system

Abstract

Provide a system. 【Solution means】 Means for a user to input a question by voice, Means for capturing voice input and sending it to the server, Means for the server to convert voice data into text data, Means for analyzing text data to generate an appropriate answer, Means for converting the generated answer text into voice data, Means for sending voice data to the terminal, Means for the terminal to play the voice data and the 3D hologram to display the answer, A system including.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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 recent years, while various products and services have diversified in response to consumer needs, how to improve the quality of customer service has become an issue. In conventional face-to-face customer service, responses are often standardized, and it is difficult to provide detailed explanations and responses according to individual needs. Also, in remote environments and stores, it is difficult to provide satisfactory customer service to all customers with limited resources. Furthermore, in general chatbots and voice assistants, due to the lack of visual elements, it is difficult to provide an interface that is easy for users to understand and friendly. As a result, the improvement of the user experience is hindered. The present invention aims to solve these problems and provide an effective customer service system that combines vision and voice.

Means for Solving the Problems

[0005] This invention provides a system that includes means for a user to input a question by voice, means for capturing the voice input and sending it to a server, means for the server to convert the voice data into text data, means for analyzing the text data to generate an appropriate answer, means for converting the generated answer text into voice data, means for sending the voice data to a terminal, and means for the terminal to play the voice data and for a 3D hologram to display the answer. As a result, users can receive appropriate answers from generative artificial intelligence in both audio and visual formats simply by inputting a question by voice. In particular, by using generative artificial intelligence as a means for generating answers to questions, detailed and specific answers are provided, and by using speech recognition artificial intelligence to convert the voice data into text data, rapid and accurate analysis becomes possible. The introduction of this system dramatically improves the quality of the user experience and enables flexible customer service that responds to diverse needs.

[0006] A "user" is the entity that operates the system and sends questions or requests.

[0007] A "terminal" is a device that allows a user to input voice data and send it to a server, and also has the function of displaying 3D holograms.

[0008] A "server" is a central processing unit that performs speech recognition, text analysis, response generation, and speech data conversion, and is responsible for processing the speech data sent from the terminal.

[0009] "Voice data" refers to the digital representation of voice information entered by a user into a device.

[0010] "Text data" refers to character information obtained by analyzing audio data.

[0011] "Generative artificial intelligence" refers to systems that have algorithms or programs that generate appropriate answers based on input text data or questions.

[0012] "Speech recognition artificial intelligence" refers to a system that possesses algorithms and programs that analyze speech data and convert it into text data.

[0013] A "3D hologram" is a technology that displays visually three-dimensional characters or images, providing users with visual feedback.

[0014] "Capture" is the process by which a device uses its microphone to capture audio data and temporarily store it.

[0015] "Transmitting audio data" refers to the process of transferring audio data from a terminal to a server over a network.

[0016] "Audio data playback" refers to the process by which a device plays back received audio data using a speaker or other means, providing audio information to the user.

[0017] An "effective customer service system combining visuals and audio" is a system that uses 3D holograms and audio data to provide users with intuitive and user-friendly feedback and responses. [Brief explanation of the drawing]

[0018] [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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It 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 an 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 an emotion engine is combined.

Modes for Carrying Out the Invention

[0019] 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.

[0020] First, the language used in the following description will be explained.

[0021] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] 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.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] The present invention is a system in which a user inputs a question by voice, which is then processed using voice AI and generative AI, and the results are provided visually and audibly as a 3D hologram. The system of the present invention consists of the following components: a user, a terminal, and a server.

[0040] Components and operation

[0041] User

[0042] The user operates the system and inputs their questions by voice into the terminal. This voice input initiates the system's operation.

[0043] terminal

[0044] The terminal is equipped with a microphone for user voice input and a network interface for capturing voice data and sending it to the server. It also has a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[0045] 1. Capture audio data

[0046] 2. Sending audio data to the server

[0047] 3. Playback of audio data received from the server.

[0048] 4. Display of 3D holograms

[0049] server

[0050] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[0051] 1. Speech recognition: Converts speech data into text data.

[0052] 2. Question Analysis: Analyze text data to understand the user's questions.

[0053] 3. Answer generation: Generator AI is used to generate appropriate answers.

[0054] 4. Speech Conversion: Converts the generated response text into audio data.

[0055] 5. Sending audio data to the terminal

[0056] Specific example

[0057] Example 1: Asking about the camera function of a smartphone

[0058] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[0059] 2. The device captures this audio and sends it to the server.

[0060] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0061] 4. The server uses generative AI to analyze this text and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0062] 5. The server converts this response text into audio data using voice AI and sends the audio data to the terminal.

[0063] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0064] This process allows users to obtain sufficient information through high-quality visual and audio. This enables users to receive specific and easy-to-understand instructions on how to use the product or service.

[0065] The following describes the processing flow.

[0066] Step 1:

[0067] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[0068] Step 2:

[0069] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[0070] Step 3:

[0071] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[0072] Step 4:

[0073] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[0074] Step 5:

[0075] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the intent of the question. It then generates an answer to the user's question.

[0076] Step 6:

[0077] The server uses the response calculated by the generative AI to convert the text into audio data. Specifically, it generates audio data that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0078] Step 7:

[0079] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[0080] Step 8:

[0081] The device plays the received audio data and provides audio feedback to the user through its speaker. Simultaneously, a 3D hologram display device projects a hologram character that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0082] This allows users to obtain specific answers to their questions visually and audibly. Because this system can respond quickly and accurately to a wide range of questions, it can significantly improve the user experience.

[0083] (Example 1)

[0084] 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."

[0085] Conventional information provision systems lack the means to provide visual and intuitive answers to questions entered by users via voice. Furthermore, there is a need for a system that can efficiently process the voice data entered by users accurately and quickly, generate appropriate answers, and provide them. Moreover, a system capable of providing highly accurate and appropriate answers even to complex questions is required.

[0086] 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.

[0087] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into voice data, and means for transmitting the voice data and 3D hologram data to the terminal. This makes it possible for a user to simply input a question by voice and receive a highly accurate visual and audible response to that question.

[0088] "Voice input" refers to the user using their voice to communicate questions or instructions to the device.

[0089] "Capture" refers to the electronic acquisition of audio data and other input data.

[0090] A "server" refers to a centralized computer system that performs functions such as processing, analyzing, and generating responses for audio data.

[0091] "Voice data" refers to data that records the user's voice in digital format.

[0092] "Text data" refers to data that includes character information converted from audio data.

[0093] "Generative artificial intelligence" refers to artificial intelligence technology used to generate appropriate answers to questions.

[0094] "Speech recognition artificial intelligence" refers to artificial intelligence technology used to convert speech data into text data.

[0095] "Speech conversion" refers to the process of converting text data into audio data.

[0096] "3D hologram" refers to a technology that projects three-dimensional, stereoscopic images.

[0097] A "terminal" refers to a device used by a user to input voice and to display voice data and 3D holograms.

[0098] This invention is a system in which a user inputs a question by voice, and the system utilizes speech recognition artificial intelligence and generative artificial intelligence to provide an answer to that question in the form of both voice and a 3D hologram. The system consists of a user, a terminal, and a server.

[0099] System Components

[0100] User

[0101] The user speaks their question into the device's microphone. This voice input initiates the system's operation. As a concrete example, consider a scenario where the user says, "Please tell me how to use the camera function on this smartphone."

[0102] terminal

[0103] The device is equipped with a microphone to receive the user's voice, a network interface (e.g., Wi-Fi or 4G / 5G) to send the captured audio data to the server, a speaker to play the audio data received from the server, and a 3D hologram projection device to visually display the response.

[0104] server

[0105] The server hosts speech recognition artificial intelligence (e.g., Google® Cloud Speech-to-Text and AWS® Transcribe) and generative artificial intelligence (e.g., OpenAI® GPT-3® and BERT) to process the received audio data. The server provides the following functions:

[0106] 1. Speech Recognition: Converts speech data received from the device into text data.

[0107] 2. Question Analysis: Analyze the converted text data to understand the user's question.

[0108] 3. Answer generation: Generate appropriate answers to user questions.

[0109] 4. Speech Conversion: Convert the generated response text into audio data.

[0110] 5. Data transmission: The generated audio data and 3D hologram data are sent to the terminal.

[0111] Specific example

[0112] Example 1: Asking about the camera function of a smartphone

[0113] 1. The user asks into the microphone, "How do I use the camera function on this smartphone?"

[0114] 2. The device captures this audio and sends it to the server.

[0115] 3. The server uses speech recognition artificial intelligence to convert the voice data into text data and generates the text message, "Please tell me how to use the camera function on this smartphone."

[0116] 4. The server uses generative artificial intelligence to analyze the text data and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0117] 5. The server converts this response text into audio data and sends the audio data and 3D hologram data to the terminal.

[0118] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0119] Example of a prompt

[0120] User: "How do I use the camera function on this smartphone?"

[0121] System: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0122] This system allows users to quickly obtain high-quality visual and auditory information, making it easy to understand how to use products and services.

[0123] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0124] Step 1:

[0125] The user speaks a question into the device's microphone. For example, they might ask, "How do I use the camera function on this smartphone?" This voice input initiates the system's operation.

[0126] Step 2:

[0127] The device captures the user's voice using its microphone. Specifically, it converts the voice into digital format as audio data.

[0128] Input: User's voice

[0129] Operation: Capture and digitize audio data using a microphone.

[0130] Output: Digital audio data

[0131] Step 3:

[0132] The device transmits the captured audio data to the server via a network interface (e.g., Wi-Fi or 4G / 5G).

[0133] Input: Digital audio data

[0134] Operation: Send voice data using the network interface.

[0135] Output: Audio data sent to the server

[0136] Step 4:

[0137] The server converts the received audio data into text data using speech recognition artificial intelligence (for example, Google Cloud Speech-to-Text or AWS Transcribe).

[0138] Input: Audio data sent to the server

[0139] Operation: Convert audio data to text data using speech recognition AI.

[0140] Output: Text data (Example: "Please tell me how to use the camera function on this smartphone.")

[0141] Step 5:

[0142] The server uses generative artificial intelligence (such as OpenAI GPT-3 or BERT) to analyze text data and understand the user's question. It then extracts key keywords and the gist of the question.

[0143] Input: Text data obtained from speech recognition

[0144] Operation: Use generative AI to analyze text data and understand the intent of the question.

[0145] Output: Understanding the question and extracting necessary information

[0146] Step 6:

[0147] The server uses generative AI to generate the best possible answer to a question. For example, it can generate text explaining "how to use the camera function on a smartphone."

[0148] Input: Understanding the question and related information

[0149] Operation: Generate response text using a generative AI.

[0150] Output: Generated answer text (Example: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen.")

[0151] Step 7:

[0152] The server converts the generated response text into speech data using speech AI (for example, Google Text-to-Speech or Amazon Polly).

[0153] Input: Generated response text

[0154] Operation: Convert text data to speech data using voice AI.

[0155] Output: Generated audio data

[0156] Step 8:

[0157] The server sends the generated audio data and 3D hologram data to the terminal.

[0158] Input: Generated audio data and 3D hologram data

[0159] Operation: Send data to the terminal using a data transmission protocol (e.g., HTTPS).

[0160] Output: Audio data and 3D hologram data sent to the terminal.

[0161] Step 9:

[0162] The device plays the received audio data through its speaker. Specifically, it explains, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0163] Input: Audio data sent from the server

[0164] Operation: Play audio data through the speaker.

[0165] Output: Played audio

[0166] Step 10:

[0167] The device displays the received 3D hologram data using a hologram projection device. Specifically, it displays a hologram that visually shows the operating procedures for the smartphone.

[0168] Input: 3D hologram data sent from the server

[0169] Operation: Display data using a hologram projector.

[0170] Output: Displayed 3D hologram

[0171] This process allows users to intuitively obtain information from both audio and visual sources.

[0172] (Application Example 1)

[0173] 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."

[0174] In physical stores, there is a lack of means for customers to quickly and visually obtain information about products. Traditional methods require customers to ask store staff directly or read product labels, which are time-consuming and may not provide satisfactory information. Furthermore, in today's world where contactless interactions are required, there is a need for more efficient and hygienic means of providing information. This invention aims to solve these problems and provide a system that delivers information to customers in an intuitive and visual manner.

[0175] 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.

[0176] In this invention, the server includes means for the user to input a question by voice, means for capturing the voice input and sending it to the server, means for the server to convert the voice data into text data, means for analyzing the text data to generate an appropriate answer, means for converting the generated answer text into voice data, means for sending the voice data to a terminal, means for the terminal to play the voice data and for a 3D hologram to display the answer, means for analysis to provide product information based on the user's question, and means for visually presenting the analysis results as a 3D hologram. This enables customers to instantly obtain product information through voice input in a physical store and to understand it visually through a 3D hologram.

[0177] A "user" is a person who operates the system and uses voice input.

[0178] "Voice input" refers to the act of a user giving questions or instructions to a system by voice through a microphone.

[0179] "Capture" refers to the process of acquiring audio input in digital format and saving it as data.

[0180] A "server" is a central control unit that processes audio data, converts it to text data, and generates responses using generative artificial intelligence.

[0181] "Text data" refers to the representation of voice input as text information through speech recognition.

[0182] "Generative artificial intelligence" is a technology that uses natural language processing based on input text data to create appropriate answers to questions.

[0183] "Answer text" refers to the textual information generated by a generative artificial intelligence system in response to a user's question.

[0184] "Audio data" refers to audio information generated from text data using speech synthesis technology.

[0185] A "terminal" is a device used by a user, and includes equipment such as a microphone, speaker, and 3D hologram projection device.

[0186] "Playback" is the process of outputting audio data as actual sound through a speaker.

[0187] A "3D hologram" is a technology that visually presents the answer content as a three-dimensional, stereoscopic image.

[0188] "Product information" refers to detailed information about products sold in physical stores, such as their characteristics, usage instructions, stock availability, and price.

[0189] "Analysis" is the process of processing data based on user input to generate appropriate answers or information.

[0190] "Presentation" refers to the act of visually showing the analysis results to the user.

[0191] Embodiments for carrying out this invention are described below.

[0192] The system of this invention allows users to ask questions via voice input and provides visual answers to those questions in the form of 3D holograms. The main components consist of a user, a terminal, and a server.

[0193] Hardware configuration

[0194] 1. User's terminal

[0195] Smart glasses (with HUD function), smartphone, or tablet

[0196] Microphone and speaker

[0197] 3D hologram projection device (e.g., HoloLens®)

[0198] 2. Server

[0199] Speech recognition API (e.g., Google Cloud Speech-to-Text)

[0200] Generative AI (e.g., OpenAI GPT-4(registered trademark))

[0201] 3D hologram generation software (e.g., Unity 3D)

[0202] Database (e.g., Firebase)

[0203] Software Processing

[0204] From voice input to text conversion

[0205] 1. The user asks a question into the microphone of the smart glasses.

[0206] For example, a user might ask, "What material is this sofa made of?"

[0207] Capture and transmit audio data

[0208] 2. The device captures the user's voice and sends it to the server in digital format.

[0209] Speech recognition and analysis

[0210] 3. The server uses the Google Cloud Speech-to-Text API to convert the audio data into text data. The text data generated is "What material is this sofa made of?".

[0211] Question analysis and answer generation

[0212] 4. The server inputs text data into OpenAI GPT-4 and uses a generative AI to analyze the question content.

[0213] The generative AI will generate the answer "The materials of this sofa are high-quality leather and memory foam" to this question.

[0214] Voice conversion and data transmission

[0215] 5. The server converts the generated response text into audio data using the Google Cloud Text-to-Speech API and sends this audio data to the device.

[0216] 3D hologram display

[0217] 6. The terminal plays the received audio data and uses a 3D hologram projection device to visually display the response, "The material of this sofa is high-quality leather and memory foam."

[0218] Specific example

[0219] Consider a scenario where a user is in a furniture store, wearing smart glasses, and asks a question by voice: "What material is this sofa made of?" The smart glasses capture this question and send it to a server. The server uses a speech recognition API to convert the question into text, and then uses generative AI to analyze it and generate an appropriate answer. This answer is sent to the device as audio data and 3D hologram data, and displayed in the user's field of view.

[0220] Example of a prompt

[0221] User: Voice input "What material is this sofa made of?"

[0222] System: Analyzing...

[0223] System: Answer: "The materials for this sofa are high-quality leather and memory foam."

[0224] Display: 3D hologram visually describes the details of the sofa.

[0225] The system of this invention enables users to quickly and intuitively obtain and visually understand product information within a physical store. This results in more efficient and effective information delivery compared to conventional methods.

[0226] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0227] Step 1:

[0228] The user performs voice input. The user speaks their question into the microphone of the smart glasses. For example, they might ask, "What material is this sofa made of?"

