System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a voice input from a user; means for converting the received voice input into text data; means for analyzing the text data and understanding an intention of the user; means for searching contents of a digital book based on an analysis result; means for extracting corresponding information based on a search result; means for converting the extracted information into voice data with emotional expression; and means for transmitting the voice data to a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional audiobook systems have the problem that users must rewind and review parts they missed in order to understand specific information or technical terms. Furthermore, it is difficult to gain a deep understanding of technical content and terminology, hindering efficient learning. The present invention aims to solve these problems and provide users with a deeper understanding and a more comfortable listening experience. [Means for solving the problem]

[0005] The system according to the present invention includes a means for receiving voice input from a user, a means for converting the received voice input into text data, a means for analyzing the text data and understanding the user's intent, a means for searching the contents of a digital book based on the analysis results, a means for extracting relevant information based on the search results, a means for converting the extracted information into voice data accompanied by emotional expressions, and a means for transmitting the voice data to a user's terminal. The system further includes a means for adding appropriate background music to the voice data, thereby providing an effective learning and comfortable listening experience, including a means for playing back voices on the user's terminal.

[0006] "Voice input" is the act of digitally capturing a user's voice through a microphone.

[0007] "Text data" is digital data that represents voice input as a string of characters.

[0008] "Natural language processing" is a technology that enables computers to understand human language and perform appropriate processing.

[0009] "Digital Book" means the electronically stored content of a book, whether in text or multimedia format.

[0010] "Searching" is the process of finding specific information within a database or storage system.

[0011] "Extraction" is the act of extracting only the necessary parts from data or information.

[0012] "Emotional expression" is a technique for adding emotional nuances to voice data, and is a means of generating more natural voices.

[0013] "Audio Data" means digitally encoded audio information.

[0014] "Background music" is music that is added to audio data and is an element that enhances the listening experience.

[0015] "Terminal" refers to the device used by the user, including smartphones, tablets, PCs, etc.

[0016] A "speech recognition engine" is a software or hardware system for converting voice input into text data.

[0017] A "text-to-speech engine" is a software or hardware system for converting text data into speech data. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10]1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0022] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0023] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0024] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0026] [First embodiment]

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

[0028] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0031] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0033] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0035] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[0040] 1. User operations

[0041] A user uses the device's voice input interface to ask a question, for example, "What is Schrodinger's cat?" This voice input is captured by the device and stored as digital audio data.

[0042] 2. Terminal Processing

[0043] The device sends the captured audio data to the server using a network protocol such as an HTTP POST request. It also has the ability to receive and play the audio data returned from the server. The device acts as a bridge between the server and the user, properly transmitting the information the server requests and accurately conveying the information provided by the server to the user.

[0044] 3. Server Processing

[0045] The server receives the voice data sent from the terminal. After receiving the data, the server performs the following processes in order.

[0046] Speech Recognition Processing

[0047] The server uses a speech recognition engine to convert the voice data into text data, which allows it to understand what the user is asking as text information.

[0048] Natural Language Processing

[0049] The converted text data is passed to a natural language processing engine to analyze the user's intent. For example, it may recognize that the user is looking for an explanation of Schrodinger's cat.

[0050] Database search

[0051] Based on the user's intent, the server searches the digital book database to retrieve the relevant information, in this case extracting the required information from the chapter or section about Schrodinger's Cat.

[0052] Emotional Expression and Narration Generation

[0053] The acquired information is converted into emotionally expressive audio data using a text-to-speech engine, providing users with a natural and easy-to-understand presentation of the information. The listening experience can also be further enhanced by adding appropriate background music.

[0054] 4. Working Example

[0055] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[0056] User Action:

[0057] User: "What is Schrodinger's cat?"

[0058] Terminal handling:

[0059] The device captures the audio and sends the data to the server.

[0060] Server Action:

[0061] The server converts the audio data into text data, analyzes it, and extracts the relevant information from the digital book.

[0062] After that, audio data with emotional expressions is generated, background music is added, and the data is sent to the device.

[0063] Terminal handling:

[0064] The device plays the received audio data.

[0065] User Action:

[0066] The user listens to the audio playback and gets a detailed explanation of "Schrödinger's Cat."

[0067] This allows users to gain a deeper understanding of technical terms and difficult content. The distinctive feature of the present invention is that, as claimed, a system has been realized in which these functions and processes are integrated.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user speaks into the device's voice input interface to ask the question they want to know. In this example, they ask the question, "What is Schrodinger's cat?"

[0071] Step 2:

[0072] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[0073] Step 3:

[0074] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[0075] Step 4:

[0076] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[0077] Step 5:

[0078] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[0079] Step 6:

[0080] The server passes the converted text data to a natural language processing engine, which analyzes the text and identifies the user's intent.

[0081] Step 7:

[0082] The server searches the digital book database based on the user's intent, searching for information about "Schrödinger's Cat" and extracting relevant text.

[0083] Step 8:

[0084] The server uses a text-to-speech engine to convert the extracted text into emotionally charged speech data, where emotions and intonation are added to the narration.

[0085] Step 9:

[0086] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[0087] Step 10:

[0088] The server then sends the completed audio data to the device, again via an HTTP POST request or WebSocket.

[0089] Step 11:

[0090] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[0091] Step 12:

[0092] The device then plays the converted audio data through a speaker or headphones, allowing the user to listen to a detailed explanation of "Schrödinger's Cat."

[0093] Through the above steps, the system can quickly and accurately provide the information the user desires.

[0094] Example 1

[0095] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0096] Today's users want to quickly and easily understand digital books and specialized information. However, text-based information search can be time-consuming and difficult to understand when it contains a lot of technical terminology. While voice-based information retrieval systems exist, they typically lack emotional expression and background music, which leaves users unsatisfied. To address these challenges, a system is needed that allows users to simply ask questions and receive specific information in voice-activated speech.

[0097] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0098] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and understanding the user's intent, means for searching the contents of digital books and extracting relevant information, means for converting the acquired information into voice data with emotional expressions and adding background music, and means for transmitting the voice data to the user's terminal, thereby enabling the user to easily ask questions by voice and instantly receive specialized information in voice with emotional expressions.

[0099] "Voice input" refers to voice data provided by a user speaking into a microphone.

[0100] A "server" refers to a computer system that provides services to other devices and software on a network.

[0101] A "terminal" refers to a component having input and output devices that can be directly operated by a user.

[0102] "Audio data" refers to data that has been recorded or processed by converting audio into digital form.

[0103] "Text data" refers to data that has been converted from voice data into text information.

[0104] "Analysis means" refers to a series of processes that understand the user's intent based on text data and perform the necessary processing.

[0105] "Search method" refers to the process used to locate specific keywords or content within a digital book database.

[0106] "Extraction means" refers to the process for extracting the required information from the search results.

[0107] "Emotionally-expressed voice data" refers to voice data to which emotions and intonation have been added, as opposed to voice data generated simply from text.

[0108] "Background music" refers to music that is added to audio data to enhance the user's listening experience.

[0109] "Transmission" refers to a process for transferring data from one device to another.

[0110] "Receiving means" refers to the process by which one device receives data sent from another device.

[0111] "Playback means" refers to a process for allowing a user to listen to audio data through a speaker or the like.

[0112] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[0113] User operations

[0114] The user asks a question using the device's voice input interface. For example, the user might say, "What is Schrodinger's cat?" The device captures and stores this voice in digital form. This voice input interface can be a regular microphone, a smartphone microphone, or even a smart speaker.

[0115] Terminal handling

[0116] The device sends the captured audio data to the server using an HTTP POST request. HTTPS is often used as the network protocol. The device also has the ability to receive and play back audio data with emotional expressions returned from the server. For example, if a user wants to know more about "Schrödinger's Cat," the device sends this question to the server.

[0117] Server Processing

[0118] After receiving the voice data transmitted from the terminal, the server performs the following processes in order.

[0119] Speech Recognition Processing

[0120] The server converts the voice data into text data using a speech recognition engine (for example, Google Speech-to-Text API), which makes it possible to understand the content of the user's question as text information.

[0121] Natural Language Processing

[0122] The converted text data is passed to a natural language processing engine (e.g., a generative AI model such as GPT-3) to analyze the user's intent. For example, it may be analyzed that the user is looking for an explanation of Schrödinger's cat.

[0123] Database search

[0124] Based on the user's intent, the server searches a digital book database (e.g., Amazon Athena or other cloud database) and retrieves relevant information, typically a chapter or section about Schrödinger's cat.

[0125] Emotional Expression and Narration Generation

[0126] The acquired text information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (e.g., Amazon Polly), and appropriate background music (e.g., Bensound's free music library) is added to the voice data to improve the user's listening experience.

[0127] Example

[0128] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[0129] User Action:

[0130] User: "What is Schrodinger's cat?"

[0131] Terminal handling:

[0132] The device captures the audio and sends the data to the server.

[0133] Server Action:

[0134] The server converts the audio data into text data, analyzes it, extracts relevant information from the digital book, generates audio data with emotional expressions, adds background music, and transmits it to the device.

[0135] Terminal handling:

[0136] The terminal plays back the received audio data.

[0137] User Action:

[0138] The user can listen to the audio playback and get a detailed explanation of "Schrödinger's Cat."

[0139] Examples of prompt statements

[0140] Below is an example of a prompt sentence to input to the generative AI model.

[0141] text

[0142] "What is Schrodinger's cat?"

[0143] Using this prompt, the natural language processing engine understands that you are looking for an explanation of "Schrödinger's cat" and searches for and provides the corresponding information.

[0144] This system allows users to quickly and emotionally understand the contents of digital books through voice input.

[0145] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0146] Step 1:

[0147] User voice input

[0148] The user asks a question to the device's voice input interface, for example, "What is Schrodinger's cat?"

[0149] Input: User's voice data

[0150] Output: Digital audio data

[0151] Specific behavior:

[0152] Users ask questions into their smartphone or smart speaker, and the built-in microphone captures the audio.

[0153] Step 2:

[0154] Sending audio data by the device

[0155] The device sends the captured audio data to the server using an HTTP POST request.

[0156] Input: User's digital voice data

[0157] Output: HTTP request sent to the server

[0158] Specific behavior:

[0159] The device sends the audio data to the server via an internet connection, using HTTPS as the communication protocol.

[0160] Step 3:

[0161] Receiving audio data by the server

[0162] The server receives the voice data transmitted from the terminal.

[0163] Input: Audio data via HTTP POST request

[0164] Output: Audio data in the server

[0165] Specific behavior:

[0166] The server monitors the API endpoint and adds received audio data to its internal memory or to a processing queue.

[0167] Step 4:

[0168] Server-based speech-to-text conversion

[0169] The server converts the voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text).

[0170] Input: Audio data in the server

[0171] Output: Text data

[0172] Specific behavior:

[0173] The server sends the voice data to the voice recognition API and receives text data as a response.

[0174] Step 5:

[0175] Analysis of text data by the server

[0176] The server uses a natural language processing engine (e.g., GPT-3) to analyze the text data and understand the user's intent.

[0177] Input: Text data

[0178] Output: Analysis results (information indicating the user's intent)

[0179] Specific behavior:

[0180] The server inputs the text data into a natural language processing engine and receives the analyzed results.

[0181] Step 6:

[0182] Server-based search for digital books

[0183] The server searches the digital book database based on the analysis results and obtains the relevant information.

[0184] Input: Analysis results

[0185] Output: Part of the digital book data

[0186] Specific behavior:

[0187] The server uses an SQL query to search a digital book database and extract the section or chapter about Schrödinger's cat.

[0188] Step 7:

[0189] Converting acquired information into voice and adding emotional expressions

[0190] The server uses a text-to-speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into voice data with emotional expressions.

[0191] Input: Text data of a digital book

[0192] Output: Voice data with emotional expressions

[0193] Specific behavior:

[0194] The server sends the text data to the speech synthesis API, sets emotion parameters, and obtains speech data.

[0195] Step 8:

[0196] Add background music

[0197] The server adds background music to the generated emotionally expressive voice data.

[0198] Input: Voice data with emotional expressions, background music file

[0199] Output: Audio data with background music

[0200] Specific behavior:

[0201] The server uses an audio editing tool (e.g., FFmpeg) to combine the audio data with background music.

[0202] Step 9:

[0203] Sending audio data to the device

[0204] The server sends the final voice data with emotional expressions to the terminal as an HTTP response.

[0205] Input: Audio data with background music

[0206] Output: Audio data via HTTP response

[0207] Specific behavior:

[0208] The server generates a response at the API endpoint and sends the audio data to the device.

[0209] Step 10:

[0210] Playback of audio data by the device

[0211] The terminal reproduces the voice data with emotional expressions received from the server.

[0212] Input: Audio data from the server

[0213] Output: Audio playback through speakers

[0214] Specific behavior:

[0215] The device will launch its built-in audio player and play audio through speakers or earphones.

[0216] Step 11:

[0217] User hears audio playback

[0218] The user listens to the audio data played back from the terminal and receives the answer to the question.

[0219] Input: Device audio output

[0220] Output: User understanding

[0221] Specific behavior:

[0222] The user listens to the audio that is played and understands the explanation about "Schrödinger's cat."

[0223] Through each step, users can quickly and emotionally understand the content of the digital book through voice input.

[0224] (Application example 1)

[0225] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0226] In modern content distribution services, it is important for users to quickly and easily obtain specific information. In particular, services that offer a wide range of digital content require systems that allow users to instantly obtain detailed information about specific books or audiobooks. However, current systems lack the means to accurately analyze user intent, search for relevant information, and provide information in a natural-sounding voice that expresses emotions. This leaves users with an insufficient search experience, making it difficult to provide a richer user experience.

[0227] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0228] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intent, means for searching based on the analysis, means for extracting information from the search results, means for converting the extracted information into voice data with emotional expressions, means for transmitting the voice data to the user's terminal, and means for searching for related content based on the user's voice question and providing an answer with emotional expressions. This improves the user's search experience in the content distribution service and makes it possible to provide a richer user experience.

[0229] The "means for receiving voice input from the user" is a function for capturing voice uttered by the user as digital data and inputting it into the system.

[0230] The "means for converting received voice input into text data" is a function that converts captured voice data into text information using a voice recognition engine.

[0231] "Means for analyzing text data and understanding user intent" refers to a function that uses natural language processing technology to analyze and understand the meaning within text data and user requests.

[0232] The "analysis-based search means" is a function that searches related digital books and content databases according to the analyzed user intent.

[0233] "Means for extracting information from search results" refers to the function of extracting specific information that a user desires from searched digital books or content.

[0234] The "means for converting extracted information into voice data with emotional expressions" is a function that uses a text-to-speech synthesis engine to convert extracted text information into a voice format with emotional expressions.

[0235] The "means for transmitting voice data to the user's terminal" is a function for delivering the generated voice data to the user's terminal via a network.

[0236] "Means for searching for related content based on a user's voice question and providing an answer with emotional expressions" is a function that analyzes a user's voice question, searches for content related to that question, and then returns an answer in an emotionally rich voice.

[0237] The system for realizing this application example combines the following means in a series of processes: The user, terminal, and server work together to search for and provide relevant content based on the user's voice question.

[0238] System program generation and operation

[0239] 1. Audio capture and transmission (terminal)

[0240] The user types a voice question using the device's microphone, and this voice data is captured and stored digitally on the device, then sent to the server via an HTTP POST request.

[0241] 2. Speech recognition and text conversion (server)

[0242] The server converts the received voice data into text data using a speech recognition engine (e.g., Google Speech-to-Text API). Through this step, the server understands what the user has asked as text information.

[0243] 3. Natural Language Processing and Intention Analysis (Server)

[0244] The converted text data is passed to a natural language processing engine (e.g., NLTK, spaCy) to analyze the user's intent, for example, to understand a specific request such as "I want to know the meaning of a specific scientific term."

[0245] 4. Digital Book Database Search (Server)

[0246] Based on the analyzed user intent, the server searches the corresponding digital book database, identifies the chapter or section containing the relevant information, and extracts the required information.

[0247] 5. Emotional speech generation (server)

[0248] The extracted information is converted into audio data with emotional expressions using a text-to-speech synthesis engine (e.g., Google Text-to-Speech API), allowing users to receive information in a natural and easy-to-understand manner. In addition, appropriate background music may be added in some cases to enhance the listening experience.

[0249] 6. Sending and Playing Audio Data (Terminal)

[0250] The final generated voice data is sent from the server to the terminal, which then plays the received voice data and provides the information to the user.

[0251] Hardware and software used

[0252] Hardware: Smartphone, microphone

[0253] software:

[0254] speech_recognition (speech recognition library)

[0255] requests (a library for sending HTTP requests)

[0256] pyttsx3 (speech synthesis library)

[0257] Google Speech-to-Text API (for voice recognition)

[0258] NLTK or spaCy (for natural language processing)

[0259] Google Text-to-Speech API (for speech synthesis)

[0260] Examples of specific examples and prompts

[0261] Examples:

[0262] 1. The user opens the "Audio Assistant" feature in the smartphone app and asks a voice question such as, "Tell me more about this book."

[0263] 2. The app captures the audio and sends it to the server.

[0264] 3. The server converts the speech into text and retrieves relevant information from a database.

[0265] 4. The information is converted into voice with emotional expressions and sent to a smartphone.

[0266] 5. The app plays a sound and provides the information the user requested.

[0267] Example prompt sentence:

[0268] "What is Schrodinger's cat? Can you explain it in detail?"

[0269] This embodiment allows users to easily obtain detailed information through voice queries and enjoy a richer user experience.

[0270] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0271] Step 1:

[0272] A user taps the microphone button on a smartphone app and asks a question by voice. For example, they say, "Tell me more about this book." Input: User's voice data. Output: Voice data captured on the device.

[0273] Step 2:

[0274] The audio data captured on the device is stored digitally and then sent to the server using an HTTP POST request. Input: Captured audio data. Output: Audio data sent to the server.

[0275] Step 3:

[0276] The server converts the received voice data into text data using a speech recognition engine (such as the Google Speech-to-Text API). Input: Voice data sent to the server. Output: Text data converted by the speech recognition engine.

[0277] Step 4:

[0278] The server uses a natural language processing engine (NLTK, spaCy, etc.) to analyze the text data and understand the user's intent. Input: Text data converted by a speech recognition engine. Output: Analyzed user intent.

[0279] Step 5:

[0280] The server searches the corresponding digital book database based on the analyzed user intent. At this stage, the relevant chapter or page is identified and the necessary information is extracted. Input: Analyzed user intent. Output: Information on the searched digital book.

[0281] Step 6:

[0282] The extracted information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (such as Google Text-to-Speech API). Input: Searched digital book information. Output: Voice data with emotional expressions.

