993] The server accesses a flight information database (e.g., SQLite, MySQL) based on the user's request.

[1994] Output: Required information (flight information).

[1995] The server generates the information "The flight to New York leaves from Gate 32 at 14:45" and sends it to the terminal.

[1996] Output: A message containing information.

[1997] Step 7: Information Dissemination

[1998] The device communicates the information it has acquired to the user.

[1999] Input: Flight information.

[2000] Output: Voice message.

[2001] Step 8: Entertainment Suggestions and Customization

[2002] The server generates scripts for entertainment options (jokes, quizzes, music, etc.) and sends them to the terminal.

[2003] Input: Server entertainment planning and sentiment information.

[2004] The device suggests to the user, "Would you like to hear a joke or play a quick game while you wait?"

[2005] The user replies, "I'd like to hear a joke."

[2006] The device's emotion engine generates appropriate jokes based on the user's current emotions. For example, if the user is feeling stressed, it will provide lighthearted jokes to help them relax.

[2007] Output: Emotionally customized entertainment.

[2008] In this way, input, data processing, data calculation, and output are performed at each processing step, enabling personalized service for each user.

[2009] (Application Example 2)

[2010] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[2011] Traditional automated dialogue systems struggle to take user emotions into account, resulting in a limited user experience. Furthermore, insufficient multilingual support makes it difficult to serve users who speak different languages. This makes it challenging to enhance user satisfaction, particularly in virtual stores where natural dialogue and high-quality information delivery are essential.

[2012] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[2013] In this invention, the server includes means for recognizing a user, means for selecting the user's language, means for recognizing the user's emotions, means for providing information based on the input voice and emotions, and means for generating the entertainment using a generative artificial intelligence model. This enables the provision of personalized information and entertainment based on the user's emotions.

[2014] "Means of recognizing a user" refers to technologies that use cameras and voice recognition devices to detect and identify a user's face and voice.

[2015] "Means of selecting a language" refers to a technology that analyzes and selects the language used by the user via a speech recognition device.

[2016] "Methods for analyzing input speech" refer to technologies that convert voice input from a user into text data and understand its content.

[2017] "Means of recognizing emotions" refers to technologies that analyze a user's voice tone and facial expressions to identify the user's emotional state.

[2018] "Means of providing information" refers to technologies that search for relevant data based on user requests and provide that information to the user.

[2019] "Means of providing entertainment" refers to the technology that generates and delivers content that users can enjoy.

[2020] A "generative artificial intelligence model" is a technology that uses artificial intelligence algorithms to generate content tailored to the user.

[2021] A "prompt message" is an instruction message that is input into a generative artificial intelligence model to generate an appropriate response or content.

[2022] This invention relates to a system that combines means for recognizing emotions in user recognition, language selection, voice input analysis, information provision, and entertainment provision. The aim of this system is to improve the user experience in virtual stores.

[2023] 1. System Configuration

[2024] hardware

[2025] Camera: A device used to capture the user's face and perform facial recognition.

[2026] Speech recognition device: A device that captures the user's voice and performs language selection and speech analysis.

[2027] Server: A central device that processes and manages various types of data.

[2028] software

[2029] Face recognition technology: Uses ZaCV or similar face recognition technology.

[2030] Speech recognition technology: We use Google Speech-to-Text API and Amazon Transcribe.

[2031] Emotion recognition engine: Recognizes user emotions using Microsoft Azure Face API and other tools.

[2032] Natural language processing techniques: We use Google NLP API and spaCy.

[2033] Generative AI models: Generative AI models such as OpenAI GPT-3 are used.

[2034] 2. Data Calculation and Processing

[2035] User recognition and language selection

[2036] The device first uses a camera to capture the user's face and recognizes the user using facial recognition technology. Next, a voice recognition device captures the user's voice to determine which language to use. When the user responds to the question, "Hello, in what language would you like me to guide you?" with "English, please," the voice recognition technology analyzes the voice and selects the appropriate language.

[2037] emotion recognition

[2038] The device analyzes the user's voice tone and facial expressions to identify their emotions. For example, it can recognize emotions such as "joy" or "anxiety" from the user's voice tone and facial expressions. This process uses the Microsoft Azure Face API.