[0229] Input: User's voice question

[0230] Output: Captured audio data

[0231] Step 2:

[0232] The device captures audio data and sends it to the server. The smart glasses (device) capture the user's voice digitally through the microphone and send it to the server via the network.

[0233] Input: Captured audio data

[0234] Output: Audio data sent to the server

[0235] Step 3:

[0236] The server converts the audio data into text data. The server uses the Google Cloud Speech-to-Text API to convert the transmitted audio data into text data. At this point, the audio data becomes the text "What material is this sofa made of?".

[0237] Input: Audio data sent to the server

[0238] Output: Text data

[0239] Step 4:

[0240] The server analyzes the text data and generates an answer. The server uses OpenAI GPT-4 to analyze the converted text data and generate an appropriate answer based on the user's question. In this case, it generates the answer, "The material of this sofa is high-quality leather and memory foam."

[0241] Input: Text data

[0242] Output: Answer text

[0243] Step 5:

[0244] The server converts the generated response text into audio data. The server uses the Google Cloud Text-to-Speech API to convert the generated response text into audio data. At this time, the response text "This sofa is made of high-quality leather and memory foam." is converted into audio data.

[0245] Input: Answer text

[0246] Output: Audio data

[0247] Step 6:

[0248] The server sends audio data to the terminal. The server sends the generated audio data to the terminal via the network.

[0249] Input: Audio data

[0250] Output: Audio data sent to the terminal

[0251] Step 7:

[0252] The device plays the received audio data and displays a 3D hologram. The device (smart glasses) plays the received audio data and simultaneously uses a 3D hologram projector to visually display the answer. In this case, the audio plays "The material of this sofa is high-quality leather and memory foam," and the 3D hologram visually presents details about the sofa's materials.

[0253] Input: Audio data sent to the terminal

[0254] Output: Played audio data and displayed 3D hologram

[0255] 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.

[0256] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[0257] Components and operation

[0258] User

[0259] The user operates the system and inputs questions by voice into a terminal. The user's emotions are also analyzed through this voice input.

[0260] terminal

[0261] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[0262] 1. Capture audio data

[0263] 2. Sending audio data to the server

[0264] 3. Playback of audio data received from the server.

[0265] 4. Display of 3D holograms

[0266] server

[0267] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[0268] 1. Speech recognition: Converts speech data into text data.

[0269] 2. Question Analysis: Analyze text data to understand the user's questions.

[0270] 3. Answer generation: Generator AI is used to generate appropriate answers.

[0271] 4. Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[0272] 5. Speech Conversion: Converts the generated response text into audio data.

[0273] 6. Sending audio data to the terminal

[0274] Emotional Engine

[0275] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram.

[0276] Specific example

[0277] Example 1: Asking about the camera function of a smartphone

[0278] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[0279] 2. The device captures this audio and sends it to the server.

[0280] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0281] 4. The server passes the converted text data to a generative AI, which analyzes the intent of the question and generates an answer.

[0282] 5. The server analyzes the user's emotions from the voice data using an emotion engine and generates emotion data such as "interested" and "confused".

[0283] 6. The server converts the generated response text into voice data and sends the voice data and emotion data to the terminal.

[0284] 7. The terminal plays the voice data and provides feedback to the user through the speaker. Also, based on the emotion data, it changes the expression of the 3D hologram and answers in a friendly tone according to the user's emotion, such as "To use the camera function of the smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0285] As a result, the user can obtain a specific and emotion - considerate answer to the question. By combining the emotion engine, a more personalized user experience is realized.

[0286] The following explains the processing flow.

[0287] Step 1:

[0288] The user inputs a question vocally towards the microphone of the terminal. Specifically, the user says, "Please teach me how to use the camera function of this smartphone."

[0289] Step 2:

[0290] The terminal captures the voice data from the microphone. This voice data is temporarily stored in the terminal in digital format.

[0291] Step 3:

[0292] The terminal sends the captured voice data to the server. Specifically, it converts the voice data into an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[0293] Step 4:

[0294] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[0295] Step 5:

[0296] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the user's question. It then generates an answer to the user's question.

[0297] Step 6:

[0298] The server uses the answer calculated by the generative AI to re-analyze the text and verify that the answer is appropriate. At this point, the text "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is obtained.

[0299] Step 7:

[0300] The server converts this response text into audio data. Specifically, it uses a speech synthesis engine to convert the text into speech and generates the audio data, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0301] Step 8:

[0302] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[0303] Step 9:

[0304] The server starts the emotion engine together with the voice data and analyzes the emotion from the user's voice data. Specifically, it generates emotion data such as "interest" and "confusion" by using information such as the tone, speed, and rhythm of the voice.

[0305] Step 10:

[0306] The server also transmits the emotion data to the terminal simultaneously with the voice data.

[0307] Step 11:

[0308] The terminal plays back the received voice data and provides feedback as voice to the user through the speaker. At the same time, it changes the expression of the 3D hologram based on the emotion data. For example, when the user is confused, the hologram character talks in a friendly expression and tone, saying "To use the camera function of the smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0309] Through this process, the user can obtain a specific and emotion - considerate answer to the question visually and audibly. The whole system is designed to cooperate smoothly and improve the user experience to the extreme.

[0310] (Example 2)

[0311] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0312] Conventional voice dialogue systems are required not only to generate appropriate responses to voice input, but also to recognize the user's emotions and provide feedback based on those emotions. However, previous systems have been unable to recognize emotions, resulting in a limited user experience and difficulty in providing personalized responses. Furthermore, while it is expected that using 3D holograms as visual feedback will further improve user interaction, this has also not yet been realized.

[0313] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for recognizing the user's emotions and generating emotion data, means for converting the generated response text into voice data, and means for transmitting the voice data and emotion data to the terminal. This makes it possible to provide personalized responses based on the user's emotions as feedback in voice and 3D hologram form.

[0314] A "user" is a person who uses voice input to ask questions to the system.

[0315] A "terminal" is a device that captures the user's voice and sends it to a server, and uses the received voice data and emotion data to provide feedback to the user.

[0316] A "server" is a computer system that converts voice data into text data, analyzes it to generate appropriate responses, and further recognizes and analyzes the user's emotions.

[0317] "Voice data" refers to information that represents a user's voice input in digital format.

[0318] "Text data" refers to data represented as characters converted by speech recognition, and includes the content of the user's question.

[0319] "Generative artificial intelligence" is an artificial intelligence technology that analyzes text data to generate appropriate responses.

[0320] An "emotion engine" is software or a system that recognizes a user's emotions from voice data and generates emotion data.

[0321] "Emotional data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0322] "Speech recognition artificial intelligence" is an artificial intelligence technology that converts speech data into text data.

[0323] A "3D hologram" is a device or technology that provides visual feedback to users by displaying three-dimensional images based on emotional data.

[0324] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[0325] User

[0326] The user operates the system and inputs their questions by voice into the terminal. For example, they might say to their smartphone, "Please tell me how to use the camera function on this smartphone."

[0327] terminal

[0328] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to a server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms. Specific processing includes the following:

[0329] Microphone: Records the user's voice and captures it as digital audio data.

[0330] Network interface: Sends captured audio data to the server.

[0331] Speaker: Plays audio data received from the server.

[0332] Hologram projection device: Adjusts and projects 3D holographic facial expressions based on emotional data.

[0333] server

[0334] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specific processing includes the following:

[0335] Speech recognition: The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert speech data into text data.

[0336] Question analysis: Analyzes the converted text data to understand the user's question.

[0337] Answer generation: Generative artificial intelligence (e.g., a generative AI model) is used to generate appropriate answers.

[0338] Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[0339] Speech conversion: The generated response text is converted into speech data using speech synthesis technology.

[0340] Data transmission: The generated voice data and emotion data are sent to the device.

[0341] Emotional Engine

[0342] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This allows the user's emotions to be reflected in voice responses and 3D holograms.

[0343] Specific example

[0344] Example 1: When asking about the camera function of a smartphone

[0345] 1. The user asks, "How do I use the camera function on this smartphone?" into the device's microphone.

[0346] 2. The device captures this audio and sends it to the server.

[0347] 3. The server uses speech recognition artificial intelligence to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0348] 4. The server analyzes the text data using a generative AI model, understands the intent of the question, and generates an answer. For example, it might generate an answer such as, "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0349] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[0350] 6. The server converts the response text into audio data and sends the audio data and sentiment data to the terminal.

[0351] 7. The device plays audio data through its speaker and displays 3D holographic facial expressions based on emotional data. For example, it might respond in a friendly tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0352] Examples of prompts for generative AI models

[0353] Prompt: "How would you explain the camera function of a smartphone if a user asked about it?"

[0354] Expected output: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0355] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0356] Step 1:

[0357] The user inputs the question by voice. The user speaks the question into the device's microphone. For example, they might say, "Please tell me how to use the camera function on this smartphone." The input is recorded as voice data on the device.

[0358] Step 2:

[0359] The terminal captures audio data and sends it to the server. The terminal is equipped with a microphone for recording audio and a function to capture audio data in digital format. The captured audio data is sent to the server via the network interface. The input is audio data, and the output is the audio data sent to the server.

[0360] Step 3:

[0361] The server converts the audio data into text data. The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert the audio data into text data. The input is the captured audio data, and the output is text data. For example, the audio "Please tell me how to use the camera function on this smartphone" is converted to the text "Please tell me how to use the camera function on this smartphone".

[0362] Step 4:

[0363] The server analyzes text data and generates appropriate answers. The server uses generative artificial intelligence (e.g., a generative AI model) to analyze the converted text data and generate appropriate answers. The input is text data, and the output is the answer text. For example, in response to the question "How do I use the camera function on this smartphone?", it generates answer text such as "To use the camera function on this smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0364] Step 5:

[0365] The server recognizes the user's emotions and generates emotion data. Using the emotion engine installed on the server, it analyzes the user's emotions from the audio data. The input is audio data, and the output is emotion data. For example, it can recognize emotions such as "interested" or "confused" from the user's voice.

[0366] Step 6:

[0367] The server converts the generated response text into audio data. The server uses speech synthesis technology (e.g., speech synthesis AI) to convert the generated response text into audio data. The input is the response text, and the output is audio data. For example, the text "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen." will be converted into audio data.

[0368] Step 7:

[0369] The server sends voice data and emotion data to the terminal. The server sends the generated voice data and emotion data to the terminal via the network interface. The input is voice data and emotion data, and the output is the data sent to the terminal.

[0370] Step 8:

[0371] The device plays audio data and provides feedback via a 3D hologram. The device plays the received audio data through its speaker and further changes the expression of the 3D hologram based on emotion data. The input is audio data and emotion data received from the server, and the output is audio feedback and visual feedback. For example, the audio "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is played in a friendly tone, and the expression of the 3D hologram is displayed in a friendly manner.

[0372] (Application Example 2)

[0373] 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 device 14 will be referred to as the "terminal."

[0374] While there is a need to efficiently learn and implement maintenance and operating procedures within factories, conventional manuals and simple voice guidance systems struggle to provide flexible responses tailored to user understanding and on-site conditions. Furthermore, they often lack appropriate feedback that reflects user emotions and comprehension, potentially leading to decreased efficiency and safety in actual operations. To address these challenges, a system is needed that can recognize user emotions and provide personalized guidance tailored to individual situations.

[0375] 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.

[0376] In this invention, the server includes means for converting audio data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into audio data, means for analyzing the user's emotions from the audio data using an emotion engine, and means for changing the tone of the response and the facial expressions of the 3D hologram according to the user's emotions. This enables personalized maintenance and operation procedure guidance that takes into account the user's emotions and level of understanding.

[0377] A "user" refers to a person who operates this system and inputs questions using voice input.

[0378] "Voice input" refers to the act of a user using a microphone to communicate questions or instructions to a system by voice.

[0379] "Capture" refers to the process of taking in and recording audio input.

[0380] A "server" refers to a remote computing device that processes audio data, converts it to text data, analyzes questions, generates answers, and performs sentiment analysis.

[0381] "Voice data" refers to the captured voice input of the user.

[0382] "Text data" refers to audio data converted into written text.

[0383] "Generative artificial intelligence" refers to advanced machine learning models that analyze questions and generate appropriate answers.

[0384] "Speech recognition artificial intelligence" refers to a machine learning model used to convert speech data into text data.

[0385] An "emotion engine" refers to a system that analyzes emotions from a user's voice data and generates emotional data.

[0386] A "3D hologram" refers to a three-dimensional visual representation displayed in space.

[0387] "Response tone" refers to the emotional expression used in the generated voice response.

[0388] This invention is a system for efficiently learning and implementing maintenance and operating procedures within a factory. The system consists of user, terminal, server, and emotion engine components. The details of each component and their specific operation are described below.

[0389] User

[0390] The user operates the system and inputs questions by voice into the terminal. For example, the user might say to the terminal, "Please tell me the maintenance procedure for this machine." This voice input initiates the system's operation.

[0391] terminal

[0392] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also has a speaker and a hologram projection device for playing back the voice data received from the server and the 3D hologram.

[0393] Typical hardware examples include the following:

[0394] Microphone: A highly sensitive voice input device.

[0395] Speaker: A device that reproduces sound clearly.

[0396] Hologram projector: Displays 3D holograms.

[0397] server

[0398] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specifically, it uses the following software services:

[0399] Speech Recognition AI: Uses Microsoft® Azure® Cognitive Services to convert speech data into text data.

[0400] Generative AI: Uses OpenAI GPT-4 to analyze text data and generate appropriate responses.

[0401] Emotion Engine: Analyzes emotions from the user's voice and generates emotion data.

[0402] Specific server processing:

[0403] 1. Speech Recognition: The server uses speech recognition AI to convert speech data into text data. Example: "Please use Azure's speech recognition API to convert this speech data to text."

[0404] 2. Question Analysis and Answer Generation: Use a generative AI model to analyze text data and generate appropriate answers. Example: "Using GPT-4, analyze the following question and generate appropriate maintenance procedures: 'Please tell me the maintenance procedures for this machine.'"

[0405] 3. Emotion Recognition: Use an emotion engine to analyze the user's emotions from voice data and generate emotion data. Example: "Analyze the user's emotions (e.g., interested, confused) from their voice data and generate emotion data."

[0406] Emotional Engine

[0407] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This generated emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram. For example, if the user is confused, the system will respond in a more polite and friendly tone. Specifically, the generated response text is converted into voice data, and the tone is adjusted based on the emotion data.

[0408] Specific example

[0409] For example, if a user asks, "Please tell me the maintenance procedure for this machine," the system will operate as follows:

[0410] 1. The user asks a question into the device's microphone.

[0411] 2. The device captures this audio and sends it to the server.

[0412] 3. The server uses speech recognition AI to convert the audio data into text and analyze the content of the question.

[0413] 4. Generative AI generates appropriate answers based on the analysis results.

[0414] 5. The emotion engine analyzes the user's emotions and adjusts the tone of responses and the facial expressions of the hologram accordingly.

[0415] 6. The device plays the generated audio data and displays the hologram.

[0416] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

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

[0418] Step 1:

[0419] The user enters the question by voice.

[0420] The user operates the system and inputs their question by voice into the device's microphone. This voice input initiates the system's processing.

[0421] Input: User's voice

[0422] Output: Captured audio data

[0423] Step 2:

[0424] The device captures audio and sends it to the server.

[0425] The device captures the user's voice using a microphone and sends this audio data to the server via a network interface.

[0426] Input: Captured audio data

[0427] Output: Audio data sent to the server

[0428] Step 3:

[0429] The server converts the audio data into text data.

[0430] The server uses speech recognition AI (e.g., Microsoft Azure Cognitive Services) to convert the audio data into text data. The specific prompt is, "Please use the Azure speech recognition API to convert this audio data to text."

[0431] Input: Audio data sent to the server

[0432] Output: Converted text data

[0433] Step 4:

[0434] The server analyzes the text data and generates the appropriate response.

[0435] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze text data and generate appropriate responses. The specific prompt is: "Use GPT-4 to analyze the following question and generate appropriate maintenance instructions: 'Please tell me the maintenance instructions for this machine.'"

[0436] Input: Converted text data

[0437] Output: Generated answer text

[0438] Step 5:

[0439] The server analyzes the user's emotions and generates emotional data.

[0440] The server uses an emotion engine to analyze the user's emotions from voice data and generate emotion data. Specifically, it analyzes characteristics such as the tone, volume, and speed of the user's voice. Example: "Analyze the user's voice data to determine their emotions (e.g., interested, confused) and generate emotion data."

[0441] Input: Audio data

[0442] Output: Sentiment data

[0443] Step 6:

[0444] The server converts the response text into audio data and adjusts the tone based on sentiment data.