[0283] Step 7:

[0284] If necessary, the server adds appropriate background music to the audio data, improving the listening experience. Input: Audio data with emotional expressions. Output: Audio data with emotional expressions and background music.

[0285] Step 8:

[0286] The server finally sends the generated voice data to the terminal via the network. Input: Voice data with emotional expressions and background music. Output: Voice data sent to the terminal.

[0287] Step 9:

[0288] The terminal plays the received audio data and provides information to the user. Input: Audio data sent to the terminal. Output: Audio information that the user can hear.

[0289] This allows users to quickly and emotively obtain detailed information about specific digital content through audio.

[0290] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0291] This system, when a user makes a voice inquiry about specific information, searches for that information in a digital book, uses an emotion recognition engine to determine the user's emotion, and provides a voice response accompanied by an appropriate emotional expression, operates in cooperation with three entities: a server, a terminal, and a user.

[0292] 1. User operations

[0293] The user asks a question into the voice input interface, in this example "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[0294] 2. Terminal Processing

[0295] The device captures the user's voice and sends the digital audio data to a server using protocols such as HTTP POST requests or WebSockets, and also receives and plays the audio data returned from the server.

[0296] 3. Server Processing

[0297] The server receives the voice data sent from the terminal and performs the following processes in order.

[0298] Speech Recognition Processing

[0299] The server uses a speech recognition engine to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[0300] Natural Language Processing

[0301] The server passes the text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0302] Emotion Recognition Processing

[0303] The converted text and voice data are passed to an emotion recognition engine to determine the user's emotions. The engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[0304] Database search

[0305] The server then searches a digital book database for information about "Schrödinger's Cat" and extracts the relevant text.

[0306] Emotional Expression and Narration Generation

[0307] The acquired text is then passed to a text-to-speech synthesis engine, where it is converted into voice data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated voice to have an inflection and tone that matches the user's emotions. Appropriate background music can also be added to the voice data to improve the listening experience.

[0308] 4. Working Example

[0309] A specific example will now be given: Suppose a user is listening to an audiobook on physics and wants to know more about Schrodinger's cat.

[0310] User Action:

[0311] The user speaks, "What is Schrodinger's cat?"

[0312] Terminal handling:

[0313] The device captures the audio and sends it to the server.

[0314] Server Action:

[0315] The server converts the voice data into text and analyzes it with a natural language processing engine. It then uses an emotion recognition engine to identify the user's emotion (e.g., curiosity). It then searches and extracts relevant information from a digital book database, adds emotional expressions, generates voice data, and adds background music.

[0316] Terminal handling:

[0317] The terminal receives and plays back the audio data sent from the server.

[0318] User Action:

[0319] Users listen to the audio and get a detailed explanation of "Schrödinger's Cat," which is delivered with inflection and tone that reflects the user's emotions, making for a more comprehensible and immersive listening experience.

[0320] In this way, the system can provide information quickly and accurately while taking into account the user's feelings.

[0321] The processing flow will be explained below.

[0322] Step 1:

[0323] The user speaks what they want to know into the device's voice input interface, asking the question, "What is Schrodinger's cat?"

[0324] Step 2:

[0325] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[0326] Step 3:

[0327] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[0328] Step 4:

[0329] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[0330] Step 5:

[0331] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[0332] Step 6:

[0333] The server then passes the converted text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0334] Step 7:

[0335] The server passes the text and voice data to an emotion recognition engine to determine the user's emotion, which infers the emotion from the user's tone of voice and text expression.

[0336] Step 8:

[0337] The server searches the digital book database based on the user's intent, retrieves information about "Schrödinger's Cat," and extracts the relevant text.

[0338] Step 9:

[0339] The server uses a text-to-speech engine to convert the extracted text information into emotionally charged speech data, which adds tone and inflection to match the user's emotions.

[0340] Step 10:

[0341] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[0342] Step 11:

[0343] The server sends the completed audio data to the device via an HTTP POST request or WebSocket.

[0344] Step 12:

[0345] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[0346] Step 13:

[0347] The device then plays the converted audio data through speakers or headphones, allowing users to listen to a detailed explanation of "Schrödinger's Cat." The audio is provided with a tone and background music that matches the user's emotions, providing a clearer and more immersive listening experience.

[0348] Example 2

[0349] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0350] Conventional voice dialogue systems provide information without considering the user's emotions, making it difficult to provide appropriate responses based on the user's emotions and intentions. Furthermore, there is a need to improve the user's listening experience by providing responses accompanied by appropriate background music in addition to speech.

[0351] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0352] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into digital format, means for transmitting the digital voice input to the server, means for converting the voice input into text data, means for analyzing the text data and understanding the user's intention, means for determining the user's emotions from the analyzed text data and voice data, means for searching the contents of a digital book, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for adding background music to the generated voice data, means for transmitting the voice data to the user's terminal, and means for playing the voice data on the user's terminal, thereby enabling appropriate responses that take the user's emotions into consideration and a high-quality listening experience.

[0353] "User voice input" refers to questions or instructions given by the user to the system through voice.

[0354] "Digital format" refers to a format in which an analog signal is converted into digital data.

[0355] A "server" refers to a computer system that receives requests from clients via a network and provides services.

[0356] "Text data" refers to data expressed as character information.

[0357] A "natural language processing engine" refers to a system that analyzes text data and understands and generates human language.

[0358] An "emotion recognition engine" refers to a system for determining a user's emotions from voice data and text data.

[0359] "Digital Book" refers to book data stored in electronic format.

[0360] "Text-to-speech engine" refers to a system for converting text data into speech data.

[0361] "Background music" refers to music that is primarily intended to complement audio data and enhance the listening experience.

[0362] "User terminal" refers to a device that is directly operated by a user, such as a computer system or electronic device that communicates with a server.

[0363] "Audio data" refers to audio information expressed as digital data.

[0364] "Search means" refers to a system or method for locating specific information from a database or storage.

[0365] "Playback means" refers to a system or function that allows the user to listen to the audio data sent from the server.

[0366] This system searches for specific information in digital books when a user makes a voice inquiry, determines the user's emotions, and provides a voice response accompanied by appropriate emotional expressions. This system operates in cooperation with three entities: the user, the terminal, and the server.

[0367] First, the user asks a question to the voice input interface. Let's take the question "What is Schrodinger's cat?" as an example. This voice input is captured as digital voice data by the device. The device uses a microphone to capture the voice and converts it into a digital format. This digital voice data is sent to the server using a protocol such as an HTTP POST request or WebSocket.

[0368] The server receives the voice data sent from the device and first converts the voice data into text data using a speech recognition engine. For example, a general API service (e.g., Google Cloud Speech-to-Text API) can be used as the speech recognition engine. This results in the text data "What is Schrodinger's cat?"

[0369] The server then passes this text data to a natural language processing engine to analyze the user's intent. The natural language processing engine uses a generative AI model (e.g., the OpenAI GPT model). This analysis determines that the user is looking for information about "Schrödinger's cat."

[0370] The server then passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions. A common API service (e.g., IBM Watson Emotion Analysis) is used as the emotion recognition engine. This engine estimates the user's emotions (e.g., curiosity, confusion, excitement) from the user's tone of voice and the context of the text.

[0371] Next, the server searches a digital book database to obtain information about "Schrödinger's Cat." The digital book database uses a common API service (e.g., the API of an e-book store). The server identifies and extracts the relevant text.

[0372] The acquired text is then converted into voice data by adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine and passed to a text-to-speech synthesis engine. For example, a common API service (e.g., Amazon Polly) can be used as the voice synthesis engine. The voice data is given inflection and tone according to the user's emotions. The listening experience can also be improved by adding background music to the generated voice data.

[0373] Finally, the generated audio data is sent back to the device from the server. The device then plays the received audio data through the speaker. The user can then listen to the audio and receive a detailed explanation of "Schrödinger's Cat." The explanation is delivered with intonation and tone that reflects the user's emotions, providing a more understandable and immersive listening experience.

[0374] Prompt Sentence Examples

[0375] "Please explain in detail how the system will provide an answer when a user asks a question about Schrodinger's cat."

[0376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0377] Step 1:

[0378] The user asks a question into the voice input interface.

[0379] Input: User speech (e.g., "What is Schrodinger's cat?")

[0380] Output: Audio data

[0381] Specific operation: The user speaks a question into the device's microphone, which captures the voice as an analog signal.

[0382] Step 2:

[0383] The terminal converts the user's voice into a digital format.

[0384] Input: Analog audio signal

[0385] Output: Digital audio data

[0386] How it works: The device uses a microphone to capture audio, converts the analog audio signal into digital form, and stores the digital audio data in the device's memory.

[0387] Step 3:

[0388] The terminal transmits digital audio data to the server.

[0389] Input: Digital audio data

[0390] Output: Request to the server (HTTP POST or WebSocket)

[0391] What happens: The device extracts the digital audio data and sends it to the server using a network protocol (e.g., HTTP POST request or WebSocket).

[0392] Step 4:

[0393] The server receives the digital voice data and converts the voice data into text data using a voice recognition engine.

[0394] Input: Digital audio data

[0395] Output: Text data (e.g., "What is Schrodinger's cat?")

[0396] How it works: The server receives digital voice data sent from the device and passes it to a speech recognition engine (e.g., Google Cloud Speech-to-Text API), which analyzes the voice data and generates corresponding text data.

[0397] Step 5:

[0398] The server passes the text data to a natural language processing engine to analyze the user's intent.

[0399] Input: Text data (e.g., "What is Schrodinger's cat?")

[0400] Output: User intent (e.g., "I'm looking for information about Schrodinger's cat")

[0401] How it works: The server passes the generated text data to a natural language processing engine (e.g., OpenAI GPT model), which analyzes the text data and interprets the user's intent.

[0402] Step 6:

[0403] The server passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions.

[0404] Input: Text and audio data

[0405] Output: User emotion (e.g., curiosity, confusion, excitement)

[0406] Specific operation: The server passes the text and voice data to an emotion recognition engine (e.g., IBM Watson Emotion Analysis). The engine analyzes the data and estimates the user's emotions.

[0407] Step 7:

[0408] The server searches the digital book database and extracts the relevant information.

[0409] Input: User intent (e.g., "information about Schrodinger's cat")

[0410] Output: Corresponding text information

[0411] Specific operation: The server searches a digital book database (e.g., an API of an e-book store) and extracts relevant information based on the user's intent.

[0412] Step 8:

[0413] The server converts the extracted information into voice data accompanied by emotional expressions.

[0414] Input: relevant text information and user sentiment

[0415] Output: Generated audio data

[0416] Specific operation: The server adds emotional expressions determined by the emotion recognition engine to the extracted text information, and passes the data to a text-to-speech synthesis engine (e.g., Amazon Polly) to generate voice data.

[0417] Step 9:

[0418] The server adds appropriate background music to the generated audio data.

[0419] Input: Generated audio data

[0420] Output: Audio data including background music

[0421] Specific operation: The server selects background music suitable for the generated audio data and incorporates it into the audio data, thereby improving the listening experience.

[0422] Step 10:

[0423] The server sends the final audio data to the terminal.

[0424] Input: Audio data including background music

[0425] Output: Request to the device (HTTP POST or WebSocket)

[0426] Specific operation: The server generates the final audio data including background music and sends it to the terminal via a network protocol.

[0427] Step 11:

[0428] The terminal receives the audio data sent from the server and plays it back.

[0429] Input: Audio data including background music

[0430] Output: Audio output through speakers

[0431] Specific operation: The terminal receives the voice data sent from the server and plays it through the speaker, allowing the user to listen to the voice and obtain detailed answers to their questions.

[0432] (Application example 2)

[0433] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0434] Current content delivery services lack systems that can quickly and accurately respond to questions or concerns that arise while users are listening to audiobooks or other digital content. This requires users to interrupt the content and perform a search, which detracts from the listening experience. Furthermore, existing systems struggle to provide appropriate answers that reflect the user's emotions, creating a need for improved user experience.

[0435] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intention, means for searching for the details of digital content based on the analysis results, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for transmitting the voice data to the user's information processing device, means for analyzing the user's emotions using an emotion recognition engine, and means for generating voice by adding an appropriate emotional expression based on the emotions. This allows the user to receive an answer according to the emotion through an information processing device such as a smartphone without interrupting the content, enabling a more natural and immersive listening experience.

[0436] "Voice input from the user" refers to voice data spoken by the user, and is an input means used by the system to receive and analyze this data.

[0437] The "means for converting received voice input into text data" refers to a process for converting a user's voice data into corresponding text data, such as using a voice recognition engine.

[0438] "Means for analyzing text data and understanding user intent" refers to the process of using a natural language processing engine to analyze what the user is looking for from the converted text data.

[0439] "Means for searching the contents of digital content" refers to the process of searching databases such as digital books and audiobooks based on the user's intent to find relevant information.

[0440] "Means for extracting relevant information based on search results" refers to the process of extracting information from the searched digital content that directly answers the user's question.

[0441] The "means for converting extracted information into voice data accompanied by emotional expression" refers to the process of generating voice with intonation and tone appropriate to the user's emotions when converting extracted information into voice data using a text-to-speech synthesis engine.

[0442] "Means for transmitting voice data to a user's information processing device" refers to a process for transmitting the generated voice data to a user's information processing device such as a smartphone or PC via the Internet or other communication means.

[0443] "Means for analyzing user emotions using an emotion recognition engine" is a technology for estimating emotions from a user's voice data and text data, and is a process for identifying the emotions the user is feeling.

[0444] "Means for generating voice by adding appropriate emotional expressions based on emotions" is a technology that uses the results of an emotion recognition engine to add intonation and tone to the generated voice data according to the user's emotions.

[0445] The present invention is a system in which, when a user expresses a question or interest through voice input, the system searches for the relevant information from digital content, determines the user's emotion using an emotion recognition engine, and provides a voice response accompanied by an appropriate emotional expression. This system operates in cooperation with three entities: a server, a terminal, and the user.

[0446] 1. User operations

[0447] The user asks a question to the voice input interface, for example, "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[0448] 2. Terminal Processing

[0449] The user's voice is captured by a device such as a smartphone or tablet. The device then uses a communication protocol such as an HTTP POST request or WebSocket to send the digital audio data to a server. The device also has the ability to receive and play the digital audio data returned from the server.

[0450] 3. Server Processing

[0451] The server receives the voice data sent from the terminal and performs the following processes in order.

[0452] Speech Recognition Processing

[0453] The server uses a speech recognition engine (such as Google Speech-to-Text) to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[0454] Natural Language Processing

[0455] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0456] Emotion Recognition Processing

[0457] The converted text and voice data are passed to an emotion recognition engine (such as IBM Watson Tone Analyzer) to determine the user's emotions. This engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[0458] Database search

[0459] The server then searches a digital content database (e.g., Kindle, Google Books) to retrieve information about "Schrödinger's Cat" and extracts the relevant text.

[0460] Emotional Expression and Narration Generation

[0461] The acquired text is then passed to a text-to-speech engine (e.g., Amazon Polly) where it is converted into audio data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated audio to have an inflection and tone that matches the user's emotions. Appropriate background music and sound effects can also be added to the audio data to improve the listening experience.

[0462] 4. Working Example

[0463] Here is a specific example: Let us consider the case where a user is listening to an audiobook and thinks, "I want to know more about Schrodinger's cat."

[0464] User operations

[0465] The user speaks, "What is Schrodinger's cat?" The server generates a response in an uplifting tone, depending on the curiosity inferred from the user's voice.

[0466] Search and Response

[0467] The server performs voice recognition, natural language processing, and emotion recognition, searches for relevant information in a digital content database, adds emotional expressions, generates audio data, and sends it along with background music to the user's device, which receives and plays it.

[0468] Examples of prompt statements

[0469] Initial prompt: "A user is listening to an audiobook and asks a question about a passage they're unsure about. How can you create a content delivery app that responds to this question with an emotionally relevant answer?"

[0470] Question prompt: "What is Schrodinger's cat?"

[0471] This invention allows users to receive natural emotional responses without interrupting the content, improving the listening experience.

[0472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0473] Step 1:

[0474] A user speaks into a device such as a smartphone or tablet. For example, a specific question might be, "What is Schrödinger's cat?" The device captures and stores this speech as digital audio data. The input is the user's voice, and the output is digital audio data.

[0475] Step 2:

[0476] The device sends the stored digital audio data to the server. The audio data is securely transmitted using a communication protocol such as an HTTP POST request or WebSocket. The input of this step is the digital audio data, and the output is the data transmitted to the server.

[0477] Step 3:

[0478] The server receives the digital voice data sent from the device. It converts the received voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text). Specifically, it analyzes the voice waveform and generates a corresponding text string. The input is digital voice data, and the output is the text data "What is Schrödinger's cat?"

[0479] Step 4:

[0480] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent. Through this analysis, the server understands the content of the user's question and the information they are looking for from the text. Specifically, it performs grammatical analysis and semantic analysis. The input is text data, and the output is the user's intent, which is "I'm looking for information about Schrodinger's cat."

[0481] Step 5:

[0482] The server passes the converted text and voice data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotion. Specifically, it identifies the emotional state from the tone of the voice and the content of the text. The input is text and voice data, and the output is a determination that the user's emotion is "curiosity."

[0483] Step 6:

[0484] The server searches a digital content database (e.g., Kindle, Google Books) and retrieves information about "Schrödinger's Cat" based on the user's intent. Specifically, it uses a content search API to extract the relevant text. The input is the user's intent, and the output is text data containing the relevant information.

[0485] Step 7:

[0486] The server adds appropriate emotional expressions to the acquired text data based on the results of the emotion recognition engine and converts it into voice data. Specifically, it uses a text-to-speech synthesis engine (e.g., Amazon Polly) to add intonation and tone according to the emotion to the voice. The input is text data and emotional information, and the output is voice data accompanied by emotional expressions.

[0487] Step 8:

[0488] The server adds appropriate background music and sound effects to the generated audio data. Specifically, it uses an audio mixing tool to combine the music track and the audio track. The input is audio data and background music, and the output is audio data with background music.

[0489] Step 9:

[0490] The server sends the final audio data to the user's terminal. The input is the audio data with background music, and the output is the data sent to the user's terminal.

[0491] Step 10:

[0492] The device receives the audio data sent from the server and plays it through the audio playback application. Specifically, it activates the audio playback function and outputs the data from the speaker. The input is audio data with background music, and the output is the audio that the user actually hears.

[0493] By following these steps, if a user has a question while listening to an audiobook, they can receive an answer that suits their feelings without interrupting the content.

[0494] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0495] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0496] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0497] [Second embodiment]

[0498] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0499] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0500] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0501] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0502] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0503] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0504] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0505] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0506] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0507] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0508] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0509] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0510] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[0511] 1. User operations

[0512] A user uses the device's voice input interface to ask a question, for example, "What is Schrodinger's cat?" This voice input is captured by the device and stored as digital audio data.

