System

Abstract

A system is provided.SOLUTION: A system comprising: means for capturing a user's voice; means for analyzing the captured voice and assessing the user's current singing ability; means for generating a customized practice plan based on the user's goals; means for analyzing the user's voice and providing feedback in real-time; and means for tracking the user's progress and recording milestones achieved.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] Many individuals face financial and time constraints when it comes to voice training, making it difficult to continue regular lessons and practice. It is also difficult to maintain motivation when practicing independently, making it difficult to effectively improve skills. The goal of this project is to solve these problems. [Means for solving the problem]

[0005] This invention provides a system that captures and analyzes a user's voice and evaluates their current singing ability. It also generates a customized practice plan based on the user's goals and provides real-time feedback. It also tracks the user's progress and records and saves achieved milestones, allowing the user to effectively and continuously improve their skills.

[0006] "User" refers to an individual who uses the system to improve their singing ability.

[0007] "Voice" refers to waveform data of sounds including the user's vocalizations and singing.

[0008] "Means for acquiring" refers to a function for recording or inputting voice spoken by a user.

[0009] "Means for analyzing" refers to the function of processing recorded or input voice data and evaluating and analyzing its content.

[0010] "Singing ability" refers to a skill level that is comprehensively evaluated based on the user's vocal characteristics, pitch accuracy, sense of rhythm, pronunciation quality, etc.

[0011] "Means for evaluating" refers to a function for measuring the user's singing ability based on the analyzed voice data and making an appropriate evaluation.

[0012] "Goal" refers to a specific level or skill regarding the improvement of singing ability that the user wishes to achieve.

[0013] "Customized practice plan" refers to an individual practice menu designed based on the user's current ability and goals.

[0014] "Means for generating" refers to a function that creates a customized practice plan based on the user's ability assessment and goals.

[0015] "Real-time feedback" refers to the ability to instantly analyze the user's voice data while they are speaking and provide suggestions for improvement and advice.

[0016] "Means for tracking" refers to the ability to record the user's practice progress and track that history.

[0017] A "milestone" is a major goal that indicates progress or achievements a user has achieved within a specific time period.

[0018] "Means of recording" refers to the function of saving the user's progress and milestones as data.

[0019] "Means for preservation" refers to the ability to store recorded data so that it is available for future reference and analysis. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0028] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0041] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0042] System Overview

[0043] To use the system, users first enter basic information (such as their name and current singing ability). They then upload an audio file of their actual singing, and the system analyzes that audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[0044] Analysis of audio data

[0045] User

[0046] The user records their singing as an audio file and uploads it to the device.

[0047] Terminal

[0048] The device receives and saves the uploaded audio file, and uses a dedicated library (such as librosa) to analyze the saved audio file.

[0049] server

[0050] The server reads the audio file and analyzes it. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value, etc. This allows the user's current singing ability to be evaluated.

[0051] Generate a customized practice plan

[0052] server

[0053] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0054] Providing real-time feedback

[0055] User

[0056] The user sings in real time and inputs the voice into the terminal.

[0057] Terminal

[0058] The device captures live audio and processes it in real time.

[0059] server

[0060] The server analyzes the voice data in real time and provides immediate feedback to the user, including information on pitch stability and vocal accuracy.

[0061] Progress Tracking and Data Storage

[0062] server

[0063] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0064] Specific examples

[0065] For example, if User A wants to improve his singing ability, he uses the system as follows:

[0066] 1. When User A logs in for the first time, basic information (name, current pitch) is entered.

[0067] 2. User A uploads the audio file of his singing.

[0068] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[0069] 4. User A's target pitch is set to 350.

[0070] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0071] 6. User A sings in real time and the server provides real-time feedback.

[0072] 7. User A's progress is recorded and goal achievement is tracked periodically.

[0073] 8. All data is saved and User A can look back on it later.

[0074] The above is an embodiment of this system.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] A user logs in to the system and enters basic information (such as name and current singing ability), which is received by the terminal and sent to the server.

[0078] Step 2:

[0079] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, etc.

[0080] Step 3:

[0081] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[0082] Step 4:

[0083] The server reads the saved audio file and analyzes the audio data using an audio analysis library (e.g., librosa). Specifically, it extracts pitch and amplitude features from the audio data.

[0084] Step 5:

[0085] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user data. For example, the average pitch and stability are used as evaluation criteria.

[0086] Step 6:

[0087] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[0088] Step 7:

[0089] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[0090] Step 8:

[0091] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[0092] Step 9:

[0093] The server analyzes the audio data in real time and provides immediate feedback to the user, including pitch accuracy and rhythmic stability.

[0094] Step 10:

[0095] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[0096] Step 11:

[0097] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[0098] Example 1

[0099] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0100] Conventional voice training systems have difficulty providing appropriate feedback and practice plans tailored to each user's individual singing ability, making effective training difficult. Furthermore, there are insufficient methods for tracking a user's progress in detail and visually confirming their achievement. As a result, many users are unable to receive effective instruction to improve their singing ability, making it difficult for them to maintain their motivation.

[0101] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0102] In this invention, the server includes means for extracting pitch and amplitude characteristics from the user's voice data and evaluating the user's current ability based on the analysis results, means for generating a customized practice plan based on the user's goals, and means for analyzing the user's voice in real time and providing feedback. This allows the user to receive feedback tailored to their own characteristics in real time and implement an effective singing practice plan. Furthermore, detailed tracking of the user's progress and visual confirmation of achievement level are expected to maintain ongoing motivation.

[0103] "Audio data" refers to data in which the voice of a user is recorded in digital format.

[0104] "Analysis" is the process of extracting certain characteristics (such as pitch or amplitude) from audio data and using that data to evaluate the user's singing ability.

[0105] A "customized practice plan" refers to a practice menu that is individually optimized based on the user's current singing ability and goals.

[0106] "Real-time feedback" is a function that instantly provides analysis results and suggests necessary advice and corrections while the user is singing.

[0107] "Progress tracking" is the process of recording a user's practice and milestones achieved so that they can be reviewed later.

[0108] "Pitch" is a characteristic that indicates the pitch of a sound and is determined by the frequency of the sound.

[0109] "Amplitude" is a characteristic that indicates the height of waves in sound, and affects the loudness and intensity of the sound.

[0110] "Feature extraction" is the process of extracting important characteristics, such as pitch and amplitude, from audio data.

[0111] "Degree of achievement" is an index that indicates how much progress has been made toward the goal set by the user.

[0112] "Milestones" mark important milestones in the development of a user's practice.

[0113] This invention is a system that provides an AI voice analysis tool and a virtual voice training service to help users improve their singing ability at home. It has various functions to support users' singing practice and maintain their motivation. Specific embodiments of this system are described below.

[0114] System Overview

[0115] When a user uses the system, they first enter basic information (such as their name and current singing ability). Next, they upload an audio file of their actual singing, and the system analyzes the audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[0116] Hardware and software used

[0117] Terminal

[0118] The terminal is a device that receives and stores the user's voice files, and includes PCs, smartphones, etc. A dedicated library (such as librosa) is used for voice analysis.

[0119] server

[0120] The server is a central computer that reads and analyzes the audio data. Specifically, the server extracts pitch and amplitude characteristics from the audio data and evaluates the user's current singing ability. A computer with a high-performance CPU and GPU is recommended to process data in real time as needed.

[0121] Analysis of audio data

[0122] When a user records themselves singing and uploads the audio file, the device receives the file and sends it to the server. The server analyzes the audio file and calculates the average pitch and amplitude fluctuations to evaluate the user's current singing ability. This process uses a voice analysis library such as librosa.

[0123] Generate a customized practice plan

[0124] The server compares the analysis results with the user's set goals, and based on the differences, identifies the necessary practice items and generates a customized practice plan. For example, if the user's goals are to improve their high-pitched notes or vibrato control, a training menu specifically tailored to those areas will be generated.

[0125] Providing real-time feedback

[0126] When a user sings in real time and inputs the voice into the device, the device captures the live voice and transmits it to the server in real time. The server immediately analyzes the voice and provides feedback to the user, such as pitch stability and vocal accuracy.

[0127] Progress Tracking and Data Storage

[0128] The server records the user's practice progress and saves the achieved milestones in a database. The progress data is saved in JSON format for future reference and analysis, allowing users to visually confirm their own progress.

[0129] Examples of concrete examples and prompts

[0130] For example, when User A logs in for the first time, he or she enters his or her name and current pitch (250). When User A uploads an audio file of his or her singing, the server analyzes the audio file and calculates the current pitch (for example, 250). If User A's target pitch is 350, the server generates a high-pitched practice plan and provides it to User A. When singing in real time, the server provides instant feedback and records progress.

[0131] An example prompt using a generative AI model is, "Analyze the user's uploaded audio file, calculate the average pitch, and generate a customized practice plan. Also, provide real-time feedback."

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1: Initial Registration

[0134] User

[0135] A user logs into the system for the first time and enters their name and current singing ability (e.g., current pitch value).

[0136] Terminal

[0137] The terminal receives basic information entered by the user and transmits the data to the server.

[0138] server

[0139] The server stores the received user information in a database and creates a user profile.

[0140] Input: User's basic information (name, current pitch value)

[0141] Output: Creates a user profile and saves it to the database.

[0142] Step 2: Upload your audio file

[0143] User

[0144] The user records their singing and uploads the audio file to the device.

[0145] Terminal

[0146] The device receives the uploaded audio file, temporarily stores it, and then sends it to the server using a file transfer protocol.

[0147] server

[0148] The server retrieves the audio file uploaded from the terminal and stores it in a database.

[0149] Input: Recorded audio file

[0150] Output: Audio file saved on the server

[0151] Step 3: Analyzing the audio data

[0152] server

[0153] The server reads the saved audio file and analyzes it using an audio analysis library such as librosa. It extracts pitch and amplitude characteristics from the audio data and calculates the average pitch and amplitude fluctuations. The analysis results are stored in a database and the user's current singing ability is evaluated.

[0154] Input: Saved audio file

[0155] Output: Analysis results (average pitch, amplitude fluctuation), saved to database

[0156] Step 4: Generate a customized practice plan

[0157] server

[0158] The server compares the analysis results with the user's set goals and identifies the necessary practice areas based on the difference. It then generates a customized practice plan and provides it to the user. For example, it can include how to practice high notes and how to control vibrato to reach the target pitch.

[0159] Input: Analysis results, user goals

[0160] Output: Customized practice plan

[0161] Step 5: Provide real-time feedback

[0162] User

[0163] The user sings in real time and inputs the voice into the terminal.

[0164] Terminal

[0165] The terminal captures the input voice in real time and transmits the real-time voice data to the server.

[0166] server

[0167] The server instantly analyzes the received real-time voice data and generates feedback, which is then sent to the user in real time (e.g., pitch stability, pronunciation accuracy, etc.).

[0168] Input: Real-time audio data

[0169] Output: Real-time feedback

[0170] Step 6: Progress Tracking and Data Storage

[0171] server

[0172] The server records the user's practice progress and saves the achieved milestones in a database. The saved progress data is managed in JSON format or similar and is used for future reference and analysis. Progress reports are generated and sent to the user periodically.

[0173] Input: User's practice data, achieved milestones

[0174] Output: Progress data (JSON format), progress report

[0175] (Application example 1)

[0176] 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."

[0177] Previous systems for improving singing ability struggled to provide personalized practice plans and were unable to track users' progress in real time. Furthermore, analyzing users' own voice data and providing specific feedback required advanced expertise. Therefore, there was a need for a system that would allow users to easily improve their singing ability at home.

[0178] 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.

[0179] In this invention, the server includes means for acquiring a user's voice, means for analyzing the acquired voice and assessing the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for processing the singing data based on the user's input and providing the generated practice plan, and means for analyzing the user's voice data to extract pitch and amplitude characteristics, thereby enabling a user to receive a personalized practice plan to improve their singing ability from the convenience of their own home, with real-time feedback and progress tracking.

[0180] definition statement

[0181] The "means for acquiring the user's voice" refers to a device or system for recording or inputting the voice sung by the user.

[0182] The "means for analyzing the captured voice and evaluating the user's current singing ability" is an algorithm or program for analyzing the recorded voice and quantifying or evaluating the singing ability.

[0183] The "means for generating a customized exercise plan based on the user's goals" is a program or system for creating an individual exercise plan according to the goals set by the user.

[0184] The "means for analyzing the user's voice in real time and providing feedback" is a system for analyzing voice data in real time and providing immediate feedback based on the results.

[0185] A "means for tracking a user's progress and recording achieved milestones" is a system for continuously monitoring a user's practice progress and recording goals and significant milestones achieved.

[0186] "Means for processing singing data based on user input and providing a generated practice plan" refers to a system that processes audio data based on information entered by the user and provides a customized practice plan.

[0187] The "means for analyzing the user's voice data to extract pitch and amplitude characteristics" refers to an algorithm or program for extracting characteristics such as pitch and intensity from the user's recorded voice data.

[0188] "Means for storing user progress data and storing it in a format that can be used for future reference and analysis" refers to a system that stores a user's practice progress and stores it in a format that can be used for future analysis and feedback.

[0189] The "means for inputting prompt sentences into a generative AI model and obtaining a customized practice plan" refers to a system for inputting instructions or questions into a generative AI model and automatically generating an individual practice plan based on the input.

[0190] MODE FOR CARRYING OUT THE INVENTION

[0191] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who wish to improve their singing ability. The system includes a function to support users in practicing singing at home and ensure sustained motivation.

[0192] System Overview

[0193] To use the system, users enter basic information (such as their name and current singing ability). By uploading an audio file of the user's actual singing, the server analyzes the audio data and evaluates the user's current singing ability. Based on the evaluation results, a customized practice plan tailored to the user's goals is generated.

[0194] Analysis of audio data

[0195] User

[0196] Users record their own singing as an audio file and upload it via their smartphone or other device.

[0197] Terminal

[0198] The device receives the uploaded audio file and sends the data to a server, where it uses a dedicated library such as librosa for analysis.

[0199] server

[0200] The server receives and analyzes the voice data. Specifically, it extracts pitch and amplitude characteristics from the voice data, calculates the average pitch, and evaluates the user's singing ability.