[2039] Providing information

[2040] The server receives a user request (e.g., "I am looking for a smart TV") and analyzes its content using natural language processing technology. It then retrieves the information the user is looking for from relevant databases, generates a specific response (e.g., "Here are the top 3 smart TVs available"), and sends it to the device.

[2041] Entertainment provider

[2042] The server uses a generative artificial intelligence model to generate entertainment options (e.g., jokes) based on the user's emotions. The terminal suggests these options, and if the user shows interest, it provides the generated entertainment content. For example, a user in a "relaxed" emotional state would be offered relaxing jokes.

[2043] Specific example

[2044] 1. The user accesses the virtual store. A camera recognizes the user, and a voice recognition device selects the language.

[2045] 2. Acquisition of text data: When the user asks "I am looking for a smart TV," speech recognition technology analyzes this and converts it into text.

[2046] 3. User emotion recognition: The emotion recognition engine recognizes "excitement" based on the user's voice and facial expressions.

[2047] 4. Information provision: The server generates information such as "Here are the top 3 smart TVs available" and provides it to the user through the terminal.

[2048] 5. Entertainment Suggestion: When the user is relaxed, the device will suggest, "Would you like to hear a joke?"

[2049] 6. Provide a joke: If the user answers "yes," the following joke will be provided: "Why don't scientists trust atoms? Because they make up everything!"

[2050] Example of a prompt

[2051] "A user has asked for information about smart TVs. Please provide the following information and a fun joke."

[2052] The user's emotional state is one of relaxation.

[2053] User question: I am looking for a smart TV.

[2054] Information provided: Here are the top 3 smart TVs available.

[2055] A funny joke: Why don't scientists trust atoms? Because they make up everything!

[2056] As described above, this system can improve the user experience in virtual stores by analyzing the user's voice and emotions and providing personalized information and entertainment.

[2057] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2058] Step 1:

[2059] The device uses a camera to capture the user's face. The input is video data captured by the camera, and the output is the user's face data identified via face recognition technology (OpenCV). Specifically, the camera captures the user's face in real time, and the face recognition algorithm analyzes this data to extract the user's facial features.

[2060] Step 2:

[2061] The device uses a speech recognition device to capture the user's voice and select a language. The input is voice data from the user, and the output is language data selected using speech recognition technology (Google Speech-to-Text API). Specifically, if the device asks the user, "Hello, in what language would you like me to guide you?", and the user replies, "English please," the speech recognition technology analyzes this voice and selects "English" as the language to use.

[2062] Step 3:

[2063] The device captures the user's voice tone and facial expression data and identifies emotions using an emotion recognition engine (Microsoft Azure Face API). The input is the user's voice and video data, and the output is analyzed emotion data (e.g., "excitement," "anxiety," "joy"). Specifically, it analyzes the user's voice tone and facial expressions in real time to identify their emotional state.

[2064] Step 4:

[2065] The server uses natural language processing technology (Google NLP API) to analyze user requests. The input is the user's utterance converted into text data by a speech recognition device, and the output is the analyzed user intent data. For example, if a user says "I need information about my flight to New York," this is analyzed to identify the intent "I am seeking flight information."

[2066] Step 5:

[2067] The server searches for and provides information based on the user's request. The input is the identified user's intent data, and the output is related information data (e.g., "The flight to New York leaves from Gate 32 at 14:45"). Specifically, the server accesses a flight information database, retrieves the necessary information, and formats it into text.

[2068] Step 6:

[2069] The server uses a generative artificial intelligence model (OpenAI GPT-3) to generate entertainment based on the user's emotions. The input is analyzed emotion data and user requests, and the output is generated entertainment content (e.g., jokes, music). Specifically, based on information that "the user wants to relax," the server generates jokes to help the user relax.

[2070] Step 7:

[2071] The terminal provides the user with generated information and entertainment content. The input is information data and entertainment content transmitted from the server, and the output is provided to the user in audio and video format. Specifically, the terminal will verbally announce the information, "The flight to New York leaves from Gate 32 at 14:45," and then suggest an entertainment option, "Would you like to hear a joke?"

[2072] As described above, each step works in conjunction to provide information and entertainment to users.

[2073] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[2074] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[2075] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[2076] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[2077] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[2078] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[2079] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[2080] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[2081] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[2082] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[2083] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[2084] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[2085] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[2086] 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.

[2087] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[2088] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[2089] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[2090] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[2091] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[2092] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[2093] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2094] The following is further disclosed regarding the embodiments described above.