[0445] The server converts the generated response text into audio data and adjusts the tone based on sentiment data. This sentiment data helps create user-friendly feedback, such as a more approachable or polite tone.

[0446] Input: Generated response text, sentiment data

[0447] Output: Voice data adjusted based on emotion

[0448] Step 7:

[0449] The server sends the audio data to the terminal.

[0450] The server sends the response audio data and emotion data to the terminal via the network interface.

[0451] Input: Voice data adjusted based on emotion

[0452] Output: Audio data sent to the terminal

[0453] Step 8:

[0454] The device plays audio data and displays a 3D hologram.

[0455] The device plays audio data received from the server through its speaker and displays a 3D hologram based on the emotional data. For example, if the user is in a state of "confusion," the hologram will display a more friendly expression and respond in a more polite voice.

[0456] Input: Voice data and emotion data sent to the device.

[0457] Output: Audio and 3D hologram played for the user

[0458] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] [Second Embodiment]

[0463] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0464] 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.

[0465] 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).

[0466] 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.

[0467] 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.

[0468] 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).

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] 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".

[0475] The present invention is a system in which a user inputs a question by voice, which is then processed using voice AI and generative AI, and the results are provided visually and audibly as a 3D hologram. The system of the present invention consists of the following components: a user, a terminal, and a server.

[0476] Components and operation

[0477] User

[0478] The user operates the system and inputs their questions by voice into the terminal. This voice input initiates the system's operation.

[0479] terminal

[0480] The terminal is equipped with a microphone for user voice input and a network interface for capturing voice data and sending it to the server. It also has a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[0481] 1. Capture audio data

[0482] 2. Sending audio data to the server

[0483] 3. Playback of audio data received from the server.

[0484] 4. Display of 3D holograms

[0485] server

[0486] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[0487] 1. Speech recognition: Converts speech data into text data.

[0488] 2. Question Analysis: Analyze text data to understand the user's questions.

[0489] 3. Answer generation: Generator AI is used to generate appropriate answers.

[0490] 4. Speech Conversion: Converts the generated response text into audio data.

[0491] 5. Sending audio data to the terminal

[0492] Specific example

[0493] Example 1: Asking about the camera function of a smartphone

[0494] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[0495] 2. The device captures this audio and sends it to the server.

[0496] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0497] 4. The server uses generative AI to analyze this text and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0498] 5. The server converts this response text into audio data using voice AI and sends the audio data to the terminal.

[0499] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0500] This process allows users to obtain sufficient information through high-quality visual and audio. This enables users to receive specific and easy-to-understand instructions on how to use the product or service.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[0504] Step 2:

[0505] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[0506] Step 3:

[0507] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[0508] Step 4:

[0509] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[0510] Step 5:

[0511] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the intent of the question. It then generates an answer to the user's question.

[0512] Step 6:

[0513] The server uses the response calculated by the generative AI to convert the text into audio data. Specifically, it generates audio data that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0514] Step 7:

[0515] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[0516] Step 8:

[0517] The device plays the received audio data and provides audio feedback to the user through its speaker. Simultaneously, a 3D hologram display device projects a hologram character that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0518] This allows users to obtain specific answers to their questions visually and audibly. Because this system can respond quickly and accurately to a wide range of questions, it can significantly improve the user experience.

[0519] (Example 1)

[0520] 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".

[0521] Conventional information provision systems lack the means to provide visual and intuitive answers to questions entered by users via voice. Furthermore, there is a need for a system that can efficiently process the voice data entered by users accurately and quickly, generate appropriate answers, and provide them. Moreover, a system capable of providing highly accurate and appropriate answers even to complex questions is required.

[0522] 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.

[0523] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into voice data, and means for transmitting the voice data and 3D hologram data to the terminal. This makes it possible for a user to simply input a question by voice and receive a highly accurate visual and audible response to that question.

[0524] "Voice input" refers to the user using their voice to communicate questions or instructions to the device.

[0525] "Capture" refers to the electronic acquisition of audio data and other input data.

[0526] A "server" refers to a centralized computer system that performs functions such as processing, analyzing, and generating responses for audio data.

[0527] "Voice data" refers to data that records the user's voice in digital format.

[0528] "Text data" refers to data that includes character information converted from audio data.

[0529] "Generative artificial intelligence" refers to artificial intelligence technology used to generate appropriate answers to questions.

[0530] "Speech recognition artificial intelligence" refers to artificial intelligence technology used to convert speech data into text data.

[0531] "Speech conversion" refers to the process of converting text data into audio data.

[0532] "3D hologram" refers to a technology that projects three-dimensional, stereoscopic images.

[0533] A "terminal" refers to a device used by a user to input voice and to display voice data and 3D holograms.

[0534] This invention is a system in which a user inputs a question by voice, and the system utilizes speech recognition artificial intelligence and generative artificial intelligence to provide an answer to that question in the form of both voice and a 3D hologram. The system consists of a user, a terminal, and a server.

[0535] System Components

[0536] User

[0537] The user speaks their question into the device's microphone. This voice input initiates the system's operation. As a concrete example, consider a scenario where the user says, "Please tell me how to use the camera function on this smartphone."

[0538] terminal

[0539] The device is equipped with a microphone to receive the user's voice, a network interface (e.g., Wi-Fi or 4G / 5G) to send the captured audio data to the server, a speaker to play the audio data received from the server, and a 3D hologram projection device to visually display the response.

[0540] server

[0541] The server hosts speech recognition artificial intelligence (e.g., Google Cloud Speech-to-Text and AWS Transcribe) and generative artificial intelligence (e.g., OpenAI GPT-3 and BERT) to process the received audio data. The server provides the following functions:

[0542] 1. Speech Recognition: Converts speech data received from the device into text data.

[0543] 2. Question Analysis: Analyze the converted text data to understand the user's question.

[0544] 3. Answer generation: Generate appropriate answers to user questions.

[0545] 4. Speech Conversion: Convert the generated response text into audio data.

[0546] 5. Data transmission: The generated audio data and 3D hologram data are sent to the terminal.

[0547] Specific example

[0548] Example 1: Asking about the camera function of a smartphone

[0549] 1. The user asks into the microphone, "How do I use the camera function on this smartphone?"

[0550] 2. The device captures this audio and sends it to the server.

[0551] 3. The server uses speech recognition artificial intelligence to convert the voice data into text data and generates the text message, "Please tell me how to use the camera function on this smartphone."

[0552] 4. The server uses generative artificial intelligence to analyze the text data and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0553] 5. The server converts this response text into audio data and sends the audio data and 3D hologram data to the terminal.

[0554] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0555] Example of a prompt

[0556] User: "How do I use the camera function on this smartphone?"

[0557] System: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0558] This system allows users to quickly obtain high-quality visual and auditory information, making it easy to understand how to use products and services.

[0559] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0560] Step 1:

[0561] The user speaks a question into the device's microphone. For example, they might ask, "How do I use the camera function on this smartphone?" This voice input initiates the system's operation.

[0562] Step 2:

[0563] The device captures the user's voice using its microphone. Specifically, it converts the voice into digital format as audio data.

[0564] Input: User's voice

[0565] Operation: Capture and digitize audio data using a microphone.

[0566] Output: Digital audio data

[0567] Step 3:

[0568] The device transmits the captured audio data to the server via a network interface (e.g., Wi-Fi or 4G / 5G).

[0569] Input: Digital audio data

[0570] Operation: Send voice data using the network interface.

[0571] Output: Audio data sent to the server

[0572] Step 4:

[0573] The server converts the received audio data into text data using speech recognition artificial intelligence (for example, Google Cloud Speech-to-Text or AWS Transcribe).

[0574] Input: Audio data sent to the server

[0575] Operation: Convert audio data to text data using speech recognition AI.

[0576] Output: Text data (Example: "Please tell me how to use the camera function on this smartphone.")

[0577] Step 5:

[0578] The server uses generative artificial intelligence (such as OpenAI GPT-3 or BERT) to analyze text data and understand the user's question. It then extracts key keywords and the gist of the question.

[0579] Input: Text data obtained from speech recognition

[0580] Operation: Use generative AI to analyze text data and understand the intent of the question.

[0581] Output: Understanding the question and extracting necessary information

[0582] Step 6:

[0583] The server uses generative AI to generate the best possible answer to a question. For example, it can generate text explaining "how to use the camera function on a smartphone."

[0584] Input: Understanding the question and related information

[0585] Operation: Generate response text using a generative AI.

[0586] Output: Generated answer text (Example: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen.")

[0587] Step 7:

[0588] The server converts the generated response text into speech data using speech AI (for example, Google Text-to-Speech or Amazon Polly).

[0589] Input: Generated response text

[0590] Operation: Convert text data to speech data using voice AI.

[0591] Output: Generated audio data

[0592] Step 8:

[0593] The server sends the generated audio data and 3D hologram data to the terminal.

[0594] Input: Generated audio data and 3D hologram data

[0595] Operation: Send data to the terminal using a data transmission protocol (e.g., HTTPS).

[0596] Output: Audio data and 3D hologram data sent to the terminal.

[0597] Step 9:

[0598] The device plays the received audio data through its speaker. Specifically, it explains, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0599] Input: Audio data sent from the server

[0600] Operation: Play audio data through the speaker.

[0601] Output: Played audio

[0602] Step 10:

[0603] The device displays the received 3D hologram data using a hologram projection device. Specifically, it displays a hologram that visually shows the operating procedures for the smartphone.

[0604] Input: 3D hologram data sent from the server

[0605] Operation: Display data using a hologram projector.

[0606] Output: Displayed 3D hologram

[0607] This process allows users to intuitively obtain information from both audio and visual sources.

[0608] (Application Example 1)

[0609] 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."

[0610] In physical stores, there is a lack of means for customers to quickly and visually obtain information about products. Traditional methods require customers to ask store staff directly or read product labels, which are time-consuming and may not provide satisfactory information. Furthermore, in today's world where contactless interactions are required, there is a need for more efficient and hygienic means of providing information. This invention aims to solve these problems and provide a system that delivers information to customers in an intuitive and visual manner.

[0611] 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.

[0612] In this invention, the server includes means for the user to input a question by voice, means for capturing the voice input and sending it to the server, means for the server to convert the voice data into text data, means for analyzing the text data to generate an appropriate answer, means for converting the generated answer text into voice data, means for sending the voice data to a terminal, means for the terminal to play the voice data and for a 3D hologram to display the answer, means for analysis to provide product information based on the user's question, and means for visually presenting the analysis results as a 3D hologram. This enables customers to instantly obtain product information through voice input in a physical store and to understand it visually through a 3D hologram.

[0613] A "user" is a person who operates the system and uses voice input.

[0614] "Voice input" refers to the act of a user giving questions or instructions to a system by voice through a microphone.

[0615] "Capture" refers to the process of acquiring audio input in digital format and saving it as data.

[0616] A "server" is a central control unit that processes audio data, converts it to text data, and generates responses using generative artificial intelligence.

[0617] "Text data" refers to the representation of voice input as text information through speech recognition.

[0618] "Generative artificial intelligence" is a technology that uses natural language processing based on input text data to create appropriate answers to questions.

[0619] "Answer text" refers to the textual information generated by a generative artificial intelligence system in response to a user's question.

[0620] "Audio data" refers to audio information generated from text data using speech synthesis technology.

[0621] A "terminal" is a device used by a user, and includes equipment such as a microphone, speaker, and 3D hologram projection device.

[0622] "Playback" is the process of outputting audio data as actual sound through a speaker.

[0623] A "3D hologram" is a technology that visually presents the answer content as a three-dimensional, stereoscopic image.

[0624] "Product information" refers to detailed information about products sold in physical stores, such as their characteristics, usage instructions, stock availability, and price.

[0625] "Analysis" is the process of processing data based on user input to generate appropriate answers or information.

[0626] "Presentation" refers to the act of visually showing the analysis results to the user.

[0627] Embodiments for carrying out this invention are described below.

[0628] The system of this invention allows users to ask questions via voice input and provides visual answers to those questions in the form of 3D holograms. The main components consist of a user, a terminal, and a server.

[0629] Hardware configuration

[0630] 1. User's terminal

[0631] Smart glasses (with HUD function), smartphone, or tablet

[0632] Microphone and speaker

[0633] 3D hologram projection device (e.g., HoloLens)

[0634] 2. Server

[0635] Speech recognition API (e.g., Google Cloud Speech-to-Text)

[0636] Generative AI (e.g. OpenAI GPT-4)

[0637] 3D hologram generation software (e.g., Unity 3D)

[0638] Database (e.g., Firebase)

[0639] Software Processing

[0640] From voice input to text conversion

[0641] 1. The user asks a question into the microphone of the smart glasses.

[0642] For example, a user might ask, "What material is this sofa made of?"

[0643] Capture and transmit audio data

[0644] 2. The device captures the user's voice and sends it to the server in digital format.

[0645] Speech recognition and analysis

[0646] 3. The server uses the Google Cloud Speech-to-Text API to convert the audio data into text data. The text data generated is "What material is this sofa made of?".

[0647] Question analysis and answer generation

[0648] 4. The server inputs text data into OpenAI GPT-4 and uses a generative AI to analyze the question content.

[0649] The generative AI will generate the answer "The materials of this sofa are high-quality leather and memory foam" to this question.

[0650] Voice conversion and data transmission

[0651] 5. The server converts the generated response text into audio data using the Google Cloud Text-to-Speech API and sends this audio data to the device.

[0652] 3D hologram display

[0653] 6. The terminal plays the received audio data and uses a 3D hologram projection device to visually display the response, "The material of this sofa is high-quality leather and memory foam."

[0654] Specific example

[0655] Consider a scenario where a user is in a furniture store, wearing smart glasses, and asks a question by voice: "What material is this sofa made of?" The smart glasses capture this question and send it to a server. The server uses a speech recognition API to convert the question into text, and then uses generative AI to analyze it and generate an appropriate answer. This answer is sent to the device as audio data and 3D hologram data, and displayed in the user's field of view.

[0656] Example of a prompt

[0657] User: Voice input "What material is this sofa made of?"

[0658] System: Analyzing...

[0659] System: Answer: "The materials for this sofa are high-quality leather and memory foam."

[0660] Display: 3D hologram visually describes the details of the sofa.

[0661] The system of this invention enables users to quickly and intuitively obtain and visually understand product information within a physical store. This results in more efficient and effective information delivery compared to conventional methods.

[0662] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0663] Step 1:

[0664] The user performs voice input. The user speaks their question into the microphone of the smart glasses. For example, they might ask, "What material is this sofa made of?"

[0665] Input: User's voice question

[0666] Output: Captured audio data

[0667] Step 2:

[0668] The device captures audio data and sends it to the server. The smart glasses (device) capture the user's voice digitally through the microphone and send it to the server via the network.

[0669] Input: Captured audio data

[0670] Output: Audio data sent to the server

[0671] Step 3:

[0672] The server converts the audio data into text data. The server uses the Google Cloud Speech-to-Text API to convert the transmitted audio data into text data. At this point, the audio data becomes the text "What material is this sofa made of?".

[0673] Input: Audio data sent to the server

[0674] Output: Text data

[0675] Step 4:

[0676] The server analyzes the text data and generates an answer. The server uses OpenAI GPT-4 to analyze the converted text data and generate an appropriate answer based on the user's question. In this case, it generates the answer, "The material of this sofa is high-quality leather and memory foam."

[0677] Input: Text data

[0678] Output: Answer text

[0679] Step 5:

[0680] The server converts the generated response text into audio data. The server uses the Google Cloud Text-to-Speech API to convert the generated response text into audio data. At this time, the response text "This sofa is made of high-quality leather and memory foam." is converted into audio data.

[0681] Input: Answer text

[0682] Output: Audio data

[0683] Step 6:

[0684] The server sends audio data to the terminal. The server sends the generated audio data to the terminal via the network.

[0685] Input: Audio data

[0686] Output: Audio data sent to the terminal

[0687] Step 7:

[0688] The device plays the received audio data and displays a 3D hologram. The device (smart glasses) plays the received audio data and simultaneously uses a 3D hologram projector to visually display the answer. In this case, the audio plays "The material of this sofa is high-quality leather and memory foam," and the 3D hologram visually presents details about the sofa's materials.

[0689] Input: Audio data sent to the terminal

[0690] Output: Played audio data and displayed 3D hologram

[0691] 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.

[0692] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[0693] Components and operation

[0694] User

[0695] The user operates the system and inputs questions by voice into a terminal. The user's emotions are also analyzed through this voice input.

[0696] terminal

[0697] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[0698] 1. Capture audio data

[0699] 2. Sending audio data to the server

[0700] 3. Playback of audio data received from the server.