[0201] Generate a customized practice plan

[0202] server

[0203] The server compares the user's singing ability assessment results with the set goals, and based on the results, identifies necessary practice items and generates a customized practice plan, including exercises on how to extend high notes, vibrato control, and vocal technique.

[0204] Providing real-time feedback

[0205] User

[0206] The user sings in real time and inputs the singing voice into the terminal.

[0207] Terminal

[0208] The device captures live audio and immediately transmits it to the server.

[0209] server

[0210] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[0211] Progress Tracking and Data Storage

[0212] server

[0213] The server records the user's progress and saves the milestones they achieve, allowing them to visually see their growth. Progress data is saved in a format such as JSON for future reference and analysis.

[0214] Specific examples

[0215] For example, if User A wants to improve his singing ability and uses this system:

[0216] 1. User A enters basic information (name, current pitch) when logging in for the first time.

[0217] 2. User A uploads the audio file of his singing.

[0218] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[0219] 4. User A's target pitch is set to 350.

[0220] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0221] 6. User A sings in real time and the server provides real-time feedback.

[0222] 7. User A's progress is recorded and goal achievement is tracked periodically.

[0223] 8. All data is saved and User A can look back on it later.

[0224] Example prompt for a generative AI model:

[0225] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Detailed explanation of the processing steps

[0228] Step 1:

[0229] The user logs in to the system for the first time and enters basic information (such as name, current singing ability, etc.), which is then stored in the database.

[0230] Input: User's basic information (name, current singing ability, etc.)

[0231] Output: User information stored in the database

[0232] Step 2:

[0233] Users record themselves singing and upload the audio file to their device.

[0234] Input: Recorded audio file\

[0235] Output: Audio file uploaded to device

[0236] Step 3:

[0237] The device receives the uploaded audio file and sends the data to the server.

[0238] Input: Uploaded audio file

[0239] Output: Audio data sent to the server

[0240] Step 4:

[0241] The server analyzes the received audio data using the librosa library and extracts pitch and amplitude characteristics from the audio data.

[0242] Input: Audio data sent to the server\

[0243] Output: Extracted pitch and amplitude characteristics data

[0244] Specific operation: Analyzes audio data using the librosa library and quantifies pitch and amplitude

[0245] Step 5:

[0246] The server evaluates the user's current singing ability based on the extracted characteristic data.

[0247] Input: Extracted pitch and amplitude characteristics data

[0248] Output: User's singing ability evaluation result

[0249] Specific operation: Calculate the average pitch and generate the evaluation result

[0250] Step 6:

[0251] The server compares the user's goals with the evaluation results and generates a customized practice plan, such as how to extend the high notes or control vibrato.

[0252] Input: User's goal, singing ability evaluation results

[0253] Output: Customized practice plan

[0254] Specific actions: Identify necessary practice items based on goals and assessment results and create a plan

[0255] Step 7:

[0256] The user sings in real time and inputs the live audio into the device.

[0257] Input: Live Audio

[0258] Output: Live audio input to the device

[0259] Step 8:

[0260] The device captures live audio and instantly transmits it to the server.

[0261] Input: Live audio input into the device

[0262] Output: Live audio data sent to the server

[0263] Step 9:

[0264] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[0265] Input: Live audio data sent to the server

[0266] Output: Real-time feedback

[0267] What it does: Analyzes live audio and generates feedback using the librosa library

[0268] Step 10:

[0269] The server tracks the user's progress and records milestones achieved. Progress data is stored in a format that can be used for future reference and analysis.

[0270] Input: User practice data and progress

[0271] Output: Saved progress data and milestones\

[0272] Specific operation: Save data in JSON format etc. and update tracking information

[0273] Example of a generated prompt statement

[0274] The prompt to the generative AI model is:

[0275] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[0276] 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.

[0277] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0278] System Overview

[0279] To use the system, users enter basic information (such as their name, current singing ability, and goals). They then upload an audio file of their singing, which is then analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation results and the user's goals. The system also incorporates an emotion engine that recognizes the user's emotions, providing feedback and advice based on the user's emotions.

[0280] Analysis of audio data

[0281] User

[0282] The user records their singing as an audio file and uploads it to the device.

[0283] Terminal

[0284] The device receives this audio file and saves it in the specified directory. A dedicated library (such as librosa) is used to analyze the saved audio file.

[0285] server

[0286] The server reads and analyzes the audio file. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value and stability. This evaluates the user's current singing ability.

[0287] Generate a customized practice plan

[0288] server

[0289] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0290] Emotional Recognition and Feedback

[0291] User

[0292] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[0293] Terminal

[0294] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice.

[0295] server

[0296] The server analyzes the voice data and emotional data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythm, and vocal accuracy, as well as advice based on the user's emotions. For example, if the user is nervous, the system will provide advice such as "Try relaxing and taking a breather."

[0297] Progress Tracking and Data Storage

[0298] server

[0299] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0300] Specific examples

[0301] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[0302] 1. When User B logs in for the first time, basic information (name, current pitch, goal, etc.) is entered.

[0303] 2. User B uploads the audio file of his singing.

[0304] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[0305] 4. User B's target pitch is set to 300.

[0306] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0307] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[0308] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B.

[0309] 8. User B's progress is recorded and goal achievement is tracked periodically.

[0310] 9. All data is saved and User B can look back on it later.

[0311] The above is an embodiment of this system.

[0312] The processing flow will be explained below.

[0313] Step 1:

[0314] A user logs in to the system and enters basic information (such as name, current singing ability, goals, etc.). The terminal receives this information and sends it to the server.

[0315] Step 2:

[0316] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, and emotional information.

[0317] Step 3:

[0318] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[0319] Step 4:

[0320] The server reads the saved audio file and analyzes the audio data using an audio analysis library. Specifically, it extracts pitch and amplitude features from the audio data and calculates the average pitch value and stability.

[0321] Step 5:

[0322] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user's data, including average pitch, sense of rhythm, and vocal accuracy.

[0323] Step 6:

[0324] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[0325] Step 7:

[0326] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[0327] Step 8:

[0328] The user sings in real time, and the device captures their voice and facial expressions. The captured voice data is saved as a temporary file, and the facial expression data is processed for emotion recognition.

[0329] Step 9:

[0330] The device analyzes the user's facial expressions and voice tone to activate the emotion engine, which identifies the user's emotional state (e.g., tension, relaxation, joy, sadness).

[0331] Step 10:

[0332] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythmic stability, and vocal accuracy, as well as emotional advice. For example, if the user is nervous, the server will provide advice such as "Try relaxing and taking a breather."

[0333] Step 11:

[0334] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[0335] Step 12:

[0336] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[0337] Example 2

[0338] 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."

[0339] Conventional singing practice systems have difficulty accurately assessing a user's singing ability when practicing independently at home, and they lack the feedback needed to maintain motivation. This makes it difficult to effectively improve singing ability and provide an optimal practice plan for each user. Furthermore, since feedback does not take emotions into account, it is difficult to respond to fluctuations in performance due to the user's psychological state. Therefore, a new system for improving singing ability and maintaining motivation is needed.

[0340] 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.

[0341] In this invention, the server includes means for capturing a user's voice, means for analyzing the captured voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for recognizing the user's emotions and providing feedback or advice based on the emotions, and means for tracking the user's progress and recording achieved milestones, thereby enabling users to efficiently and effectively improve their singing ability at home and receive appropriate feedback to maintain their motivation.

[0342] "User" refers to an individual who uses the system to practice singing.

[0343] "Voice acquisition means" refers to a device or function for recording the user's voice and inputting it into the system.

[0344] "Audio analysis means" refers to software or algorithms used to analyze acquired audio data and evaluate singing characteristics such as pitch and amplitude.

[0345] "Customized practice plan generation means" refers to a device or function that creates an individually tailored practice menu based on the user's singing ability evaluation and goals.

[0346] The "real-time voice analysis means" refers to a function for instantly analyzing voice data when a user sings in real time.

[0347] "Feedback providing means" refers to a device or function that provides advice or guidance to the user in real time or at a later time based on the results of voice analysis.

[0348] "Emotion recognition means" refers to a device or software that identifies and analyzes the user's current emotions from their facial expressions and tone of voice.

[0349] "Emotion-based feedback means" refers to a function for providing appropriate advice and support to users based on emotion recognition results.

[0350] "Progress Tracking Measures" refers to devices or software that store a user's practice records and continuously track milestone achievements.

[0351] "Milestone recording means" refers to a function that allows a user to record important goals and achievements achieved during practice.

[0352] "Progress data storage means" refers to a device or function that accumulates data about a user's practice and stores it for future reference and analysis.

[0353] The "means for providing a practice menu for improving skills" refers to a function for providing a specific practice menu for the user to improve a specific singing skill based on the analyzed voice data.

[0354] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0355] System Overview

[0356] To use the system, users enter basic information (such as their name, current singing ability, and goals). This information is used to personalize the system. The user uploads an audio file of their singing, and the audio data is analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation and goals.

[0357] Analysis of audio data

[0358] The user records their singing as an audio file and uploads it to the device. The device receives the audio file and saves it in a specified directory. A dedicated library such as Librosa is used to analyze the saved audio file. The server reads and analyzes the audio file, extracting pitch (height) and amplitude characteristics from the audio data. The average pitch value and stability are then calculated to evaluate the user's current singing ability.

[0359] Generate a customized practice plan

[0360] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0361] Emotional Recognition and Feedback

[0362] The user sings in real time and the device captures the audio. When the device captures the live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and vocal tone. The server analyzes the audio and emotional data in real time. The system provides the user with immediate feedback, including pitch accuracy, sense of rhythm, and vocal accuracy, as well as advice based on the user's emotions.

[0363] Progress Tracking and Data Storage

[0364] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0365] Specific examples

[0366] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[0367] 1. User B enters basic information (name, current pitch, goal, etc.) when logging in for the first time.

[0368] 2. User B uploads the audio file of his singing.

[0369] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[0370] 4. User B's target pitch is set to 300.

[0371] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0372] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[0373] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B. For example, it may provide advice such as "Try to relax and take a deep breath."

[0374] 8. User B's progress is recorded and goal achievement is tracked periodically. All data is saved so User B can review it later.

[0375] Prompt Sentence Examples

[0376] "Analyzes audio files sung by users, extracts pitch and amplitude characteristics, and evaluates the user's singing ability."

[0377] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0378] Step 1:

[0379] User

[0380] When a user logs in for the first time, they enter basic information such as their name, current singing ability, and goals. This data is used to personalize the system. The information is sent to the server and saved as a user profile.

[0381] Input: Basic information such as name, current singing ability, goals, etc.

[0382] Output: User profile (e.g., JSON format)

[0383] Step 2:

[0384] User

[0385] Users record themselves singing and upload the audio file to the system, preferably in MP3 or WAV format.

[0386] Input: Recorded audio file

[0387] Output: Uploaded audio file

[0388] Step 3:

[0389] Terminal

[0390] The device receives the audio file uploaded by the user and saves it in the specified directory. At this time, it checks the integrity of the file and returns an error message if the file is incomplete.

[0391] Input: Uploaded audio file

[0392] Output: Saved audio file

[0393] Step 4:

[0394] server

[0395] The server reads the saved audio file and analyzes the audio data using a dedicated library such as Librosa. The analysis items include pitch (height) and amplitude (strength). The average pitch and stability are calculated to evaluate the user's singing ability.

[0396] Input: Saved audio file

[0397] Output: Singing ability evaluation results (average pitch, amplitude, stability, etc.)

[0398] Step 5:

[0399] server

[0400] The server compares the user's singing ability assessment results with pre-set goals. Based on the results, it identifies necessary practice items and generates a customized practice plan, suggesting, for example, how to extend the high range, control vibrato, and vocal techniques.

[0401] Input: Singing ability assessment results, user goals

[0402] Output: Customized practice plan

[0403] Step 6:

[0404] User

[0405] The user sings in real time and the device captures the voice.

[0406] Input: Real-time singing voice

[0407] Output: Captured live audio

[0408] Step 7:

[0409] Terminal

[0410] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice, and emotional data is also acquired at the same time.

[0411] Input: Live captured audio, facial expression data

[0412] Output: Emotion data

[0413] Step 8:

[0414] server

[0415] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user, such as feedback on pitch accuracy and rhythm, along with emotion-based advice, such as "Try relaxing and taking a deep breath."

[0416] Input: Real-time voice data, emotion data

[0417] Output: Feedback (advice based on pitch accuracy, rhythm, and emotion)

[0418] Step 9:

[0419] server

[0420] The server records the user's practice progress and reports achieved milestones. The progress data is stored in JSON format for the user to refer to later.

[0421] Input: Practice progress information

[0422] Output: Progress data (JSON format) and milestones achieved

[0423] The above is the specific processing flow of this program.

[0424] (Application example 2)

[0425] 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."

[0426] Currently, there is a lack of effective systems for managing the stress and improving the skills of robot operators in factories. Conventional methods make it difficult to accurately grasp the emotional state of operators, which often results in delayed response when stress accumulates. Furthermore, training plans for skill improvement are difficult to individually optimize, and feedback tailored to each operator's skills and emotions is not provided. Therefore, a system that can more efficiently manage stress for robot operators and improve their skills is needed.

[0427] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the user's voice, means for analyzing the acquired voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for analyzing the user's facial expressions and recognizing emotions, and means for customizing practice plans and feedback based on the user's voice and emotional data. This makes it possible to grasp the operator's stress level in real time and provide feedback accordingly. Furthermore, by providing a customized practice plan based on each operator's skill improvement, efficient skill improvement is possible.

[0428] The "means for acquiring user's voice" is a device or software for capturing the voice uttered by the robot operator and storing it as digital data.

[0429] "Means for analyzing the captured audio and assessing the user's current singing ability" refers to software or algorithms that analyze the captured audio data and assess the operator's skill level and stress level based on the content of the data.

[0430] "Means for generating a customized practice plan based on the user's goals" refers to software or a system for creating optimal practice menus and tasks according to the goals set by the operator.

[0431] "Means for analyzing the user's voice in real time and providing feedback" refers to a device or software that analyzes the operator's voice in real time and immediately provides suggestions for improvement or advice based on the results.