[0513] 2. Terminal Processing

[0514] The device sends the captured audio data to the server using a network protocol such as an HTTP POST request. It also has the ability to receive and play the audio data returned from the server. The device acts as a bridge between the server and the user, properly transmitting the information the server requests and accurately conveying the information provided by the server to the user.

[0515] 3. Server Processing

[0516] The server receives the voice data sent from the terminal. After receiving the data, the server performs the following processes in order.

[0517] Speech Recognition Processing

[0518] The server uses a speech recognition engine to convert the voice data into text data, which allows it to understand what the user is asking as text information.

[0519] Natural Language Processing

[0520] The converted text data is passed to a natural language processing engine to analyze the user's intent. For example, it may recognize that the user is looking for an explanation of Schrodinger's cat.

[0521] Database search

[0522] Based on the user's intent, the server searches the digital book database to retrieve the relevant information, in this case extracting the required information from the chapter or section about Schrodinger's Cat.

[0523] Emotional Expression and Narration Generation

[0524] The acquired information is converted into emotionally expressive audio data using a text-to-speech engine, providing users with a natural and easy-to-understand presentation of the information. The listening experience can also be further enhanced by adding appropriate background music.

[0525] 4. Working Example

[0526] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[0527] User Action:

[0528] User: "What is Schrodinger's cat?"

[0529] Terminal handling:

[0530] The device captures the audio and sends the data to the server.

[0531] Server Action:

[0532] The server converts the audio data into text data, analyzes it, and extracts the relevant information from the digital book.

[0533] After that, audio data with emotional expressions is generated, background music is added, and the data is sent to the device.

[0534] Terminal handling:

[0535] The device plays the received audio data.

[0536] User Action:

[0537] The user listens to the audio playback and gets a detailed explanation of "Schrödinger's Cat."

[0538] This allows users to gain a deeper understanding of technical terms and difficult content. The distinctive feature of the present invention is that, as claimed, a system has been realized in which these functions and processes are integrated.

[0539] The processing flow will be explained below.

[0540] Step 1:

[0541] The user speaks into the device's voice input interface to ask the question they want to know. In this example, they ask the question, "What is Schrodinger's cat?"

[0542] Step 2:

[0543] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[0544] Step 3:

[0545] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[0546] Step 4:

[0547] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[0548] Step 5:

[0549] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[0550] Step 6:

[0551] The server passes the converted text data to a natural language processing engine, which analyzes the text and identifies the user's intent.

[0552] Step 7:

[0553] The server searches the digital book database based on the user's intent, searching for information about "Schrödinger's Cat" and extracting relevant text.

[0554] Step 8:

[0555] The server uses a text-to-speech engine to convert the extracted text into emotionally charged speech data, where emotions and intonation are added to the narration.

[0556] Step 9:

[0557] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[0558] Step 10:

[0559] The server then sends the completed audio data to the device, again via an HTTP POST request or WebSocket.

[0560] Step 11:

[0561] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[0562] Step 12:

[0563] The device then plays the converted audio data through a speaker or headphones, allowing the user to listen to a detailed explanation of "Schrödinger's Cat."

[0564] Through the above steps, the system can quickly and accurately provide the information the user desires.

[0565] Example 1

[0566] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0567] Today's users want to quickly and easily understand digital books and specialized information. However, text-based information search can be time-consuming and difficult to understand when it contains a lot of technical terminology. While voice-based information retrieval systems exist, they typically lack emotional expression and background music, which leaves users unsatisfied. To address these challenges, a system is needed that allows users to simply ask questions and receive specific information in voice-activated speech.

[0568] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0569] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and understanding the user's intent, means for searching the contents of digital books and extracting relevant information, means for converting the acquired information into voice data with emotional expressions and adding background music, and means for transmitting the voice data to the user's terminal, thereby enabling the user to easily ask questions by voice and instantly receive specialized information in voice with emotional expressions.

[0570] "Voice input" refers to voice data provided by a user speaking into a microphone.

[0571] A "server" refers to a computer system that provides services to other devices and software on a network.

[0572] A "terminal" refers to a component having input and output devices that can be directly operated by a user.

[0573] "Audio data" refers to data that has been recorded or processed by converting audio into digital form.

[0574] "Text data" refers to data that has been converted from voice data into text information.

[0575] "Analysis means" refers to a series of processes that understand the user's intent based on text data and perform the necessary processing.

[0576] "Search method" refers to the process used to locate specific keywords or content within a digital book database.

[0577] "Extraction means" refers to the process for extracting the required information from the search results.

[0578] "Emotionally-expressed voice data" refers to voice data to which emotions and intonation have been added, as opposed to voice data generated simply from text.

[0579] "Background music" refers to music that is added to audio data to enhance the user's listening experience.

[0580] "Transmission" refers to a process for transferring data from one device to another.

[0581] "Receiving means" refers to the process by which one device receives data sent from another device.

[0582] "Playback means" refers to a process for allowing a user to listen to audio data through a speaker or the like.

[0583] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[0584] User operations

[0585] The user asks a question using the device's voice input interface. For example, the user might say, "What is Schrodinger's cat?" The device captures and stores this voice in digital form. This voice input interface can be a regular microphone, a smartphone microphone, or even a smart speaker.

[0586] Terminal handling

[0587] The device sends the captured audio data to the server using an HTTP POST request. HTTPS is often used as the network protocol. The device also has the ability to receive and play back audio data with emotional expressions returned from the server. For example, if a user wants to know more about "Schrödinger's Cat," the device sends this question to the server.

[0588] Server Processing

[0589] After receiving the voice data transmitted from the terminal, the server performs the following processes in order.

[0590] Speech Recognition Processing

[0591] The server converts the voice data into text data using a speech recognition engine (for example, Google Speech-to-Text API), which makes it possible to understand the content of the user's question as text information.

[0592] Natural Language Processing

[0593] The converted text data is passed to a natural language processing engine (e.g., a generative AI model such as GPT-3) to analyze the user's intent. For example, it may be analyzed that the user is looking for an explanation of Schrödinger's cat.

[0594] Database search

[0595] Based on the user's intent, the server searches a digital book database (e.g., Amazon Athena or other cloud database) and retrieves relevant information, typically a chapter or section about Schrödinger's cat.

[0596] Emotional Expression and Narration Generation

[0597] The acquired text information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (e.g., Amazon Polly), and appropriate background music (e.g., Bensound's free music library) is added to the voice data to improve the user's listening experience.

[0598] Example

[0599] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[0600] User Action:

[0601] User: "What is Schrodinger's cat?"

[0602] Terminal handling:

[0603] The device captures the audio and sends the data to the server.

[0604] Server Action:

[0605] The server converts the audio data into text data, analyzes it, extracts relevant information from the digital book, generates audio data with emotional expressions, adds background music, and transmits it to the device.

[0606] Terminal handling:

[0607] The terminal plays back the received audio data.

[0608] User Action:

[0609] The user can listen to the audio playback and get a detailed explanation of "Schrödinger's Cat."

[0610] Examples of prompt statements

[0611] Below is an example of a prompt sentence to input to the generative AI model.

[0612] text

[0613] "What is Schrodinger's cat?"

[0614] Using this prompt, the natural language processing engine understands that you are looking for an explanation of "Schrödinger's cat" and searches for and provides the corresponding information.

[0615] This system allows users to quickly and emotionally understand the contents of digital books through voice input.

[0616] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0617] Step 1:

[0618] User voice input

[0619] The user asks a question to the device's voice input interface, for example, "What is Schrodinger's cat?"

[0620] Input: User's voice data

[0621] Output: Digital audio data

[0622] Specific behavior:

[0623] Users ask questions into their smartphone or smart speaker, and the built-in microphone captures the audio.

[0624] Step 2:

[0625] Sending audio data by the device

[0626] The device sends the captured audio data to the server using an HTTP POST request.

[0627] Input: User's digital voice data

[0628] Output: HTTP request sent to the server

[0629] Specific behavior:

[0630] The device sends the audio data to the server via an internet connection, using HTTPS as the communication protocol.

[0631] Step 3:

[0632] Receiving audio data by the server

[0633] The server receives the voice data transmitted from the terminal.

[0634] Input: Audio data via HTTP POST request

[0635] Output: Audio data in the server

[0636] Specific behavior:

[0637] The server monitors the API endpoint and adds received audio data to its internal memory or to a processing queue.

[0638] Step 4:

[0639] Server-based speech-to-text conversion

[0640] The server converts the voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text).

[0641] Input: Audio data in the server

[0642] Output: Text data

[0643] Specific behavior:

[0644] The server sends the voice data to the voice recognition API and receives text data as a response.

[0645] Step 5:

[0646] Analysis of text data by the server

[0647] The server uses a natural language processing engine (e.g., GPT-3) to analyze the text data and understand the user's intent.

[0648] Input: Text data

[0649] Output: Analysis results (information indicating the user's intent)

[0650] Specific behavior:

[0651] The server inputs the text data into a natural language processing engine and receives the analyzed results.

[0652] Step 6:

[0653] Server-based search for digital books

[0654] The server searches the digital book database based on the analysis results and obtains the relevant information.

[0655] Input: Analysis results

[0656] Output: Part of the digital book data

[0657] Specific behavior:

[0658] The server uses an SQL query to search a digital book database and extract the section or chapter about Schrödinger's cat.

[0659] Step 7:

[0660] Converting acquired information into voice and adding emotional expressions

[0661] The server uses a text-to-speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into voice data with emotional expressions.

[0662] Input: Text data of a digital book

[0663] Output: Voice data with emotional expressions

[0664] Specific behavior:

[0665] The server sends the text data to the speech synthesis API, sets emotion parameters, and obtains speech data.

[0666] Step 8:

[0667] Add background music

[0668] The server adds background music to the generated emotionally expressive voice data.

[0669] Input: Voice data with emotional expressions, background music file

[0670] Output: Audio data with background music

[0671] Specific behavior:

[0672] The server uses an audio editing tool (e.g., FFmpeg) to combine the audio data with background music.

[0673] Step 9:

[0674] Sending audio data to the device

[0675] The server sends the final voice data with emotional expressions to the terminal as an HTTP response.

[0676] Input: Audio data with background music

[0677] Output: Audio data via HTTP response

[0678] Specific behavior:

[0679] The server generates a response at the API endpoint and sends the audio data to the device.

[0680] Step 10:

[0681] Playback of audio data by the device

[0682] The terminal reproduces the voice data with emotional expressions received from the server.

[0683] Input: Audio data from the server

[0684] Output: Audio playback through speakers

[0685] Specific behavior:

[0686] The device will launch its built-in audio player and play audio through speakers or earphones.

[0687] Step 11:

[0688] User hears audio playback

[0689] The user listens to the audio data played back from the terminal and receives the answer to the question.

[0690] Input: Device audio output

[0691] Output: User understanding

[0692] Specific behavior:

[0693] The user listens to the audio that is played and understands the explanation about "Schrödinger's cat."

[0694] Through each step, users can quickly and emotionally understand the content of the digital book through voice input.

[0695] (Application example 1)

[0696] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0697] In modern content distribution services, it is important for users to quickly and easily obtain specific information. In particular, services that offer a wide range of digital content require systems that allow users to instantly obtain detailed information about specific books or audiobooks. However, current systems lack the means to accurately analyze user intent, search for relevant information, and provide information in a natural-sounding voice that expresses emotions. This leaves users with an insufficient search experience, making it difficult to provide a richer user experience.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0699] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intent, means for searching based on the analysis, means for extracting information from the search results, means for converting the extracted information into voice data with emotional expressions, means for transmitting the voice data to the user's terminal, and means for searching for related content based on the user's voice question and providing an answer with emotional expressions. This improves the user's search experience in the content distribution service and makes it possible to provide a richer user experience.

[0700] The "means for receiving voice input from the user" is a function for capturing voice uttered by the user as digital data and inputting it into the system.

[0701] The "means for converting received voice input into text data" is a function that converts captured voice data into text information using a voice recognition engine.

[0702] "Means for analyzing text data and understanding user intent" refers to a function that uses natural language processing technology to analyze and understand the meaning within text data and user requests.

[0703] The "analysis-based search means" is a function that searches related digital books and content databases according to the analyzed user intent.

[0704] "Means for extracting information from search results" refers to the function of extracting specific information that a user desires from searched digital books or content.

[0705] The "means for converting extracted information into voice data with emotional expressions" is a function that uses a text-to-speech synthesis engine to convert extracted text information into a voice format with emotional expressions.

[0706] The "means for transmitting voice data to the user's terminal" is a function for delivering the generated voice data to the user's terminal via a network.

[0707] "Means for searching for related content based on a user's voice question and providing an answer with emotional expressions" is a function that analyzes a user's voice question, searches for content related to that question, and then returns an answer in an emotionally rich voice.

[0708] The system for realizing this application example combines the following means in a series of processes: The user, terminal, and server work together to search for and provide relevant content based on the user's voice question.

[0709] System program generation and operation

[0710] 1. Audio capture and transmission (terminal)

[0711] The user types a voice question using the device's microphone, and this voice data is captured and stored digitally on the device, then sent to the server via an HTTP POST request.

[0712] 2. Speech recognition and text conversion (server)

[0713] The server converts the received voice data into text data using a speech recognition engine (e.g., Google Speech-to-Text API). Through this step, the server understands what the user has asked as text information.

[0714] 3. Natural Language Processing and Intention Analysis (Server)

[0715] The converted text data is passed to a natural language processing engine (e.g., NLTK, spaCy) to analyze the user's intent, for example, to understand a specific request such as "I want to know the meaning of a specific scientific term."

[0716] 4. Digital Book Database Search (Server)

[0717] Based on the analyzed user intent, the server searches the corresponding digital book database, identifies the chapter or section containing the relevant information, and extracts the required information.

[0718] 5. Emotional speech generation (server)

[0719] The extracted information is converted into audio data with emotional expressions using a text-to-speech synthesis engine (e.g., Google Text-to-Speech API), allowing users to receive information in a natural and easy-to-understand manner. In addition, appropriate background music may be added in some cases to enhance the listening experience.

[0720] 6. Sending and Playing Audio Data (Terminal)

[0721] The final generated voice data is sent from the server to the terminal, which then plays the received voice data and provides the information to the user.

[0722] Hardware and software used

[0723] Hardware: Smartphone, microphone

[0724] software:

[0725] speech_recognition (speech recognition library)

[0726] requests (a library for sending HTTP requests)

[0727] pyttsx3 (speech synthesis library)

[0728] Google Speech-to-Text API (for voice recognition)

[0729] NLTK or spaCy (for natural language processing)

[0730] Google Text-to-Speech API (for speech synthesis)

[0731] Examples of specific examples and prompts

[0732] Examples:

[0733] 1. The user opens the "Audio Assistant" feature in the smartphone app and asks a voice question such as, "Tell me more about this book."

[0734] 2. The app captures the audio and sends it to the server.

[0735] 3. The server converts the speech into text and retrieves relevant information from a database.

[0736] 4. The information is converted into voice with emotional expressions and sent to a smartphone.

[0737] 5. The app plays a sound and provides the information the user requested.

[0738] Example prompt sentence:

[0739] "What is Schrodinger's cat? Can you explain it in detail?"

[0740] This embodiment allows users to easily obtain detailed information through voice queries and enjoy a richer user experience.

[0741] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0742] Step 1:

[0743] A user taps the microphone button on a smartphone app and asks a question by voice. For example, they say, "Tell me more about this book." Input: User's voice data. Output: Voice data captured on the device.

[0744] Step 2:

[0745] The audio data captured on the device is stored digitally and then sent to the server using an HTTP POST request. Input: Captured audio data. Output: Audio data sent to the server.

[0746] Step 3:

[0747] The server converts the received voice data into text data using a speech recognition engine (such as the Google Speech-to-Text API). Input: Voice data sent to the server. Output: Text data converted by the speech recognition engine.

[0748] Step 4:

[0749] The server uses a natural language processing engine (NLTK, spaCy, etc.) to analyze the text data and understand the user's intent. Input: Text data converted by a speech recognition engine. Output: Analyzed user intent.

[0750] Step 5:

[0751] The server searches the corresponding digital book database based on the analyzed user intent. At this stage, the relevant chapter or page is identified and the necessary information is extracted. Input: Analyzed user intent. Output: Information on the searched digital book.

[0752] Step 6:

[0753] The extracted information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (such as Google Text-to-Speech API). Input: Searched digital book information. Output: Voice data with emotional expressions.

[0754] Step 7:

[0755] If necessary, the server adds appropriate background music to the audio data, improving the listening experience. Input: Audio data with emotional expressions. Output: Audio data with emotional expressions and background music.

[0756] Step 8:

[0757] The server finally sends the generated voice data to the terminal via the network. Input: Voice data with emotional expressions and background music. Output: Voice data sent to the terminal.

[0758] Step 9:

[0759] The terminal plays the received audio data and provides information to the user. Input: Audio data sent to the terminal. Output: Audio information that the user can hear.

[0760] This allows users to quickly and emotively obtain detailed information about specific digital content through audio.

[0761] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0762] This system, when a user makes a voice inquiry about specific information, searches for that information in a digital book, uses an emotion recognition engine to determine the user's emotion, and provides a voice response accompanied by an appropriate emotional expression, operates in cooperation with three entities: a server, a terminal, and a user.

[0763] 1. User operations

[0764] The user asks a question into the voice input interface, in this example "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[0765] 2. Terminal Processing

[0766] The device captures the user's voice and sends the digital audio data to a server using protocols such as HTTP POST requests or WebSockets, and also receives and plays the audio data returned from the server.

[0767] 3. Server Processing

[0768] The server receives the voice data sent from the terminal and performs the following processes in order.

[0769] Speech Recognition Processing

[0770] The server uses a speech recognition engine to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[0771] Natural Language Processing

[0772] The server passes the text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0773] Emotion Recognition Processing

[0774] The converted text and voice data are passed to an emotion recognition engine to determine the user's emotions. The engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[0775] Database search

[0776] The server then searches a digital book database for information about "Schrödinger's Cat" and extracts the relevant text.

[0777] Emotional Expression and Narration Generation

[0778] The acquired text is then passed to a text-to-speech synthesis engine, where it is converted into voice data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated voice to have an inflection and tone that matches the user's emotions. Appropriate background music can also be added to the voice data to improve the listening experience.

[0779] 4. Working Example

[0780] A specific example will now be given: Suppose a user is listening to an audiobook on physics and wants to know more about Schrodinger's cat.

[0781] User Action:

[0782] The user speaks, "What is Schrodinger's cat?"

[0783] Terminal handling:

[0784] The device captures the audio and sends it to the server.