[0701] 4. Display of 3D holograms

[0702] server

[0703] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[0704] 1. Speech recognition: Converts speech data into text data.

[0705] 2. Question Analysis: Analyze text data to understand the user's questions.

[0706] 3. Answer generation: Generator AI is used to generate appropriate answers.

[0707] 4. Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[0708] 5. Speech Conversion: Converts the generated response text into audio data.

[0709] 6. Sending audio data to the terminal

[0710] Emotional Engine

[0711] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram.

[0712] Specific example

[0713] Example 1: Asking about the camera function of a smartphone

[0714] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[0715] 2. The device captures this audio and sends it to the server.

[0716] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0717] 4. The server passes the converted text data to a generative AI, which analyzes the intent of the question and generates an answer.

[0718] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[0719] 6. The server converts the generated response text into audio data and sends the audio data and sentiment data to the terminal.

[0720] 7. The device plays audio data and provides feedback to the user through the speaker. It also changes the expression of the 3D hologram based on emotional data and responds in a friendly tone that matches the user's emotions, saying, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0721] This allows users to receive specific and emotionally sensitive answers to their questions. By combining this with an emotion engine, a more personalized user experience can be achieved.

[0722] The following describes the processing flow.

[0723] Step 1:

[0724] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[0725] Step 2:

[0726] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[0727] Step 3:

[0728] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[0729] Step 4:

[0730] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[0731] Step 5:

[0732] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the user's question. It then generates an answer to the user's question.

[0733] Step 6:

[0734] The server uses the answer calculated by the generative AI to re-analyze the text and verify that the answer is appropriate. At this point, the text "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is obtained.

[0735] Step 7:

[0736] The server converts this response text into audio data. Specifically, it uses a speech synthesis engine to convert the text into speech and generates the audio data, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0737] Step 8:

[0738] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[0739] Step 9:

[0740] The server activates an emotion engine along with the voice data and analyzes the user's emotions from the voice data. Specifically, it uses information such as the tone, speed, and rhythm of the voice to generate emotion data such as "interest" and "confusion."

[0741] Step 10:

[0742] The server sends emotional data to the terminal simultaneously with the audio data.

[0743] Step 11:

[0744] The device plays back the received audio data and provides audio feedback to the user through the speaker. Simultaneously, it changes the facial expression of the 3D hologram based on emotional data. For example, if the user is confused, the hologram character will say in a friendly expression and tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0745] This process allows users to receive specific and emotionally sensitive answers to their questions, both visually and audibly. The entire system is designed to work seamlessly together, maximizing the user experience.

[0746] (Example 2)

[0747] 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".

[0748] Conventional voice dialogue systems are required not only to generate appropriate responses to voice input, but also to recognize the user's emotions and provide feedback based on those emotions. However, previous systems have been unable to recognize emotions, resulting in a limited user experience and difficulty in providing personalized responses. Furthermore, while it is expected that using 3D holograms as visual feedback will further improve user interaction, this has also not yet been realized.

[0749] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for recognizing the user's emotions and generating emotion data, means for converting the generated response text into voice data, and means for transmitting the voice data and emotion data to the terminal. This makes it possible to provide personalized responses based on the user's emotions as feedback in voice and 3D hologram form.

[0750] A "user" is a person who uses voice input to ask questions to the system.

[0751] A "terminal" is a device that captures the user's voice and sends it to a server, and uses the received voice data and emotion data to provide feedback to the user.

[0752] A "server" is a computer system that converts voice data into text data, analyzes it to generate appropriate responses, and further recognizes and analyzes the user's emotions.

[0753] "Voice data" refers to information that represents a user's voice input in digital format.

[0754] "Text data" refers to data represented as characters converted by speech recognition, and includes the content of the user's question.

[0755] "Generative artificial intelligence" is an artificial intelligence technology that analyzes text data to generate appropriate responses.

[0756] An "emotion engine" is software or a system that recognizes a user's emotions from voice data and generates emotion data.

[0757] "Emotional data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0758] "Speech recognition artificial intelligence" is an artificial intelligence technology that converts speech data into text data.

[0759] A "3D hologram" is a device or technology that provides visual feedback to users by displaying three-dimensional images based on emotional data.

[0760] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[0761] User

[0762] The user operates the system and inputs their questions by voice into the terminal. For example, they might say to their smartphone, "Please tell me how to use the camera function on this smartphone."

[0763] terminal

[0764] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to a server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms. Specific processing includes the following:

[0765] Microphone: Records the user's voice and captures it as digital audio data.

[0766] Network interface: Sends captured audio data to the server.

[0767] Speaker: Plays audio data received from the server.

[0768] Hologram projection device: Adjusts and projects 3D holographic facial expressions based on emotional data.

[0769] server

[0770] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specific processing includes the following:

[0771] Speech recognition: The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert speech data into text data.

[0772] Question analysis: Analyzes the converted text data to understand the user's question.

[0773] Answer generation: Generative artificial intelligence (e.g., a generative AI model) is used to generate appropriate answers.

[0774] Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[0775] Speech conversion: The generated response text is converted into speech data using speech synthesis technology.

[0776] Data transmission: The generated voice data and emotion data are sent to the device.

[0777] Emotional Engine

[0778] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This allows the user's emotions to be reflected in voice responses and 3D holograms.

[0779] Specific example

[0780] Example 1: When asking about the camera function of a smartphone

[0781] 1. The user asks, "How do I use the camera function on this smartphone?" into the device's microphone.

[0782] 2. The device captures this audio and sends it to the server.

[0783] 3. The server uses speech recognition artificial intelligence to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0784] 4. The server analyzes the text data using a generative AI model, understands the intent of the question, and generates an answer. For example, it might generate an answer such as, "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0785] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[0786] 6. The server converts the response text into audio data and sends the audio data and sentiment data to the terminal.

[0787] 7. The device plays audio data through its speaker and displays 3D holographic facial expressions based on emotional data. For example, it might respond in a friendly tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0788] Examples of prompts for generative AI models

[0789] Prompt: "How would you explain the camera function of a smartphone if a user asked about it?"

[0790] Expected output: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] The user inputs the question by voice. The user speaks the question into the device's microphone. For example, they might say, "Please tell me how to use the camera function on this smartphone." The input is recorded as voice data on the device.

[0794] Step 2:

[0795] The terminal captures audio data and sends it to the server. The terminal is equipped with a microphone for recording audio and a function to capture audio data in digital format. The captured audio data is sent to the server via the network interface. The input is audio data, and the output is the audio data sent to the server.

[0796] Step 3:

[0797] The server converts the audio data into text data. The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert the audio data into text data. The input is the captured audio data, and the output is text data. For example, the audio "Please tell me how to use the camera function on this smartphone" is converted to the text "Please tell me how to use the camera function on this smartphone".

[0798] Step 4:

[0799] The server analyzes text data and generates appropriate answers. The server uses generative artificial intelligence (e.g., a generative AI model) to analyze the converted text data and generate appropriate answers. The input is text data, and the output is the answer text. For example, in response to the question "How do I use the camera function on this smartphone?", it generates answer text such as "To use the camera function on this smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0800] Step 5:

[0801] The server recognizes the user's emotions and generates emotion data. Using the emotion engine installed on the server, it analyzes the user's emotions from the audio data. The input is audio data, and the output is emotion data. For example, it can recognize emotions such as "interested" or "confused" from the user's voice.

[0802] Step 6:

[0803] The server converts the generated response text into audio data. The server uses speech synthesis technology (e.g., speech synthesis AI) to convert the generated response text into audio data. The input is the response text, and the output is audio data. For example, the text "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen." will be converted into audio data.

[0804] Step 7:

[0805] The server sends voice data and emotion data to the terminal. The server sends the generated voice data and emotion data to the terminal via the network interface. The input is voice data and emotion data, and the output is the data sent to the terminal.

[0806] Step 8:

[0807] The device plays audio data and provides feedback via a 3D hologram. The device plays the received audio data through its speaker and further changes the expression of the 3D hologram based on emotion data. The input is audio data and emotion data received from the server, and the output is audio feedback and visual feedback. For example, the audio "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is played in a friendly tone, and the expression of the 3D hologram is displayed in a friendly manner.

[0808] (Application Example 2)

[0809] 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."

[0810] While there is a need to efficiently learn and implement maintenance and operating procedures within factories, conventional manuals and simple voice guidance systems struggle to provide flexible responses tailored to user understanding and on-site conditions. Furthermore, they often lack appropriate feedback that reflects user emotions and comprehension, potentially leading to decreased efficiency and safety in actual operations. To address these challenges, a system is needed that can recognize user emotions and provide personalized guidance tailored to individual situations.

[0811] 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.

[0812] In this invention, the server includes means for converting audio data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into audio data, means for analyzing the user's emotions from the audio data using an emotion engine, and means for changing the tone of the response and the facial expressions of the 3D hologram according to the user's emotions. This enables personalized maintenance and operation procedure guidance that takes into account the user's emotions and level of understanding.

[0813] A "user" refers to a person who operates this system and inputs questions using voice input.

[0814] "Voice input" refers to the act of a user using a microphone to communicate questions or instructions to a system by voice.

[0815] "Capture" refers to the process of taking in and recording audio input.

[0816] A "server" refers to a remote computing device that processes audio data, converts it to text data, analyzes questions, generates answers, and performs sentiment analysis.

[0817] "Voice data" refers to the captured voice input of the user.

[0818] "Text data" refers to audio data converted into written text.

[0819] "Generative artificial intelligence" refers to advanced machine learning models that analyze questions and generate appropriate answers.

[0820] "Speech recognition artificial intelligence" refers to a machine learning model used to convert speech data into text data.

[0821] An "emotion engine" refers to a system that analyzes emotions from a user's voice data and generates emotional data.

[0822] A "3D hologram" refers to a three-dimensional visual representation displayed in space.

[0823] "Response tone" refers to the emotional expression used in the generated voice response.

[0824] This invention is a system for efficiently learning and implementing maintenance and operating procedures within a factory. The system consists of user, terminal, server, and emotion engine components. The details of each component and their specific operation are described below.

[0825] User

[0826] The user operates the system and inputs questions by voice into the terminal. For example, the user might say to the terminal, "Please tell me the maintenance procedure for this machine." This voice input initiates the system's operation.

[0827] terminal

[0828] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also has a speaker and a hologram projection device for playing back the voice data received from the server and the 3D hologram.

[0829] Typical hardware examples include the following:

[0830] Microphone: A highly sensitive voice input device.

[0831] Speaker: A device that reproduces sound clearly.

[0832] Hologram projector: Displays 3D holograms.

[0833] server

[0834] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specifically, it uses the following software services:

[0835] Speech Recognition AI: Converts speech data into text data using Microsoft Azure Cognitive Services.

[0836] Generative AI: Uses OpenAI GPT-4 to analyze text data and generate appropriate responses.

[0837] Emotion Engine: Analyzes emotions from the user's voice and generates emotion data.

[0838] Specific server processing:

[0839] 1. Speech Recognition: The server uses speech recognition AI to convert speech data into text data. Example: "Please use Azure's speech recognition API to convert this speech data to text."

[0840] 2. Question Analysis and Answer Generation: Use a generative AI model to analyze text data and generate appropriate answers. Example: "Using GPT-4, analyze the following question and generate appropriate maintenance procedures: 'Please tell me the maintenance procedures for this machine.'"

[0841] 3. Emotion Recognition: Use an emotion engine to analyze the user's emotions from voice data and generate emotion data. Example: "Analyze the user's emotions (e.g., interested, confused) from their voice data and generate emotion data."

[0842] Emotional Engine

[0843] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This generated emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram. For example, if the user is confused, the system will respond in a more polite and friendly tone. Specifically, the generated response text is converted into voice data, and the tone is adjusted based on the emotion data.

[0844] Specific example

[0845] For example, if a user asks, "Please tell me the maintenance procedure for this machine," the system will operate as follows:

[0846] 1. The user asks a question into the device's microphone.

[0847] 2. The device captures this audio and sends it to the server.

[0848] 3. The server uses speech recognition AI to convert the audio data into text and analyze the content of the question.

[0849] 4. Generative AI generates appropriate answers based on the analysis results.

[0850] 5. The emotion engine analyzes the user's emotions and adjusts the tone of responses and the facial expressions of the hologram accordingly.

[0851] 6. The device plays the generated audio data and displays the hologram.

[0852] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[0853] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0854] Step 1:

[0855] The user enters the question by voice.

[0856] The user operates the system and inputs their question by voice into the device's microphone. This voice input initiates the system's processing.

[0857] Input: User's voice

[0858] Output: Captured audio data

[0859] Step 2:

[0860] The device captures audio and sends it to the server.

[0861] The device captures the user's voice using a microphone and sends this audio data to the server via a network interface.

[0862] Input: Captured audio data

[0863] Output: Audio data sent to the server

[0864] Step 3:

[0865] The server converts the audio data into text data.

[0866] The server uses speech recognition AI (e.g., Microsoft Azure Cognitive Services) to convert the audio data into text data. The specific prompt is, "Please use the Azure speech recognition API to convert this audio data to text."

[0867] Input: Audio data sent to the server

[0868] Output: Converted text data

[0869] Step 4:

[0870] The server analyzes the text data and generates the appropriate response.

[0871] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze text data and generate appropriate responses. The specific prompt is: "Use GPT-4 to analyze the following question and generate appropriate maintenance instructions: 'Please tell me the maintenance instructions for this machine.'"

[0872] Input: Converted text data

[0873] Output: Generated answer text

[0874] Step 5:

[0875] The server analyzes the user's emotions and generates emotional data.

[0876] The server uses an emotion engine to analyze the user's emotions from voice data and generate emotion data. Specifically, it analyzes characteristics such as the tone, volume, and speed of the user's voice. Example: "Analyze the user's voice data to determine their emotions (e.g., interested, confused) and generate emotion data."

[0877] Input: Audio data

[0878] Output: Sentiment data

[0879] Step 6:

[0880] The server converts the response text into audio data and adjusts the tone based on sentiment data.

[0881] The server converts the generated response text into audio data and adjusts the tone based on sentiment data. This sentiment data helps create user-friendly feedback, such as a more approachable or polite tone.

[0882] Input: Generated response text, sentiment data

[0883] Output: Voice data adjusted based on emotion

[0884] Step 7:

[0885] The server sends the audio data to the terminal.

[0886] The server sends the response audio data and emotion data to the terminal via the network interface.

[0887] Input: Voice data adjusted based on emotion

[0888] Output: Audio data sent to the terminal

[0889] Step 8:

[0890] The device plays audio data and displays a 3D hologram.

[0891] The device plays audio data received from the server through its speaker and displays a 3D hologram based on the emotional data. For example, if the user is in a state of "confusion," the hologram will display a more friendly expression and respond in a more polite voice.

[0892] Input: Voice data and emotion data sent to the device.

[0893] Output: Audio and 3D hologram played for the user

[0894] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] [Third Embodiment]

[0899] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0900] 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.

[0901] 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).

[0902] 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.

[0903] 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.

[0904] 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).

[0905] 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.

[0906] 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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".

[0911] The present invention is a system in which a user inputs a question by voice, which is then processed using voice AI and generative AI, and the results are provided visually and audibly as a 3D hologram. The system of the present invention consists of the following components: a user, a terminal, and a server.

[0912] Components and operation

[0913] User

[0914] The user operates the system and inputs their questions by voice into the terminal. This voice input initiates the system's operation.

[0915] terminal

[0916] The terminal is equipped with a microphone for user voice input and a network interface for capturing voice data and sending it to the server. It also has a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[0917] 1. Capture audio data

[0918] 2. Sending audio data to the server

[0919] 3. Playback of audio data received from the server.

[0920] 4. Display of 3D holograms

[0921] server

[0922] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[0923] 1. Speech recognition: Converts speech data into text data.

[0924] 2. Question Analysis: Analyze text data to understand the user's questions.

[0925] 3. Answer generation: Generator AI is used to generate appropriate answers.

[0926] 4. Speech Conversion: Converts the generated response text into audio data.

[0927] 5. Sending audio data to the terminal

[0928] Specific example

[0929] Example 1: Asking about the camera function of a smartphone

[0930] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[0931] 2. The device captures this audio and sends it to the server.

[0932] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[0933] 4. The server uses generative AI to analyze this text and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0934] 5. The server converts this response text into audio data using voice AI and sends the audio data to the terminal.

[0935] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0936] This process allows users to obtain sufficient information through high-quality visual and audio. This enables users to receive specific and easy-to-understand instructions on how to use the product or service.

[0937] The following describes the processing flow.

[0938] Step 1:

[0939] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[0940] Step 2:

[0941] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[0942] Step 3:

[0943] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[0944] Step 4:

[0945] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[0946] Step 5:

[0947] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the intent of the question. It then generates an answer to the user's question.