[0432] "Means for tracking user progress and recording achieved milestones" refers to a system for tracking the progress of operators' practice and work, and recording data on goals and milestones achieved.

[0433] "Means for analyzing the user's facial expressions and recognizing emotions" refers to software or algorithms that use a camera to capture the operator's facial expressions and identify emotions using image analysis technology.

[0434] "Means for customizing practice plans and feedback based on the user's voice and emotional data" refers to a system that creates and provides practice plans and feedback optimized for each operator based on acquired and analyzed voice and emotional data.

[0435] System Overview

[0436] The system is designed to help manage stress and improve the skills of robot operators in factories. Its main components include voice data acquisition and analysis, facial expression analysis, real-time feedback, and progress management. The system combines hardware such as a head-mounted display (HMD) and webcam with software such as OpenCV, librosa, and Keras.

[0437] Acquisition and analysis of audio data

[0438] User

[0439] The robot operator inputs voice using a microphone built into the head-mounted display (HMD), which allows voice data to be acquired in real time during operation.

[0440] Terminal

[0441] The device saves the captured voice data, which is then analyzed using a voice analysis library such as librosa to extract features for evaluating the user's skill level and stress level.

[0442] server

[0443] The server analyzes the audio data to assess the operator's skill level and stress level, using functions to extract pitch and amplitude characteristics, and generates a customized practice plan based on the analysis results.

[0444] Facial Expression Analysis and Emotion Recognition

[0445] User

[0446] The robot operator captures facial expressions using a camera built into the head-mounted display.

[0447] Terminal

[0448] The device recognizes emotions from captured facial expression data. It uses OpenCV to detect faces and inputs them into an emotion recognition model built with Keras to analyze the operator's emotional state in real time.

[0449] server

[0450] The server generates feedback based on the analyzed voice and emotional data, providing advice and suggestions for improvement in real time according to the operator's emotional state.

[0451] Tracking progress and providing feedback

[0452] server

[0453] The server tracks the operators' progress and records the milestones they achieve, allowing them to visually confirm their progress in improving their skills and managing stress. The progress data is saved in JSON format or similar for future reference and analysis.

[0454] Specific examples

[0455] For example, when Robot Operator A uses the system, the process goes through the following steps:

[0456] 1. Operator A puts on the head-mounted display and begins capturing voice and facial expressions.

[0457] 2. The audio data acquired by the device is analyzed using librosa, and features such as pitch and amplitude are extracted.

[0458] 3. Based on the analysis results, the server evaluates Operator A's current skill level and stress state.

[0459] 4. At the same time, the device analyzes the facial expression data captured by the camera using OpenCV and Keras to recognize the emotional state.

[0460] 5. The server generates real-time feedback based on the voice and emotion data. For example, if Operator A is nervous, the server will provide advice such as "Relax."

[0461] 6. The server records Operator A's progress data so that it can be reviewed later.

[0462] Example prompts to input to a generative AI model:

[0463] "Operator A's audio and video analysis has confirmed that he has a high stress level. Please generate feedback and a training plan based on his emotional state."

[0464] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0465] Step 1:

[0466] The user puts on the head-mounted display and starts capturing voice. The user's voice is picked up by a microphone and saved as digital data. This digital data becomes the input data for voice analysis.

[0467] Step 2:

[0468] The voice data acquired by the device is read using the librosa library. Using librosa, features such as pitch and amplitude characteristics are extracted from the voice data. These features become the output data for voice analysis.

[0469] Step 3:

[0470] The server receives the features of the voice data sent from the device and evaluates the operator's skill level and stress level. The evaluation results become the input data for generating a practice plan.

[0471] Step 4:

[0472] The user captures their facial expressions using a camera built into the head-mounted display, and this video data becomes the input data for emotion recognition.

[0473] Step 5:

[0474] The facial expression data captured by the device is analyzed using OpenCV to detect the face. The detected facial features are input into a Keras emotion recognition model to recognize the user's emotional state. The emotion recognition results are used as input data for generating feedback.

[0475] Step 6:

[0476] The server integrates the results of the voice data evaluation and emotion recognition, and generates appropriate feedback in real time, which is then presented to the user.

[0477] Step 7:

[0478] The server tracks user progress and records milestones achieved, and this progress data is stored in a format such as JSON for future reference and analysis.

[0479] Step 8:

[0480] The server uses a generative AI model to generate prompts based on the input data and presents them to the user, providing feedback and practice plans according to their emotional state.These prompts allow users to visualize their progress.

[0481] 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.

[0482] 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.

[0483] 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.

[0484] [Second embodiment]

[0485] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0486] 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.

[0487] 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).

[0488] 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.

[0489] 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.

[0490] 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).

[0491] 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. 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.

[0492] 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.

[0493] 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.

[0494] 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.

[0495] In the smart glasses 214, 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.

[0496] 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."

[0497] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0498] System Overview

[0499] To use the system, users first enter basic information (such as their name and current singing ability). They then upload an audio file of their actual singing, and the system analyzes that audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[0500] Analysis of audio data

[0501] User

[0502] The user records their singing as an audio file and uploads it to the device.

[0503] Terminal

[0504] The device receives and saves the uploaded audio file, and uses a dedicated library (such as librosa) to analyze the saved audio file.

[0505] server

[0506] The server reads the audio file and analyzes it. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value, etc. This allows the user's current singing ability to be evaluated.

[0507] Generate a customized practice plan

[0508] server

[0509] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0510] Providing real-time feedback

[0511] User

[0512] The user sings in real time and inputs the voice into the terminal.

[0513] Terminal

[0514] The device captures live audio and processes it in real time.

[0515] server

[0516] The server analyzes the voice data in real time and provides immediate feedback to the user, including information on pitch stability and vocal accuracy.

[0517] Progress Tracking and Data Storage

[0518] server

[0519] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0520] Specific examples

[0521] For example, if User A wants to improve his singing ability, he uses the system as follows:

[0522] 1. When User A logs in for the first time, basic information (name, current pitch) is entered.

[0523] 2. User A uploads the audio file of his singing.

[0524] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[0525] 4. User A's target pitch is set to 350.

[0526] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0527] 6. User A sings in real time and the server provides real-time feedback.

[0528] 7. User A's progress is recorded and goal achievement is tracked periodically.

[0529] 8. All data is saved and User A can look back on it later.

[0530] The above is an embodiment of this system.

[0531] The processing flow will be explained below.

[0532] Step 1:

[0533] A user logs in to the system and enters basic information (such as name and current singing ability), which is received by the terminal and sent to the server.

[0534] Step 2:

[0535] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, etc.

[0536] Step 3:

[0537] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[0538] Step 4:

[0539] The server reads the saved audio file and analyzes the audio data using an audio analysis library (e.g., librosa). Specifically, it extracts pitch and amplitude features from the audio data.

[0540] Step 5:

[0541] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user data. For example, the average pitch and stability are used as evaluation criteria.

[0542] Step 6:

[0543] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[0544] Step 7:

[0545] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[0546] Step 8:

[0547] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[0548] Step 9:

[0549] The server analyzes the audio data in real time and provides immediate feedback to the user, including pitch accuracy and rhythmic stability.

[0550] Step 10:

[0551] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[0552] Step 11:

[0553] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[0554] Example 1

[0555] 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."

[0556] Conventional voice training systems have difficulty providing appropriate feedback and practice plans tailored to each user's individual singing ability, making effective training difficult. Furthermore, there are insufficient methods for tracking a user's progress in detail and visually confirming their achievement. As a result, many users are unable to receive effective instruction to improve their singing ability, making it difficult for them to maintain their motivation.

[0557] 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.

[0558] In this invention, the server includes means for extracting pitch and amplitude characteristics from the user's voice data and evaluating the user's current ability based on the analysis results, means for generating a customized practice plan based on the user's goals, and means for analyzing the user's voice in real time and providing feedback. This allows the user to receive feedback tailored to their own characteristics in real time and implement an effective singing practice plan. Furthermore, detailed tracking of the user's progress and visual confirmation of achievement level are expected to maintain ongoing motivation.

[0559] "Audio data" refers to data in which the voice of a user is recorded in digital format.

[0560] "Analysis" is the process of extracting certain characteristics (such as pitch or amplitude) from audio data and using that data to evaluate the user's singing ability.

[0561] A "customized practice plan" refers to a practice menu that is individually optimized based on the user's current singing ability and goals.

[0562] "Real-time feedback" is a function that instantly provides analysis results and suggests necessary advice and corrections while the user is singing.

[0563] "Progress tracking" is the process of recording a user's practice and milestones achieved so that they can be reviewed later.

[0564] "Pitch" is a characteristic that indicates the pitch of a sound and is determined by the frequency of the sound.

[0565] "Amplitude" is a characteristic that indicates the height of waves in sound, and affects the loudness and intensity of the sound.

[0566] "Feature extraction" is the process of extracting important characteristics, such as pitch and amplitude, from audio data.

[0567] "Degree of achievement" is an index that indicates how much progress has been made toward the goal set by the user.

[0568] "Milestones" mark important milestones in the development of a user's practice.

[0569] This invention is a system that provides an AI voice analysis tool and a virtual voice training service to help users improve their singing ability at home. It has various functions to support users' singing practice and maintain their motivation. Specific embodiments of this system are described below.

[0570] System Overview

[0571] When a user uses the system, they first enter basic information (such as their name and current singing ability). Next, they upload an audio file of their actual singing, and the system analyzes the audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[0572] Hardware and software used

[0573] Terminal

[0574] The terminal is a device that receives and stores the user's voice files, and includes PCs, smartphones, etc. A dedicated library (such as librosa) is used for voice analysis.

[0575] server

[0576] The server is a central computer that reads and analyzes the audio data. Specifically, the server extracts pitch and amplitude characteristics from the audio data and evaluates the user's current singing ability. A computer with a high-performance CPU and GPU is recommended to process data in real time as needed.

[0577] Analysis of audio data

[0578] When a user records themselves singing and uploads the audio file, the device receives the file and sends it to the server. The server analyzes the audio file and calculates the average pitch and amplitude fluctuations to evaluate the user's current singing ability. This process uses a voice analysis library such as librosa.

[0579] Generate a customized practice plan

[0580] The server compares the analysis results with the user's set goals, and based on the differences, identifies the necessary practice items and generates a customized practice plan. For example, if the user's goals are to improve their high-pitched notes or vibrato control, a training menu specifically tailored to those areas will be generated.

[0581] Providing real-time feedback

[0582] When a user sings in real time and inputs the voice into the device, the device captures the live voice and transmits it to the server in real time. The server immediately analyzes the voice and provides feedback to the user, such as pitch stability and vocal accuracy.

[0583] Progress Tracking and Data Storage

[0584] The server records the user's practice progress and saves the achieved milestones in a database. The progress data is saved in JSON format for future reference and analysis, allowing users to visually confirm their own progress.

[0585] Examples of concrete examples and prompts

[0586] For example, when User A logs in for the first time, he or she enters his or her name and current pitch (250). When User A uploads an audio file of his or her singing, the server analyzes the audio file and calculates the current pitch (for example, 250). If User A's target pitch is 350, the server generates a high-pitched practice plan and provides it to User A. When singing in real time, the server provides instant feedback and records progress.

[0587] An example prompt using a generative AI model is, "Analyze the user's uploaded audio file, calculate the average pitch, and generate a customized practice plan. Also, provide real-time feedback."

[0588] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0589] Step 1: Initial Registration

[0590] User

[0591] A user logs into the system for the first time and enters their name and current singing ability (e.g., current pitch value).

[0592] Terminal

[0593] The terminal receives basic information entered by the user and transmits the data to the server.

[0594] server

[0595] The server stores the received user information in a database and creates a user profile.

[0596] Input: User's basic information (name, current pitch value)

[0597] Output: Creates a user profile and saves it to the database.

[0598] Step 2: Upload your audio file

[0599] User

[0600] The user records their singing and uploads the audio file to the device.

[0601] Terminal

[0602] The device receives the uploaded audio file, temporarily stores it, and then sends it to the server using a file transfer protocol.

[0603] server

[0604] The server retrieves the audio file uploaded from the terminal and stores it in a database.

[0605] Input: Recorded audio file

[0606] Output: Audio file saved on the server

[0607] Step 3: Analyzing the audio data

[0608] server

[0609] The server reads the saved audio file and analyzes it using an audio analysis library such as librosa. It extracts pitch and amplitude characteristics from the audio data and calculates the average pitch and amplitude fluctuations. The analysis results are stored in a database and the user's current singing ability is evaluated.

[0610] Input: Saved audio file

[0611] Output: Analysis results (average pitch, amplitude fluctuation), saved to database

[0612] Step 4: Generate a customized practice plan

[0613] server

[0614] The server compares the analysis results with the user's set goals and identifies the necessary practice areas based on the difference. It then generates a customized practice plan and provides it to the user. For example, it can include how to practice high notes and how to control vibrato to reach the target pitch.

[0615] Input: Analysis results, user goals

[0616] Output: Customized practice plan

[0617] Step 5: Provide real-time feedback

[0618] User

[0619] The user sings in real time and inputs the voice into the terminal.

[0620] Terminal

[0621] The terminal captures the input voice in real time and transmits the real-time voice data to the server.

[0622] server

[0623] The server instantly analyzes the received real-time voice data and generates feedback, which is then sent to the user in real time (e.g., pitch stability, pronunciation accuracy, etc.).

[0624] Input: Real-time audio data

[0625] Output: Real-time feedback

[0626] Step 6: Progress Tracking and Data Storage

[0627] server

[0628] The server records the user's practice progress and saves the achieved milestones in a database. The saved progress data is managed in JSON format or similar and is used for future reference and analysis. Progress reports are generated and sent to the user periodically.

[0629] Input: User's practice data, achieved milestones

[0630] Output: Progress data (JSON format), progress report

[0631] (Application example 1)

[0632] 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."

[0633] Previous systems for improving singing ability struggled to provide personalized practice plans and were unable to track users' progress in real time. Furthermore, analyzing users' own voice data and providing specific feedback required advanced expertise. Therefore, there was a need for a system that would allow users to easily improve their singing ability at home.