[0785] Server Action:

[0786] The server converts the voice data into text and analyzes it with a natural language processing engine. It then uses an emotion recognition engine to identify the user's emotion (e.g., curiosity). It then searches and extracts relevant information from a digital book database, adds emotional expressions, generates voice data, and adds background music.

[0787] Terminal handling:

[0788] The terminal receives and plays back the audio data sent from the server.

[0789] User Action:

[0790] Users listen to the audio and get a detailed explanation of "Schrödinger's Cat," which is delivered with inflection and tone that reflects the user's emotions, making for a more comprehensible and immersive listening experience.

[0791] In this way, the system can provide information quickly and accurately while taking into account the user's feelings.

[0792] The processing flow will be explained below.

[0793] Step 1:

[0794] The user speaks what they want to know into the device's voice input interface, asking the question, "What is Schrodinger's cat?"

[0795] Step 2:

[0796] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[0797] Step 3:

[0798] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[0799] Step 4:

[0800] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[0801] Step 5:

[0802] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[0803] Step 6:

[0804] The server then passes the converted text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0805] Step 7:

[0806] The server passes the text and voice data to an emotion recognition engine to determine the user's emotion, which infers the emotion from the user's tone of voice and text expression.

[0807] Step 8:

[0808] The server searches the digital book database based on the user's intent, retrieves information about "Schrödinger's Cat," and extracts the relevant text.

[0809] Step 9:

[0810] The server uses a text-to-speech engine to convert the extracted text information into emotionally charged speech data, which adds tone and inflection to match the user's emotions.

[0811] Step 10:

[0812] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[0813] Step 11:

[0814] The server sends the completed audio data to the device via an HTTP POST request or WebSocket.

[0815] Step 12:

[0816] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[0817] Step 13:

[0818] The device then plays the converted audio data through speakers or headphones, allowing users to listen to a detailed explanation of "Schrödinger's Cat." The audio is provided with a tone and background music that matches the user's emotions, providing a clearer and more immersive listening experience.

[0819] Example 2

[0820] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0821] Conventional voice dialogue systems provide information without considering the user's emotions, making it difficult to provide appropriate responses based on the user's emotions and intentions. Furthermore, there is a need to improve the user's listening experience by providing responses accompanied by appropriate background music in addition to speech.

[0822] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0823] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into digital format, means for transmitting the digital voice input to the server, means for converting the voice input into text data, means for analyzing the text data and understanding the user's intention, means for determining the user's emotions from the analyzed text data and voice data, means for searching the contents of a digital book, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for adding background music to the generated voice data, means for transmitting the voice data to the user's terminal, and means for playing the voice data on the user's terminal, thereby enabling appropriate responses that take the user's emotions into consideration and a high-quality listening experience.

[0824] "User voice input" refers to questions or instructions given by the user to the system through voice.

[0825] "Digital format" refers to a format in which an analog signal is converted into digital data.

[0826] A "server" refers to a computer system that receives requests from clients via a network and provides services.

[0827] "Text data" refers to data expressed as character information.

[0828] A "natural language processing engine" refers to a system that analyzes text data and understands and generates human language.

[0829] An "emotion recognition engine" refers to a system for determining a user's emotions from voice data and text data.

[0830] "Digital Book" refers to book data stored in electronic format.

[0831] "Text-to-speech engine" refers to a system for converting text data into speech data.

[0832] "Background music" refers to music that is primarily intended to complement audio data and enhance the listening experience.

[0833] "User terminal" refers to a device that is directly operated by a user, such as a computer system or electronic device that communicates with a server.

[0834] "Audio data" refers to audio information expressed as digital data.

[0835] "Search means" refers to a system or method for locating specific information from a database or storage.

[0836] "Playback means" refers to a system or function that allows the user to listen to the audio data sent from the server.

[0837] This system searches for specific information in digital books when a user makes a voice inquiry, determines the user's emotions, and provides a voice response accompanied by appropriate emotional expressions. This system operates in cooperation with three entities: the user, the terminal, and the server.

[0838] First, the user asks a question to the voice input interface. Let's take the question "What is Schrodinger's cat?" as an example. This voice input is captured as digital voice data by the device. The device uses a microphone to capture the voice and converts it into a digital format. This digital voice data is sent to the server using a protocol such as an HTTP POST request or WebSocket.

[0839] The server receives the voice data sent from the device and first converts the voice data into text data using a speech recognition engine. For example, a general API service (e.g., Google Cloud Speech-to-Text API) can be used as the speech recognition engine. This results in the text data "What is Schrodinger's cat?"

[0840] The server then passes this text data to a natural language processing engine to analyze the user's intent. The natural language processing engine uses a generative AI model (e.g., the OpenAI GPT model). This analysis determines that the user is looking for information about "Schrödinger's cat."

[0841] The server then passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions. A common API service (e.g., IBM Watson Emotion Analysis) is used as the emotion recognition engine. This engine estimates the user's emotions (e.g., curiosity, confusion, excitement) from the user's tone of voice and the context of the text.

[0842] Next, the server searches a digital book database to obtain information about "Schrödinger's Cat." The digital book database uses a common API service (e.g., the API of an e-book store). The server identifies and extracts the relevant text.

[0843] The acquired text is then converted into voice data by adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine and passed to a text-to-speech synthesis engine. For example, a common API service (e.g., Amazon Polly) can be used as the voice synthesis engine. The voice data is given inflection and tone according to the user's emotions. The listening experience can also be improved by adding background music to the generated voice data.

[0844] Finally, the generated audio data is sent back to the device from the server. The device then plays the received audio data through the speaker. The user can then listen to the audio and receive a detailed explanation of "Schrödinger's Cat." The explanation is delivered with intonation and tone that reflects the user's emotions, providing a more understandable and immersive listening experience.

[0845] Prompt Sentence Examples

[0846] "Please explain in detail how the system will provide an answer when a user asks a question about Schrodinger's cat."

[0847] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0848] Step 1:

[0849] The user asks a question into the voice input interface.

[0850] Input: User speech (e.g., "What is Schrodinger's cat?")

[0851] Output: Audio data

[0852] Specific operation: The user speaks a question into the device's microphone, which captures the voice as an analog signal.

[0853] Step 2:

[0854] The terminal converts the user's voice into a digital format.

[0855] Input: Analog audio signal

[0856] Output: Digital audio data

[0857] How it works: The device uses a microphone to capture audio, converts the analog audio signal into digital form, and stores the digital audio data in the device's memory.

[0858] Step 3:

[0859] The terminal transmits digital audio data to the server.

[0860] Input: Digital audio data

[0861] Output: Request to the server (HTTP POST or WebSocket)

[0862] What happens: The device extracts the digital audio data and sends it to the server using a network protocol (e.g., HTTP POST request or WebSocket).

[0863] Step 4:

[0864] The server receives the digital voice data and converts the voice data into text data using a voice recognition engine.

[0865] Input: Digital audio data

[0866] Output: Text data (e.g., "What is Schrodinger's cat?")

[0867] How it works: The server receives digital voice data sent from the device and passes it to a speech recognition engine (e.g., Google Cloud Speech-to-Text API), which analyzes the voice data and generates corresponding text data.

[0868] Step 5:

[0869] The server passes the text data to a natural language processing engine to analyze the user's intent.

[0870] Input: Text data (e.g., "What is Schrodinger's cat?")

[0871] Output: User intent (e.g., "I'm looking for information about Schrodinger's cat")

[0872] How it works: The server passes the generated text data to a natural language processing engine (e.g., OpenAI GPT model), which analyzes the text data and interprets the user's intent.

[0873] Step 6:

[0874] The server passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions.

[0875] Input: Text and audio data

[0876] Output: User emotion (e.g., curiosity, confusion, excitement)

[0877] Specific operation: The server passes the text and voice data to an emotion recognition engine (e.g., IBM Watson Emotion Analysis). The engine analyzes the data and estimates the user's emotions.

[0878] Step 7:

[0879] The server searches the digital book database and extracts the relevant information.

[0880] Input: User intent (e.g., "information about Schrodinger's cat")

[0881] Output: Corresponding text information

[0882] Specific operation: The server searches a digital book database (e.g., an API of an e-book store) and extracts relevant information based on the user's intent.

[0883] Step 8:

[0884] The server converts the extracted information into voice data accompanied by emotional expressions.

[0885] Input: relevant text information and user sentiment

[0886] Output: Generated audio data

[0887] Specific operation: The server adds emotional expressions determined by the emotion recognition engine to the extracted text information, and passes the data to a text-to-speech synthesis engine (e.g., Amazon Polly) to generate voice data.

[0888] Step 9:

[0889] The server adds appropriate background music to the generated audio data.

[0890] Input: Generated audio data

[0891] Output: Audio data including background music

[0892] Specific operation: The server selects background music suitable for the generated audio data and incorporates it into the audio data, thereby improving the listening experience.

[0893] Step 10:

[0894] The server sends the final audio data to the terminal.

[0895] Input: Audio data including background music

[0896] Output: Request to the device (HTTP POST or WebSocket)

[0897] Specific operation: The server generates the final audio data including background music and sends it to the terminal via a network protocol.

[0898] Step 11:

[0899] The terminal receives the audio data sent from the server and plays it back.

[0900] Input: Audio data including background music

[0901] Output: Audio output through speakers

[0902] Specific operation: The terminal receives the voice data sent from the server and plays it through the speaker, allowing the user to listen to the voice and obtain detailed answers to their questions.

[0903] (Application example 2)

[0904] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0905] Current content delivery services lack systems that can quickly and accurately respond to questions or concerns that arise while users are listening to audiobooks or other digital content. This requires users to interrupt the content and perform a search, which detracts from the listening experience. Furthermore, existing systems struggle to provide appropriate answers that reflect the user's emotions, creating a need for improved user experience.

[0906] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intention, means for searching for the details of digital content based on the analysis results, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for transmitting the voice data to the user's information processing device, means for analyzing the user's emotions using an emotion recognition engine, and means for generating voice by adding an appropriate emotional expression based on the emotions. This allows the user to receive an answer according to the emotion through an information processing device such as a smartphone without interrupting the content, enabling a more natural and immersive listening experience.

[0907] "Voice input from the user" refers to voice data spoken by the user, and is an input means used by the system to receive and analyze this data.

[0908] The "means for converting received voice input into text data" refers to a process for converting a user's voice data into corresponding text data, such as using a voice recognition engine.

[0909] "Means for analyzing text data and understanding user intent" refers to the process of using a natural language processing engine to analyze what the user is looking for from the converted text data.

[0910] "Means for searching the contents of digital content" refers to the process of searching databases such as digital books and audiobooks based on the user's intent to find relevant information.

[0911] "Means for extracting relevant information based on search results" refers to the process of extracting information from the searched digital content that directly answers the user's question.

[0912] The "means for converting extracted information into voice data accompanied by emotional expression" refers to the process of generating voice with intonation and tone appropriate to the user's emotions when converting extracted information into voice data using a text-to-speech synthesis engine.

[0913] "Means for transmitting voice data to a user's information processing device" refers to a process for transmitting the generated voice data to a user's information processing device such as a smartphone or PC via the Internet or other communication means.

[0914] "Means for analyzing user emotions using an emotion recognition engine" is a technology for estimating emotions from a user's voice data and text data, and is a process for identifying the emotions the user is feeling.

[0915] "Means for generating voice by adding appropriate emotional expressions based on emotions" is a technology that uses the results of an emotion recognition engine to add intonation and tone to the generated voice data according to the user's emotions.

[0916] The present invention is a system in which, when a user expresses a question or interest through voice input, the system searches for the relevant information from digital content, determines the user's emotion using an emotion recognition engine, and provides a voice response accompanied by an appropriate emotional expression. This system operates in cooperation with three entities: a server, a terminal, and the user.

[0917] 1. User operations

[0918] The user asks a question to the voice input interface, for example, "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[0919] 2. Terminal Processing

[0920] The user's voice is captured by a device such as a smartphone or tablet. The device then uses a communication protocol such as an HTTP POST request or WebSocket to send the digital audio data to a server. The device also has the ability to receive and play the digital audio data returned from the server.

[0921] 3. Server Processing

[0922] The server receives the voice data sent from the terminal and performs the following processes in order.

[0923] Speech Recognition Processing

[0924] The server uses a speech recognition engine (such as Google Speech-to-Text) to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[0925] Natural Language Processing

[0926] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[0927] Emotion Recognition Processing

[0928] The converted text and voice data are passed to an emotion recognition engine (such as IBM Watson Tone Analyzer) to determine the user's emotions. This engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[0929] Database search

[0930] The server then searches a digital content database (e.g., Kindle, Google Books) to retrieve information about "Schrödinger's Cat" and extracts the relevant text.

[0931] Emotional Expression and Narration Generation

[0932] The acquired text is then passed to a text-to-speech engine (e.g., Amazon Polly) where it is converted into audio data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated audio to have an inflection and tone that matches the user's emotions. Appropriate background music and sound effects can also be added to the audio data to improve the listening experience.

[0933] 4. Working Example

[0934] Here is a specific example: Let us consider the case where a user is listening to an audiobook and thinks, "I want to know more about Schrodinger's cat."

[0935] User operations

[0936] The user speaks, "What is Schrodinger's cat?" The server generates a response in an uplifting tone, depending on the curiosity inferred from the user's voice.

[0937] Search and Response

[0938] The server performs voice recognition, natural language processing, and emotion recognition, searches for relevant information in a digital content database, adds emotional expressions, generates audio data, and sends it along with background music to the user's device, which receives and plays it.

[0939] Examples of prompt statements

[0940] Initial prompt: "A user is listening to an audiobook and asks a question about a passage they're unsure about. How can you create a content delivery app that responds to this question with an emotionally relevant answer?"

[0941] Question prompt: "What is Schrodinger's cat?"

[0942] This invention allows users to receive natural emotional responses without interrupting the content, improving the listening experience.

[0943] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0944] Step 1:

[0945] A user speaks into a device such as a smartphone or tablet. For example, a specific question might be, "What is Schrödinger's cat?" The device captures and stores this speech as digital audio data. The input is the user's voice, and the output is digital audio data.

[0946] Step 2:

[0947] The device sends the stored digital audio data to the server. The audio data is securely transmitted using a communication protocol such as an HTTP POST request or WebSocket. The input of this step is the digital audio data, and the output is the data transmitted to the server.

[0948] Step 3:

[0949] The server receives the digital voice data sent from the device. It converts the received voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text). Specifically, it analyzes the voice waveform and generates a corresponding text string. The input is digital voice data, and the output is the text data "What is Schrödinger's cat?"

[0950] Step 4:

[0951] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent. Through this analysis, the server understands the content of the user's question and the information they are looking for from the text. Specifically, it performs grammatical analysis and semantic analysis. The input is text data, and the output is the user's intent, which is "I'm looking for information about Schrodinger's cat."

[0952] Step 5:

[0953] The server passes the converted text and voice data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotion. Specifically, it identifies the emotional state from the tone of the voice and the content of the text. The input is text and voice data, and the output is a determination that the user's emotion is "curiosity."

[0954] Step 6:

[0955] The server searches a digital content database (e.g., Kindle, Google Books) and retrieves information about "Schrödinger's Cat" based on the user's intent. Specifically, it uses a content search API to extract the relevant text. The input is the user's intent, and the output is text data containing the relevant information.

[0956] Step 7:

[0957] The server adds appropriate emotional expressions to the acquired text data based on the results of the emotion recognition engine and converts it into voice data. Specifically, it uses a text-to-speech synthesis engine (e.g., Amazon Polly) to add intonation and tone according to the emotion to the voice. The input is text data and emotional information, and the output is voice data accompanied by emotional expressions.

[0958] Step 8:

[0959] The server adds appropriate background music and sound effects to the generated audio data. Specifically, it uses an audio mixing tool to combine the music track and the audio track. The input is audio data and background music, and the output is audio data with background music.

[0960] Step 9:

[0961] The server sends the final audio data to the user's terminal. The input is the audio data with background music, and the output is the data sent to the user's terminal.

[0962] Step 10:

[0963] The device receives the audio data sent from the server and plays it through the audio playback application. Specifically, it activates the audio playback function and outputs the data from the speaker. The input is audio data with background music, and the output is the audio that the user actually hears.

[0964] By following these steps, if a user has a question while listening to an audiobook, they can receive an answer that suits their feelings without interrupting the content.

[0965] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0966] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0967] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0968] [Third embodiment]

[0969] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0970] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0971] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0972] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0973] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0974] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0975] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0976] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0977] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0978] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0979] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0980] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0981] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[0982] 1. User operations

[0983] A user uses the device's voice input interface to ask a question, for example, "What is Schrodinger's cat?" This voice input is captured by the device and stored as digital audio data.

[0984] 2. Terminal Processing

[0985] The device sends the captured audio data to the server using a network protocol such as an HTTP POST request. It also has the ability to receive and play the audio data returned from the server. The device acts as a bridge between the server and the user, properly transmitting the information the server requests and accurately conveying the information provided by the server to the user.

[0986] 3. Server Processing

[0987] The server receives the voice data sent from the terminal. After receiving the data, the server performs the following processes in order.

[0988] Speech Recognition Processing

[0989] The server uses a speech recognition engine to convert the voice data into text data, which allows it to understand what the user is asking as text information.

[0990] Natural Language Processing

[0991] The converted text data is passed to a natural language processing engine to analyze the user's intent. For example, it may recognize that the user is looking for an explanation of Schrodinger's cat.

[0992] Database search

[0993] Based on the user's intent, the server searches the digital book database to retrieve the relevant information, in this case extracting the required information from the chapter or section about Schrodinger's Cat.

[0994] Emotional Expression and Narration Generation

[0995] The acquired information is converted into emotionally expressive audio data using a text-to-speech engine, providing users with a natural and easy-to-understand presentation of the information. The listening experience can also be further enhanced by adding appropriate background music.

[0996] 4. Working Example

[0997] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[0998] User Action:

[0999] User: "What is Schrodinger's cat?"

[1000] Terminal handling:

[1001] The device captures the audio and sends the data to the server.

[1002] Server Action:

[1003] The server converts the audio data into text data, analyzes it, and extracts the relevant information from the digital book.

[1004] After that, audio data with emotional expressions is generated, background music is added, and the data is sent to the device.

[1005] Terminal handling:

[1006] The device plays the received audio data.

[1007] User Action:

[1008] The user listens to the audio playback and gets a detailed explanation of "Schrödinger's Cat."

[1009] This allows users to gain a deeper understanding of technical terms and difficult content. The distinctive feature of the present invention is that, as claimed, a system has been realized in which these functions and processes are integrated.

[1010] The processing flow will be explained below.

[1011] Step 1:

[1012] The user speaks into the device's voice input interface to ask what they want to know. In this example, they ask the question, "What is Schrodinger's cat?"