[0948] Step 6:

[0949] The server uses the response calculated by the generative AI to convert the text into audio data. Specifically, it generates audio data that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0950] Step 7:

[0951] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[0952] Step 8:

[0953] The device plays the received audio data and provides audio feedback to the user through its speaker. Simultaneously, a 3D hologram display device projects a hologram character that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0954] This allows users to obtain specific answers to their questions visually and audibly. Because this system can respond quickly and accurately to a wide range of questions, it can significantly improve the user experience.

[0955] (Example 1)

[0956] 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."

[0957] Conventional information provision systems lack the means to provide visual and intuitive answers to questions entered by users via voice. Furthermore, there is a need for a system that can efficiently process the voice data entered by users accurately and quickly, generate appropriate answers, and provide them. Moreover, a system capable of providing highly accurate and appropriate answers even to complex questions is required.

[0958] 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.

[0959] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into voice data, and means for transmitting the voice data and 3D hologram data to the terminal. This makes it possible for a user to simply input a question by voice and receive a highly accurate visual and audible response to that question.

[0960] "Voice input" refers to the user using their voice to communicate questions or instructions to the device.

[0961] "Capture" refers to the electronic acquisition of audio data and other input data.

[0962] A "server" refers to a centralized computer system that performs functions such as processing, analyzing, and generating responses for audio data.

[0963] "Voice data" refers to data that records the user's voice in digital format.

[0964] "Text data" refers to data that includes character information converted from audio data.

[0965] "Generative artificial intelligence" refers to artificial intelligence technology used to generate appropriate answers to questions.

[0966] "Speech recognition artificial intelligence" refers to artificial intelligence technology used to convert speech data into text data.

[0967] "Speech conversion" refers to the process of converting text data into audio data.

[0968] "3D hologram" refers to a technology that projects three-dimensional, stereoscopic images.

[0969] A "terminal" refers to a device used by a user to input voice and to display voice data and 3D holograms.

[0970] This invention is a system in which a user inputs a question by voice, and the system utilizes speech recognition artificial intelligence and generative artificial intelligence to provide an answer to that question in the form of both voice and a 3D hologram. The system consists of a user, a terminal, and a server.

[0971] System Components

[0972] User

[0973] The user speaks their question into the device's microphone. This voice input initiates the system's operation. As a concrete example, consider a scenario where the user says, "Please tell me how to use the camera function on this smartphone."

[0974] terminal

[0975] The device is equipped with a microphone to receive the user's voice, a network interface (e.g., Wi-Fi or 4G / 5G) to send the captured audio data to the server, a speaker to play the audio data received from the server, and a 3D hologram projection device to visually display the response.

[0976] server

[0977] The server hosts speech recognition artificial intelligence (e.g., Google Cloud Speech-to-Text and AWS Transcribe) and generative artificial intelligence (e.g., OpenAI GPT-3 and BERT) to process the received audio data. The server provides the following functions:

[0978] 1. Speech Recognition: Converts speech data received from the device into text data.

[0979] 2. Question Analysis: Analyze the converted text data to understand the user's question.

[0980] 3. Answer generation: Generate appropriate answers to user questions.

[0981] 4. Speech Conversion: Convert the generated response text into audio data.

[0982] 5. Data transmission: The generated audio data and 3D hologram data are sent to the terminal.

[0983] Specific example

[0984] Example 1: Asking about the camera function of a smartphone

[0985] 1. The user asks into the microphone, "How do I use the camera function on this smartphone?"

[0986] 2. The device captures this audio and sends it to the server.

[0987] 3. The server uses speech recognition artificial intelligence to convert the voice data into text data and generates the text message, "Please tell me how to use the camera function on this smartphone."

[0988] 4. The server uses generative artificial intelligence to analyze the text data and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[0989] 5. The server converts this response text into audio data and sends the audio data and 3D hologram data to the terminal.

[0990] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0991] Example of a prompt

[0992] User: "How do I use the camera function on this smartphone?"

[0993] System: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[0994] This system allows users to quickly obtain high-quality visual and auditory information, making it easy to understand how to use products and services.

[0995] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0996] Step 1:

[0997] The user speaks a question into the device's microphone. For example, they might ask, "How do I use the camera function on this smartphone?" This voice input initiates the system's operation.

[0998] Step 2:

[0999] The device captures the user's voice using its microphone. Specifically, it converts the voice into digital format as audio data.

[1000] Input: User's voice

[1001] Operation: Capture and digitize audio data using a microphone.

[1002] Output: Digital audio data

[1003] Step 3:

[1004] The device transmits the captured audio data to the server via a network interface (e.g., Wi-Fi or 4G / 5G).

[1005] Input: Digital audio data

[1006] Operation: Send voice data using the network interface.

[1007] Output: Audio data sent to the server

[1008] Step 4:

[1009] The server converts the received audio data into text data using speech recognition artificial intelligence (for example, Google Cloud Speech-to-Text or AWS Transcribe).

[1010] Input: Audio data sent to the server

[1011] Operation: Convert audio data to text data using speech recognition AI.

[1012] Output: Text data (Example: "Please tell me how to use the camera function on this smartphone.")

[1013] Step 5:

[1014] The server uses generative artificial intelligence (such as OpenAI GPT-3 or BERT) to analyze text data and understand the user's question. It then extracts key keywords and the gist of the question.

[1015] Input: Text data obtained from speech recognition

[1016] Operation: Use generative AI to analyze text data and understand the intent of the question.

[1017] Output: Understanding the question and extracting necessary information

[1018] Step 6:

[1019] The server uses generative AI to generate the best possible answer to a question. For example, it can generate text explaining "how to use the camera function on a smartphone."

[1020] Input: Understanding the question and related information

[1021] Operation: Generate response text using a generative AI.

[1022] Output: Generated answer text (Example: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen.")

[1023] Step 7:

[1024] The server converts the generated response text into speech data using speech AI (for example, Google Text-to-Speech or Amazon Polly).

[1025] Input: Generated response text

[1026] Operation: Convert text data to speech data using voice AI.

[1027] Output: Generated audio data

[1028] Step 8:

[1029] The server sends the generated audio data and 3D hologram data to the terminal.

[1030] Input: Generated audio data and 3D hologram data

[1031] Operation: Send data to the terminal using a data transmission protocol (e.g., HTTPS).

[1032] Output: Audio data and 3D hologram data sent to the terminal.

[1033] Step 9:

[1034] The device plays the received audio data through its speaker. Specifically, it explains, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1035] Input: Audio data sent from the server

[1036] Operation: Play audio data through the speaker.

[1037] Output: Played audio

[1038] Step 10:

[1039] The device displays the received 3D hologram data using a hologram projection device. Specifically, it displays a hologram that visually shows the operating procedures for the smartphone.

[1040] Input: 3D hologram data sent from the server

[1041] Operation: Display data using a hologram projector.

[1042] Output: Displayed 3D hologram

[1043] This process allows users to intuitively obtain information from both audio and visual sources.

[1044] (Application Example 1)

[1045] 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."

[1046] In physical stores, there is a lack of means for customers to quickly and visually obtain information about products. Traditional methods require customers to ask store staff directly or read product labels, which are time-consuming and may not provide satisfactory information. Furthermore, in today's world where contactless interactions are required, there is a need for more efficient and hygienic means of providing information. This invention aims to solve these problems and provide a system that delivers information to customers in an intuitive and visual manner.

[1047] 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.

[1048] In this invention, the server includes means for the user to input a question by voice, means for capturing the voice input and sending it to the server, means for the server to convert the voice data into text data, means for analyzing the text data to generate an appropriate answer, means for converting the generated answer text into voice data, means for sending the voice data to a terminal, means for the terminal to play the voice data and for a 3D hologram to display the answer, means for analysis to provide product information based on the user's question, and means for visually presenting the analysis results as a 3D hologram. This enables customers to instantly obtain product information through voice input in a physical store and to understand it visually through a 3D hologram.

[1049] A "user" is a person who operates the system and uses voice input.

[1050] "Voice input" refers to the act of a user giving questions or instructions to a system by voice through a microphone.

[1051] "Capture" refers to the process of acquiring audio input in digital format and saving it as data.

[1052] A "server" is a central control unit that processes audio data, converts it to text data, and generates responses using generative artificial intelligence.

[1053] "Text data" refers to the representation of voice input as text information through speech recognition.

[1054] "Generative artificial intelligence" is a technology that uses natural language processing based on input text data to create appropriate answers to questions.

[1055] "Answer text" refers to the textual information generated by a generative artificial intelligence system in response to a user's question.

[1056] "Audio data" refers to audio information generated from text data using speech synthesis technology.

[1057] A "terminal" is a device used by a user, and includes equipment such as a microphone, speaker, and 3D hologram projection device.

[1058] "Playback" is the process of outputting audio data as actual sound through a speaker.

[1059] A "3D hologram" is a technology that visually presents the answer content as a three-dimensional, stereoscopic image.

[1060] "Product information" refers to detailed information about products sold in physical stores, such as their characteristics, usage instructions, stock availability, and price.

[1061] "Analysis" is the process of processing data based on user input to generate appropriate answers or information.

[1062] "Presentation" refers to the act of visually showing the analysis results to the user.

[1063] Embodiments for carrying out this invention are described below.

[1064] The system of this invention allows users to ask questions via voice input and provides visual answers to those questions in the form of 3D holograms. The main components consist of a user, a terminal, and a server.

[1065] Hardware configuration

[1066] 1. User's terminal

[1067] Smart glasses (with HUD function), smartphone, or tablet

[1068] Microphone and speaker

[1069] 3D hologram projection device (e.g., HoloLens)

[1070] 2. Server

[1071] Speech recognition API (e.g., Google Cloud Speech-to-Text)

[1072] Generative AI (e.g. OpenAI GPT-4)

[1073] 3D hologram generation software (e.g., Unity 3D)

[1074] Database (e.g., Firebase)

[1075] Software Processing

[1076] From voice input to text conversion

[1077] 1. The user asks a question into the microphone of the smart glasses.

[1078] For example, a user might ask, "What material is this sofa made of?"

[1079] Capture and transmit audio data

[1080] 2. The device captures the user's voice and sends it to the server in digital format.

[1081] Speech recognition and analysis

[1082] 3. The server uses the Google Cloud Speech-to-Text API to convert the audio data into text data. The text data generated is "What material is this sofa made of?".

[1083] Question analysis and answer generation

[1084] 4. The server inputs text data into OpenAI GPT-4 and uses a generative AI to analyze the question content.

[1085] The generative AI will generate the answer "The materials of this sofa are high-quality leather and memory foam" to this question.

[1086] Voice conversion and data transmission

[1087] 5. The server converts the generated response text into audio data using the Google Cloud Text-to-Speech API and sends this audio data to the device.

[1088] 3D hologram display

[1089] 6. The terminal plays the received audio data and uses a 3D hologram projection device to visually display the response, "The material of this sofa is high-quality leather and memory foam."

[1090] Specific example

[1091] Consider a scenario where a user is in a furniture store, wearing smart glasses, and asks a question by voice: "What material is this sofa made of?" The smart glasses capture this question and send it to a server. The server uses a speech recognition API to convert the question into text, and then uses generative AI to analyze it and generate an appropriate answer. This answer is sent to the device as audio data and 3D hologram data, and displayed in the user's field of view.

[1092] Example of a prompt

[1093] User: Voice input "What material is this sofa made of?"

[1094] System: Analyzing...

[1095] System: Answer: "The materials for this sofa are high-quality leather and memory foam."

[1096] Display: 3D hologram visually describes the details of the sofa.

[1097] The system of this invention enables users to quickly and intuitively obtain and visually understand product information within a physical store. This results in more efficient and effective information delivery compared to conventional methods.

[1098] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1099] Step 1:

[1100] The user performs voice input. The user speaks their question into the microphone of the smart glasses. For example, they might ask, "What material is this sofa made of?"

[1101] Input: User's voice question

[1102] Output: Captured audio data

[1103] Step 2:

[1104] The device captures audio data and sends it to the server. The smart glasses (device) capture the user's voice digitally through the microphone and send it to the server via the network.

[1105] Input: Captured audio data

[1106] Output: Audio data sent to the server

[1107] Step 3:

[1108] The server converts the audio data into text data. The server uses the Google Cloud Speech-to-Text API to convert the transmitted audio data into text data. At this point, the audio data becomes the text "What material is this sofa made of?".

[1109] Input: Audio data sent to the server

[1110] Output: Text data

[1111] Step 4:

[1112] The server analyzes the text data and generates an answer. The server uses OpenAI GPT-4 to analyze the converted text data and generate an appropriate answer based on the user's question. In this case, it generates the answer, "The material of this sofa is high-quality leather and memory foam."

[1113] Input: Text data

[1114] Output: Answer text

[1115] Step 5:

[1116] The server converts the generated response text into audio data. The server uses the Google Cloud Text-to-Speech API to convert the generated response text into audio data. At this time, the response text "This sofa is made of high-quality leather and memory foam." is converted into audio data.

[1117] Input: Answer text

[1118] Output: Audio data

[1119] Step 6:

[1120] The server sends audio data to the terminal. The server sends the generated audio data to the terminal via the network.

[1121] Input: Audio data

[1122] Output: Audio data sent to the terminal

[1123] Step 7:

[1124] The device plays the received audio data and displays a 3D hologram. The device (smart glasses) plays the received audio data and simultaneously uses a 3D hologram projector to visually display the answer. In this case, the audio plays "The material of this sofa is high-quality leather and memory foam," and the 3D hologram visually presents details about the sofa's materials.

[1125] Input: Audio data sent to the terminal

[1126] Output: Played audio data and displayed 3D hologram

[1127] 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.

[1128] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[1129] Components and operation

[1130] User

[1131] The user operates the system and inputs questions by voice into a terminal. The user's emotions are also analyzed through this voice input.

[1132] terminal

[1133] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[1134] 1. Capture audio data

[1135] 2. Sending audio data to the server

[1136] 3. Playback of audio data received from the server.

[1137] 4. Display of 3D holograms

[1138] server

[1139] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[1140] 1. Speech recognition: Converts speech data into text data.

[1141] 2. Question Analysis: Analyze text data to understand the user's questions.

[1142] 3. Answer generation: Generator AI is used to generate appropriate answers.

[1143] 4. Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[1144] 5. Speech Conversion: Converts the generated response text into audio data.

[1145] 6. Sending audio data to the terminal

[1146] Emotional Engine

[1147] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram.

[1148] Specific example

[1149] Example 1: Asking about the camera function of a smartphone

[1150] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[1151] 2. The device captures this audio and sends it to the server.

[1152] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[1153] 4. The server passes the converted text data to a generative AI, which analyzes the intent of the question and generates an answer.

[1154] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[1155] 6. The server converts the generated response text into audio data and sends the audio data and sentiment data to the terminal.

[1156] 7. The device plays audio data and provides feedback to the user through the speaker. It also changes the expression of the 3D hologram based on emotional data and responds in a friendly tone that matches the user's emotions, saying, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1157] This allows users to receive specific and emotionally sensitive answers to their questions. By combining this with an emotion engine, a more personalized user experience can be achieved.

[1158] The following describes the processing flow.

[1159] Step 1:

[1160] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[1161] Step 2:

[1162] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[1163] Step 3:

[1164] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[1165] Step 4:

[1166] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[1167] Step 5:

[1168] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the user's question. It then generates an answer to the user's question.

[1169] Step 6:

[1170] The server uses the answer calculated by the generative AI to re-analyze the text and verify that the answer is appropriate. At this point, the text "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is obtained.

[1171] Step 7:

[1172] The server converts this response text into audio data. Specifically, it uses a speech synthesis engine to convert the text into speech and generates the audio data, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1173] Step 8:

[1174] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[1175] Step 9:

[1176] The server activates an emotion engine along with the voice data and analyzes the user's emotions from the voice data. Specifically, it uses information such as the tone, speed, and rhythm of the voice to generate emotion data such as "interest" and "confusion."

[1177] Step 10:

[1178] The server sends emotional data to the terminal simultaneously with the audio data.

[1179] Step 11:

[1180] The device plays back the received audio data and provides audio feedback to the user through the speaker. Simultaneously, it changes the facial expression of the 3D hologram based on emotional data. For example, if the user is confused, the hologram character will say in a friendly expression and tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1181] This process allows users to receive specific and emotionally sensitive answers to their questions, both visually and audibly. The entire system is designed to work seamlessly together, maximizing the user experience.

[1182] (Example 2)

[1183] 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."