[0634] 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.

[0635] In this invention, the server includes means for acquiring a user's voice, means for analyzing the acquired voice and assessing the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for processing the singing data based on the user's input and providing the generated practice plan, and means for analyzing the user's voice data to extract pitch and amplitude characteristics, thereby enabling a user to receive a personalized practice plan to improve their singing ability from the convenience of their own home, with real-time feedback and progress tracking.

[0636] definition statement

[0637] The "means for acquiring the user's voice" refers to a device or system for recording or inputting the voice sung by the user.

[0638] The "means for analyzing the captured voice and evaluating the user's current singing ability" is an algorithm or program for analyzing the recorded voice and quantifying or evaluating the singing ability.

[0639] The "means for generating a customized exercise plan based on the user's goals" is a program or system for creating an individual exercise plan according to the goals set by the user.

[0640] The "means for analyzing the user's voice in real time and providing feedback" is a system for analyzing voice data in real time and providing immediate feedback based on the results.

[0641] A "means for tracking a user's progress and recording achieved milestones" is a system for continuously monitoring a user's practice progress and recording goals and significant milestones achieved.

[0642] "Means for processing singing data based on user input and providing a generated practice plan" refers to a system that processes audio data based on information entered by the user and provides a customized practice plan.

[0643] The "means for analyzing the user's voice data to extract pitch and amplitude characteristics" refers to an algorithm or program for extracting characteristics such as pitch and intensity from the user's recorded voice data.

[0644] "Means for storing user progress data and storing it in a format that can be used for future reference and analysis" refers to a system that stores a user's practice progress and stores it in a format that can be used for future analysis and feedback.

[0645] The "means for inputting prompt sentences into a generative AI model and obtaining a customized practice plan" refers to a system for inputting instructions or questions into a generative AI model and automatically generating an individual practice plan based on the input.

[0646] MODE FOR CARRYING OUT THE INVENTION

[0647] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who wish to improve their singing ability. The system includes a function to support users in practicing singing at home and ensure sustained motivation.

[0648] System Overview

[0649] To use the system, users enter basic information (such as their name and current singing ability). By uploading an audio file of the user's actual singing, the server analyzes the audio data and evaluates the user's current singing ability. Based on the evaluation results, a customized practice plan tailored to the user's goals is generated.

[0650] Analysis of audio data

[0651] User

[0652] Users record their own singing as an audio file and upload it via their smartphone or other device.

[0653] Terminal

[0654] The device receives the uploaded audio file and sends the data to a server, where it uses a dedicated library such as librosa for analysis.

[0655] server

[0656] The server receives and analyzes the voice data. Specifically, it extracts pitch and amplitude characteristics from the voice data, calculates the average pitch, and evaluates the user's singing ability.

[0657] Generate a customized practice plan

[0658] server

[0659] The server compares the user's singing ability assessment results with the set goals, and based on the results, identifies necessary practice items and generates a customized practice plan, including exercises on how to extend high notes, vibrato control, and vocal technique.

[0660] Providing real-time feedback

[0661] User

[0662] The user sings in real time and inputs the singing voice into the terminal.

[0663] Terminal

[0664] The device captures live audio and immediately transmits it to the server.

[0665] server

[0666] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[0667] Progress Tracking and Data Storage

[0668] server

[0669] The server records the user's progress and saves the milestones they achieve, allowing them to visually see their growth. Progress data is saved in a format such as JSON for future reference and analysis.

[0670] Specific examples

[0671] For example, if User A wants to improve his singing ability and uses this system:

[0672] 1. User A enters basic information (name, current pitch) when logging in for the first time.

[0673] 2. User A uploads the audio file of his singing.

[0674] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[0675] 4. User A's target pitch is set to 350.

[0676] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0677] 6. User A sings in real time and the server provides real-time feedback.

[0678] 7. User A's progress is recorded and goal achievement is tracked periodically.

[0679] 8. All data is saved and User A can look back on it later.

[0680] Example prompt for a generative AI model:

[0681] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[0682] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0683] Detailed explanation of the processing steps

[0684] Step 1:

[0685] The user logs in to the system for the first time and enters basic information (such as name, current singing ability, etc.), which is then stored in the database.

[0686] Input: User's basic information (name, current singing ability, etc.)

[0687] Output: User information stored in the database

[0688] Step 2:

[0689] Users record themselves singing and upload the audio file to their device.

[0690] Input: Recorded audio file\

[0691] Output: Audio file uploaded to device

[0692] Step 3:

[0693] The device receives the uploaded audio file and sends the data to the server.

[0694] Input: Uploaded audio file

[0695] Output: Audio data sent to the server

[0696] Step 4:

[0697] The server analyzes the received audio data using the librosa library and extracts pitch and amplitude characteristics from the audio data.

[0698] Input: Audio data sent to the server\

[0699] Output: Extracted pitch and amplitude characteristics data

[0700] Specific operation: Analyzes audio data using the librosa library and quantifies pitch and amplitude

[0701] Step 5:

[0702] The server evaluates the user's current singing ability based on the extracted characteristic data.

[0703] Input: Extracted pitch and amplitude characteristics data

[0704] Output: User's singing ability evaluation result

[0705] Specific operation: Calculate the average pitch and generate the evaluation result

[0706] Step 6:

[0707] The server compares the user's goals with the evaluation results and generates a customized practice plan, such as how to extend the high notes or control vibrato.

[0708] Input: User's goal, singing ability evaluation results

[0709] Output: Customized practice plan

[0710] Specific actions: Identify necessary practice items based on goals and assessment results and create a plan

[0711] Step 7:

[0712] The user sings in real time and inputs the live audio into the device.

[0713] Input: Live Audio

[0714] Output: Live audio input to the device

[0715] Step 8:

[0716] The device captures live audio and instantly transmits it to the server.

[0717] Input: Live audio input into the device

[0718] Output: Live audio data sent to the server

[0719] Step 9:

[0720] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[0721] Input: Live audio data sent to the server

[0722] Output: Real-time feedback

[0723] What it does: Analyzes live audio and generates feedback using the librosa library

[0724] Step 10:

[0725] The server tracks the user's progress and records milestones achieved. Progress data is stored in a format that can be used for future reference and analysis.

[0726] Input: User practice data and progress

[0727] Output: Saved progress data and milestones\

[0728] Specific operation: Save data in JSON format etc. and update tracking information

[0729] Example of a generated prompt statement

[0730] The prompt to the generative AI model is:

[0731] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[0732] 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.

[0733] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0734] System Overview

[0735] To use the system, users enter basic information (such as their name, current singing ability, and goals). They then upload an audio file of their singing, which is then analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation results and the user's goals. The system also incorporates an emotion engine that recognizes the user's emotions, providing feedback and advice based on the user's emotions.

[0736] Analysis of audio data

[0737] User

[0738] The user records their singing as an audio file and uploads it to the device.

[0739] Terminal

[0740] The device receives this audio file and saves it in the specified directory. A dedicated library (such as librosa) is used to analyze the saved audio file.

[0741] server

[0742] The server reads and analyzes the audio file. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value and stability. This evaluates the user's current singing ability.

[0743] Generate a customized practice plan

[0744] server

[0745] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0746] Emotional Recognition and Feedback

[0747] User

[0748] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[0749] Terminal

[0750] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice.

[0751] server

[0752] The server analyzes the voice data and emotional data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythm, and vocal accuracy, as well as advice based on the user's emotions. For example, if the user is nervous, the system will provide advice such as "Try relaxing and taking a breather."

[0753] Progress Tracking and Data Storage

[0754] server

[0755] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0756] Specific examples

[0757] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[0758] 1. When User B logs in for the first time, basic information (name, current pitch, goal, etc.) is entered.

[0759] 2. User B uploads the audio file of his singing.

[0760] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[0761] 4. User B's target pitch is set to 300.

[0762] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0763] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[0764] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B.

[0765] 8. User B's progress is recorded and goal achievement is tracked periodically.

[0766] 9. All data is saved and User B can look back on it later.

[0767] The above is an embodiment of this system.

[0768] The processing flow will be explained below.

[0769] Step 1:

[0770] A user logs in to the system and enters basic information (such as name, current singing ability, goals, etc.). The terminal receives this information and sends it to the server.

[0771] Step 2:

[0772] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, and emotional information.

[0773] Step 3:

[0774] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[0775] Step 4:

[0776] The server reads the saved audio file and analyzes the audio data using an audio analysis library. Specifically, it extracts pitch and amplitude features from the audio data and calculates the average pitch value and stability.

[0777] Step 5:

[0778] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user's data, including average pitch, sense of rhythm, and vocal accuracy.

[0779] Step 6:

[0780] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[0781] Step 7:

[0782] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[0783] Step 8:

[0784] The user sings in real time, and the device captures their voice and facial expressions. The captured voice data is saved as a temporary file, and the facial expression data is processed for emotion recognition.

[0785] Step 9:

[0786] The device analyzes the user's facial expressions and voice tone to activate the emotion engine, which identifies the user's emotional state (e.g., tension, relaxation, joy, sadness).

[0787] Step 10:

[0788] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythmic stability, and vocal accuracy, as well as emotional advice. For example, if the user is nervous, the server will provide advice such as "Try relaxing and taking a breather."

[0789] Step 11:

[0790] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[0791] Step 12:

[0792] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[0793] Example 2

[0794] 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."

[0795] Conventional singing practice systems have difficulty accurately assessing a user's singing ability when practicing independently at home, and they lack the feedback needed to maintain motivation. This makes it difficult to effectively improve singing ability and provide an optimal practice plan for each user. Furthermore, since feedback does not take emotions into account, it is difficult to respond to fluctuations in performance due to the user's psychological state. Therefore, a new system for improving singing ability and maintaining motivation is needed.

[0796] 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.

[0797] In this invention, the server includes means for capturing a user's voice, means for analyzing the captured voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for recognizing the user's emotions and providing feedback or advice based on the emotions, and means for tracking the user's progress and recording achieved milestones, thereby enabling users to efficiently and effectively improve their singing ability at home and receive appropriate feedback to maintain their motivation.

[0798] "User" refers to an individual who uses the system to practice singing.

[0799] "Voice acquisition means" refers to a device or function for recording the user's voice and inputting it into the system.

[0800] "Audio analysis means" refers to software or algorithms used to analyze acquired audio data and evaluate singing characteristics such as pitch and amplitude.

[0801] "Customized practice plan generation means" refers to a device or function that creates an individually tailored practice menu based on the user's singing ability evaluation and goals.

[0802] The "real-time voice analysis means" refers to a function for instantly analyzing voice data when a user sings in real time.

[0803] "Feedback providing means" refers to a device or function that provides advice or guidance to the user in real time or at a later time based on the results of voice analysis.

[0804] "Emotion recognition means" refers to a device or software that identifies and analyzes the user's current emotions from their facial expressions and tone of voice.

[0805] "Emotion-based feedback means" refers to a function for providing appropriate advice and support to users based on emotion recognition results.

[0806] "Progress Tracking Measures" refers to devices or software that store a user's practice records and continuously track milestone achievements.

[0807] "Milestone recording means" refers to a function that allows a user to record important goals and achievements achieved during practice.

[0808] "Progress data storage means" refers to a device or function that accumulates data about a user's practice and stores it for future reference and analysis.

[0809] The "means for providing a practice menu for improving skills" refers to a function for providing a specific practice menu for the user to improve a specific singing skill based on the analyzed voice data.

[0810] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0811] System Overview

[0812] To use the system, users enter basic information (such as their name, current singing ability, and goals). This information is used to personalize the system. The user uploads an audio file of their singing, and the audio data is analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation and goals.

[0813] Analysis of audio data

[0814] The user records their singing as an audio file and uploads it to the device. The device receives the audio file and saves it in a specified directory. A dedicated library such as Librosa is used to analyze the saved audio file. The server reads and analyzes the audio file, extracting pitch (height) and amplitude characteristics from the audio data. The average pitch value and stability are then calculated to evaluate the user's current singing ability.

[0815] Generate a customized practice plan

[0816] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0817] Emotional Recognition and Feedback

[0818] The user sings in real time and the device captures the audio. When the device captures the live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and vocal tone. The server analyzes the audio and emotional data in real time. The system provides the user with immediate feedback, including pitch accuracy, sense of rhythm, and vocal accuracy, as well as advice based on the user's emotions.

[0819] Progress Tracking and Data Storage

[0820] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0821] Specific examples

[0822] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[0823] 1. User B enters basic information (name, current pitch, goal, etc.) when logging in for the first time.

[0824] 2. User B uploads the audio file of his singing.

[0825] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[0826] 4. User B's target pitch is set to 300.

[0827] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0828] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[0829] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B. For example, it may provide advice such as "Try to relax and take a deep breath."

[0830] 8. User B's progress is recorded and goal achievement is tracked periodically. All data is saved so User B can review it later.

[0831] Prompt Sentence Examples

[0832] "Analyzes audio files sung by users, extracts pitch and amplitude characteristics, and evaluates the user's singing ability."

[0833] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0834] Step 1:

[0835] User

[0836] When a user logs in for the first time, they enter basic information such as their name, current singing ability, and goals. This data is used to personalize the system. The information is sent to the server and saved as a user profile.

[0837] Input: Basic information such as name, current singing ability, goals, etc.

[0838] Output: User profile (e.g., JSON format)

[0839] Step 2:

[0840] User

[0841] Users record themselves singing and upload the audio file to the system, preferably in MP3 or WAV format.

[0842] Input: Recorded audio file

[0843] Output: Uploaded audio file

[0844] Step 3:

[0845] Terminal

[0846] The device receives the audio file uploaded by the user and saves it in the specified directory. At this time, it checks the integrity of the file and returns an error message if the file is incomplete.

[0847] Input: Uploaded audio file

[0848] Output: Saved audio file

[0849] Step 4:

[0850] server

[0851] The server reads the saved audio file and analyzes the audio data using a dedicated library such as Librosa. The analysis items include pitch (height) and amplitude (strength). The average pitch and stability are calculated to evaluate the user's singing ability.

[0852] Input: Saved audio file

[0853] Output: Singing ability evaluation results (average pitch, amplitude, stability, etc.)