[1013] Step 2:

[1014] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[1015] Step 3:

[1016] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[1017] Step 4:

[1018] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[1019] Step 5:

[1020] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[1021] Step 6:

[1022] The server passes the converted text data to a natural language processing engine, which analyzes the text and identifies the user's intent.

[1023] Step 7:

[1024] The server searches the digital book database based on the user's intent, searching for information about "Schrödinger's Cat" and extracting relevant text.

[1025] Step 8:

[1026] The server uses a text-to-speech engine to convert the extracted text into emotionally charged speech data, where emotions and intonation are added to the narration.

[1027] Step 9:

[1028] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[1029] Step 10:

[1030] The server then sends the completed audio data to the device, again via an HTTP POST request or WebSocket.

[1031] Step 11:

[1032] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[1033] Step 12:

[1034] The device then plays the converted audio data through a speaker or headphones, allowing the user to listen to a detailed explanation of "Schrödinger's Cat."

[1035] Through the above steps, the system can quickly and accurately provide the information the user desires.

[1036] Example 1

[1037] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1038] Today's users want to quickly and easily understand digital books and specialized information. However, text-based information search can be time-consuming and difficult to understand when it contains a lot of technical terminology. While voice-based information retrieval systems exist, they typically lack emotional expression and background music, which leaves users unsatisfied. To address these challenges, a system is needed that allows users to simply ask questions and receive specific information in voice-activated speech.

[1039] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1040] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and understanding the user's intent, means for searching the contents of digital books and extracting relevant information, means for converting the acquired information into voice data with emotional expressions and adding background music, and means for transmitting the voice data to the user's terminal, thereby enabling the user to easily ask questions by voice and instantly receive specialized information in voice with emotional expressions.

[1041] "Voice input" refers to voice data provided by a user speaking into a microphone.

[1042] A "server" refers to a computer system that provides services to other devices and software on a network.

[1043] A "terminal" refers to a component having input and output devices that can be directly operated by a user.

[1044] "Audio data" refers to data that has been recorded or processed by converting audio into digital form.

[1045] "Text data" refers to data that has been converted from voice data into text information.

[1046] "Analysis means" refers to a series of processes that understand the user's intent based on text data and perform the necessary processing.

[1047] "Search method" refers to the process used to locate specific keywords or content within a digital book database.

[1048] "Extraction method" refers to the process for extracting the required information from the search results.

[1049] "Emotionally-expressed voice data" refers to voice data to which emotions and intonation have been added, as opposed to voice data generated simply from text.

[1050] "Background music" refers to music that is added to audio data to enhance the user's listening experience.

[1051] "Transmission" refers to a process for transferring data from one device to another.

[1052] "Receiving means" refers to the process by which one device receives data sent from another device.

[1053] "Playback means" refers to a process for letting the user hear audio data through a speaker or the like.

[1054] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[1055] User operations

[1056] The user asks a question using the device's voice input interface. For example, the user might say, "What is Schrodinger's cat?" The device captures and stores this voice in digital form. This voice input interface can be a regular microphone, a smartphone microphone, or even a smart speaker.

[1057] Terminal handling

[1058] The device sends the captured audio data to the server using an HTTP POST request. HTTPS is often used as the network protocol. The device also has the ability to receive and play back audio data with emotional expressions returned from the server. For example, if a user wants to know more about "Schrödinger's Cat," the device sends this question to the server.

[1059] Server Processing

[1060] After receiving the voice data transmitted from the terminal, the server performs the following processes in order.

[1061] Speech Recognition Processing

[1062] The server converts the voice data into text data using a speech recognition engine (for example, Google Speech-to-Text API), which makes it possible to understand the content of the user's question as text information.

[1063] Natural Language Processing

[1064] The converted text data is passed to a natural language processing engine (e.g., a generative AI model such as GPT-3) to analyze the user's intent. For example, it may be analyzed that the user is looking for an explanation of Schrödinger's cat.

[1065] Database search

[1066] Based on the user's intent, the server searches a digital book database (e.g., Amazon Athena or other cloud database) and retrieves relevant information, typically a chapter or section about Schrödinger's cat.

[1067] Emotional Expression and Narration Generation

[1068] The acquired text information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (e.g., Amazon Polly), and appropriate background music (e.g., Bensound's free music library) is added to the voice data to improve the user's listening experience.

[1069] Example

[1070] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[1071] User Action:

[1072] User: "What is Schrodinger's cat?"

[1073] Terminal handling:

[1074] The device captures the audio and sends the data to the server.

[1075] Server Action:

[1076] The server converts the audio data into text data, analyzes it, extracts relevant information from the digital book, generates audio data with emotional expressions, adds background music, and transmits it to the device.

[1077] Terminal handling:

[1078] The terminal plays back the received audio data.

[1079] User Action:

[1080] The user can listen to the audio playback and get a detailed explanation of "Schrödinger's Cat."

[1081] Examples of prompt statements

[1082] Below is an example of a prompt sentence to input to the generative AI model.

[1083] text

[1084] "What is Schrodinger's cat?"

[1085] Using this prompt, the natural language processing engine understands that you are looking for an explanation of "Schrödinger's cat" and searches for and provides the corresponding information.

[1086] This system allows users to quickly and emotionally understand the contents of digital books through voice input.

[1087] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1088] Step 1:

[1089] User voice input

[1090] The user asks a question to the device's voice input interface, for example, "What is Schrodinger's cat?"

[1091] Input: User's voice data

[1092] Output: Digital audio data

[1093] Specific behavior:

[1094] Users ask questions into their smartphone or smart speaker, and the built-in microphone captures the audio.

[1095] Step 2:

[1096] Sending audio data by the device

[1097] The device sends the captured audio data to the server using an HTTP POST request.

[1098] Input: User's digital voice data

[1099] Output: HTTP request sent to the server

[1100] Specific behavior:

[1101] The device sends the audio data to the server via an internet connection, using HTTPS as the communication protocol.

[1102] Step 3:

[1103] Receiving audio data by the server

[1104] The server receives the voice data transmitted from the terminal.

[1105] Input: Audio data via HTTP POST request

[1106] Output: Audio data in the server

[1107] Specific behavior:

[1108] The server monitors the API endpoint and adds received audio data to its internal memory or to a processing queue.

[1109] Step 4:

[1110] Server-based speech-to-text conversion

[1111] The server converts the voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text).

[1112] Input: Audio data in the server

[1113] Output: Text data

[1114] Specific behavior:

[1115] The server sends the voice data to the voice recognition API and receives text data as a response.

[1116] Step 5:

[1117] Analysis of text data by the server

[1118] The server uses a natural language processing engine (e.g., GPT-3) to analyze the text data and understand the user's intent.

[1119] Input: Text data

[1120] Output: Analysis results (information indicating the user's intent)

[1121] Specific behavior:

[1122] The server inputs the text data into a natural language processing engine and receives the analyzed results.

[1123] Step 6:

[1124] Server-based search for digital books

[1125] The server searches the digital book database based on the analysis results and obtains the relevant information.

[1126] Input: Analysis results

[1127] Output: Part of the digital book data

[1128] Specific behavior:

[1129] The server uses an SQL query to search a digital book database and extract the section or chapter about Schrödinger's cat.

[1130] Step 7:

[1131] Converting acquired information into voice and adding emotional expressions

[1132] The server uses a text-to-speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into voice data with emotional expressions.

[1133] Input: Text data of a digital book

[1134] Output: Voice data with emotional expressions

[1135] Specific behavior:

[1136] The server sends the text data to the speech synthesis API, sets emotion parameters, and obtains speech data.

[1137] Step 8:

[1138] Add background music

[1139] The server adds background music to the generated emotionally expressive voice data.

[1140] Input: Voice data with emotional expressions, background music file

[1141] Output: Audio data with background music

[1142] Specific behavior:

[1143] The server uses an audio editing tool (e.g., FFmpeg) to combine the audio data with background music.

[1144] Step 9:

[1145] Sending audio data to the device

[1146] The server sends the final voice data with emotional expressions to the terminal as an HTTP response.

[1147] Input: Audio data with background music

[1148] Output: Audio data via HTTP response

[1149] Specific behavior:

[1150] The server generates a response at the API endpoint and sends the audio data to the device.

[1151] Step 10:

[1152] Playback of audio data by the device

[1153] The terminal reproduces the voice data with emotional expressions received from the server.

[1154] Input: Audio data from the server

[1155] Output: Audio playback through speakers

[1156] Specific behavior:

[1157] The device will launch its built-in audio player and play audio through speakers or earphones.

[1158] Step 11:

[1159] User hears audio playback

[1160] The user listens to the audio data played back from the terminal and receives the answer to the question.

[1161] Input: Device audio output

[1162] Output: User understanding

[1163] Specific behavior:

[1164] The user listens to the audio that is played and understands the explanation about "Schrödinger's cat."

[1165] Through each step, users can quickly and emotionally understand the content of the digital book through voice input.

[1166] (Application example 1)

[1167] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1168] In modern content distribution services, it is important for users to quickly and easily obtain specific information. In particular, services that offer a wide range of digital content require systems that allow users to instantly obtain detailed information about specific books or audiobooks. However, current systems lack the means to accurately analyze user intent, search for relevant information, and provide information in a natural-sounding voice that expresses emotions. This leaves users with an insufficient search experience, making it difficult to provide a richer user experience.

[1169] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1170] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intent, means for searching based on the analysis, means for extracting information from the search results, means for converting the extracted information into voice data with emotional expressions, means for transmitting the voice data to the user's terminal, and means for searching for related content based on the user's voice question and providing an answer with emotional expressions. This improves the user's search experience in the content distribution service and makes it possible to provide a richer user experience.

[1171] The "means for receiving voice input from the user" is a function for capturing voice uttered by the user as digital data and inputting it into the system.

[1172] The "means for converting received voice input into text data" is a function that converts captured voice data into text information using a voice recognition engine.

[1173] "Means for analyzing text data and understanding user intent" refers to a function that uses natural language processing technology to analyze and understand the meaning within text data and user requests.

[1174] The "analysis-based search means" is a function that searches related digital books and content databases according to the analyzed user intent.

[1175] "Means for extracting information from search results" refers to the function of extracting specific information that a user desires from searched digital books or content.

[1176] The "means for converting extracted information into voice data with emotional expressions" is a function that uses a text-to-speech synthesis engine to convert extracted text information into a voice format with emotional expressions.

[1177] The "means for transmitting voice data to the user's terminal" is a function for delivering the generated voice data to the user's terminal via a network.

[1178] "Means for searching for related content based on a user's voice question and providing an answer with emotional expressions" is a function that analyzes a user's voice question, searches for content related to that question, and then returns an answer in an emotionally rich voice.

[1179] The system for realizing this application example combines the following means in a series of processes: The user, terminal, and server work together to search for and provide relevant content based on the user's voice question.

[1180] System program generation and operation

[1181] 1. Audio capture and transmission (terminal)

[1182] The user types a voice question using the device's microphone, and this voice data is captured and stored digitally on the device, then sent to the server via an HTTP POST request.

[1183] 2. Speech recognition and text conversion (server)

[1184] The server converts the received voice data into text data using a speech recognition engine (e.g., Google Speech-to-Text API). Through this step, the server understands what the user has asked as text information.

[1185] 3. Natural Language Processing and Intention Analysis (Server)

[1186] The converted text data is passed to a natural language processing engine (e.g., NLTK, spaCy) to analyze the user's intent, for example, to understand a specific request such as "I want to know the meaning of a specific scientific term."

[1187] 4. Digital Book Database Search (Server)

[1188] Based on the analyzed user intent, the server searches the corresponding digital book database, identifies the chapter or section containing the relevant information, and extracts the required information.

[1189] 5. Emotional speech generation (server)

[1190] The extracted information is converted into audio data with emotional expressions using a text-to-speech synthesis engine (e.g., Google Text-to-Speech API), allowing users to receive information in a natural and easy-to-understand manner. In addition, appropriate background music may be added in some cases to enhance the listening experience.

[1191] 6. Sending and Playing Audio Data (Terminal)

[1192] The final generated voice data is sent from the server to the terminal, which then plays the received voice data and provides the information to the user.

[1193] Hardware and software used

[1194] Hardware: Smartphone, microphone

[1195] software:

[1196] speech_recognition (speech recognition library)

[1197] requests (a library for sending HTTP requests)

[1198] pyttsx3 (speech synthesis library)

[1199] Google Speech-to-Text API (for voice recognition)

[1200] NLTK or spaCy (for natural language processing)

[1201] Google Text-to-Speech API (for speech synthesis)

[1202] Examples of specific examples and prompts

[1203] Examples:

[1204] 1. The user opens the "Audio Assistant" feature in the smartphone app and asks a voice question such as, "Tell me more about this book."

[1205] 2. The app captures the audio and sends it to the server.

[1206] 3. The server converts the speech into text and retrieves relevant information from a database.

[1207] 4. The information is converted into voice with emotional expressions and sent to a smartphone.

[1208] 5. The app plays a sound and provides the information the user requested.

[1209] Example prompt sentence:

[1210] "What is Schrodinger's cat? Can you explain it in detail?"

[1211] This embodiment allows users to easily obtain detailed information through voice queries and enjoy a richer user experience.

[1212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1213] Step 1:

[1214] A user taps the microphone button on a smartphone app and asks a question by voice. For example, they say, "Tell me more about this book." Input: User's voice data. Output: Voice data captured on the device.

[1215] Step 2:

[1216] The audio data captured on the device is stored digitally and then sent to the server using an HTTP POST request. Input: Captured audio data. Output: Audio data sent to the server.

[1217] Step 3:

[1218] The server converts the received voice data into text data using a speech recognition engine (such as the Google Speech-to-Text API). Input: Voice data sent to the server. Output: Text data converted by the speech recognition engine.

[1219] Step 4:

[1220] The server uses a natural language processing engine (NLTK, spaCy, etc.) to analyze the text data and understand the user's intent. Input: Text data converted by a speech recognition engine. Output: Analyzed user intent.

[1221] Step 5:

[1222] The server searches the corresponding digital book database based on the analyzed user intent. At this stage, the relevant chapter or page is identified and the necessary information is extracted. Input: Analyzed user intent. Output: Information on the searched digital book.

[1223] Step 6:

[1224] The extracted information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (such as Google Text-to-Speech API). Input: Searched digital book information. Output: Voice data with emotional expressions.

[1225] Step 7:

[1226] If necessary, the server adds appropriate background music to the audio data, improving the listening experience. Input: Audio data with emotional expressions. Output: Audio data with emotional expressions and background music.

[1227] Step 8:

[1228] The server finally sends the generated voice data to the terminal via the network. Input: Voice data with emotional expressions and background music. Output: Voice data sent to the terminal.

[1229] Step 9:

[1230] The terminal plays the received audio data and provides information to the user. Input: Audio data sent to the terminal. Output: Audio information that the user can hear.

[1231] This allows users to quickly and emotively obtain detailed information about specific digital content through audio.

[1232] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1233] This system, when a user makes a voice inquiry about specific information, searches for that information in a digital book, uses an emotion recognition engine to determine the user's emotion, and provides a voice response accompanied by an appropriate emotional expression, operates in cooperation with three entities: a server, a terminal, and a user.

[1234] 1. User operations

[1235] The user asks a question into the voice input interface, in this example "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[1236] 2. Terminal Processing

[1237] The device captures the user's voice and sends the digital audio data to a server using protocols such as HTTP POST requests or WebSockets, and also receives and plays the audio data returned from the server.

[1238] 3. Server Processing

[1239] The server receives the voice data sent from the terminal and performs the following processes in order.

[1240] Speech Recognition Processing

[1241] The server uses a speech recognition engine to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[1242] Natural Language Processing

[1243] The server passes the text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1244] Emotion Recognition Processing

[1245] The converted text and voice data are passed to an emotion recognition engine to determine the user's emotions. The engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[1246] Database search

[1247] The server then searches a digital book database for information about "Schrödinger's Cat" and extracts the relevant text.

[1248] Emotional Expression and Narration Generation

[1249] The acquired text is then passed to a text-to-speech synthesis engine, where it is converted into voice data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated voice to have an inflection and tone that matches the user's emotions. Appropriate background music can also be added to the voice data to improve the listening experience.

[1250] 4. Working Example

[1251] A specific example will now be given: Suppose a user is listening to an audiobook on physics and wants to know more about Schrodinger's cat.

[1252] User Action:

[1253] The user speaks, "What is Schrodinger's cat?"

[1254] Terminal handling:

[1255] The device captures the audio and sends it to the server.

[1256] Server Action:

[1257] The server converts the voice data into text and analyzes it with a natural language processing engine. It then uses an emotion recognition engine to identify the user's emotion (e.g., curiosity). It then searches and extracts relevant information from a digital book database, adds emotional expressions, generates voice data, and adds background music.

[1258] Terminal handling:

[1259] The terminal receives and plays back the audio data sent from the server.

[1260] User Action:

[1261] Users listen to the audio and get a detailed explanation of "Schrödinger's Cat," which is delivered with inflection and tone that reflects the user's emotions, making for a more comprehensible and immersive listening experience.

[1262] In this way, the system can provide information quickly and accurately while taking into account the user's feelings.

[1263] The processing flow will be explained below.

[1264] Step 1:

[1265] The user speaks what they want to know into the device's voice input interface, asking the question, "What is Schrodinger's cat?"

[1266] Step 2:

[1267] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[1268] Step 3:

[1269] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[1270] Step 4:

[1271] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[1272] Step 5:

[1273] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[1274] Step 6:

[1275] The server then passes the converted text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1276] Step 7:

[1277] The server passes the text and voice data to an emotion recognition engine to determine the user's emotion, which infers the emotion from the user's tone of voice and text expression.

[1278] Step 8:

[1279] The server searches the digital book database based on the user's intent, retrieves information about "Schrödinger's Cat," and extracts the relevant text.

[1280] Step 9:

[1281] The server uses a text-to-speech engine to convert the extracted text information into emotionally charged speech data, which adds tone and inflection to match the user's emotions.

[1282] Step 10:

[1283] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[1284] Step 11:

[1285] The server sends the completed audio data to the device via an HTTP POST request or WebSocket.

[1286] Step 12:

[1287] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[1288] Step 13:

[1289] The device then plays the converted audio data through speakers or headphones, allowing users to listen to a detailed explanation of "Schrödinger's Cat." The audio is provided with a tone and background music that matches the user's emotions, providing a clearer and more immersive listening experience.

[1290] Example 2

[1291] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1292] Conventional voice dialogue systems provide information without considering the user's emotions, making it difficult to provide appropriate responses based on the user's emotions and intentions. Furthermore, there is a need to improve the user's listening experience by providing responses accompanied by appropriate background music in addition to speech.