[2095] (Claim 1)

[2096] Means of recognizing the user,

[2097] Means for selecting the user's language,

[2098] A means for analyzing the voice input from the user,

[2099] A means for providing information based on the input voice,

[2100] In addition to providing the aforementioned information, means of providing entertainment,

[2101] A system that includes this.

[2102] (Claim 2)

[2103] The system according to claim 1, characterized in that the means for recognizing the user includes a camera and a voice recognition device.

[2104] (Claim 3)

[2105] The system according to claim 1, characterized in that the means for providing the entertainment generates content using a generative artificial intelligence model.

[2106] "Example 1"

[2107] (Claim 1)

[2108] A means by which the terminal recognizes the user using a camera and a voice recognition device,

[2109] A means for automatically selecting the language spoken by the user,

[2110] A means for converting the user's spoken content into text data using a speech recognition device and sending it to a server,

[2111] A means for analyzing the aforementioned text data using natural language processing technology and obtaining the information requested by the user,

[2112] Means for transmitting the aforementioned information to a terminal and providing it to the user,

[2113] In addition to the aforementioned information provision, a means of providing entertainment using a generative artificial intelligence model,

[2114] A system that includes this.

[2115] (Claim 2)

[2116] The system according to claim 1, characterized in that the terminal for recognizing the user includes a camera and a voice recognition device.

[2117] (Claim 3)

[2118] The system according to claim 1, characterized in that it customizes entertainment content using the aforementioned generative artificial intelligence model.

[2119] "Application Example 1"

[2120] (Claim 1)

[2121] Means of recognizing the user,

[2122] Means for selecting the user's language,

[2123] A means for analyzing the voice input from the user,

[2124] A means for providing information based on the input voice,

[2125] In addition to providing the aforementioned information, means of providing entertainment,

[2126] A means of interacting with customers in a store using smart glasses,

[2127] The smart glasses include means for automatically selecting the user's language and displaying information to the user,

[2128] A means of offering users options such as coupons and games,

[2129] A system that includes this.

[2130] (Claim 2)

[2131] The system according to claim 1, characterized in that the means for recognizing the user includes a camera and a voice recognition device.

[2132] (Claim 3)

[2133] The system according to claim 1, characterized in that the means for providing the entertainment generates content using a generative artificial intelligence model.

[2134] "Example 2 of combining an emotion engine"

[2135] (Claim 1)

[2136] Means of recognizing the user,

[2137] Means for selecting the user's language,

[2138] A means for analyzing the voice input from the user,

[2139] A means for providing information based on the input voice,

[2140] The means for recognizing the user's emotions,

[2141] In addition to providing the aforementioned information, means of providing entertainment,

[2142] A means of customizing entertainment based on the aforementioned emotions,

[2143] A system that includes this.

[2144] (Claim 2)

[2145] The system according to claim 1, characterized in that the means for recognizing the user includes a camera and a voice recognition device.

[2146] (Claim 3)

[2147] The system according to claim 1, characterized in that the means for providing the entertainment generates content using a generative artificial intelligence model.

[2148] "Application example 2 of combining emotional engines"

[2149] (Claim 1)

[2150] Means of recognizing the user,

[2151] Means for selecting the user's language,

[2152] A means for analyzing the voice input from the user,

[2153] The means for recognizing the user's emotions,

[2154] A means for providing information based on the input voice and emotion,

[2155] In addition to providing the aforementioned information, means of providing entertainment,

[2156] A means for generating the aforementioned entertainment using a generative artificial intelligence model,

[2157] A system that includes this.

[2158] (Claim 2)

[2159] The system according to claim 1, characterized in that the means for recognizing the user includes a camera and a voice recognition device.

[2160] (Claim 3)

[2161] The system according to claim 1, characterized in that the means for providing the entertainment generates content using a generative artificial intelligence model and prompt sentences. [Explanation of Symbols]

[2162] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of recognizing the user, Means for selecting the user's language, A means for analyzing the voice input from the user, A means for providing information based on the input voice, In addition to providing the aforementioned information, means of providing entertainment, A system that includes this.

2. The system according to claim 1, characterized in that the means for recognizing the user includes a camera and a voice recognition device.

3. The system according to claim 1, characterized in that the means for providing the entertainment generates content using a generative artificial intelligence model.

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