[1184] Conventional voice dialogue systems are required not only to generate appropriate responses to voice input, but also to recognize the user's emotions and provide feedback based on those emotions. However, previous systems have been unable to recognize emotions, resulting in a limited user experience and difficulty in providing personalized responses. Furthermore, while it is expected that using 3D holograms as visual feedback will further improve user interaction, this has also not yet been realized.

[1185] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for recognizing the user's emotions and generating emotion data, means for converting the generated response text into voice data, and means for transmitting the voice data and emotion data to the terminal. This makes it possible to provide personalized responses based on the user's emotions as feedback in voice and 3D hologram form.

[1186] A "user" is a person who uses voice input to ask questions to the system.

[1187] A "terminal" is a device that captures the user's voice and sends it to a server, and uses the received voice data and emotion data to provide feedback to the user.

[1188] A "server" is a computer system that converts voice data into text data, analyzes it to generate appropriate responses, and further recognizes and analyzes the user's emotions.

[1189] "Voice data" refers to information that represents a user's voice input in digital format.

[1190] "Text data" refers to data represented as characters converted by speech recognition, and includes the content of the user's question.

[1191] "Generative artificial intelligence" is an artificial intelligence technology that analyzes text data to generate appropriate responses.

[1192] An "emotion engine" is software or a system that recognizes a user's emotions from voice data and generates emotion data.

[1193] "Emotional data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[1194] "Speech recognition artificial intelligence" is an artificial intelligence technology that converts speech data into text data.

[1195] A "3D hologram" is a device or technology that provides visual feedback to users by displaying three-dimensional images based on emotional data.

[1196] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[1197] User

[1198] The user operates the system and inputs their questions by voice into the terminal. For example, they might say to their smartphone, "Please tell me how to use the camera function on this smartphone."

[1199] terminal

[1200] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to a server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms. Specific processing includes the following:

[1201] Microphone: Records the user's voice and captures it as digital audio data.

[1202] Network interface: Sends captured audio data to the server.

[1203] Speaker: Plays audio data received from the server.

[1204] Hologram projection device: Adjusts and projects 3D holographic facial expressions based on emotional data.

[1205] server

[1206] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specific processing includes the following:

[1207] Speech recognition: The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert speech data into text data.

[1208] Question analysis: Analyzes the converted text data to understand the user's question.

[1209] Answer generation: Generative artificial intelligence (e.g., a generative AI model) is used to generate appropriate answers.

[1210] Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[1211] Speech conversion: The generated response text is converted into speech data using speech synthesis technology.

[1212] Data transmission: The generated voice data and emotion data are sent to the device.

[1213] Emotional Engine

[1214] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This allows the user's emotions to be reflected in voice responses and 3D holograms.

[1215] Specific example

[1216] Example 1: When asking about the camera function of a smartphone

[1217] 1. The user asks, "How do I use the camera function on this smartphone?" into the device's microphone.

[1218] 2. The device captures this audio and sends it to the server.

[1219] 3. The server uses speech recognition artificial intelligence to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[1220] 4. The server analyzes the text data using a generative AI model, understands the intent of the question, and generates an answer. For example, it might generate an answer such as, "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1221] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[1222] 6. The server converts the response text into audio data and sends the audio data and sentiment data to the terminal.

[1223] 7. The device plays audio data through its speaker and displays 3D holographic facial expressions based on emotional data. For example, it might respond in a friendly tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1224] Examples of prompts for generative AI models

[1225] Prompt: "How would you explain the camera function of a smartphone if a user asked about it?"

[1226] Expected output: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1227] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1228] Step 1:

[1229] The user inputs the question by voice. The user speaks the question into the device's microphone. For example, they might say, "Please tell me how to use the camera function on this smartphone." The input is recorded as voice data on the device.

[1230] Step 2:

[1231] The terminal captures audio data and sends it to the server. The terminal is equipped with a microphone for recording audio and a function to capture audio data in digital format. The captured audio data is sent to the server via the network interface. The input is audio data, and the output is the audio data sent to the server.

[1232] Step 3:

[1233] The server converts the audio data into text data. The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert the audio data into text data. The input is the captured audio data, and the output is text data. For example, the audio "Please tell me how to use the camera function on this smartphone" is converted to the text "Please tell me how to use the camera function on this smartphone".

[1234] Step 4:

[1235] The server analyzes text data and generates appropriate answers. The server uses generative artificial intelligence (e.g., a generative AI model) to analyze the converted text data and generate appropriate answers. The input is text data, and the output is the answer text. For example, in response to the question "How do I use the camera function on this smartphone?", it generates answer text such as "To use the camera function on this smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1236] Step 5:

[1237] The server recognizes the user's emotions and generates emotion data. Using the emotion engine installed on the server, it analyzes the user's emotions from the audio data. The input is audio data, and the output is emotion data. For example, it can recognize emotions such as "interested" or "confused" from the user's voice.

[1238] Step 6:

[1239] The server converts the generated response text into audio data. The server uses speech synthesis technology (e.g., speech synthesis AI) to convert the generated response text into audio data. The input is the response text, and the output is audio data. For example, the text "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen." will be converted into audio data.

[1240] Step 7:

[1241] The server sends voice data and emotion data to the terminal. The server sends the generated voice data and emotion data to the terminal via the network interface. The input is voice data and emotion data, and the output is the data sent to the terminal.

[1242] Step 8:

[1243] The device plays audio data and provides feedback via a 3D hologram. The device plays the received audio data through its speaker and further changes the expression of the 3D hologram based on emotion data. The input is audio data and emotion data received from the server, and the output is audio feedback and visual feedback. For example, the audio "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is played in a friendly tone, and the expression of the 3D hologram is displayed in a friendly manner.

[1244] (Application Example 2)

[1245] 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."

[1246] While there is a need to efficiently learn and implement maintenance and operating procedures within factories, conventional manuals and simple voice guidance systems struggle to provide flexible responses tailored to user understanding and on-site conditions. Furthermore, they often lack appropriate feedback that reflects user emotions and comprehension, potentially leading to decreased efficiency and safety in actual operations. To address these challenges, a system is needed that can recognize user emotions and provide personalized guidance tailored to individual situations.

[1247] 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.

[1248] In this invention, the server includes means for converting audio data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into audio data, means for analyzing the user's emotions from the audio data using an emotion engine, and means for changing the tone of the response and the facial expressions of the 3D hologram according to the user's emotions. This enables personalized maintenance and operation procedure guidance that takes into account the user's emotions and level of understanding.

[1249] A "user" refers to a person who operates this system and inputs questions using voice input.

[1250] "Voice input" refers to the act of a user using a microphone to communicate questions or instructions to a system by voice.

[1251] "Capture" refers to the process of taking in and recording audio input.

[1252] A "server" refers to a remote computing device that processes audio data, converts it to text data, analyzes questions, generates answers, and performs sentiment analysis.

[1253] "Voice data" refers to the captured voice input of the user.

[1254] "Text data" refers to audio data converted into written text.

[1255] "Generative artificial intelligence" refers to advanced machine learning models that analyze questions and generate appropriate answers.

[1256] "Speech recognition artificial intelligence" refers to a machine learning model used to convert speech data into text data.

[1257] An "emotion engine" refers to a system that analyzes emotions from a user's voice data and generates emotional data.

[1258] A "3D hologram" refers to a three-dimensional visual representation displayed in space.

[1259] "Response tone" refers to the emotional expression used in the generated voice response.

[1260] This invention is a system for efficiently learning and implementing maintenance and operating procedures within a factory. The system consists of user, terminal, server, and emotion engine components. The details of each component and their specific operation are described below.

[1261] User

[1262] The user operates the system and inputs questions by voice into the terminal. For example, the user might say to the terminal, "Please tell me the maintenance procedure for this machine." This voice input initiates the system's operation.

[1263] terminal

[1264] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also has a speaker and a hologram projection device for playing back the voice data received from the server and the 3D hologram.

[1265] Typical hardware examples include the following:

[1266] Microphone: A highly sensitive voice input device.

[1267] Speaker: A device that reproduces sound clearly.

[1268] Hologram projector: Displays 3D holograms.

[1269] server

[1270] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specifically, it uses the following software services:

[1271] Speech Recognition AI: Converts speech data into text data using Microsoft Azure Cognitive Services.

[1272] Generative AI: Uses OpenAI GPT-4 to analyze text data and generate appropriate responses.

[1273] Emotion Engine: Analyzes emotions from the user's voice and generates emotion data.

[1274] Specific server processing:

[1275] 1. Speech Recognition: The server uses speech recognition AI to convert speech data into text data. Example: "Please use Azure's speech recognition API to convert this speech data to text."

[1276] 2. Question Analysis and Answer Generation: Use a generative AI model to analyze text data and generate appropriate answers. Example: "Using GPT-4, analyze the following question and generate appropriate maintenance procedures: 'Please tell me the maintenance procedures for this machine.'"

[1277] 3. Emotion Recognition: Use an emotion engine to analyze the user's emotions from voice data and generate emotion data. Example: "Analyze the user's emotions (e.g., interested, confused) from their voice data and generate emotion data."

[1278] Emotional Engine

[1279] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This generated emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram. For example, if the user is confused, the system will respond in a more polite and friendly tone. Specifically, the generated response text is converted into voice data, and the tone is adjusted based on the emotion data.

[1280] Specific example

[1281] For example, if a user asks, "Please tell me the maintenance procedure for this machine," the system will operate as follows:

[1282] 1. The user asks a question into the device's microphone.

[1283] 2. The device captures this audio and sends it to the server.

[1284] 3. The server uses speech recognition AI to convert the audio data into text and analyze the content of the question.

[1285] 4. Generative AI generates appropriate answers based on the analysis results.

[1286] 5. The emotion engine analyzes the user's emotions and adjusts the tone of responses and the facial expressions of the hologram accordingly.

[1287] 6. The device plays the generated audio data and displays the hologram.

[1288] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[1289] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1290] Step 1:

[1291] The user enters the question by voice.

[1292] The user operates the system and inputs their question by voice into the device's microphone. This voice input initiates the system's processing.

[1293] Input: User's voice

[1294] Output: Captured audio data

[1295] Step 2:

[1296] The device captures audio and sends it to the server.

[1297] The device captures the user's voice using a microphone and sends this audio data to the server via a network interface.

[1298] Input: Captured audio data

[1299] Output: Audio data sent to the server

[1300] Step 3:

[1301] The server converts the audio data into text data.

[1302] The server uses speech recognition AI (e.g., Microsoft Azure Cognitive Services) to convert the audio data into text data. The specific prompt is, "Please use the Azure speech recognition API to convert this audio data to text."

[1303] Input: Audio data sent to the server

[1304] Output: Converted text data

[1305] Step 4:

[1306] The server analyzes the text data and generates the appropriate response.

[1307] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze text data and generate appropriate responses. The specific prompt is: "Use GPT-4 to analyze the following question and generate appropriate maintenance instructions: 'Please tell me the maintenance instructions for this machine.'"

[1308] Input: Converted text data

[1309] Output: Generated answer text

[1310] Step 5:

[1311] The server analyzes the user's emotions and generates emotional data.

[1312] The server uses an emotion engine to analyze the user's emotions from voice data and generate emotion data. Specifically, it analyzes characteristics such as the tone, volume, and speed of the user's voice. Example: "Analyze the user's voice data to determine their emotions (e.g., interested, confused) and generate emotion data."

[1313] Input: Audio data

[1314] Output: Sentiment data

[1315] Step 6:

[1316] The server converts the response text into audio data and adjusts the tone based on sentiment data.

[1317] The server converts the generated response text into audio data and adjusts the tone based on sentiment data. This sentiment data helps create user-friendly feedback, such as a more approachable or polite tone.

[1318] Input: Generated response text, sentiment data

[1319] Output: Voice data adjusted based on emotion

[1320] Step 7:

[1321] The server sends the audio data to the terminal.

[1322] The server sends the response audio data and emotion data to the terminal via the network interface.

[1323] Input: Voice data adjusted based on emotion

[1324] Output: Audio data sent to the terminal

[1325] Step 8:

[1326] The device plays audio data and displays a 3D hologram.

[1327] The device plays audio data received from the server through its speaker and displays a 3D hologram based on the emotional data. For example, if the user is in a state of "confusion," the hologram will display a more friendly expression and respond in a more polite voice.

[1328] Input: Voice data and emotion data sent to the device.

[1329] Output: Audio and 3D hologram played for the user

[1330] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[1331] 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.

[1332] 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.

[1333] 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.

[1334] [Fourth Embodiment]

[1335] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1336] 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.

[1337] 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).

[1338] 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.

[1339] 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.

[1340] 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).

[1341] 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.

[1342] 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.

[1343] 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.

[1344] 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.

[1345] 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.

[1346] 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.

[1347] 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".

[1348] The present invention is a system in which a user inputs a question by voice, which is then processed using voice AI and generative AI, and the results are provided visually and audibly as a 3D hologram. The system of the present invention consists of the following components: a user, a terminal, and a server.

[1349] Components and operation

[1350] User

[1351] The user operates the system and inputs their questions by voice into the terminal. This voice input initiates the system's operation.

[1352] terminal

[1353] The terminal is equipped with a microphone for user voice input and a network interface for capturing voice data and sending it to the server. It also has a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[1354] 1. Capture audio data

[1355] 2. Sending audio data to the server

[1356] 3. Playback of audio data received from the server.

[1357] 4. Display of 3D holograms

[1358] server

[1359] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[1360] 1. Speech recognition: Converts speech data into text data.

[1361] 2. Question Analysis: Analyze text data to understand the user's questions.

[1362] 3. Answer generation: Generator AI is used to generate appropriate answers.

[1363] 4. Speech Conversion: Converts the generated response text into audio data.

[1364] 5. Sending audio data to the terminal

[1365] Specific example

[1366] Example 1: Asking about the camera function of a smartphone

[1367] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[1368] 2. The device captures this audio and sends it to the server.

[1369] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[1370] 4. The server uses generative AI to analyze this text and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1371] 5. The server converts this response text into audio data using voice AI and sends the audio data to the terminal.

[1372] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1373] This process allows users to obtain sufficient information through high-quality visual and audio. This enables users to receive specific and easy-to-understand instructions on how to use the product or service.

[1374] The following describes the processing flow.

[1375] Step 1:

[1376] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[1377] Step 2:

[1378] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[1379] Step 3:

[1380] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[1381] Step 4:

[1382] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[1383] Step 5:

[1384] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the intent of the question. It then generates an answer to the user's question.

[1385] Step 6:

[1386] The server uses the response calculated by the generative AI to convert the text into audio data. Specifically, it generates audio data that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1387] Step 7:

[1388] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[1389] Step 8:

[1390] The device plays the received audio data and provides audio feedback to the user through its speaker. Simultaneously, a 3D hologram display device projects a hologram character that says, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1391] This allows users to obtain specific answers to their questions visually and audibly. Because this system can respond quickly and accurately to a wide range of questions, it can significantly improve the user experience.

[1392] (Example 1)

[1393] 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".

[1394] Conventional information provision systems lack the means to provide visual and intuitive answers to questions entered by users via voice. Furthermore, there is a need for a system that can efficiently process the voice data entered by users accurately and quickly, generate appropriate answers, and provide them. Moreover, a system capable of providing highly accurate and appropriate answers even to complex questions is required.

[1395] 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.

[1396] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into voice data, and means for transmitting the voice data and 3D hologram data to the terminal. This makes it possible for a user to simply input a question by voice and receive a highly accurate visual and audible response to that question.

[1397] "Voice input" refers to the user using their voice to communicate questions or instructions to the device.

[1398] "Capture" refers to the electronic acquisition of audio data and other input data.

[1399] A "server" refers to a centralized computer system that performs functions such as processing, analyzing, and generating responses for audio data.

[1400] "Voice data" refers to data that records the user's voice in digital format.

[1401] "Text data" refers to data that includes character information converted from audio data.

[1402] "Generative artificial intelligence" refers to artificial intelligence technology used to generate appropriate answers to questions.

[1403] "Speech recognition artificial intelligence" refers to artificial intelligence technology used to convert speech data into text data.

[1404] "Speech conversion" refers to the process of converting text data into audio data.

[1405] "3D hologram" refers to a technology that projects three-dimensional, stereoscopic images.

[1406] A "terminal" refers to a device used by a user to input voice and to display voice data and 3D holograms.

[1407] This invention is a system in which a user inputs a question by voice, and the system utilizes speech recognition artificial intelligence and generative artificial intelligence to provide an answer to that question in the form of both voice and a 3D hologram. The system consists of a user, a terminal, and a server.

[1408] System Components

[1409] User

[1410] The user speaks their question into the device's microphone. This voice input initiates the system's operation. As a concrete example, consider a scenario where the user says, "Please tell me how to use the camera function on this smartphone."