[1293] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1294] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into digital format, means for transmitting the digital voice input to the server, means for converting the voice input into text data, means for analyzing the text data and understanding the user's intention, means for determining the user's emotions from the analyzed text data and voice data, means for searching the contents of a digital book, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for adding background music to the generated voice data, means for transmitting the voice data to the user's terminal, and means for playing the voice data on the user's terminal, thereby enabling appropriate responses that take the user's emotions into consideration and a high-quality listening experience.

[1295] "User voice input" refers to questions or instructions given by the user to the system through voice.

[1296] "Digital format" refers to a format in which an analog signal is converted into digital data.

[1297] A "server" refers to a computer system that receives requests from clients via a network and provides services.

[1298] "Text data" refers to data expressed as character information.

[1299] A "natural language processing engine" refers to a system that analyzes text data and understands and generates human language.

[1300] An "emotion recognition engine" refers to a system for determining a user's emotions from voice data and text data.

[1301] "Digital Book" refers to book data stored in electronic format.

[1302] "Text-to-speech engine" refers to a system for converting text data into speech data.

[1303] "Background music" refers to music that is primarily intended to complement audio data and enhance the listening experience.

[1304] "User terminal" refers to a device that is directly operated by a user, such as a computer system or electronic device that communicates with a server.

[1305] "Audio data" refers to audio information expressed as digital data.

[1306] "Search means" refers to a system or method for locating specific information from a database or storage.

[1307] "Playback means" refers to a system or function that allows the user to listen to the audio data sent from the server.

[1308] This system searches for specific information in digital books when a user makes a voice inquiry, determines the user's emotions, and provides a voice response accompanied by appropriate emotional expressions. This system operates in cooperation with three entities: the user, the terminal, and the server.

[1309] First, the user asks a question to the voice input interface. Let's take the question "What is Schrodinger's cat?" as an example. This voice input is captured as digital voice data by the device. The device uses a microphone to capture the voice and converts it into a digital format. This digital voice data is sent to the server using a protocol such as an HTTP POST request or WebSocket.

[1310] The server receives the voice data sent from the device and first converts the voice data into text data using a speech recognition engine. For example, a general API service (e.g., Google Cloud Speech-to-Text API) can be used as the speech recognition engine. This results in the text data "What is Schrodinger's cat?"

[1311] The server then passes this text data to a natural language processing engine to analyze the user's intent. The natural language processing engine uses a generative AI model (e.g., the OpenAI GPT model). This analysis determines that the user is looking for information about "Schrödinger's cat."

[1312] The server then passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions. A common API service (e.g., IBM Watson Emotion Analysis) is used as the emotion recognition engine. This engine estimates the user's emotions (e.g., curiosity, confusion, excitement) from the user's tone of voice and the context of the text.

[1313] Next, the server searches a digital book database to obtain information about "Schrödinger's Cat." The digital book database uses a common API service (e.g., the API of an e-book store). The server identifies and extracts the relevant text.

[1314] The acquired text is then converted into voice data by adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine and passed to a text-to-speech synthesis engine. For example, a common API service (e.g., Amazon Polly) can be used as the voice synthesis engine. The voice data is given inflection and tone according to the user's emotions. The listening experience can also be improved by adding background music to the generated voice data.

[1315] Finally, the generated audio data is sent back to the device from the server. The device then plays the received audio data through the speaker. The user can then listen to the audio and receive a detailed explanation of "Schrödinger's Cat." The explanation is delivered with intonation and tone that reflects the user's emotions, providing a more understandable and immersive listening experience.

[1316] Prompt Sentence Examples

[1317] "Please explain in detail how the system will provide an answer when a user asks a question about Schrodinger's cat."

[1318] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1319] Step 1:

[1320] The user asks a question into the voice input interface.

[1321] Input: User speech (e.g., "What is Schrodinger's cat?")

[1322] Output: Audio data

[1323] Specific operation: The user speaks a question into the device's microphone, which captures the voice as an analog signal.

[1324] Step 2:

[1325] The terminal converts the user's voice into a digital format.

[1326] Input: Analog audio signal

[1327] Output: Digital audio data

[1328] How it works: The device uses a microphone to capture audio, converts the analog audio signal into digital form, and stores the digital audio data in the device's memory.

[1329] Step 3:

[1330] The terminal transmits digital audio data to the server.

[1331] Input: Digital audio data

[1332] Output: Request to the server (HTTP POST or WebSocket)

[1333] What happens: The device extracts the digital audio data and sends it to the server using a network protocol (e.g., HTTP POST request or WebSocket).

[1334] Step 4:

[1335] The server receives the digital voice data and converts the voice data into text data using a voice recognition engine.

[1336] Input: Digital audio data

[1337] Output: Text data (e.g., "What is Schrodinger's cat?")

[1338] How it works: The server receives digital voice data sent from the device and passes it to a speech recognition engine (e.g., Google Cloud Speech-to-Text API), which analyzes the voice data and generates corresponding text data.

[1339] Step 5:

[1340] The server passes the text data to a natural language processing engine to analyze the user's intent.

[1341] Input: Text data (e.g., "What is Schrodinger's cat?")

[1342] Output: User intent (e.g., "I'm looking for information about Schrodinger's cat")

[1343] How it works: The server passes the generated text data to a natural language processing engine (e.g., OpenAI GPT model), which analyzes the text data and interprets the user's intent.

[1344] Step 6:

[1345] The server passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions.

[1346] Input: Text and audio data

[1347] Output: User emotion (e.g., curiosity, confusion, excitement)

[1348] Specific operation: The server passes the text and voice data to an emotion recognition engine (e.g., IBM Watson Emotion Analysis). The engine analyzes the data and estimates the user's emotions.

[1349] Step 7:

[1350] The server searches the digital book database and extracts the relevant information.

[1351] Input: User intent (e.g., "information about Schrodinger's cat")

[1352] Output: Corresponding text information

[1353] Specific operation: The server searches a digital book database (e.g., an API of an e-book store) and extracts relevant information based on the user's intent.

[1354] Step 8:

[1355] The server converts the extracted information into voice data accompanied by emotional expressions.

[1356] Input: relevant text information and user sentiment

[1357] Output: Generated audio data

[1358] Specific operation: The server adds emotional expressions determined by the emotion recognition engine to the extracted text information, and passes the data to a text-to-speech synthesis engine (e.g., Amazon Polly) to generate voice data.

[1359] Step 9:

[1360] The server adds appropriate background music to the generated audio data.

[1361] Input: Generated audio data

[1362] Output: Audio data including background music

[1363] Specific operation: The server selects background music suitable for the generated audio data and incorporates it into the audio data, thereby improving the listening experience.

[1364] Step 10:

[1365] The server sends the final audio data to the terminal.

[1366] Input: Audio data including background music

[1367] Output: Request to the device (HTTP POST or WebSocket)

[1368] Specific operation: The server generates the final audio data including background music and sends it to the terminal via a network protocol.

[1369] Step 11:

[1370] The terminal receives the audio data sent from the server and plays it back.

[1371] Input: Audio data including background music

[1372] Output: Audio output through speakers

[1373] Specific operation: The terminal receives the voice data sent from the server and plays it through the speaker, allowing the user to listen to the voice and obtain detailed answers to their questions.

[1374] (Application example 2)

[1375] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1376] Current content delivery services lack systems that can quickly and accurately respond to questions or concerns that arise while users are listening to audiobooks or other digital content. This requires users to interrupt the content and perform a search, which detracts from the listening experience. Furthermore, existing systems struggle to provide appropriate answers that reflect the user's emotions, creating a need for improved user experience.

[1377] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intention, means for searching for the details of digital content based on the analysis results, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for transmitting the voice data to the user's information processing device, means for analyzing the user's emotions using an emotion recognition engine, and means for generating voice by adding an appropriate emotional expression based on the emotions. This allows the user to receive an answer according to the emotion through an information processing device such as a smartphone without interrupting the content, enabling a more natural and immersive listening experience.

[1378] "Voice input from the user" refers to voice data spoken by the user, and is an input means used by the system to receive and analyze this data.

[1379] The "means for converting received voice input into text data" refers to a process for converting a user's voice data into corresponding text data, such as using a voice recognition engine.

[1380] "Means for analyzing text data and understanding user intent" refers to the process of using a natural language processing engine to analyze what the user is looking for from the converted text data.

[1381] "Means for searching the contents of digital content" refers to the process of searching databases such as digital books and audiobooks based on the user's intent to find relevant information.

[1382] "Means for extracting relevant information based on search results" refers to the process of extracting information from the searched digital content that directly answers the user's question.

[1383] The "means for converting extracted information into voice data accompanied by emotional expression" refers to the process of generating voice with intonation and tone appropriate to the user's emotions when converting extracted information into voice data using a text-to-speech synthesis engine.

[1384] "Means for transmitting voice data to a user's information processing device" refers to a process for transmitting the generated voice data to a user's information processing device such as a smartphone or PC via the Internet or other communication means.

[1385] "Means for analyzing user emotions using an emotion recognition engine" is a technology for estimating emotions from a user's voice data and text data, and is a process for identifying the emotions the user is feeling.

[1386] "Means for generating voice by adding appropriate emotional expressions based on emotions" is a technology that uses the results of an emotion recognition engine to add intonation and tone to the generated voice data according to the user's emotions.

[1387] The present invention is a system in which, when a user expresses a question or interest through voice input, the system searches for the relevant information from digital content, determines the user's emotion using an emotion recognition engine, and provides a voice response accompanied by an appropriate emotional expression. This system operates in cooperation with three entities: a server, a terminal, and the user.

[1388] 1. User operations

[1389] The user asks a question to the voice input interface, for example, "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[1390] 2. Terminal Processing

[1391] The user's voice is captured by a device such as a smartphone or tablet. The device then uses a communication protocol such as an HTTP POST request or WebSocket to send the digital audio data to a server. The device also has the ability to receive and play the digital audio data returned from the server.

[1392] 3. Server Processing

[1393] The server receives the voice data sent from the terminal and performs the following processes in order.

[1394] Speech Recognition Processing

[1395] The server uses a speech recognition engine (such as Google Speech-to-Text) to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[1396] Natural Language Processing

[1397] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1398] Emotion Recognition Processing

[1399] The converted text and voice data are passed to an emotion recognition engine (such as IBM Watson Tone Analyzer) to determine the user's emotions. This engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[1400] Database search

[1401] The server then searches a digital content database (e.g., Kindle, Google Books) to retrieve information about "Schrödinger's Cat" and extracts the relevant text.

[1402] Emotional Expression and Narration Generation

[1403] The acquired text is then passed to a text-to-speech engine (e.g., Amazon Polly) where it is converted into audio data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated audio to have an inflection and tone that matches the user's emotions. Appropriate background music and sound effects can also be added to the audio data to improve the listening experience.

[1404] 4. Working Example

[1405] Here is a specific example: Let us consider the case where a user is listening to an audiobook and thinks, "I want to know more about Schrodinger's cat."

[1406] User operations

[1407] The user speaks, "What is Schrodinger's cat?" The server generates a response in an uplifting tone, depending on the curiosity inferred from the user's voice.

[1408] Search and Response

[1409] The server performs voice recognition, natural language processing, and emotion recognition, searches for relevant information in a digital content database, adds emotional expressions, generates audio data, and sends it along with background music to the user's device, which receives and plays it.

[1410] Examples of prompt statements

[1411] Initial prompt: "A user is listening to an audiobook and asks a question about a passage they're unsure about. How can you create a content delivery app that responds to this question with an emotionally relevant answer?"

[1412] Question prompt: "What is Schrodinger's cat?"

[1413] This invention allows users to receive natural emotional responses without interrupting the content, improving the listening experience.

[1414] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1415] Step 1:

[1416] A user speaks into a device such as a smartphone or tablet. For example, a specific question might be, "What is Schrödinger's cat?" The device captures and stores this speech as digital audio data. The input is the user's voice, and the output is digital audio data.

[1417] Step 2:

[1418] The device sends the stored digital audio data to the server. The audio data is securely transmitted using a communication protocol such as an HTTP POST request or WebSocket. The input of this step is the digital audio data, and the output is the data transmitted to the server.

[1419] Step 3:

[1420] The server receives the digital voice data sent from the device. It converts the received voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text). Specifically, it analyzes the voice waveform and generates a corresponding text string. The input is digital voice data, and the output is the text data "What is Schrödinger's cat?"

[1421] Step 4:

[1422] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent. Through this analysis, the server understands the content of the user's question and the information they are looking for from the text. Specifically, it performs grammatical analysis and semantic analysis. The input is text data, and the output is the user's intent, which is "I'm looking for information about Schrodinger's cat."

[1423] Step 5:

[1424] The server passes the converted text and voice data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotion. Specifically, it identifies the emotional state from the tone of the voice and the content of the text. The input is text and voice data, and the output is a determination that the user's emotion is "curiosity."

[1425] Step 6:

[1426] The server searches a digital content database (e.g., Kindle, Google Books) and retrieves information about "Schrödinger's Cat" based on the user's intent. Specifically, it uses a content search API to extract the relevant text. The input is the user's intent, and the output is text data containing the relevant information.

[1427] Step 7:

[1428] The server adds appropriate emotional expressions to the acquired text data based on the results of the emotion recognition engine and converts it into voice data. Specifically, it uses a text-to-speech synthesis engine (e.g., Amazon Polly) to add intonation and tone according to the emotion to the voice. The input is text data and emotional information, and the output is voice data accompanied by emotional expressions.

[1429] Step 8:

[1430] The server adds appropriate background music and sound effects to the generated audio data. Specifically, it uses an audio mixing tool to combine the music track and the audio track. The input is audio data and background music, and the output is audio data with background music.

[1431] Step 9:

[1432] The server sends the final audio data to the user's terminal. The input is the audio data with background music, and the output is the data sent to the user's terminal.

[1433] Step 10:

[1434] The device receives the audio data sent from the server and plays it through the audio playback application. Specifically, it activates the audio playback function and outputs the data from the speaker. The input is audio data with background music, and the output is the audio that the user actually hears.

[1435] By following these steps, if a user has a question while listening to an audiobook, they can receive an answer that suits their feelings without interrupting the content.

[1436] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1437] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1438] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1439] [Fourth embodiment]

[1440] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1441] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1442] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1443] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1444] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1445] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1446] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1447] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1448] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1449] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1450] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1451] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1452] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1453] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[1454] 1. User operations

[1455] A user uses the device's voice input interface to ask a question, for example, "What is Schrodinger's cat?" This voice input is captured by the device and stored as digital audio data.

[1456] 2. Terminal Processing

[1457] The device sends the captured audio data to the server using a network protocol such as an HTTP POST request. It also has the ability to receive and play the audio data returned from the server. The device acts as a bridge between the server and the user, properly transmitting the information the server requests and accurately conveying the information provided by the server to the user.

[1458] 3. Server Processing

[1459] The server receives the voice data sent from the terminal. After receiving the data, the server performs the following processes in order.

[1460] Speech Recognition Processing

[1461] The server uses a speech recognition engine to convert the voice data into text data, which allows it to understand what the user is asking as text information.

[1462] Natural Language Processing

[1463] The converted text data is passed to a natural language processing engine to analyze the user's intent. For example, it may recognize that the user is looking for an explanation of Schrodinger's cat.

[1464] Database search

[1465] Based on the user's intent, the server searches the digital book database to retrieve the relevant information, in this case extracting the required information from the chapter or section about Schrodinger's Cat.

[1466] Emotional Expression and Narration Generation

[1467] The acquired information is converted into emotionally expressive audio data using a text-to-speech engine, providing users with a natural and easy-to-understand presentation of the information. The listening experience can also be further enhanced by adding appropriate background music.

[1468] 4. Working Example

[1469] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[1470] User Action:

[1471] User: "What is Schrodinger's cat?"

[1472] Terminal handling:

[1473] The device captures the audio and sends the data to the server.

[1474] Server Action:

[1475] The server converts the audio data into text data, analyzes it, and extracts the relevant information from the digital book.

[1476] After that, audio data with emotional expressions is generated, background music is added, and the data is sent to the device.

[1477] Terminal handling:

[1478] The device plays the received audio data.

[1479] User Action:

[1480] The user listens to the audio playback and gets a detailed explanation of "Schrödinger's Cat."

[1481] This allows users to gain a deeper understanding of technical terms and difficult content. The distinctive feature of the present invention is that, as claimed, a system has been realized in which these functions and processes are integrated.

[1482] The processing flow will be explained below.

[1483] Step 1:

[1484] The user speaks into the device's voice input interface to ask what they want to know. In this example, they ask the question, "What is Schrodinger's cat?"

[1485] Step 2:

[1486] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[1487] Step 3:

[1488] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[1489] Step 4:

[1490] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[1491] Step 5:

[1492] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[1493] Step 6:

[1494] The server passes the converted text data to a natural language processing engine, which analyzes the text and identifies the user's intent.

[1495] Step 7:

[1496] The server searches the digital book database based on the user's intent, searching for information about "Schrödinger's Cat" and extracting relevant text.

[1497] Step 8:

[1498] The server uses a text-to-speech engine to convert the extracted text into emotionally charged speech data, where emotions and intonation are added to the narration.

[1499] Step 9:

[1500] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[1501] Step 10:

[1502] The server then sends the completed audio data to the device, again via an HTTP POST request or WebSocket.

[1503] Step 11:

[1504] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[1505] Step 12:

[1506] The device then plays the converted audio data through a speaker or headphones, allowing the user to listen to a detailed explanation of "Schrödinger's Cat."

[1507] Through the above steps, the system can quickly and accurately provide the information the user desires.

[1508] Example 1

[1509] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1510] Today's users want to quickly and easily understand digital books and specialized information. However, text-based information search can be time-consuming and difficult to understand when it contains a lot of technical terminology. While voice-based information retrieval systems exist, they typically lack emotional expression and background music, which leaves users unsatisfied. To address these challenges, a system is needed that allows users to simply ask questions and receive specific information in voice-activated speech.

[1511] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1512] In this invention, the server includes means for converting voice data into text data, means for analyzing the text data and understanding the user's intent, means for searching the contents of digital books and extracting relevant information, means for converting the acquired information into voice data with emotional expressions and adding background music, and means for transmitting the voice data to the user's terminal, thereby enabling the user to easily ask questions by voice and instantly receive specialized information in voice with emotional expressions.

[1513] "Voice input" refers to voice data provided by a user speaking into a microphone.

[1514] A "server" refers to a computer system that provides services to other devices and software on a network.

[1515] A "terminal" refers to a component having input and output devices that can be directly operated by a user.

[1516] "Audio data" refers to data that has been recorded or processed by converting audio into digital form.

[1517] "Text data" refers to data that has been converted from voice data into text information.