[0854] Step 5:

[0855] server

[0856] The server compares the user's singing ability assessment results with pre-set goals. Based on the results, it identifies necessary practice items and generates a customized practice plan, suggesting, for example, how to extend the high range, control vibrato, and vocal techniques.

[0857] Input: Singing ability assessment results, user goals

[0858] Output: Customized practice plan

[0859] Step 6:

[0860] User

[0861] The user sings in real time and the device captures the voice.

[0862] Input: Real-time singing voice

[0863] Output: Captured live audio

[0864] Step 7:

[0865] Terminal

[0866] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice, and emotional data is also acquired at the same time.

[0867] Input: Live captured audio, facial expression data

[0868] Output: Emotion data

[0869] Step 8:

[0870] server

[0871] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user, such as feedback on pitch accuracy and rhythm, along with emotion-based advice, such as "Try relaxing and taking a deep breath."

[0872] Input: Real-time voice data, emotion data

[0873] Output: Feedback (advice based on pitch accuracy, rhythm, and emotion)

[0874] Step 9:

[0875] server

[0876] The server records the user's practice progress and reports achieved milestones. The progress data is stored in JSON format for the user to refer to later.

[0877] Input: Practice progress information

[0878] Output: Progress data (JSON format) and milestones achieved

[0879] The above is the specific processing flow of this program.

[0880] (Application example 2)

[0881] 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."

[0882] Currently, there is a lack of effective systems for managing the stress and improving the skills of robot operators in factories. Conventional methods make it difficult to accurately grasp the emotional state of operators, which often results in delayed response when stress accumulates. Furthermore, training plans for skill improvement are difficult to individually optimize, and feedback tailored to each operator's skills and emotions is not provided. Therefore, a system that can more efficiently manage stress for robot operators and improve their skills is needed.

[0883] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the user's voice, means for analyzing the acquired voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for analyzing the user's facial expressions and recognizing emotions, and means for customizing practice plans and feedback based on the user's voice and emotional data. This makes it possible to grasp the operator's stress level in real time and provide feedback accordingly. Furthermore, by providing a customized practice plan based on each operator's skill improvement, efficient skill improvement is possible.

[0884] The "means for acquiring user's voice" is a device or software for capturing the voice uttered by the robot operator and storing it as digital data.

[0885] "Means for analyzing the captured audio and assessing the user's current singing ability" refers to software or algorithms that analyze the captured audio data and assess the operator's skill level and stress level based on the content of the data.

[0886] "Means for generating a customized practice plan based on the user's goals" refers to software or a system for creating optimal practice menus and tasks according to the goals set by the operator.

[0887] "Means for analyzing the user's voice in real time and providing feedback" refers to a device or software that analyzes the operator's voice in real time and immediately provides suggestions for improvement or advice based on the results.

[0888] "Means for tracking user progress and recording achieved milestones" refers to a system for tracking the progress of operators' practice and work, and recording data on goals and milestones achieved.

[0889] "Means for analyzing the user's facial expressions and recognizing emotions" refers to software or algorithms that use a camera to capture the operator's facial expressions and identify emotions using image analysis technology.

[0890] "Means for customizing practice plans and feedback based on the user's voice and emotional data" refers to a system that creates and provides practice plans and feedback optimized for each operator based on acquired and analyzed voice and emotional data.

[0891] System Overview

[0892] The system is designed to help manage stress and improve the skills of robot operators in factories. Its main components include voice data acquisition and analysis, facial expression analysis, real-time feedback, and progress management. The system combines hardware such as a head-mounted display (HMD) and webcam with software such as OpenCV, librosa, and Keras.

[0893] Acquisition and analysis of audio data

[0894] User

[0895] The robot operator inputs voice using a microphone built into the head-mounted display (HMD), which allows voice data to be acquired in real time during operation.

[0896] Terminal

[0897] The device saves the captured voice data, which is then analyzed using a voice analysis library such as librosa to extract features for evaluating the user's skill level and stress level.

[0898] server

[0899] The server analyzes the audio data to assess the operator's skill level and stress level, using functions to extract pitch and amplitude characteristics, and generates a customized practice plan based on the analysis results.

[0900] Facial Expression Analysis and Emotion Recognition

[0901] User

[0902] The robot operator captures facial expressions using a camera built into the head-mounted display.

[0903] Terminal

[0904] The device recognizes emotions from captured facial expression data. It uses OpenCV to detect faces and inputs them into an emotion recognition model built with Keras to analyze the operator's emotional state in real time.

[0905] server

[0906] The server generates feedback based on the analyzed voice and emotional data, providing advice and suggestions for improvement in real time according to the operator's emotional state.

[0907] Tracking progress and providing feedback

[0908] server

[0909] The server tracks the operators' progress and records the milestones they achieve, allowing them to visually confirm their progress in improving their skills and managing stress. The progress data is saved in JSON format or similar for future reference and analysis.

[0910] Specific examples

[0911] For example, when Robot Operator A uses the system, the process goes through the following steps:

[0912] 1. Operator A puts on the head-mounted display and begins capturing voice and facial expressions.

[0913] 2. The audio data acquired by the device is analyzed using librosa, and features such as pitch and amplitude are extracted.

[0914] 3. Based on the analysis results, the server evaluates Operator A's current skill level and stress state.

[0915] 4. At the same time, the device analyzes the facial expression data captured by the camera using OpenCV and Keras to recognize the emotional state.

[0916] 5. The server generates real-time feedback based on the voice and emotion data. For example, if Operator A is nervous, the server will provide advice such as "Relax."

[0917] 6. The server records Operator A's progress data so that it can be reviewed later.

[0918] Example prompts to input to a generative AI model:

[0919] "Operator A's audio and video analysis has confirmed that he has a high stress level. Please generate feedback and a training plan based on his emotional state."

[0920] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0921] Step 1:

[0922] The user puts on the head-mounted display and starts capturing voice. The user's voice is picked up by a microphone and saved as digital data. This digital data becomes the input data for voice analysis.

[0923] Step 2:

[0924] The voice data acquired by the device is read using the librosa library. Using librosa, features such as pitch and amplitude characteristics are extracted from the voice data. These features become the output data for voice analysis.

[0925] Step 3:

[0926] The server receives the features of the voice data sent from the device and evaluates the operator's skill level and stress level. The evaluation results become the input data for generating a practice plan.

[0927] Step 4:

[0928] The user captures their facial expressions using a camera built into the head-mounted display, and this video data becomes the input data for emotion recognition.

[0929] Step 5:

[0930] The facial expression data captured by the device is analyzed using OpenCV to detect the face. The detected facial features are input into a Keras emotion recognition model to recognize the user's emotional state. The emotion recognition results are used as input data for generating feedback.

[0931] Step 6:

[0932] The server integrates the results of the voice data evaluation and emotion recognition, and generates appropriate feedback in real time, which is then presented to the user.

[0933] Step 7:

[0934] The server tracks user progress and records milestones achieved, and this progress data is stored in a format such as JSON for future reference and analysis.

[0935] Step 8:

[0936] The server uses a generative AI model to generate prompts based on the input data and presents them to the user, providing feedback and practice plans according to their emotional state.These prompts allow users to visualize their progress.

[0937] 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.

[0938] 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.

[0939] 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.

[0940] [Third embodiment]

[0941] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0942] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0943] 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).

[0944] 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.

[0945] 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.

[0946] 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).

[0947] 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. 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] 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."

[0953] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[0954] System Overview

[0955] To use the system, users first enter basic information (such as their name and current singing ability). They then upload an audio file of their actual singing, and the system analyzes that audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[0956] Analysis of audio data

[0957] User

[0958] The user records their singing as an audio file and uploads it to the device.

[0959] Terminal

[0960] The device receives and saves the uploaded audio file, and uses a dedicated library (such as librosa) to analyze the saved audio file.

[0961] server

[0962] The server reads the audio file and analyzes it. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value, etc. This allows the user's current singing ability to be evaluated.

[0963] Generate a customized practice plan

[0964] server

[0965] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[0966] Providing real-time feedback

[0967] User

[0968] The user sings in real time and inputs the voice into the terminal.

[0969] Terminal

[0970] The device captures live audio and processes it in real time.

[0971] server

[0972] The server analyzes the voice data in real time and provides immediate feedback to the user, including information on pitch stability and vocal accuracy.

[0973] Progress Tracking and Data Storage

[0974] server

[0975] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[0976] Specific examples

[0977] For example, if User A wants to improve his singing ability, he uses the system as follows:

[0978] 1. When User A logs in for the first time, basic information (name, current pitch) is entered.

[0979] 2. User A uploads the audio file of his singing.

[0980] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[0981] 4. User A's target pitch is set to 350.

[0982] 5. The server generates a customized practice plan, recommending high-pitched practice.

[0983] 6. User A sings in real time and the server provides real-time feedback.

[0984] 7. User A's progress is recorded and goal achievement is tracked periodically.

[0985] 8. All data is saved and User A can look back on it later.

[0986] The above is an embodiment of this system.

[0987] The processing flow will be explained below.

[0988] Step 1:

[0989] A user logs in to the system and enters basic information (such as name and current singing ability), which is received by the terminal and sent to the server.

[0990] Step 2:

[0991] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, etc.

[0992] Step 3:

[0993] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[0994] Step 4:

[0995] The server reads the saved audio file and analyzes the audio data using an audio analysis library (e.g., librosa). Specifically, it extracts pitch and amplitude features from the audio data.

[0996] Step 5:

[0997] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user data. For example, the average pitch and stability are used as evaluation criteria.

[0998] Step 6:

[0999] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[1000] Step 7:

[1001] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[1002] Step 8:

[1003] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[1004] Step 9:

[1005] The server analyzes the audio data in real time and provides immediate feedback to the user, including pitch accuracy and rhythmic stability.

[1006] Step 10:

[1007] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[1008] Step 11:

[1009] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[1010] Example 1

[1011] 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."

[1012] Conventional voice training systems have difficulty providing appropriate feedback and practice plans tailored to each user's individual singing ability, making effective training difficult. Furthermore, there are insufficient methods for tracking a user's progress in detail and visually confirming their achievement. As a result, many users are unable to receive effective instruction to improve their singing ability, making it difficult for them to maintain their motivation.

[1013] 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.

[1014] In this invention, the server includes means for extracting pitch and amplitude characteristics from the user's voice data and evaluating the user's current ability based on the analysis results, means for generating a customized practice plan based on the user's goals, and means for analyzing the user's voice in real time and providing feedback. This allows the user to receive feedback tailored to their own characteristics in real time and implement an effective singing practice plan. Furthermore, detailed tracking of the user's progress and visual confirmation of achievement level are expected to maintain ongoing motivation.

[1015] "Audio data" refers to data in which the voice of a user is recorded in digital format.

[1016] "Analysis" is the process of extracting certain characteristics (such as pitch or amplitude) from audio data and using that data to evaluate the user's singing ability.

[1017] A "customized practice plan" refers to a practice menu that is individually optimized based on the user's current singing ability and goals.

[1018] "Real-time feedback" is a function that instantly provides analysis results and suggests necessary advice and corrections while the user is singing.

[1019] "Progress tracking" is the process of recording a user's practice and milestones achieved so that they can be reviewed later.

[1020] "Pitch" is a characteristic that indicates the pitch of a sound and is determined by the frequency of the sound.

[1021] "Amplitude" is a characteristic that indicates the height of waves in sound, and affects the loudness and intensity of the sound.

[1022] "Feature extraction" is the process of extracting important characteristics, such as pitch and amplitude, from audio data.

[1023] "Degree of achievement" is an index that indicates how much progress has been made toward the goal set by the user.

[1024] "Milestones" mark important milestones in the development of a user's practice.

[1025] This invention is a system that provides an AI voice analysis tool and a virtual voice training service to help users improve their singing ability at home. It has various functions to support users' singing practice and maintain their motivation. Specific embodiments of this system are described below.

[1026] System Overview

[1027] When a user uses the system, they first enter basic information (such as their name and current singing ability). Next, they upload an audio file of their actual singing, and the system analyzes the audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[1028] Hardware and software used

[1029] Terminal

[1030] The terminal is a device that receives and stores the user's voice files, and includes PCs, smartphones, etc. A dedicated library (such as librosa) is used for voice analysis.

[1031] server

[1032] The server is a central computer that reads and analyzes the audio data. Specifically, the server extracts pitch and amplitude characteristics from the audio data and evaluates the user's current singing ability. A computer with a high-performance CPU and GPU is recommended to process data in real time as needed.

[1033] Analysis of audio data

[1034] When a user records themselves singing and uploads the audio file, the device receives the file and sends it to the server. The server analyzes the audio file and calculates the average pitch and amplitude fluctuations to evaluate the user's current singing ability. This process uses a voice analysis library such as librosa.

[1035] Generate a customized practice plan

[1036] The server compares the analysis results with the user's set goals, and based on the differences, identifies the necessary practice items and generates a customized practice plan. For example, if the user's goals are to improve their high-pitched notes or vibrato control, a training menu specifically tailored to those areas will be generated.

[1037] Providing real-time feedback

[1038] When a user sings in real time and inputs the voice into the device, the device captures the live voice and transmits it to the server in real time. The server immediately analyzes the voice and provides feedback to the user, such as pitch stability and vocal accuracy.

[1039] Progress Tracking and Data Storage

[1040] The server records the user's practice progress and saves the achieved milestones in a database. The progress data is saved in JSON format for future reference and analysis, allowing users to visually confirm their own progress.

[1041] Examples of concrete examples and prompts

[1042] For example, when User A logs in for the first time, he or she enters his or her name and current pitch (250). When User A uploads an audio file of his or her singing, the server analyzes the audio file and calculates the current pitch (for example, 250). If User A's target pitch is 350, the server generates a high-pitched practice plan and provides it to User A. When singing in real time, the server provides instant feedback and records progress.

[1043] An example prompt using a generative AI model is, "Analyze the user's uploaded audio file, calculate the average pitch, and generate a customized practice plan. Also, provide real-time feedback."

[1044] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1045] Step 1: Initial Registration

[1046] User

[1047] A user logs into the system for the first time and enters their name and current singing ability (e.g., current pitch value).