[1411] terminal

[1412] The device is equipped with a microphone to receive the user's voice, a network interface (e.g., Wi-Fi or 4G / 5G) to send the captured audio data to the server, a speaker to play the audio data received from the server, and a 3D hologram projection device to visually display the response.

[1413] server

[1414] The server hosts speech recognition artificial intelligence (e.g., Google Cloud Speech-to-Text and AWS Transcribe) and generative artificial intelligence (e.g., OpenAI GPT-3 and BERT) to process the received audio data. The server provides the following functions:

[1415] 1. Speech Recognition: Converts speech data received from the device into text data.

[1416] 2. Question Analysis: Analyze the converted text data to understand the user's question.

[1417] 3. Answer generation: Generate appropriate answers to user questions.

[1418] 4. Speech Conversion: Convert the generated response text into audio data.

[1419] 5. Data transmission: The generated audio data and 3D hologram data are sent to the terminal.

[1420] Specific example

[1421] Example 1: Asking about the camera function of a smartphone

[1422] 1. The user asks into the microphone, "How do I use the camera function on this smartphone?"

[1423] 2. The device captures this audio and sends it to the server.

[1424] 3. The server uses speech recognition artificial intelligence to convert the voice data into text data and generates the text message, "Please tell me how to use the camera function on this smartphone."

[1425] 4. The server uses generative artificial intelligence to analyze the text data and generates the response text: "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1426] 5. The server converts this response text into audio data and sends the audio data and 3D hologram data to the terminal.

[1427] 6. The device plays this audio data and displays a 3D hologram saying, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1428] Example of a prompt

[1429] User: "How do I use the camera function on this smartphone?"

[1430] System: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1431] This system allows users to quickly obtain high-quality visual and auditory information, making it easy to understand how to use products and services.

[1432] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1433] Step 1:

[1434] The user speaks a question into the device's microphone. For example, they might ask, "How do I use the camera function on this smartphone?" This voice input initiates the system's operation.

[1435] Step 2:

[1436] The device captures the user's voice using its microphone. Specifically, it converts the voice into digital format as audio data.

[1437] Input: User's voice

[1438] Operation: Capture and digitize audio data using a microphone.

[1439] Output: Digital audio data

[1440] Step 3:

[1441] The device transmits the captured audio data to the server via a network interface (e.g., Wi-Fi or 4G / 5G).

[1442] Input: Digital audio data

[1443] Operation: Send voice data using the network interface.

[1444] Output: Audio data sent to the server

[1445] Step 4:

[1446] The server converts the received audio data into text data using speech recognition artificial intelligence (for example, Google Cloud Speech-to-Text or AWS Transcribe).

[1447] Input: Audio data sent to the server

[1448] Operation: Convert audio data to text data using speech recognition AI.

[1449] Output: Text data (Example: "Please tell me how to use the camera function on this smartphone.")

[1450] Step 5:

[1451] The server uses generative artificial intelligence (such as OpenAI GPT-3 or BERT) to analyze text data and understand the user's question. It then extracts key keywords and the gist of the question.

[1452] Input: Text data obtained from speech recognition

[1453] Operation: Use generative AI to analyze text data and understand the intent of the question.

[1454] Output: Understanding the question and extracting necessary information

[1455] Step 6:

[1456] The server uses generative AI to generate the best possible answer to a question. For example, it can generate text explaining "how to use the camera function on a smartphone."

[1457] Input: Understanding the question and related information

[1458] Operation: Generate response text using a generative AI.

[1459] Output: Generated answer text (Example: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen.")

[1460] Step 7:

[1461] The server converts the generated response text into speech data using speech AI (for example, Google Text-to-Speech or Amazon Polly).

[1462] Input: Generated response text

[1463] Operation: Convert text data to speech data using voice AI.

[1464] Output: Generated audio data

[1465] Step 8:

[1466] The server sends the generated audio data and 3D hologram data to the terminal.

[1467] Input: Generated audio data and 3D hologram data

[1468] Operation: Send data to the terminal using a data transmission protocol (e.g., HTTPS).

[1469] Output: Audio data and 3D hologram data sent to the terminal.

[1470] Step 9:

[1471] The device plays the received audio data through its speaker. Specifically, it explains, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1472] Input: Audio data sent from the server

[1473] Operation: Play audio data through the speaker.

[1474] Output: Played audio

[1475] Step 10:

[1476] The device displays the received 3D hologram data using a hologram projection device. Specifically, it displays a hologram that visually shows the operating procedures for the smartphone.

[1477] Input: 3D hologram data sent from the server

[1478] Operation: Display data using a hologram projector.

[1479] Output: Displayed 3D hologram

[1480] This process allows users to intuitively obtain information from both audio and visual sources.

[1481] (Application Example 1)

[1482] 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".

[1483] In physical stores, there is a lack of means for customers to quickly and visually obtain information about products. Traditional methods require customers to ask store staff directly or read product labels, which are time-consuming and may not provide satisfactory information. Furthermore, in today's world where contactless interactions are required, there is a need for more efficient and hygienic means of providing information. This invention aims to solve these problems and provide a system that delivers information to customers in an intuitive and visual manner.

[1484] 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.

[1485] In this invention, the server includes means for the user to input a question by voice, means for capturing the voice input and sending it to the server, means for the server to convert the voice data into text data, means for analyzing the text data to generate an appropriate answer, means for converting the generated answer text into voice data, means for sending the voice data to a terminal, means for the terminal to play the voice data and for a 3D hologram to display the answer, means for analysis to provide product information based on the user's question, and means for visually presenting the analysis results as a 3D hologram. This enables customers to instantly obtain product information through voice input in a physical store and to understand it visually through a 3D hologram.

[1486] A "user" is a person who operates the system and uses voice input.

[1487] "Voice input" refers to the act of a user giving questions or instructions to a system by voice through a microphone.

[1488] "Capture" refers to the process of acquiring audio input in digital format and saving it as data.

[1489] A "server" is a central control unit that processes audio data, converts it to text data, and generates responses using generative artificial intelligence.

[1490] "Text data" refers to the representation of voice input as text information through speech recognition.

[1491] "Generative artificial intelligence" is a technology that uses natural language processing based on input text data to create appropriate answers to questions.

[1492] "Answer text" refers to the textual information generated by a generative artificial intelligence system in response to a user's question.

[1493] "Audio data" refers to audio information generated from text data using speech synthesis technology.

[1494] A "terminal" is a device used by a user, and includes equipment such as a microphone, speaker, and 3D hologram projection device.

[1495] "Playback" is the process of outputting audio data as actual sound through a speaker.

[1496] A "3D hologram" is a technology that visually presents the answer content as a three-dimensional, stereoscopic image.

[1497] "Product information" refers to detailed information about products sold in physical stores, such as their characteristics, usage instructions, stock availability, and price.

[1498] "Analysis" is the process of processing data based on user input to generate appropriate answers or information.

[1499] "Presentation" refers to the act of visually showing the analysis results to the user.

[1500] Embodiments for carrying out this invention are described below.

[1501] The system of this invention allows users to ask questions via voice input and provides visual answers to those questions in the form of 3D holograms. The main components consist of a user, a terminal, and a server.

[1502] Hardware configuration

[1503] 1. User's terminal

[1504] Smart glasses (with HUD function), smartphone, or tablet

[1505] Microphone and speaker

[1506] 3D hologram projection device (e.g., HoloLens)

[1507] 2. Server

[1508] Speech recognition API (e.g., Google Cloud Speech-to-Text)

[1509] Generative AI (e.g. OpenAI GPT-4)

[1510] 3D hologram generation software (e.g., Unity 3D)

[1511] Database (e.g., Firebase)

[1512] Software Processing

[1513] From voice input to text conversion

[1514] 1. The user asks a question into the microphone of the smart glasses.

[1515] For example, a user might ask, "What material is this sofa made of?"

[1516] Capture and transmit audio data

[1517] 2. The device captures the user's voice and sends it to the server in digital format.

[1518] Speech recognition and analysis

[1519] 3. The server uses the Google Cloud Speech-to-Text API to convert the audio data into text data. The text data generated is "What material is this sofa made of?".

[1520] Question analysis and answer generation

[1521] 4. The server inputs text data into OpenAI GPT-4 and uses a generative AI to analyze the question content.

[1522] The generative AI will generate the answer "The materials of this sofa are high-quality leather and memory foam" to this question.

[1523] Voice conversion and data transmission

[1524] 5. The server converts the generated response text into audio data using the Google Cloud Text-to-Speech API and sends this audio data to the device.

[1525] 3D hologram display

[1526] 6. The terminal plays the received audio data and uses a 3D hologram projection device to visually display the response, "The material of this sofa is high-quality leather and memory foam."

[1527] Specific example

[1528] Consider a scenario where a user is in a furniture store, wearing smart glasses, and asks a question by voice: "What material is this sofa made of?" The smart glasses capture this question and send it to a server. The server uses a speech recognition API to convert the question into text, and then uses generative AI to analyze it and generate an appropriate answer. This answer is sent to the device as audio data and 3D hologram data, and displayed in the user's field of view.

[1529] Example of a prompt

[1530] User: Voice input "What material is this sofa made of?"

[1531] System: Analyzing...

[1532] System: Answer: "The materials for this sofa are high-quality leather and memory foam."

[1533] Display: 3D hologram visually describes the details of the sofa.

[1534] The system of this invention enables users to quickly and intuitively obtain and visually understand product information within a physical store. This results in more efficient and effective information delivery compared to conventional methods.

[1535] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1536] Step 1:

[1537] The user performs voice input. The user speaks their question into the microphone of the smart glasses. For example, they might ask, "What material is this sofa made of?"

[1538] Input: User's voice question

[1539] Output: Captured audio data

[1540] Step 2:

[1541] The device captures audio data and sends it to the server. The smart glasses (device) capture the user's voice digitally through the microphone and send it to the server via the network.

[1542] Input: Captured audio data

[1543] Output: Audio data sent to the server

[1544] Step 3:

[1545] The server converts the audio data into text data. The server uses the Google Cloud Speech-to-Text API to convert the transmitted audio data into text data. At this point, the audio data becomes the text "What material is this sofa made of?".

[1546] Input: Audio data sent to the server

[1547] Output: Text data

[1548] Step 4:

[1549] The server analyzes the text data and generates an answer. The server uses OpenAI GPT-4 to analyze the converted text data and generate an appropriate answer based on the user's question. In this case, it generates the answer, "The material of this sofa is high-quality leather and memory foam."

[1550] Input: Text data

[1551] Output: Answer text

[1552] Step 5:

[1553] The server converts the generated response text into audio data. The server uses the Google Cloud Text-to-Speech API to convert the generated response text into audio data. At this time, the response text "This sofa is made of high-quality leather and memory foam." is converted into audio data.

[1554] Input: Answer text

[1555] Output: Audio data

[1556] Step 6:

[1557] The server sends audio data to the terminal. The server sends the generated audio data to the terminal via the network.

[1558] Input: Audio data

[1559] Output: Audio data sent to the terminal

[1560] Step 7:

[1561] The device plays the received audio data and displays a 3D hologram. The device (smart glasses) plays the received audio data and simultaneously uses a 3D hologram projector to visually display the answer. In this case, the audio plays "The material of this sofa is high-quality leather and memory foam," and the 3D hologram visually presents details about the sofa's materials.

[1562] Input: Audio data sent to the terminal

[1563] Output: Played audio data and displayed 3D hologram

[1564] 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.

[1565] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[1566] Components and operation

[1567] User

[1568] The user operates the system and inputs questions by voice into a terminal. The user's emotions are also analyzed through this voice input.

[1569] terminal

[1570] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms from the server. The terminal performs the following processes:

[1571] 1. Capture audio data

[1572] 2. Sending audio data to the server

[1573] 3. Playback of audio data received from the server.

[1574] 4. Display of 3D holograms

[1575] server

[1576] The server hosts voice AI and generative AI and processes voice data sent from the terminal. The server performs the following processes:

[1577] 1. Speech recognition: Converts speech data into text data.

[1578] 2. Question Analysis: Analyze text data to understand the user's questions.

[1579] 3. Answer generation: Generator AI is used to generate appropriate answers.

[1580] 4. Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[1581] 5. Speech Conversion: Converts the generated response text into audio data.

[1582] 6. Sending audio data to the terminal

[1583] Emotional Engine

[1584] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram.

[1585] Specific example

[1586] Example 1: Asking about the camera function of a smartphone

[1587] 1. The user asks the question, "How do I use the camera function on this smartphone?" into the device's microphone.

[1588] 2. The device captures this audio and sends it to the server.

[1589] 3. The server uses speech recognition AI to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[1590] 4. The server passes the converted text data to a generative AI, which analyzes the intent of the question and generates an answer.

[1591] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[1592] 6. The server converts the generated response text into audio data and sends the audio data and sentiment data to the terminal.

[1593] 7. The device plays audio data and provides feedback to the user through the speaker. It also changes the expression of the 3D hologram based on emotional data and responds in a friendly tone that matches the user's emotions, saying, "To use the smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1594] This allows users to receive specific and emotionally sensitive answers to their questions. By combining this with an emotion engine, a more personalized user experience can be achieved.

[1595] The following describes the processing flow.

[1596] Step 1:

[1597] The user voice-inputs their question into the device's microphone. Specifically, they might say, "Please tell me how to use the camera function on this smartphone."

[1598] Step 2:

[1599] The device captures audio data from the microphone. This audio data is temporarily stored on the device in digital format.

[1600] Step 3:

[1601] The device sends the captured audio data to the server. Specifically, it converts the audio data to an appropriate format and transfers it to the server using a network protocol (e.g., HTTP or WebSocket).

[1602] Step 4:

[1603] The server analyzes the received audio data using speech recognition AI and converts it into text data. During this process, the speech recognition engine operates and generates the text, "Please tell me how to use the camera function on this smartphone."

[1604] Step 5:

[1605] The server passes the converted text data to the generative AI. The generative AI analyzes this text data and understands the user's question. It then generates an answer to the user's question.

[1606] Step 6:

[1607] The server uses the answer calculated by the generative AI to re-analyze the text and verify that the answer is appropriate. At this point, the text "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is obtained.

[1608] Step 7:

[1609] The server converts this response text into audio data. Specifically, it uses a speech synthesis engine to convert the text into speech and generates the audio data, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1610] Step 8:

[1611] The server sends the generated audio data to the terminal. The audio data is then sent back to the terminal via the network protocol.

[1612] Step 9:

[1613] The server activates an emotion engine along with the voice data and analyzes the user's emotions from the voice data. Specifically, it uses information such as the tone, speed, and rhythm of the voice to generate emotion data such as "interest" and "confusion."

[1614] Step 10:

[1615] The server sends emotional data to the terminal simultaneously with the audio data.

[1616] Step 11:

[1617] The device plays back the received audio data and provides audio feedback to the user through the speaker. Simultaneously, it changes the facial expression of the 3D hologram based on emotional data. For example, if the user is confused, the hologram character will say in a friendly expression and tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1618] This process allows users to receive specific and emotionally sensitive answers to their questions, both visually and audibly. The entire system is designed to work seamlessly together, maximizing the user experience.

[1619] (Example 2)

[1620] 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".

[1621] Conventional voice dialogue systems are required not only to generate appropriate responses to voice input, but also to recognize the user's emotions and provide feedback based on those emotions. However, previous systems have been unable to recognize emotions, resulting in a limited user experience and difficulty in providing personalized responses. Furthermore, while it is expected that using 3D holograms as visual feedback will further improve user interaction, this has also not yet been realized.

[1622] The identification processing performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for converting voice data into text data, means for analyzing the text data to generate an appropriate response, means for recognizing the user's emotions and generating emotion data, means for converting the generated response text into voice data, and means for transmitting the voice data and emotion data to the terminal. This makes it possible to provide personalized responses based on the user's emotions as feedback in voice and 3D hologram form.

[1623] A "user" is a person who uses voice input to ask questions to the system.

[1624] A "terminal" is a device that captures the user's voice and sends it to a server, and uses the received voice data and emotion data to provide feedback to the user.

[1625] A "server" is a computer system that converts voice data into text data, analyzes it to generate appropriate responses, and further recognizes and analyzes the user's emotions.

[1626] "Voice data" refers to information that represents a user's voice input in digital format.

[1627] "Text data" refers to data represented as characters converted by speech recognition, and includes the content of the user's question.

[1628] "Generative artificial intelligence" is an artificial intelligence technology that analyzes text data to generate appropriate responses.

[1629] An "emotion engine" is software or a system that recognizes a user's emotions from voice data and generates emotion data.

[1630] "Emotional data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[1631] "Speech recognition artificial intelligence" is an artificial intelligence technology that converts speech data into text data.