[1518] "Analysis means" refers to a series of processes that understand the user's intent based on text data and perform the necessary processing.

[1519] "Search method" refers to the process used to locate specific keywords or content within a digital book database.

[1520] "Extraction method" refers to the process for extracting the required information from the search results.

[1521] "Emotionally-expressed voice data" refers to voice data to which emotions and intonation have been added, as opposed to voice data generated simply from text.

[1522] "Background music" refers to music that is added to audio data to enhance the user's listening experience.

[1523] "Transmission" refers to a process for transferring data from one device to another.

[1524] "Receiving means" refers to the process by which one device receives data sent from another device.

[1525] "Playback means" refers to a process for letting the user hear audio data through a speaker or the like.

[1526] This invention is a voice support system that searches for specific content in digital books and provides answers in voice with emotional expressions when a user simply asks a question by voice. This system operates in cooperation with three entities: a server, a terminal, and a user.

[1527] User operations

[1528] The user asks a question using the device's voice input interface. For example, the user might say, "What is Schrodinger's cat?" The device captures and stores this voice in digital form. This voice input interface can be a regular microphone, a smartphone microphone, or even a smart speaker.

[1529] Terminal handling

[1530] The device sends the captured audio data to the server using an HTTP POST request. HTTPS is often used as the network protocol. The device also has the ability to receive and play back audio data with emotional expressions returned from the server. For example, if a user wants to know more about "Schrödinger's Cat," the device sends this question to the server.

[1531] Server Processing

[1532] After receiving the voice data transmitted from the terminal, the server performs the following processes in order.

[1533] Speech Recognition Processing

[1534] The server converts the voice data into text data using a speech recognition engine (for example, Google Speech-to-Text API), which makes it possible to understand the content of the user's question as text information.

[1535] Natural Language Processing

[1536] The converted text data is passed to a natural language processing engine (e.g., a generative AI model such as GPT-3) to analyze the user's intent. For example, it may be analyzed that the user is looking for an explanation of Schrödinger's cat.

[1537] Database search

[1538] Based on the user's intent, the server searches a digital book database (e.g., Amazon Athena or other cloud database) and retrieves relevant information, typically a chapter or section about Schrödinger's cat.

[1539] Emotional Expression and Narration Generation

[1540] The acquired text information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (e.g., Amazon Polly), and appropriate background music (e.g., Bensound's free music library) is added to the voice data to improve the user's listening experience.

[1541] Example

[1542] If a user is listening to a physics audiobook and decides, "I want to know more about Schrodinger's cat," the system works as follows:

[1543] User Action:

[1544] User: "What is Schrodinger's cat?"

[1545] Terminal handling:

[1546] The device captures the audio and sends the data to the server.

[1547] Server Action:

[1548] The server converts the audio data into text data, analyzes it, extracts relevant information from the digital book, generates audio data with emotional expressions, adds background music, and transmits it to the device.

[1549] Terminal handling:

[1550] The terminal plays back the received audio data.

[1551] User Action:

[1552] The user can listen to the audio playback and get a detailed explanation of "Schrödinger's Cat."

[1553] Examples of prompt statements

[1554] Below is an example of a prompt sentence to input to the generative AI model.

[1555] text

[1556] "What is Schrodinger's cat?"

[1557] Using this prompt, the natural language processing engine understands that you are looking for an explanation of "Schrödinger's cat" and searches for and provides the corresponding information.

[1558] This system allows users to quickly and emotionally understand the contents of digital books through voice input.

[1559] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1560] Step 1:

[1561] User voice input

[1562] The user asks a question to the device's voice input interface, for example, "What is Schrodinger's cat?"

[1563] Input: User's voice data

[1564] Output: Digital audio data

[1565] Specific behavior:

[1566] Users ask questions into their smartphone or smart speaker, and the built-in microphone captures the audio.

[1567] Step 2:

[1568] Sending audio data by the device

[1569] The device sends the captured audio data to the server using an HTTP POST request.

[1570] Input: User's digital voice data

[1571] Output: HTTP request sent to the server

[1572] Specific behavior:

[1573] The device sends the audio data to the server via an internet connection, using HTTPS as the communication protocol.

[1574] Step 3:

[1575] Receiving audio data by the server

[1576] The server receives the voice data transmitted from the terminal.

[1577] Input: Audio data via HTTP POST request

[1578] Output: Audio data in the server

[1579] Specific behavior:

[1580] The server monitors the API endpoint and adds received audio data to its internal memory or to a processing queue.

[1581] Step 4:

[1582] Server-based speech-to-text conversion

[1583] The server converts the voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text).

[1584] Input: Audio data in the server

[1585] Output: Text data

[1586] Specific behavior:

[1587] The server sends the voice data to the voice recognition API and receives text data as a response.

[1588] Step 5:

[1589] Analysis of text data by the server

[1590] The server uses a natural language processing engine (e.g., GPT-3) to analyze the text data and understand the user's intent.

[1591] Input: Text data

[1592] Output: Analysis results (information indicating the user's intent)

[1593] Specific behavior:

[1594] The server inputs the text data into a natural language processing engine and receives the analyzed results.

[1595] Step 6:

[1596] Server-based search for digital books

[1597] The server searches the digital book database based on the analysis results and obtains the relevant information.

[1598] Input: Analysis results

[1599] Output: Part of the digital book data

[1600] Specific behavior:

[1601] The server uses an SQL query to search a digital book database and extract the section or chapter about Schrödinger's cat.

[1602] Step 7:

[1603] Converting acquired information into voice and adding emotional expressions

[1604] The server uses a text-to-speech synthesis engine (e.g., Amazon Polly) to convert the acquired information into voice data with emotional expressions.

[1605] Input: Text data of a digital book

[1606] Output: Voice data with emotional expressions

[1607] Specific behavior:

[1608] The server sends the text data to the speech synthesis API, sets emotion parameters, and obtains speech data.

[1609] Step 8:

[1610] Add background music

[1611] The server adds background music to the generated emotionally expressive voice data.

[1612] Input: Voice data with emotional expressions, background music file

[1613] Output: Audio data with background music

[1614] Specific behavior:

[1615] The server uses an audio editing tool (e.g., FFmpeg) to combine the audio data with background music.

[1616] Step 9:

[1617] Sending audio data to the device

[1618] The server sends the final voice data with emotional expressions to the terminal as an HTTP response.

[1619] Input: Audio data with background music

[1620] Output: Audio data via HTTP response

[1621] Specific behavior:

[1622] The server generates a response at the API endpoint and sends the audio data to the device.

[1623] Step 10:

[1624] Playback of audio data by the device

[1625] The terminal reproduces the voice data with emotional expressions received from the server.

[1626] Input: Audio data from the server

[1627] Output: Audio playback through speakers

[1628] Specific behavior:

[1629] The device will launch its built-in audio player and play audio through speakers or earphones.

[1630] Step 11:

[1631] User hears audio playback

[1632] The user listens to the audio data played back from the terminal and receives the answer to the question.

[1633] Input: Device audio output

[1634] Output: User understanding

[1635] Specific behavior:

[1636] The user listens to the audio that is played and understands the explanation about "Schrödinger's cat."

[1637] Through each step, users can quickly and emotionally understand the content of the digital book through voice input.

[1638] (Application example 1)

[1639] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1640] In modern content distribution services, it is important for users to quickly and easily obtain specific information. In particular, services that offer a wide range of digital content require systems that allow users to instantly obtain detailed information about specific books or audiobooks. However, current systems lack the means to accurately analyze user intent, search for relevant information, and provide information in a natural-sounding voice that expresses emotions. This leaves users with an insufficient search experience, making it difficult to provide a richer user experience.

[1641] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1642] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intent, means for searching based on the analysis, means for extracting information from the search results, means for converting the extracted information into voice data with emotional expressions, means for transmitting the voice data to the user's terminal, and means for searching for related content based on the user's voice question and providing an answer with emotional expressions. This improves the user's search experience in the content distribution service and makes it possible to provide a richer user experience.

[1643] The "means for receiving voice input from the user" is a function for capturing voice uttered by the user as digital data and inputting it into the system.

[1644] The "means for converting received voice input into text data" is a function that converts captured voice data into text information using a voice recognition engine.

[1645] "Means for analyzing text data and understanding user intent" refers to a function that uses natural language processing technology to analyze and understand the meaning of text data and user requests.

[1646] The "analysis-based search means" is a function that searches related digital books and content databases according to the analyzed user intent.

[1647] "Means for extracting information from search results" refers to the function of extracting specific information that a user desires from searched digital books or content.

[1648] The "means for converting extracted information into voice data with emotional expressions" is a function that uses a text-to-speech synthesis engine to convert extracted text information into a voice format with emotional expressions.

[1649] The "means for transmitting voice data to the user's terminal" is a function for delivering the generated voice data to the user's terminal via a network.

[1650] "Means for searching for related content based on a user's voice question and providing an answer with emotional expressions" is a function that analyzes a user's voice question, searches for content related to that question, and then returns an answer in an emotionally rich voice.

[1651] The system for realizing this application example combines the following means in a series of processes: The user, terminal, and server work together to search for and provide relevant content based on the user's voice question.

[1652] System program generation and operation

[1653] 1. Audio capture and transmission (terminal)

[1654] The user types a voice question using the device's microphone, and this voice data is captured and stored digitally on the device, then sent to the server via an HTTP POST request.

[1655] 2. Speech recognition and text conversion (server)

[1656] The server converts the received voice data into text data using a speech recognition engine (e.g., Google Speech-to-Text API). Through this step, the server understands what the user has asked as text information.

[1657] 3. Natural Language Processing and Intention Analysis (Server)

[1658] The converted text data is passed to a natural language processing engine (e.g., NLTK, spaCy) to analyze the user's intent, for example, to understand a specific request such as "I want to know the meaning of a specific scientific term."

[1659] 4. Digital Book Database Search (Server)

[1660] Based on the analyzed user intent, the server searches the corresponding digital book database, identifies the chapter or section containing the relevant information, and extracts the required information.

[1661] 5. Emotional speech generation (server)

[1662] The extracted information is converted into audio data with emotional expressions using a text-to-speech synthesis engine (e.g., Google Text-to-Speech API), allowing users to receive information in a natural and easy-to-understand manner. In addition, appropriate background music may be added in some cases to enhance the listening experience.

[1663] 6. Sending and Playing Audio Data (Terminal)

[1664] The final generated voice data is sent from the server to the terminal, which then plays the received voice data and provides the information to the user.

[1665] Hardware and software used

[1666] Hardware: Smartphone, microphone

[1667] software:

[1668] speech_recognition (speech recognition library)

[1669] requests (a library for sending HTTP requests)

[1670] pyttsx3 (speech synthesis library)

[1671] Google Speech-to-Text API (for voice recognition)

[1672] NLTK or spaCy (for natural language processing)

[1673] Google Text-to-Speech API (for speech synthesis)

[1674] Examples of concrete examples and prompts

[1675] Examples:

[1676] 1. The user opens the "Audio Assistant" feature in the smartphone app and asks a voice question such as, "Tell me more about this book."

[1677] 2. The app captures the audio and sends it to the server.

[1678] 3. The server converts the speech into text and retrieves relevant information from a database.

[1679] 4. The information is converted into voice with emotional expressions and sent to a smartphone.

[1680] 5. The app plays a sound and provides the information the user requested.

[1681] Example prompt sentence:

[1682] "What is Schrodinger's cat? Can you explain it in detail?"

[1683] This embodiment allows users to easily obtain detailed information through voice queries and enjoy a richer user experience.

[1684] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1685] Step 1:

[1686] A user taps the microphone button on a smartphone app and asks a question by voice. For example, they say, "Tell me more about this book." Input: User's voice data. Output: Voice data captured on the device.

[1687] Step 2:

[1688] The audio data captured on the device is stored in digital format and then sent to the server using an HTTP POST request. Input: Captured audio data. Output: Audio data sent to the server.

[1689] Step 3:

[1690] The server converts the received voice data into text data using a speech recognition engine (such as the Google Speech-to-Text API). Input: Voice data sent to the server. Output: Text data converted by the speech recognition engine.

[1691] Step 4:

[1692] The server uses a natural language processing engine (NLTK, spaCy, etc.) to analyze the text data and understand the user's intent. Input: Text data converted by a speech recognition engine. Output: Analyzed user intent.

[1693] Step 5:

[1694] The server searches the corresponding digital book database based on the analyzed user intent. At this stage, the relevant chapter or page is identified and the necessary information is extracted. Input: Analyzed user intent. Output: Information on the searched digital book.

[1695] Step 6:

[1696] The extracted information is converted into voice data with emotional expressions using a text-to-speech synthesis engine (such as Google Text-to-Speech API). Input: Searched digital book information. Output: Voice data with emotional expressions.

[1697] Step 7:

[1698] If necessary, the server adds appropriate background music to the audio data, improving the listening experience. Input: Audio data with emotional expressions. Output: Audio data with emotional expressions and background music.

[1699] Step 8:

[1700] The server finally sends the generated voice data to the terminal via the network. Input: Voice data with emotional expressions and background music. Output: Voice data sent to the terminal.

[1701] Step 9:

[1702] The terminal plays the received audio data and provides information to the user. Input: Audio data sent to the terminal. Output: Audio information that the user can hear.

[1703] This allows users to quickly and emotively obtain detailed information about specific digital content through audio.

[1704] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1705] This system, when a user makes a voice inquiry about specific information, searches for that information in a digital book, uses an emotion recognition engine to determine the user's emotion, and provides a voice response accompanied by an appropriate emotional expression, operates in cooperation with three entities: a server, a terminal, and a user.

[1706] 1. User operations

[1707] The user asks a question into the voice input interface, in this example "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[1708] 2. Terminal Processing

[1709] The device captures the user's voice and sends the digital audio data to a server using protocols such as HTTP POST requests or WebSockets, and also receives and plays the audio data returned from the server.

[1710] 3. Server Processing

[1711] The server receives the voice data sent from the terminal and performs the following processes in order.

[1712] Speech Recognition Processing

[1713] The server uses a speech recognition engine to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[1714] Natural Language Processing

[1715] The server passes the text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1716] Emotion Recognition Processing

[1717] The converted text and voice data are passed to an emotion recognition engine to determine the user's emotions. The engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[1718] Database search

[1719] The server then searches a digital book database for information about "Schrödinger's Cat" and extracts the relevant text.

[1720] Emotional Expression and Narration Generation

[1721] The acquired text is then passed to a text-to-speech synthesis engine, where it is converted into voice data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated voice to have an inflection and tone that matches the user's emotions. Appropriate background music can also be added to the voice data to improve the listening experience.

[1722] 4. Working Example

[1723] A specific example will now be given: Suppose a user is listening to an audiobook on physics and wants to know more about Schrodinger's cat.

[1724] User Action:

[1725] The user speaks, "What is Schrodinger's cat?"

[1726] Terminal handling:

[1727] The device captures the audio and sends it to the server.

[1728] Server Action:

[1729] The server converts the voice data into text and analyzes it with a natural language processing engine. It then uses an emotion recognition engine to identify the user's emotion (e.g., curiosity). It then searches and extracts relevant information from a digital book database, adds emotional expressions, generates voice data, and adds background music.

[1730] Terminal handling:

[1731] The terminal receives and plays back the audio data sent from the server.

[1732] User Action:

[1733] Users listen to the audio and get a detailed explanation of "Schrödinger's Cat," which is delivered with inflection and tone that reflects the user's emotions, making for a more comprehensible and immersive listening experience.

[1734] In this way, the system can provide information quickly and accurately while taking into account the user's feelings.

[1735] The processing flow will be explained below.

[1736] Step 1:

[1737] The user speaks what they want to know into the device's voice input interface, asking the question, "What is Schrodinger's cat?"

[1738] Step 2:

[1739] The device captures the user's voice through a microphone, and the captured voice is stored as digital audio data.

[1740] Step 3:

[1741] The device sends the captured audio data to the server using an HTTP POST request or WebSocket.

[1742] Step 4:

[1743] The server receives the voice data sent from the terminal and passes the received voice data to the voice recognition engine.

[1744] Step 5:

[1745] The server's speech recognition engine converts the speech data into text, which generates the text "What is Schrodinger's cat?"

[1746] Step 6:

[1747] The server then passes the converted text data to a natural language processing engine to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1748] Step 7:

[1749] The server passes the text and voice data to an emotion recognition engine to determine the user's emotion, which infers the emotion from the user's tone of voice and text expressions.

[1750] Step 8:

[1751] The server searches the digital book database based on the user's intent, retrieves information about "Schrödinger's Cat," and extracts the relevant text.

[1752] Step 9:

[1753] The server uses a text-to-speech engine to convert the extracted text information into emotionally charged speech data, which adds tone and inflection to match the user's emotions.

[1754] Step 10:

[1755] The server adds appropriate background music to the generated audio data, making the audio data easier for the user to listen to.

[1756] Step 11:

[1757] The server sends the completed audio data to the device via an HTTP POST request or WebSocket.

[1758] Step 12:

[1759] The terminal receives the audio data sent from the server, and after receiving the audio data, the audio data is decoded and converted into a playable format.

[1760] Step 13:

[1761] The device then plays the converted audio data through speakers or headphones, allowing users to listen to a detailed explanation of "Schrödinger's Cat." The audio is provided with a tone and background music that matches the user's emotions, providing a clearer and more immersive listening experience.

[1762] Example 2

[1763] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1764] Conventional voice dialogue systems provide information without considering the user's emotions, making it difficult to provide appropriate responses based on the user's emotions and intentions. Furthermore, there is a need to improve the user's listening experience by providing responses accompanied by appropriate background music in addition to speech.

[1765] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1766] In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into digital format, means for transmitting the digital voice input to the server, means for converting the voice input into text data, means for analyzing the text data and understanding the user's intention, means for determining the user's emotions from the analyzed text data and voice data, means for searching the contents of a digital book, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for adding background music to the generated voice data, means for transmitting the voice data to the user's terminal, and means for playing the voice data on the user's terminal, thereby enabling appropriate responses that take the user's emotions into consideration and a high-quality listening experience.

[1767] "User voice input" refers to questions or instructions given by the user to the system through voice.

[1768] "Digital format" refers to a format in which an analog signal is converted into digital data.

[1769] A "server" refers to a computer system that receives requests from clients via a network and provides services.

[1770] "Text data" refers to data expressed as character information.

[1771] A "natural language processing engine" refers to a system that analyzes text data and understands and generates human language.

[1772] An "emotion recognition engine" refers to a system for determining a user's emotions from voice data and text data.

[1773] "Digital Book" refers to book data stored in electronic format.

[1774] "Text-to-speech engine" refers to a system for converting text data into speech data.

[1775] "Background music" refers to music that is primarily intended to complement audio data and enhance the listening experience.