[1048] Terminal

[1049] The terminal receives basic information entered by the user and transmits the data to the server.

[1050] server

[1051] The server stores the received user information in a database and creates a user profile.

[1052] Input: User's basic information (name, current pitch value)

[1053] Output: Creates a user profile and saves it to the database.

[1054] Step 2: Upload your audio file

[1055] User

[1056] The user records their singing and uploads the audio file to the device.

[1057] Terminal

[1058] The device receives the uploaded audio file, temporarily stores it, and then sends it to the server using a file transfer protocol.

[1059] server

[1060] The server retrieves the audio file uploaded from the terminal and stores it in a database.

[1061] Input: Recorded audio file

[1062] Output: Audio file saved on the server

[1063] Step 3: Analyzing the audio data

[1064] server

[1065] The server reads the saved audio file and analyzes it using an audio analysis library such as librosa. It extracts pitch and amplitude characteristics from the audio data and calculates the average pitch and amplitude fluctuations. The analysis results are stored in a database and the user's current singing ability is evaluated.

[1066] Input: Saved audio file

[1067] Output: Analysis results (average pitch, amplitude fluctuation), saved to database

[1068] Step 4: Generate a customized practice plan

[1069] server

[1070] The server compares the analysis results with the user's set goals and identifies the necessary practice areas based on the difference. It then generates a customized practice plan and provides it to the user. For example, it can include how to practice high notes and how to control vibrato to reach the target pitch.

[1071] Input: Analysis results, user goals

[1072] Output: Customized practice plan

[1073] Step 5: Provide real-time feedback

[1074] User

[1075] The user sings in real time and inputs the voice into the terminal.

[1076] Terminal

[1077] The terminal captures the input voice in real time and transmits the real-time voice data to the server.

[1078] server

[1079] The server instantly analyzes the received real-time voice data and generates feedback, which is then sent to the user in real time (e.g., pitch stability, pronunciation accuracy, etc.).

[1080] Input: Real-time audio data

[1081] Output: Real-time feedback

[1082] Step 6: Progress Tracking and Data Storage

[1083] server

[1084] The server records the user's practice progress and saves the achieved milestones in a database. The saved progress data is managed in JSON format or similar and is used for future reference and analysis. Progress reports are generated and sent to the user periodically.

[1085] Input: User's practice data, achieved milestones

[1086] Output: Progress data (JSON format), progress report

[1087] (Application example 1)

[1088] 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."

[1089] Previous systems for improving singing ability struggled to provide personalized practice plans and were unable to track users' progress in real time. Furthermore, analyzing users' own voice data and providing specific feedback required advanced expertise. Therefore, there was a need for a system that would allow users to easily improve their singing ability at home.

[1090] 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.

[1091] In this invention, the server includes means for acquiring a user's voice, means for analyzing the acquired voice and assessing the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for processing the singing data based on the user's input and providing the generated practice plan, and means for analyzing the user's voice data to extract pitch and amplitude characteristics, thereby enabling a user to receive a personalized practice plan to improve their singing ability from the convenience of their own home, with real-time feedback and progress tracking.

[1092] definition statement

[1093] The "means for acquiring the user's voice" refers to a device or system for recording or inputting the voice sung by the user.

[1094] The "means for analyzing the captured voice and evaluating the user's current singing ability" is an algorithm or program for analyzing the recorded voice and quantifying or evaluating the singing ability.

[1095] The "means for generating a customized exercise plan based on the user's goals" is a program or system for creating an individual exercise plan according to the goals set by the user.

[1096] The "means for analyzing the user's voice in real time and providing feedback" is a system for analyzing voice data in real time and providing immediate feedback based on the results.

[1097] A "means for tracking a user's progress and recording achieved milestones" is a system for continuously monitoring a user's practice progress and recording goals and significant milestones achieved.

[1098] "Means for processing singing data based on user input and providing a generated practice plan" refers to a system that processes audio data based on information entered by the user and provides a customized practice plan.

[1099] The "means for analyzing the user's voice data to extract pitch and amplitude characteristics" refers to an algorithm or program for extracting characteristics such as pitch and intensity from the user's recorded voice data.

[1100] "Means for storing user progress data and storing it in a format that can be used for future reference and analysis" refers to a system that stores a user's practice progress and stores it in a format that can be used for future analysis and feedback.

[1101] The "means for inputting prompt sentences into a generative AI model and obtaining a customized practice plan" refers to a system for inputting instructions or questions into a generative AI model and automatically generating an individual practice plan based on the input.

[1102] MODE FOR CARRYING OUT THE INVENTION

[1103] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who wish to improve their singing ability. The system includes a function to support users in practicing singing at home and ensure sustained motivation.

[1104] System Overview

[1105] To use the system, users enter basic information (such as their name and current singing ability). By uploading an audio file of the user's actual singing, the server analyzes the audio data and evaluates the user's current singing ability. Based on the evaluation results, a customized practice plan tailored to the user's goals is generated.

[1106] Analysis of audio data

[1107] User

[1108] Users record their own singing as an audio file and upload it via their smartphone or other device.

[1109] Terminal

[1110] The device receives the uploaded audio file and sends the data to a server, where it uses a dedicated library such as librosa for analysis.

[1111] server

[1112] The server receives and analyzes the voice data. Specifically, it extracts pitch and amplitude characteristics from the voice data, calculates the average pitch, and evaluates the user's singing ability.

[1113] Generate a customized practice plan

[1114] server

[1115] The server compares the user's singing ability assessment results with the set goals, and based on the results, identifies necessary practice items and generates a customized practice plan, including exercises on how to extend high notes, vibrato control, and vocal technique.

[1116] Providing real-time feedback

[1117] User

[1118] The user sings in real time and inputs the singing voice into the terminal.

[1119] Terminal

[1120] The device captures live audio and immediately transmits it to the server.

[1121] server

[1122] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[1123] Progress Tracking and Data Storage

[1124] server

[1125] The server records the user's progress and saves the milestones they achieve, allowing them to visually see their growth. Progress data is saved in a format such as JSON for future reference and analysis.

[1126] Specific examples

[1127] For example, if User A wants to improve his singing ability and uses this system:

[1128] 1. User A enters basic information (name, current pitch) when logging in for the first time.

[1129] 2. User A uploads the audio file of his singing.

[1130] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[1131] 4. User A's target pitch is set to 350.

[1132] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1133] 6. User A sings in real time and the server provides real-time feedback.

[1134] 7. User A's progress is recorded and goal achievement is tracked periodically.

[1135] 8. All data is saved and User A can look back on it later.

[1136] Example prompt for a generative AI model:

[1137] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[1138] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1139] Detailed explanation of the processing steps

[1140] Step 1:

[1141] The user logs in to the system for the first time and enters basic information (such as name, current singing ability, etc.), which is then stored in the database.

[1142] Input: User's basic information (name, current singing ability, etc.)

[1143] Output: User information stored in the database

[1144] Step 2:

[1145] Users record themselves singing and upload the audio file to their device.

[1146] Input: Recorded audio file\

[1147] Output: Audio file uploaded to device

[1148] Step 3:

[1149] The device receives the uploaded audio file and sends the data to the server.

[1150] Input: Uploaded audio file

[1151] Output: Audio data sent to the server

[1152] Step 4:

[1153] The server analyzes the received audio data using the librosa library and extracts pitch and amplitude characteristics from the audio data.

[1154] Input: Audio data sent to the server\

[1155] Output: Extracted pitch and amplitude characteristics data

[1156] Specific operation: Analyzes audio data using the librosa library and quantifies pitch and amplitude

[1157] Step 5:

[1158] The server evaluates the user's current singing ability based on the extracted characteristic data.

[1159] Input: Extracted pitch and amplitude characteristics data

[1160] Output: User's singing ability evaluation result

[1161] Specific operation: Calculate the average pitch and generate the evaluation result

[1162] Step 6:

[1163] The server compares the user's goals with the evaluation results and generates a customized practice plan, such as how to extend the high notes or control vibrato.

[1164] Input: User's goal, singing ability evaluation results

[1165] Output: Customized practice plan

[1166] Specific actions: Identify necessary practice items based on goals and assessment results and create a plan

[1167] Step 7:

[1168] The user sings in real time and inputs the live audio into the device.

[1169] Input: Live Audio

[1170] Output: Live audio input to the device

[1171] Step 8:

[1172] The device captures live audio and instantly transmits it to the server.

[1173] Input: Live audio input into the device

[1174] Output: Live audio data sent to the server

[1175] Step 9:

[1176] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[1177] Input: Live audio data sent to the server

[1178] Output: Real-time feedback

[1179] What it does: Analyzes live audio and generates feedback using the librosa library

[1180] Step 10:

[1181] The server tracks the user's progress and records milestones achieved. Progress data is stored in a format that can be used for future reference and analysis.

[1182] Input: User practice data and progress

[1183] Output: Saved progress data and milestones\

[1184] Specific operation: Save data in JSON format etc. and update tracking information

[1185] Example of a generated prompt statement

[1186] The prompt to the generative AI model is:

[1187] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[1188] 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.

[1189] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[1190] System Overview

[1191] To use the system, users enter basic information (such as their name, current singing ability, and goals). They then upload an audio file of their singing, which is then analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation results and the user's goals. The system also incorporates an emotion engine that recognizes the user's emotions, providing feedback and advice based on the user's emotions.

[1192] Analysis of audio data

[1193] User

[1194] The user records their singing as an audio file and uploads it to the device.

[1195] Terminal

[1196] The device receives this audio file and saves it in the specified directory. A dedicated library (such as librosa) is used to analyze the saved audio file.

[1197] server

[1198] The server reads and analyzes the audio file. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value and stability. This evaluates the user's current singing ability.

[1199] Generate a customized practice plan

[1200] server

[1201] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[1202] Emotional Recognition and Feedback

[1203] User

[1204] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[1205] Terminal

[1206] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice.

[1207] server

[1208] The server analyzes the voice data and emotional data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythm, and vocal accuracy, as well as advice based on the user's emotions. For example, if the user is nervous, the system will provide advice such as "Try relaxing and taking a breather."

[1209] Progress Tracking and Data Storage

[1210] server

[1211] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[1212] Specific examples

[1213] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[1214] 1. When User B logs in for the first time, basic information (name, current pitch, goal, etc.) is entered.

[1215] 2. User B uploads the audio file of his singing.

[1216] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[1217] 4. User B's target pitch is set to 300.

[1218] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1219] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[1220] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B.

[1221] 8. User B's progress is recorded and goal achievement is tracked periodically.

[1222] 9. All data is saved and User B can look back on it later.

[1223] The above is an embodiment of this system.

[1224] The processing flow will be explained below.

[1225] Step 1:

[1226] A user logs in to the system and enters basic information (such as name, current singing ability, goals, etc.). The terminal receives this information and sends it to the server.

[1227] Step 2:

[1228] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, and emotional information.

[1229] Step 3:

[1230] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[1231] Step 4:

[1232] The server reads the saved audio file and analyzes the audio data using an audio analysis library. Specifically, it extracts pitch and amplitude features from the audio data and calculates the average pitch value and stability.

[1233] Step 5:

[1234] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user's data, including average pitch, sense of rhythm, and vocal accuracy.

[1235] Step 6:

[1236] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[1237] Step 7:

[1238] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[1239] Step 8:

[1240] The user sings in real time, and the device captures their voice and facial expressions. The captured voice data is saved as a temporary file, and the facial expression data is processed for emotion recognition.

[1241] Step 9:

[1242] The device analyzes the user's facial expressions and voice tone to activate the emotion engine, which identifies the user's emotional state (e.g., tension, relaxation, joy, sadness).

[1243] Step 10:

[1244] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythmic stability, and vocal accuracy, as well as emotional advice. For example, if the user is nervous, the server will provide advice such as "Try relaxing and taking a breather."

[1245] Step 11:

[1246] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[1247] Step 12:

[1248] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[1249] Example 2

[1250] 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."

[1251] Conventional singing practice systems have difficulty accurately assessing a user's singing ability when practicing independently at home, and they lack the feedback needed to maintain motivation. This makes it difficult to effectively improve singing ability and provide an optimal practice plan for each user. Furthermore, since feedback does not take emotions into account, it is difficult to respond to fluctuations in performance due to the user's psychological state. Therefore, a new system for improving singing ability and maintaining motivation is needed.

[1252] 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.

[1253] In this invention, the server includes means for capturing a user's voice, means for analyzing the captured voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for recognizing the user's emotions and providing feedback or advice based on the emotions, and means for tracking the user's progress and recording achieved milestones, thereby enabling users to efficiently and effectively improve their singing ability at home and receive appropriate feedback to maintain their motivation.

[1254] "User" refers to an individual who uses the system to practice singing.

[1255] "Voice acquisition means" refers to a device or function for recording the user's voice and inputting it into the system.

[1256] "Audio analysis means" refers to software or algorithms used to analyze acquired audio data and evaluate singing characteristics such as pitch and amplitude.

[1257] "Customized practice plan generation means" refers to a device or function that creates an individually tailored practice menu based on the user's singing ability evaluation and goals.

[1258] The "real-time voice analysis means" refers to a function for instantly analyzing voice data when a user sings in real time.

[1259] "Feedback providing means" refers to a device or function that provides advice or guidance to the user in real time or at a later time based on the results of voice analysis.

[1260] "Emotion recognition means" refers to a device or software that identifies and analyzes the user's current emotions from their facial expressions and tone of voice.

[1261] "Emotion-based feedback means" refers to a function for providing appropriate advice and support to users based on emotion recognition results.

[1262] "Progress Tracking Measures" refers to devices or software that store a user's practice records and continuously track milestone achievements.

[1263] "Milestone recording means" refers to a function that allows a user to record important goals and achievements achieved during practice.

[1264] "Progress data storage means" refers to a device or function that accumulates data about a user's practice and stores it for future reference and analysis.

[1265] The "means for providing a practice menu for improving skills" refers to a function for providing a specific practice menu for the user to improve a specific singing skill based on the analyzed voice data.

[1266] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[1267] System Overview

[1268] To use the system, users enter basic information (such as their name, current singing ability, and goals). This information is used to personalize the system. The user uploads an audio file of their singing, and the audio data is analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation and goals.