[1632] A "3D hologram" is a device or technology that provides visual feedback to users by displaying three-dimensional images based on emotional data.

[1633] The present invention is a system in which a user inputs a question by voice, the voice data is analyzed to generate an appropriate answer, and further, an emotion engine that recognizes the user's emotions is combined to provide visual and audible feedback. The system of the present invention consists of the user, a terminal, a server, and an emotion engine.

[1634] User

[1635] The user operates the system and inputs their questions by voice into the terminal. For example, they might say to their smartphone, "Please tell me how to use the camera function on this smartphone."

[1636] terminal

[1637] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to a server. It also includes a speaker and hologram projection device for playing back the received voice data and 3D holograms. Specific processing includes the following:

[1638] Microphone: Records the user's voice and captures it as digital audio data.

[1639] Network interface: Sends captured audio data to the server.

[1640] Speaker: Plays audio data received from the server.

[1641] Hologram projection device: Adjusts and projects 3D holographic facial expressions based on emotional data.

[1642] server

[1643] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specific processing includes the following:

[1644] Speech recognition: The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert speech data into text data.

[1645] Question analysis: Analyzes the converted text data to understand the user's question.

[1646] Answer generation: Generative artificial intelligence (e.g., a generative AI model) is used to generate appropriate answers.

[1647] Emotion Recognition: An emotion engine is used to analyze the user's emotions and generate emotion data.

[1648] Speech conversion: The generated response text is converted into speech data using speech synthesis technology.

[1649] Data transmission: The generated voice data and emotion data are sent to the device.

[1650] Emotional Engine

[1651] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This allows the user's emotions to be reflected in voice responses and 3D holograms.

[1652] Specific example

[1653] Example 1: When asking about the camera function of a smartphone

[1654] 1. The user asks, "How do I use the camera function on this smartphone?" into the device's microphone.

[1655] 2. The device captures this audio and sends it to the server.

[1656] 3. The server uses speech recognition artificial intelligence to convert the speech into text and generates the text data, "Please tell me how to use the camera function on this smartphone."

[1657] 4. The server analyzes the text data using a generative AI model, understands the intent of the question, and generates an answer. For example, it might generate an answer such as, "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1658] 5. The server uses an emotion engine to analyze the user's emotions from the voice data and generates emotion data such as "interested" or "confused."

[1659] 6. The server converts the response text into audio data and sends the audio data and sentiment data to the terminal.

[1660] 7. The device plays audio data through its speaker and displays 3D holographic facial expressions based on emotional data. For example, it might respond in a friendly tone, "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1661] Examples of prompts for generative AI models

[1662] Prompt: "How would you explain the camera function of a smartphone if a user asked about it?"

[1663] Expected output: "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen."

[1664] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1665] Step 1:

[1666] The user inputs the question by voice. The user speaks the question into the device's microphone. For example, they might say, "Please tell me how to use the camera function on this smartphone." The input is recorded as voice data on the device.

[1667] Step 2:

[1668] The terminal captures audio data and sends it to the server. The terminal is equipped with a microphone for recording audio and a function to capture audio data in digital format. The captured audio data is sent to the server via the network interface. The input is audio data, and the output is the audio data sent to the server.

[1669] Step 3:

[1670] The server converts the audio data into text data. The server uses speech recognition AI (e.g., speech recognition artificial intelligence) to convert the audio data into text data. The input is the captured audio data, and the output is text data. For example, the audio "Please tell me how to use the camera function on this smartphone" is converted to the text "Please tell me how to use the camera function on this smartphone".

[1671] Step 4:

[1672] The server analyzes text data and generates appropriate answers. The server uses generative artificial intelligence (e.g., a generative AI model) to analyze the converted text data and generate appropriate answers. The input is text data, and the output is the answer text. For example, in response to the question "How do I use the camera function on this smartphone?", it generates answer text such as "To use the camera function on this smartphone, first launch the camera app and press the shutter button at the bottom of the screen."

[1673] Step 5:

[1674] The server recognizes the user's emotions and generates emotion data. Using the emotion engine installed on the server, it analyzes the user's emotions from the audio data. The input is audio data, and the output is emotion data. For example, it can recognize emotions such as "interested" or "confused" from the user's voice.

[1675] Step 6:

[1676] The server converts the generated response text into audio data. The server uses speech synthesis technology (e.g., speech synthesis AI) to convert the generated response text into audio data. The input is the response text, and the output is audio data. For example, the text "To use the camera function of your smartphone, first launch the camera app and press the shutter button at the bottom of the screen." will be converted into audio data.

[1677] Step 7:

[1678] The server sends voice data and emotion data to the terminal. The server sends the generated voice data and emotion data to the terminal via the network interface. The input is voice data and emotion data, and the output is the data sent to the terminal.

[1679] Step 8:

[1680] The device plays audio data and provides feedback via a 3D hologram. The device plays the received audio data through its speaker and further changes the expression of the 3D hologram based on emotion data. The input is audio data and emotion data received from the server, and the output is audio feedback and visual feedback. For example, the audio "To use your smartphone's camera function, first launch the camera app and press the shutter button at the bottom of the screen." is played in a friendly tone, and the expression of the 3D hologram is displayed in a friendly manner.

[1681] (Application Example 2)

[1682] 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".

[1683] While there is a need to efficiently learn and implement maintenance and operating procedures within factories, conventional manuals and simple voice guidance systems struggle to provide flexible responses tailored to user understanding and on-site conditions. Furthermore, they often lack appropriate feedback that reflects user emotions and comprehension, potentially leading to decreased efficiency and safety in actual operations. To address these challenges, a system is needed that can recognize user emotions and provide personalized guidance tailored to individual situations.

[1684] 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.

[1685] In this invention, the server includes means for converting audio data into text data, means for analyzing the text data to generate an appropriate response, means for converting the generated response text into audio data, means for analyzing the user's emotions from the audio data using an emotion engine, and means for changing the tone of the response and the facial expressions of the 3D hologram according to the user's emotions. This enables personalized maintenance and operation procedure guidance that takes into account the user's emotions and level of understanding.

[1686] A "user" refers to a person who operates this system and inputs questions using voice input.

[1687] "Voice input" refers to the act of a user using a microphone to communicate questions or instructions to a system by voice.

[1688] "Capture" refers to the process of taking in and recording audio input.

[1689] A "server" refers to a remote computing device that processes audio data, converts it to text data, analyzes questions, generates answers, and performs sentiment analysis.

[1690] "Voice data" refers to the captured voice input of the user.

[1691] "Text data" refers to audio data converted into written text.

[1692] "Generative artificial intelligence" refers to advanced machine learning models that analyze questions and generate appropriate answers.

[1693] "Speech recognition artificial intelligence" refers to a machine learning model used to convert speech data into text data.

[1694] An "emotion engine" refers to a system that analyzes emotions from a user's voice data and generates emotional data.

[1695] A "3D hologram" refers to a three-dimensional visual representation displayed in space.

[1696] "Response tone" refers to the emotional expression used in the generated voice response.

[1697] This invention is a system for efficiently learning and implementing maintenance and operating procedures within a factory. The system consists of user, terminal, server, and emotion engine components. The details of each component and their specific operation are described below.

[1698] User

[1699] The user operates the system and inputs questions by voice into the terminal. For example, the user might say to the terminal, "Please tell me the maintenance procedure for this machine." This voice input initiates the system's operation.

[1700] terminal

[1701] The terminal is equipped with a microphone for inputting the user's voice and a network interface for capturing voice data and sending it to the server. It also has a speaker and a hologram projection device for playing back the voice data received from the server and the 3D hologram.

[1702] Typical hardware examples include the following:

[1703] Microphone: A highly sensitive voice input device.

[1704] Speaker: A device that reproduces sound clearly.

[1705] Hologram projector: Displays 3D holograms.

[1706] server

[1707] The server hosts voice AI and generative AI and processes voice data sent from the terminal. Specifically, it uses the following software services:

[1708] Speech Recognition AI: Converts speech data into text data using Microsoft Azure Cognitive Services.

[1709] Generative AI: Uses OpenAI GPT-4 to analyze text data and generate appropriate responses.

[1710] Emotion Engine: Analyzes emotions from the user's voice and generates emotion data.

[1711] Specific server processing:

[1712] 1. Speech Recognition: The server uses speech recognition AI to convert speech data into text data. Example: "Please use Azure's speech recognition API to convert this speech data to text."

[1713] 2. Question Analysis and Answer Generation: Use a generative AI model to analyze text data and generate appropriate answers. Example: "Using GPT-4, analyze the following question and generate appropriate maintenance procedures: 'Please tell me the maintenance procedures for this machine.'"

[1714] 3. Emotion Recognition: Use an emotion engine to analyze the user's emotions from voice data and generate emotion data. Example: "Analyze the user's emotions (e.g., interested, confused) from their voice data and generate emotion data."

[1715] Emotional Engine

[1716] The emotion engine analyzes the user's emotions from voice data and generates emotion data. This generated emotion data is reflected in the tone of the response and the facial expressions of the 3D hologram. For example, if the user is confused, the system will respond in a more polite and friendly tone. Specifically, the generated response text is converted into voice data, and the tone is adjusted based on the emotion data.

[1717] Specific example

[1718] For example, if a user asks, "Please tell me the maintenance procedure for this machine," the system will operate as follows:

[1719] 1. The user asks a question into the device's microphone.

[1720] 2. The device captures this audio and sends it to the server.

[1721] 3. The server uses speech recognition AI to convert the audio data into text and analyze the content of the question.

[1722] 4. Generative AI generates appropriate answers based on the analysis results.

[1723] 5. The emotion engine analyzes the user's emotions and adjusts the tone of responses and the facial expressions of the hologram accordingly.

[1724] 6. The device plays the generated audio data and displays the hologram.

[1725] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[1726] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1727] Step 1:

[1728] The user enters the question by voice.

[1729] The user operates the system and inputs their question by voice into the device's microphone. This voice input initiates the system's processing.

[1730] Input: User's voice

[1731] Output: Captured audio data

[1732] Step 2:

[1733] The device captures audio and sends it to the server.

[1734] The device captures the user's voice using a microphone and sends this audio data to the server via a network interface.

[1735] Input: Captured audio data

[1736] Output: Audio data sent to the server

[1737] Step 3:

[1738] The server converts the audio data into text data.

[1739] The server uses speech recognition AI (e.g., Microsoft Azure Cognitive Services) to convert the audio data into text data. The specific prompt is, "Please use the Azure speech recognition API to convert this audio data to text."

[1740] Input: Audio data sent to the server

[1741] Output: Converted text data

[1742] Step 4:

[1743] The server analyzes the text data and generates the appropriate response.

[1744] The server uses a generative AI model (e.g., OpenAI GPT-4) to analyze text data and generate appropriate responses. The specific prompt is: "Use GPT-4 to analyze the following question and generate appropriate maintenance instructions: 'Please tell me the maintenance instructions for this machine.'"

[1745] Input: Converted text data

[1746] Output: Generated answer text

[1747] Step 5:

[1748] The server analyzes the user's emotions and generates emotional data.

[1749] The server uses an emotion engine to analyze the user's emotions from voice data and generate emotion data. Specifically, it analyzes characteristics such as the tone, volume, and speed of the user's voice. Example: "Analyze the user's voice data to determine their emotions (e.g., interested, confused) and generate emotion data."

[1750] Input: Audio data

[1751] Output: Sentiment data

[1752] Step 6:

[1753] The server converts the response text into audio data and adjusts the tone based on sentiment data.

[1754] The server converts the generated response text into audio data and adjusts the tone based on sentiment data. This sentiment data helps create user-friendly feedback, such as a more approachable or polite tone.

[1755] Input: Generated response text, sentiment data

[1756] Output: Voice data adjusted based on emotion

[1757] Step 7:

[1758] The server sends the audio data to the terminal.

[1759] The server sends the response audio data and emotion data to the terminal via the network interface.

[1760] Input: Voice data adjusted based on emotion

[1761] Output: Audio data sent to the terminal

[1762] Step 8:

[1763] The device plays audio data and displays a 3D hologram.

[1764] The device plays audio data received from the server through its speaker and displays a 3D hologram based on the emotional data. For example, if the user is in a state of "confusion," the hologram will display a more friendly expression and respond in a more polite voice.

[1765] Input: Voice data and emotion data sent to the device.

[1766] Output: Audio and 3D hologram played for the user

[1767] This allows users to receive specific and emotionally sensitive answers to their questions. Combining this with an emotion engine enables a more personalized user experience.

[1768] 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.

[1769] 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.

[1770] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1771] 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.

[1772] 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.

[1773] 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.

[1774] 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.

[1775] 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.

[1776] 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."

[1777] 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.

[1778] 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.

[1779] 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.

[1780] 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.

[1781] 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.

[1782] 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.

[1783] 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.

[1784] 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.

[1785] 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.

[1786] 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.

[1787] 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.

[1788] 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 as being incorporated by reference.

[1789] The following is further disclosed regarding the embodiments described above.

[1790] (Claim 1)

[1791] A means for the user to input a question by voice,

[1792] A means of capturing voice input and sending it to a server,

[1793] A means by which the server converts audio data into text data,

[1794] A means of analyzing text data to generate appropriate answers,

[1795] A means of converting the generated response text into audio data,

[1796] A means of transmitting audio data to a terminal,

[1797] A means by which the device plays audio data and a 3D hologram displays the answer,

[1798] A system that includes this.

[1799] (Claim 2)

[1800] The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

[1801] (Claim 3)

[1802] The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence.

[1803] "Example 1"

[1804] (Claim 1)

[1805] A means for the user to input a question by voice,

[1806] A means of capturing voice input and sending it to a server,

[1807] A means by which the server converts audio data into text data,

[1808] A means of analyzing text data to generate appropriate answers,

[1809] A means of converting the generated response text into audio data,

[1810] A means for transmitting audio data and 3D hologram data to a terminal,

[1811] A means by which the device plays audio data and a 3D hologram displays the answer,

[1812] A system that includes this.

[1813] (Claim 2)

[1814] The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

[1815] (Claim 3)

[1816] The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence.

[1817] "Application Example 1"

[1818] (Claim 1)

[1819] A means for the user to input a question by voice,

[1820] A means of capturing voice input and sending it to a server,

[1821] A means by which the server converts audio data into text data,

[1822] A means of analyzing text data to generate appropriate answers,

[1823] A means of converting the generated response text into audio data,

[1824] A means of transmitting audio data to a terminal,

[1825] A means by which the device plays audio data and a 3D hologram displays the answer,

[1826] An analytical means for providing product information based on user questions,

[1827] A means of visually presenting the analysis results as a 3D hologram,

[1828] A system that includes this.

[1829] (Claim 2)

[1830] The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

[1831] (Claim 3)

[1832] The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence.

[1833] "Example 2 of combining an emotion engine"

[1834] (Claim 1)

[1835] A means for the user to input a question by voice,

[1836] A means of capturing voice input and sending it to a server,

[1837] A means by which the server converts audio data into text data,

[1838] A means of analyzing text data to generate appropriate answers,

[1839] A means of recognizing user emotions and generating emotional data,

[1840] A means of converting the generated response text into audio data,

[1841] A means for transmitting voice data and emotional data to a terminal,

[1842] A means by which a device plays audio data and a 3D hologram displays a response based on emotional data,

[1843] A system that includes this.

[1844] (Claim 2)

[1845] The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

[1846] (Claim 3)

[1847] The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence.

[1848] "Application example 2 when combining with an emotional engine"

[1849] (Claim 1)

[1850] A means for the user to input a question by voice,

[1851] A means of capturing voice input and sending it to a server,

[1852] A means by which the server converts audio data into text data,

[1853] A means of analyzing text data to generate appropriate answers,

[1854] A means of converting the generated response text into audio data,

[1855] A means of transmitting audio data to a terminal,

[1856] A means by which the device plays audio data and a 3D hologram displays the answer,

[1857] A means of analyzing a user's emotions from voice data using an emotion engine,

[1858] A means of changing the tone of the response and the facial expression of the 3D hologram according to the user's emotions,

[1859] A system that includes this.

[1860] (Claim 2)

[1861] The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

[1862] (Claim 3)

[1863] The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence. [Explanation of Symbols]

[1864] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for the user to input a question by voice, A means of capturing voice input and sending it to a server, A means by which the server converts audio data into text data, A means of analyzing text data to generate appropriate answers, A means of converting the generated response text into audio data, A means of transmitting audio data to a terminal, A means by which the device plays audio data and a 3D hologram displays the answer, A system that includes this.

2. The system according to claim 1, wherein the means for generating answers to user questions utilizes generative artificial intelligence.

3. The system according to claim 1, wherein the means for converting audio data to text data utilizes speech recognition artificial intelligence.

Images