[1776] "User terminal" refers to a device that is directly operated by a user, such as a computer system or electronic device that communicates with a server.

[1777] "Audio data" refers to audio information expressed as digital data.

[1778] "Search means" refers to a system or method for locating specific information from a database or storage.

[1779] "Playback means" refers to a system or function that allows the user to listen to the audio data sent from the server.

[1780] This system searches for specific information in digital books when a user makes a voice inquiry, determines the user's emotions, and provides a voice response accompanied by appropriate emotional expressions. This system operates in cooperation with three entities: the user, the terminal, and the server.

[1781] First, the user asks a question to the voice input interface. Let's take the question "What is Schrodinger's cat?" as an example. This voice input is captured as digital voice data by the device. The device uses a microphone to capture the voice and converts it into a digital format. This digital voice data is sent to the server using a protocol such as an HTTP POST request or WebSocket.

[1782] The server receives the voice data sent from the device and first converts the voice data into text data using a speech recognition engine. For example, a general API service (e.g., Google Cloud Speech-to-Text API) can be used as the speech recognition engine. This results in the text data "What is Schrodinger's cat?"

[1783] The server then passes this text data to a natural language processing engine to analyze the user's intent. The natural language processing engine uses a generative AI model (e.g., the OpenAI GPT model). This analysis determines that the user is looking for information about "Schrödinger's cat."

[1784] The server then passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions. A common API service (e.g., IBM Watson Emotion Analysis) is used as the emotion recognition engine. This engine estimates the user's emotions (e.g., curiosity, confusion, excitement) from the user's tone of voice and the context of the text.

[1785] Next, the server searches a digital book database to obtain information about "Schrödinger's Cat." The digital book database uses a common API service (e.g., the API of an e-book store). The server identifies and extracts the relevant text.

[1786] The acquired text is then converted into voice data by adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine and passed to a text-to-speech synthesis engine. For example, a common API service (e.g., Amazon Polly) can be used as the voice synthesis engine. The voice data is given inflection and tone according to the user's emotions. The listening experience can also be improved by adding background music to the generated voice data.

[1787] Finally, the generated audio data is sent back to the device from the server. The device then plays the received audio data through the speaker. The user can then listen to the audio and receive a detailed explanation of "Schrödinger's Cat." The explanation is delivered with intonation and tone that reflects the user's emotions, providing a more understandable and immersive listening experience.

[1788] Prompt Sentence Examples

[1789] "Please explain in detail how the system will provide an answer when a user asks a question about Schrodinger's cat."

[1790] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1791] Step 1:

[1792] The user asks a question into the voice input interface.

[1793] Input: User speech (e.g., "What is Schrodinger's cat?")

[1794] Output: Audio data

[1795] Specific operation: The user speaks a question into the device's microphone, which captures the voice as an analog signal.

[1796] Step 2:

[1797] The terminal converts the user's voice into a digital format.

[1798] Input: Analog audio signal

[1799] Output: Digital audio data

[1800] How it works: The device uses a microphone to capture audio, converts the analog audio signal into digital form, and stores the digital audio data in the device's memory.

[1801] Step 3:

[1802] The terminal transmits digital audio data to the server.

[1803] Input: Digital audio data

[1804] Output: Request to the server (HTTP POST or WebSocket)

[1805] What happens: The device extracts the digital audio data and sends it to the server using a network protocol (e.g., HTTP POST request or WebSocket).

[1806] Step 4:

[1807] The server receives the digital voice data and converts the voice data into text data using a voice recognition engine.

[1808] Input: Digital audio data

[1809] Output: Text data (e.g., "What is Schrodinger's cat?")

[1810] How it works: The server receives digital voice data sent from the device and passes it to a speech recognition engine (e.g., Google Cloud Speech-to-Text API), which analyzes the voice data and generates corresponding text data.

[1811] Step 5:

[1812] The server passes the text data to a natural language processing engine to analyze the user's intent.

[1813] Input: Text data (e.g., "What is Schrodinger's cat?")

[1814] Output: User intent (e.g., "I'm looking for information about Schrodinger's cat")

[1815] How it works: The server passes the generated text data to a natural language processing engine (e.g., OpenAI GPT model), which analyzes the text data and interprets the user's intent.

[1816] Step 6:

[1817] The server passes the analyzed text and voice data to an emotion recognition engine to determine the user's emotions.

[1818] Input: Text and audio data

[1819] Output: User emotion (e.g., curiosity, confusion, excitement)

[1820] Specific operation: The server passes the text and voice data to an emotion recognition engine (e.g., IBM Watson Emotion Analysis). The engine analyzes the data and estimates the user's emotions.

[1821] Step 7:

[1822] The server searches the digital book database and extracts the relevant information.

[1823] Input: User intent (e.g., "information about Schrodinger's cat")

[1824] Output: Corresponding text information

[1825] Specific operation: The server searches a digital book database (e.g., an API of an e-book store) and extracts relevant information based on the user's intent.

[1826] Step 8:

[1827] The server converts the extracted information into voice data accompanied by emotional expressions.

[1828] Input: relevant text information and user sentiment

[1829] Output: Generated audio data

[1830] Specific operation: The server adds emotional expressions determined by the emotion recognition engine to the extracted text information, and passes the data to a text-to-speech synthesis engine (e.g., Amazon Polly) to generate voice data.

[1831] Step 9:

[1832] The server adds appropriate background music to the generated audio data.

[1833] Input: Generated audio data

[1834] Output: Audio data including background music

[1835] Specific operation: The server selects background music suitable for the generated audio data and incorporates it into the audio data, thereby improving the listening experience.

[1836] Step 10:

[1837] The server sends the final audio data to the terminal.

[1838] Input: Audio data including background music

[1839] Output: Request to the device (HTTP POST or WebSocket)

[1840] Specific operation: The server generates the final audio data including background music and sends it to the terminal via a network protocol.

[1841] Step 11:

[1842] The terminal receives the audio data sent from the server and plays it back.

[1843] Input: Audio data including background music

[1844] Output: Audio output through speakers

[1845] Specific operation: The terminal receives the voice data sent from the server and plays it through the speaker, allowing the user to listen to the voice and obtain detailed answers to their questions.

[1846] (Application example 2)

[1847] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1848] Current content delivery services lack systems that can quickly and accurately respond to questions or concerns that arise while users are listening to audiobooks or other digital content. This requires users to interrupt the content and perform a search, which detracts from the listening experience. Furthermore, existing systems struggle to provide appropriate answers that reflect the user's emotions, creating a need for improved user experience.

[1849] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving voice input from a user, means for converting the received voice input into text data, means for analyzing the text data and understanding the user's intention, means for searching for the details of digital content based on the analysis results, means for extracting relevant information based on the search results, means for converting the extracted information into voice data accompanied by an emotional expression, means for transmitting the voice data to the user's information processing device, means for analyzing the user's emotions using an emotion recognition engine, and means for generating voice by adding an appropriate emotional expression based on the emotions. This allows the user to receive an answer according to the emotion through an information processing device such as a smartphone without interrupting the content, enabling a more natural and immersive listening experience.

[1850] "Voice input from the user" refers to voice data spoken by the user, and is an input means used by the system to receive and analyze this data.

[1851] The "means for converting received voice input into text data" refers to a process for converting a user's voice data into corresponding text data, such as using a voice recognition engine.

[1852] "Means for analyzing text data and understanding user intent" refers to the process of using a natural language processing engine to analyze what the user is looking for from the converted text data.

[1853] "Means for searching the contents of digital content" refers to the process of searching databases such as digital books and audiobooks based on the user's intent to find relevant information.

[1854] "Means for extracting relevant information based on search results" refers to the process of extracting information from the searched digital content that directly answers the user's question.

[1855] The "means for converting extracted information into voice data accompanied by emotional expression" refers to the process of generating voice with intonation and tone appropriate to the user's emotions when converting extracted information into voice data using a text-to-speech synthesis engine.

[1856] "Means for transmitting voice data to a user's information processing device" refers to a process for transmitting the generated voice data to a user's information processing device such as a smartphone or PC via the Internet or other communication means.

[1857] "Means for analyzing user emotions using an emotion recognition engine" is a technology for estimating emotions from a user's voice data and text data, and is a process for identifying the emotions the user is feeling.

[1858] "Means for generating voice by adding appropriate emotional expressions based on emotions" is a technology that uses the results of an emotion recognition engine to add intonation and tone to the generated voice data according to the user's emotions.

[1859] The present invention is a system in which, when a user expresses a question or interest through voice input, the system searches for the relevant information from digital content, determines the user's emotion using an emotion recognition engine, and provides a voice response accompanied by an appropriate emotional expression. This system operates in cooperation with three entities: a server, a terminal, and the user.

[1860] 1. User operations

[1861] The user asks a question to the voice input interface, for example, "What is Schrodinger's cat?" The voice input is captured by the device and stored as digital audio data.

[1862] 2. Terminal Processing

[1863] The user's voice is captured by a device such as a smartphone or tablet. The device then uses a communication protocol such as an HTTP POST request or WebSocket to send the digital audio data to a server. The device also has the ability to receive and play the digital audio data returned from the server.

[1864] 3. Server Processing

[1865] The server receives the voice data sent from the terminal and performs the following processes in order.

[1866] Speech Recognition Processing

[1867] The server uses a speech recognition engine (such as Google Speech-to-Text) to convert the voice data into text data, which results in the text "What is Schrodinger's cat?"

[1868] Natural Language Processing

[1869] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent, which determines that the user is looking for information about "Schrödinger's cat."

[1870] Emotion Recognition Processing

[1871] The converted text and voice data are passed to an emotion recognition engine (such as IBM Watson Tone Analyzer) to determine the user's emotions. This engine infers emotions from the user's tone of voice and the context of the text, determining whether the user is feeling curiosity, confusion, excitement, etc.

[1872] Database search

[1873] The server then searches a digital content database (e.g., Kindle, Google Books) to retrieve information about "Schrödinger's Cat" and extracts the relevant text.

[1874] Emotional Expression and Narration Generation

[1875] The acquired text is then passed to a text-to-speech engine (e.g., Amazon Polly) where it is converted into audio data after adding appropriate emotional expressions based on the user's emotions as determined by the emotion recognition engine. This allows the generated audio to have an inflection and tone that matches the user's emotions. Appropriate background music and sound effects can also be added to the audio data to improve the listening experience.

[1876] 4. Working Example

[1877] Here is a specific example: Let us consider the case where a user is listening to an audiobook and thinks, "I want to know more about Schrodinger's cat."

[1878] User operations

[1879] The user speaks, "What is Schrodinger's cat?" The server generates a response in an uplifting tone, depending on the curiosity inferred from the user's voice.

[1880] Search and Response

[1881] The server performs voice recognition, natural language processing, and emotion recognition, searches for relevant information in a digital content database, adds emotional expressions, generates audio data, and sends it along with background music to the user's device, which receives and plays it.

[1882] Examples of prompt statements

[1883] Initial prompt: "How can a content delivery app help users listen to an audiobook and ask questions about parts of it that they're unsure about? Responses can be tailored to their emotions."

[1884] Question prompt: "What is Schrodinger's cat?"

[1885] This invention allows users to receive natural emotional responses without interrupting the content, improving the listening experience.

[1886] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1887] Step 1:

[1888] A user speaks into a device such as a smartphone or tablet. For example, a specific question might be, "What is Schrödinger's cat?" The device captures and stores this speech as digital audio data. The input is the user's voice, and the output is digital audio data.

[1889] Step 2:

[1890] The device sends the stored digital audio data to the server. The audio data is securely transmitted using a communication protocol such as an HTTP POST request or WebSocket. The input of this step is the digital audio data, and the output is the data transmitted to the server.

[1891] Step 3:

[1892] The server receives the digital voice data sent from the device. It converts the received voice data into text data using a voice recognition engine (e.g., Google Speech-to-Text). Specifically, it analyzes the voice waveform and generates a corresponding text string. The input is digital voice data, and the output is the text data "What is Schrödinger's cat?"

[1893] Step 4:

[1894] The server passes the text data to a natural language processing engine (e.g., OpenAI GPT-3) to analyze the user's intent. Through this analysis, the server understands the content of the user's question and the information they are looking for from the text. Specifically, it performs grammatical analysis and semantic analysis. The input is text data, and the output is the user's intent, which is "I'm looking for information about Schrodinger's cat."

[1895] Step 5:

[1896] The server passes the converted text and voice data to an emotion recognition engine (e.g., IBM Watson Tone Analyzer) to determine the user's emotion. Specifically, it identifies the emotional state from the tone of the voice and the content of the text. The input is text and voice data, and the output is a determination that the user's emotion is "curiosity."

[1897] Step 6:

[1898] The server searches a digital content database (e.g., Kindle, Google Books) and retrieves information about "Schrödinger's Cat" based on the user's intent. Specifically, it uses a content search API to extract the relevant text. The input is the user's intent, and the output is text data containing the relevant information.

[1899] Step 7:

[1900] The server adds appropriate emotional expressions to the acquired text data based on the results of the emotion recognition engine and converts it into voice data. Specifically, it uses a text-to-speech synthesis engine (e.g., Amazon Polly) to add intonation and tone according to the emotion to the voice. The input is text data and emotional information, and the output is voice data accompanied by emotional expressions.

[1901] Step 8:

[1902] The server adds appropriate background music and sound effects to the generated audio data. Specifically, it uses an audio mixing tool to combine the music track and the audio track. The input is audio data and background music, and the output is audio data with background music.

[1903] Step 9:

[1904] The server sends the final audio data to the user's terminal. The input is the audio data with background music, and the output is the data sent to the user's terminal.

[1905] Step 10:

[1906] The device receives the audio data sent from the server and plays it through the audio playback application. Specifically, it activates the audio playback function and outputs the data from the speaker. The input is audio data with background music, and the output is the audio that the user actually hears.

[1907] By following these steps, if a user has a question while listening to an audiobook, they can receive an answer that suits their feelings without interrupting the content.

[1908] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1909] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1910] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1911] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1912] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1913] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1914] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1915] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1916] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1917] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1918] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1919] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1920] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1921] 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.

[1922] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1923] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1924] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1925] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1926] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1927] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1928] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1929] The following is further disclosed regarding the above embodiment.

[1930] (Claim 1)

[1931] means for receiving voice input from a user;

[1932] means for converting received voice input into text data;

[1933] A means for analyzing text data and understanding user intent;

[1934] a means for searching the contents of the digital book based on the analysis results;

[1935] means for extracting relevant information based on the search results;

[1936] means for converting the extracted information into voice data accompanied by emotional expressions;

[1937] means for transmitting voice data to a user terminal;

[1938] A system including:

[1939] (Claim 2)

[1940] 10. The system of claim 1, further comprising means for adding appropriate background music to the audio data.

[1941] (Claim 3)

[1942] 10. The system of claim 1, further comprising an audio playback means at the user's terminal.

[1943] "Example 1"

[1944] (Claim 1)

[1945] means for receiving voice input from a user;

[1946] means for transmitting the received voice data to a server;

[1947] A means for the server to convert the voice data into text data;

[1948] A means for analyzing text data and understanding user intent;

[1949] a means for searching the contents of the digital book based on the analysis results;

[1950] means for extracting relevant information based on the search results;

[1951] means for converting the extracted information into voice data accompanied by emotional expressions;

[1952] means for adding appropriate background music to the audio data;

[1953] means for transmitting voice data to a user terminal;

[1954] A system including:

[1955] (Claim 2)

[1956] 10. The system of claim 1, wherein the system adds appropriate background music to the audio data.

[1957] (Claim 3)

[1958] 10. The system of claim 1, further comprising an audio playback means at the user's terminal.

[1959] "Application Example 1"

[1960] (Claim 1)

[1961] means for receiving voice input from a user;

[1962] means for converting received voice input into text data;

[1963] A means for analyzing text data and understanding user intent;

[1964] a means for searching the contents of the digital book based on the analysis results;

[1965] means for extracting relevant information based on the search results;

[1966] means for converting the extracted information into voice data accompanied by emotional expressions;

[1967] means for transmitting voice data to a user terminal;

[1968] means for searching for relevant content based on a user's voice question and providing an answer with an emotional response;

[1969] A system including:

[1970] (Claim 2)

[1971] 10. The system of claim 1, further comprising means for adding appropriate background music to the audio data.

[1972] (Claim 3)

[1973] 10. The system of claim 1, further comprising an audio playback means at the user's terminal.

[1974] "Example 2: Combining Emotion Engines"

[1975] (Claim 1)

[1976] means for receiving voice input from a user;

[1977] means for converting the received audio input into a digital form;

[1978] means for transmitting the audio input in digital form to a server;

[1979] means for converting voice input into text data;

[1980] A means for analyzing text data and understanding user intent;

[1981] means for determining a user's emotion from the analyzed text data and voice data;

[1982] a means of searching the contents of the digital book;

[1983] means for extracting relevant information based on the search results;

[1984] means for converting the extracted information into voice data accompanied by emotional expressions;

[1985] means for adding background music to the generated audio data;

[1986] means for transmitting voice data to a user terminal;

[1987] means for playing audio data at a user terminal;

[1988] A system including:

[1989] (Claim 2)

[1990] 10. The system of claim 1, wherein the system uses a speech recognition engine, a natural language processing engine, and an emotion recognition engine appropriate for the audio data.

[1991] (Claim 3)

[1992] 10. The system of claim 1, wherein the audio data received from the server is played through a speaker.

[1993] "Application example 2 when combining emotion engines"

[1994] (Claim 1)

[1995] means for receiving voice input from a user;

[1996] means for converting received voice input into text data;

[1997] A means for analyzing text data and understanding user intent;

[1998] A means for searching the contents of the digital content based on the analysis result;

[1999] means for extracting relevant information based on the search results;

[2000] means for converting the extracted information into voice data accompanied by emotional expressions;

[2001] means for transmitting voice data to a user's information processing device;

[2002] means for analyzing a user's emotions using an emotion recognition engine;

[2003] means for generating speech by adding appropriate emotional expressions based on emotions;

[2004] A system including:

[2005] (Claim 2)

[2006] 10. The system of claim 1, further comprising means for adding appropriate background music and sound effects to the audio data.

[2007] (Claim 3)

[2008] 10. The system of claim 1, further comprising audio playback means in the user's information processing device. [Explanation of symbols]

[2009] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving voice input from a user; means for converting received voice input into text data; A means for analyzing text data and understanding user intent; a means for searching the contents of the digital book based on the analysis results; means for extracting relevant information based on the search results; means for converting the extracted information into voice data accompanied by emotional expressions; means for transmitting voice data to a user terminal; A system including:

2. 10. The system of claim 1, further comprising means for adding suitable background music to the audio data.

3. 2. The system of claim 1, further comprising audio playback means at the user's terminal.

Images