[1269] Analysis of audio data

[1270] The user records their singing as an audio file and uploads it to the device. The device receives the audio file and saves it in a specified directory. A dedicated library such as Librosa is used to analyze the saved audio file. The server reads and analyzes the audio file, extracting pitch (height) and amplitude characteristics from the audio data. The average pitch value and stability are then calculated to evaluate the user's current singing ability.

[1271] Generate a customized practice plan

[1272] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[1273] Emotional Recognition and Feedback

[1274] The user sings in real time and the device captures the audio. When the device captures the live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and vocal tone. The server analyzes the audio and emotional data in real time. The system provides the user with immediate feedback, including pitch accuracy, sense of rhythm, and vocal accuracy, as well as advice based on the user's emotions.

[1275] Progress Tracking and Data Storage

[1276] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[1277] Specific examples

[1278] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[1279] 1. User B enters basic information (name, current pitch, goal, etc.) when logging in for the first time.

[1280] 2. User B uploads the audio file of his singing.

[1281] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[1282] 4. User B's target pitch is set to 300.

[1283] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1284] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[1285] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B. For example, it may provide advice such as "Try to relax and take a deep breath."

[1286] 8. User B's progress is recorded and goal achievement is tracked periodically. All data is saved so User B can review it later.

[1287] Prompt Sentence Examples

[1288] "Analyzes audio files sung by users, extracts pitch and amplitude characteristics, and evaluates the user's singing ability."

[1289] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1290] Step 1:

[1291] User

[1292] When a user logs in for the first time, they enter basic information such as their name, current singing ability, and goals. This data is used to personalize the system. The information is sent to the server and saved as a user profile.

[1293] Input: Basic information such as name, current singing ability, goals, etc.

[1294] Output: User profile (e.g., JSON format)

[1295] Step 2:

[1296] User

[1297] Users record themselves singing and upload the audio file to the system, preferably in MP3 or WAV format.

[1298] Input: Recorded audio file

[1299] Output: Uploaded audio file

[1300] Step 3:

[1301] Terminal

[1302] The device receives the audio file uploaded by the user and saves it in the specified directory. At this time, it checks the integrity of the file and returns an error message if the file is incomplete.

[1303] Input: Uploaded audio file

[1304] Output: Saved audio file

[1305] Step 4:

[1306] server

[1307] The server reads the saved audio file and analyzes the audio data using a dedicated library such as Librosa. The analysis items include pitch (height) and amplitude (strength). The average pitch and stability are calculated to evaluate the user's singing ability.

[1308] Input: Saved audio file

[1309] Output: Singing ability evaluation results (average pitch, amplitude, stability, etc.)

[1310] Step 5:

[1311] server

[1312] The server compares the user's singing ability assessment results with pre-set goals. Based on the results, it identifies necessary practice items and generates a customized practice plan, suggesting, for example, how to extend the high range, control vibrato, and vocal techniques.

[1313] Input: Singing ability assessment results, user goals

[1314] Output: Customized practice plan

[1315] Step 6:

[1316] User

[1317] The user sings in real time and the device captures the voice.

[1318] Input: Real-time singing voice

[1319] Output: Captured live audio

[1320] Step 7:

[1321] Terminal

[1322] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice, and emotional data is also acquired at the same time.

[1323] Input: Live captured audio, facial expression data

[1324] Output: Emotion data

[1325] Step 8:

[1326] server

[1327] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user, such as feedback on pitch accuracy and rhythm, along with emotion-based advice, such as "Try relaxing and taking a deep breath."

[1328] Input: Real-time voice data, emotion data

[1329] Output: Feedback (advice based on pitch accuracy, rhythm, and emotion)

[1330] Step 9:

[1331] server

[1332] The server records the user's practice progress and reports achieved milestones. The progress data is stored in JSON format for the user to refer to later.

[1333] Input: Practice progress information

[1334] Output: Progress data (JSON format) and milestones achieved

[1335] The above is the specific processing flow of this program.

[1336] (Application example 2)

[1337] 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."

[1338] Currently, there is a lack of effective systems for managing the stress and improving the skills of robot operators in factories. Conventional methods make it difficult to accurately grasp the emotional state of operators, which often results in delayed response when stress accumulates. Furthermore, training plans for skill improvement are difficult to individually optimize, and feedback tailored to each operator's skills and emotions is not provided. Therefore, a system that can more efficiently manage stress for robot operators and improve their skills is needed.

[1339] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the user's voice, means for analyzing the acquired voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for analyzing the user's facial expressions and recognizing emotions, and means for customizing practice plans and feedback based on the user's voice and emotional data. This makes it possible to grasp the operator's stress level in real time and provide feedback accordingly. Furthermore, by providing a customized practice plan based on each operator's skill improvement, efficient skill improvement is possible.

[1340] The "means for acquiring user's voice" is a device or software for capturing the voice uttered by the robot operator and storing it as digital data.

[1341] "Means for analyzing the captured audio and assessing the user's current singing ability" refers to software or algorithms that analyze the captured audio data and assess the operator's skill level and stress level based on the content of the data.

[1342] "Means for generating a customized practice plan based on the user's goals" refers to software or a system for creating optimal practice menus and tasks according to the goals set by the operator.

[1343] "Means for analyzing the user's voice in real time and providing feedback" refers to a device or software that analyzes the operator's voice in real time and immediately provides suggestions for improvement or advice based on the results.

[1344] "Means for tracking user progress and recording achieved milestones" refers to a system for tracking the progress of operators' practice and work, and recording data on goals and milestones achieved.

[1345] "Means for analyzing the user's facial expressions and recognizing emotions" refers to software or algorithms that use a camera to capture the operator's facial expressions and identify emotions using image analysis technology.

[1346] "Means for customizing practice plans and feedback based on the user's voice and emotional data" refers to a system that creates and provides practice plans and feedback optimized for each operator based on acquired and analyzed voice and emotional data.

[1347] System Overview

[1348] The system is designed to help manage stress and improve the skills of robot operators in factories. Its main components include voice data acquisition and analysis, facial expression analysis, real-time feedback, and progress management. The system combines hardware such as a head-mounted display (HMD) and webcam with software such as OpenCV, librosa, and Keras.

[1349] Acquisition and analysis of audio data

[1350] User

[1351] The robot operator inputs voice using a microphone built into the head-mounted display (HMD), which allows voice data to be acquired in real time during operation.

[1352] Terminal

[1353] The device saves the captured voice data, which is then analyzed using a voice analysis library such as librosa to extract features for evaluating the user's skill level and stress level.

[1354] server

[1355] The server analyzes the audio data to assess the operator's skill level and stress level, using functions to extract pitch and amplitude characteristics, and generates a customized practice plan based on the analysis results.

[1356] Facial Expression Analysis and Emotion Recognition

[1357] User

[1358] The robot operator captures facial expressions using a camera built into the head-mounted display.

[1359] Terminal

[1360] The device recognizes emotions from captured facial expression data. It uses OpenCV to detect faces and inputs them into an emotion recognition model built with Keras to analyze the operator's emotional state in real time.

[1361] server

[1362] The server generates feedback based on the analyzed voice and emotional data, providing advice and suggestions for improvement in real time according to the operator's emotional state.

[1363] Tracking progress and providing feedback

[1364] server

[1365] The server tracks the operators' progress and records the milestones they achieve, allowing them to visually confirm their progress in improving their skills and managing stress. The progress data is saved in JSON format or similar for future reference and analysis.

[1366] Specific examples

[1367] For example, when Robot Operator A uses the system, the process goes through the following steps:

[1368] 1. Operator A puts on the head-mounted display and begins capturing voice and facial expressions.

[1369] 2. The audio data acquired by the device is analyzed using librosa, and features such as pitch and amplitude are extracted.

[1370] 3. Based on the analysis results, the server evaluates Operator A's current skill level and stress state.

[1371] 4. At the same time, the device analyzes the facial expression data captured by the camera using OpenCV and Keras to recognize the emotional state.

[1372] 5. The server generates real-time feedback based on the voice and emotion data. For example, if Operator A is nervous, the server will provide advice such as "Relax."

[1373] 6. The server records Operator A's progress data so that it can be reviewed later.

[1374] Example prompts to input to a generative AI model:

[1375] "Operator A's audio and video analysis has confirmed that he has a high stress level. Please generate feedback and a training plan based on his emotional state."

[1376] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1377] Step 1:

[1378] The user puts on the head-mounted display and starts capturing voice. The user's voice is picked up by a microphone and saved as digital data. This digital data becomes the input data for voice analysis.

[1379] Step 2:

[1380] The voice data acquired by the device is read using the librosa library. Using librosa, features such as pitch and amplitude characteristics are extracted from the voice data. These features become the output data for voice analysis.

[1381] Step 3:

[1382] The server receives the features of the voice data sent from the device and evaluates the operator's skill level and stress level. The evaluation results become the input data for generating a practice plan.

[1383] Step 4:

[1384] The user captures their facial expressions using a camera built into the head-mounted display, and this video data becomes the input data for emotion recognition.

[1385] Step 5:

[1386] The facial expression data captured by the device is analyzed using OpenCV to detect the face. The detected facial features are input into a Keras emotion recognition model to recognize the user's emotional state. The emotion recognition results are used as input data for generating feedback.

[1387] Step 6:

[1388] The server integrates the results of the voice data evaluation and emotion recognition, and generates appropriate feedback in real time, which is then presented to the user.

[1389] Step 7:

[1390] The server tracks user progress and records milestones achieved, and this progress data is stored in a format such as JSON for future reference and analysis.

[1391] Step 8:

[1392] The server uses a generative AI model to generate prompts based on the input data and presents them to the user, providing feedback and practice plans according to their emotional state.These prompts allow users to visualize their progress.

[1393] 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.

[1394] 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.

[1395] 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.

[1396] [Fourth embodiment]

[1397] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1398] 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.

[1399] 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).

[1400] 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.

[1401] 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.

[1402] 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).

[1403] 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. 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.

[1404] 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.

[1405] 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.

[1406] 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.

[1407] 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.

[1408] 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.

[1409] 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."

[1410] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[1411] System Overview

[1412] To use the system, users first enter basic information (such as their name and current singing ability). They then upload an audio file of their actual singing, and the system analyzes that audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[1413] Analysis of audio data

[1414] User

[1415] The user records their singing as an audio file and uploads it to the device.

[1416] Terminal

[1417] The device receives and saves the uploaded audio file, and uses a dedicated library (such as librosa) to analyze the saved audio file.

[1418] server

[1419] The server reads the audio file and analyzes it. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value, etc. This allows the user's current singing ability to be evaluated.

[1420] Generate a customized practice plan

[1421] server

[1422] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[1423] Providing real-time feedback

[1424] User

[1425] The user sings in real time and inputs the voice into the terminal.

[1426] Terminal

[1427] The device captures live audio and processes it in real time.

[1428] server

[1429] The server analyzes the voice data in real time and provides immediate feedback to the user, including information on pitch stability and vocal accuracy.

[1430] Progress Tracking and Data Storage

[1431] server

[1432] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[1433] Specific examples

[1434] For example, if User A wants to improve his singing ability, he uses the system as follows:

[1435] 1. When User A logs in for the first time, basic information (name, current pitch) is entered.

[1436] 2. User A uploads the audio file of his singing.

[1437] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[1438] 4. User A's target pitch is set to 350.

[1439] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1440] 6. User A sings in real time and the server provides real-time feedback.

[1441] 7. User A's progress is recorded and goal achievement is tracked periodically.

[1442] 8. All data is saved and User A can look back on it later.

[1443] The above is an embodiment of this system.

[1444] The processing flow will be explained below.

[1445] Step 1:

[1446] A user logs in to the system and enters basic information (such as name and current singing ability), which is received by the terminal and sent to the server.

[1447] Step 2:

[1448] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, etc.

[1449] Step 3:

[1450] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[1451] Step 4:

[1452] The server reads the saved audio file and analyzes the audio data using an audio analysis library (e.g., librosa). Specifically, it extracts pitch and amplitude features from the audio data.

[1453] Step 5:

[1454] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user data. For example, the average pitch and stability are used as evaluation criteria.

[1455] Step 6:

[1456] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[1457] Step 7:

[1458] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[1459] Step 8:

[1460] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[1461] Step 9:

[1462] The server analyzes the audio data in real time and provides immediate feedback to the user, including pitch accuracy and rhythmic stability.

[1463] Step 10:

[1464] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[1465] Step 11:

[1466] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[1467] Example 1

[1468] 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."

[1469] Conventional voice training systems have difficulty providing appropriate feedback and practice plans tailored to each user's individual singing ability, making effective training difficult. Furthermore, there are insufficient methods for tracking a user's progress in detail and visually confirming their achievement. As a result, many users are unable to receive effective instruction to improve their singing ability, making it difficult for them to maintain their motivation.

[1470] 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.

[1471] In this invention, the server includes means for extracting pitch and amplitude characteristics from the user's voice data and evaluating the user's current ability based on the analysis results, means for generating a customized practice plan based on the user's goals, and means for analyzing the user's voice in real time and providing feedback. This allows the user to receive feedback tailored to their own characteristics in real time and implement an effective singing practice plan. Furthermore, detailed tracking of the user's progress and visual confirmation of achievement level are expected to maintain ongoing motivation.

[1472] "Audio data" refers to data in which the voice of a user is recorded in digital format.

[1473] "Analysis" is the process of extracting certain characteristics (such as pitch or amplitude) from audio data and using that data to evaluate the user's singing ability.

[1474] A "customized practice plan" refers to a practice menu that is individually optimized based on the user's current singing ability and goals.

[1475] "Real-time feedback" is a function that instantly provides analysis results and suggests necessary advice and corrections while the user is singing.

[1476] "Progress tracking" is the process of recording a user's practice and milestones achieved so that they can be reviewed later.

[1477] "Pitch" is a characteristic that indicates the pitch of a sound and is determined by the frequency of the sound.

[1478] "Amplitude" is a characteristic that indicates the height of waves in sound, and affects the loudness and intensity of the sound.

[1479] "Feature extraction" is the process of extracting important characteristics, such as pitch and amplitude, from audio data.

[1480] "Degree of achievement" is an index that indicates how much progress has been made toward the goal set by the user.

[1481] "Milestones" mark important milestones in the development of a user's practice.

[1482] This invention is a system that provides an AI voice analysis tool and a virtual voice training service to help users improve their singing ability at home. It has various functions to support users' singing practice and maintain their motivation. Specific embodiments of this system are described below.

[1483] System Overview

[1484] When a user uses the system, they first enter basic information (such as their name and current singing ability). Next, they upload an audio file of their actual singing, and the system analyzes the audio data to evaluate the user's current singing ability. Based on the evaluation results, a customized practice plan is generated to match the user's goals.

[1485] Hardware and software used

[1486] Terminal

[1487] The terminal is a device that receives and stores the user's voice files, and includes PCs, smartphones, etc. A dedicated library (such as librosa) is used for voice analysis.

[1488] server

[1489] The server is a central computer that reads and analyzes the audio data. Specifically, the server extracts pitch and amplitude characteristics from the audio data and evaluates the user's current singing ability. A computer with a high-performance CPU and GPU is recommended to process data in real time as needed.

[1490] Analysis of audio data

[1491] When a user records themselves singing and uploads the audio file, the device receives the file and sends it to the server. The server analyzes the audio file and calculates the average pitch and amplitude fluctuations to evaluate the user's current singing ability. This process uses a voice analysis library such as librosa.

[1492] Generate a customized practice plan

[1493] The server compares the analysis results with the user's set goals, and based on the differences, identifies the necessary practice items and generates a customized practice plan. For example, if the user's goals are to improve their high-pitched notes or vibrato control, a training menu specifically tailored to those areas will be generated.

[1494] Providing real-time feedback

[1495] When a user sings in real time and inputs the voice into the device, the device captures the live voice and transmits it to the server in real time. The server immediately analyzes the voice and provides feedback to the user, such as pitch stability and vocal accuracy.

[1496] Progress Tracking and Data Storage

[1497] The server records the user's practice progress and saves the achieved milestones in a database. The progress data is saved in JSON format for future reference and analysis, allowing users to visually confirm their own progress.

[1498] Examples of concrete examples and prompts

[1499] For example, when User A logs in for the first time, he or she enters his or her name and current pitch (250). When User A uploads an audio file of his or her singing, the server analyzes the audio file and calculates the current pitch (for example, 250). If User A's target pitch is 350, the server generates a high-pitched practice plan and provides it to User A. When singing in real time, the server provides instant feedback and records progress.

[1500] An example prompt using a generative AI model is, "Analyze the user's uploaded audio file, calculate the average pitch, and generate a customized practice plan. Also, provide real-time feedback."

[1501] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1502] Step 1: Initial Registration

[1503] User

[1504] A user logs into the system for the first time and enters their name and current singing ability (e.g., current pitch value).

[1505] Terminal

[1506] The terminal receives basic information entered by the user and transmits the data to the server.

[1507] server

[1508] The server stores the received user information in a database and creates a user profile.

[1509] Input: User's basic information (name, current pitch value)

[1510] Output: Creates a user profile and saves it to the database.

[1511] Step 2: Upload your audio file

[1512] User

[1513] The user records their singing and uploads the audio file to the device.

[1514] Terminal

[1515] The device receives the uploaded audio file, temporarily stores it, and then sends it to the server using a file transfer protocol.

[1516] server

[1517] The server retrieves the audio file uploaded from the terminal and stores it in a database.

[1518] Input: Recorded audio file

[1519] Output: Audio file saved on the server

[1520] Step 3: Analyzing the audio data

[1521] server

[1522] The server reads the saved audio file and analyzes it using an audio analysis library such as librosa. It extracts pitch and amplitude characteristics from the audio data and calculates the average pitch and amplitude fluctuations. The analysis results are stored in a database and the user's current singing ability is evaluated.

[1523] Input: Saved audio file

[1524] Output: Analysis results (average pitch, amplitude fluctuation), saved to database

[1525] Step 4: Generate a customized practice plan

[1526] server

[1527] The server compares the analysis results with the user's set goals and identifies the necessary practice areas based on the difference. It then generates a customized practice plan and provides it to the user. For example, it can include how to practice high notes and how to control vibrato to reach the target pitch.

[1528] Input: Analysis results, user goals

[1529] Output: Customized practice plan

[1530] Step 5: Provide real-time feedback

[1531] User

[1532] The user sings in real time and inputs the voice into the terminal.

[1533] Terminal

[1534] The terminal captures the input voice in real time and transmits the real-time voice data to the server.

[1535] server

[1536] The server instantly analyzes the received real-time voice data and generates feedback, which is then sent to the user in real time (e.g., pitch stability, pronunciation accuracy, etc.).

[1537] Input: Real-time audio data

[1538] Output: Real-time feedback

[1539] Step 6: Progress Tracking and Data Storage

[1540] server

[1541] The server records the user's practice progress and saves the achieved milestones in a database. The saved progress data is managed in JSON format or similar and is used for future reference and analysis. Progress reports are generated and sent to the user periodically.

[1542] Input: User's practice data, achieved milestones

[1543] Output: Progress data (JSON format), progress report

[1544] (Application example 1)

[1545] 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."

[1546] Previous systems for improving singing ability struggled to provide personalized practice plans and were unable to track users' progress in real time. Furthermore, analyzing users' own voice data and providing specific feedback required advanced expertise. Therefore, there was a need for a system that would allow users to easily improve their singing ability at home.

[1547] 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.

[1548] In this invention, the server includes means for acquiring a user's voice, means for analyzing the acquired voice and assessing the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for processing the singing data based on the user's input and providing the generated practice plan, and means for analyzing the user's voice data to extract pitch and amplitude characteristics, thereby enabling a user to receive a personalized practice plan to improve their singing ability from the convenience of their own home, with real-time feedback and progress tracking.

[1549] definition statement

[1550] The "means for acquiring the user's voice" refers to a device or system for recording or inputting the voice sung by the user.

[1551] The "means for analyzing the captured voice and evaluating the user's current singing ability" is an algorithm or program for analyzing the recorded voice and quantifying or evaluating the singing ability.

[1552] The "means for generating a customized exercise plan based on the user's goals" is a program or system for creating an individual exercise plan according to the goals set by the user.

[1553] The "means for analyzing the user's voice in real time and providing feedback" is a system for analyzing voice data in real time and providing immediate feedback based on the results.

[1554] A "means for tracking a user's progress and recording achieved milestones" is a system for continuously monitoring a user's practice progress and recording goals and significant milestones achieved.

[1555] "Means for processing singing data based on user input and providing a generated practice plan" refers to a system that processes audio data based on information entered by the user and provides a customized practice plan.

[1556] The "means for analyzing the user's voice data to extract pitch and amplitude characteristics" refers to an algorithm or program for extracting characteristics such as pitch and intensity from the user's recorded voice data.

[1557] "Means for storing user progress data and storing it in a format that can be used for future reference and analysis" refers to a system that stores a user's practice progress and stores it in a format that can be used for future analysis and feedback.

[1558] The "means for inputting prompt sentences into a generative AI model and obtaining a customized practice plan" refers to a system for inputting instructions or questions into a generative AI model and automatically generating an individual practice plan based on the input.

[1559] MODE FOR CARRYING OUT THE INVENTION

[1560] This invention is a system that provides an AI voice analysis tool and virtual voice training service for individuals who wish to improve their singing ability. The system includes a function to support users in practicing singing at home and ensure sustained motivation.

[1561] System Overview

[1562] To use the system, users enter basic information (such as their name and current singing ability). By uploading an audio file of the user's actual singing, the server analyzes the audio data and evaluates the user's current singing ability. Based on the evaluation results, a customized practice plan tailored to the user's goals is generated.

[1563] Analysis of audio data

[1564] User

[1565] Users record their own singing as an audio file and upload it via their smartphone or other device.

[1566] Terminal

[1567] The device receives the uploaded audio file and sends the data to a server, where it uses a dedicated library such as librosa for analysis.

[1568] server

[1569] The server receives and analyzes the voice data. Specifically, it extracts pitch and amplitude characteristics from the voice data, calculates the average pitch, and evaluates the user's singing ability.

[1570] Generate a customized practice plan

[1571] server

[1572] The server compares the user's singing ability assessment results with the set goals, and based on the results, identifies necessary practice items and generates a customized practice plan, including exercises on how to extend high notes, vibrato control, and vocal technique.

[1573] Providing real-time feedback

[1574] User

[1575] The user sings in real time and inputs the singing voice into the terminal.

[1576] Terminal

[1577] The device captures live audio and immediately transmits it to the server.

[1578] server

[1579] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[1580] Progress Tracking and Data Storage

[1581] server

[1582] The server records the user's progress and saves the milestones they achieve, allowing them to visually see their growth. Progress data is saved in a format such as JSON for future reference and analysis.

[1583] Specific examples

[1584] For example, if User A wants to improve his singing ability and uses this system:

[1585] 1. User A enters basic information (name, current pitch) when logging in for the first time.

[1586] 2. User A uploads the audio file of his singing.

[1587] 3. The server analyzes the audio file and calculates the current pitch (e.g., 250).

[1588] 4. User A's target pitch is set to 350.

[1589] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1590] 6. User A sings in real time and the server provides real-time feedback.

[1591] 7. User A's progress is recorded and goal achievement is tracked periodically.

[1592] 8. All data is saved and User A can look back on it later.

[1593] Example prompt for a generative AI model:

[1594] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[1595] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1596] Detailed explanation of the processing steps

[1597] Step 1:

[1598] The user logs in to the system for the first time and enters basic information (such as name, current singing ability, etc.), which is then stored in the database.

[1599] Input: User's basic information (name, current singing ability, etc.)

[1600] Output: User information stored in the database

[1601] Step 2:

[1602] Users record themselves singing and upload the audio file to their device.

[1603] Input: Recorded audio file\

[1604] Output: Audio file uploaded to device

[1605] Step 3:

[1606] The device receives the uploaded audio file and sends the data to the server.

[1607] Input: Uploaded audio file

[1608] Output: Audio data sent to the server

[1609] Step 4:

[1610] The server analyzes the received audio data using the librosa library and extracts pitch and amplitude characteristics from the audio data.

[1611] Input: Audio data sent to the server\

[1612] Output: Extracted pitch and amplitude characteristics data

[1613] Specific operation: Analyzes audio data using the librosa library and quantifies pitch and amplitude

[1614] Step 5:

[1615] The server evaluates the user's current singing ability based on the extracted characteristic data.

[1616] Input: Extracted pitch and amplitude characteristics data

[1617] Output: User's singing ability evaluation result

[1618] Specific operation: Calculate the average pitch and generate the evaluation result

[1619] Step 6:

[1620] The server compares the user's goals with the evaluation results and generates a customized practice plan, such as how to extend the high notes or control vibrato.

[1621] Input: User's goal, singing ability evaluation results

[1622] Output: Customized practice plan

[1623] Specific actions: Identify necessary practice items based on goals and assessment results and create a plan

[1624] Step 7:

[1625] The user sings in real time and inputs the live audio into the device.

[1626] Input: Live Audio

[1627] Output: Live audio input to the device

[1628] Step 8:

[1629] The device captures live audio and instantly transmits it to the server.

[1630] Input: Live audio input into the device

[1631] Output: Live audio data sent to the server

[1632] Step 9:

[1633] The server analyzes the voice data in real time and provides immediate feedback, such as pitch stability and vocal accuracy.

[1634] Input: Live audio data sent to the server

[1635] Output: Real-time feedback

[1636] What it does: Analyzes live audio and generates feedback using the librosa library

[1637] Step 10:

[1638] The server tracks the user's progress and records milestones achieved. Progress data is stored in a format that can be used for future reference and analysis.

[1639] Input: User practice data and progress

[1640] Output: Saved progress data and milestones\

[1641] Specific operation: Save data in JSON format etc. and update tracking information

[1642] Example of a generated prompt statement

[1643] The prompt to the generative AI model is:

[1644] "Generate code for an application that analyzes user-recorded audio data, evaluates singing ability, and provides a customized practice plan based on the results. Also incorporate progress tracking functionality."

[1645] 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.

[1646] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[1647] System Overview

[1648] To use the system, users enter basic information (such as their name, current singing ability, and goals). They then upload an audio file of their singing, which is then analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation results and the user's goals. The system also incorporates an emotion engine that recognizes the user's emotions, providing feedback and advice based on the user's emotions.

[1649] Analysis of audio data

[1650] User

[1651] The user records their singing as an audio file and uploads it to the device.

[1652] Terminal

[1653] The device receives this audio file and saves it in the specified directory. A dedicated library (such as librosa) is used to analyze the saved audio file.

[1654] server

[1655] The server reads and analyzes the audio file. Specifically, it extracts pitch (height) and amplitude characteristics from the audio data and calculates the average pitch value and stability. This evaluates the user's current singing ability.

[1656] Generate a customized practice plan

[1657] server

[1658] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[1659] Emotional Recognition and Feedback

[1660] User

[1661] The user sings in real time, and the device captures the audio, which is then saved as a temporary file.

[1662] Terminal

[1663] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice.

[1664] server

[1665] The server analyzes the voice data and emotional data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythm, and vocal accuracy, as well as advice based on the user's emotions. For example, if the user is nervous, the system will provide advice such as "Try relaxing and taking a breather."

[1666] Progress Tracking and Data Storage

[1667] server

[1668] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[1669] Specific examples

[1670] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[1671] 1. When User B logs in for the first time, basic information (name, current pitch, goal, etc.) is entered.

[1672] 2. User B uploads the audio file of his singing.

[1673] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[1674] 4. User B's target pitch is set to 300.

[1675] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1676] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[1677] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B.

[1678] 8. User B's progress is recorded and goal achievement is tracked periodically.

[1679] 9. All data is saved and User B can look back on it later.

[1680] The above is an embodiment of this system.

[1681] The processing flow will be explained below.

[1682] Step 1:

[1683] A user logs in to the system and enters basic information (such as name, current singing ability, goals, etc.). The terminal receives this information and sends it to the server.

[1684] Step 2:

[1685] The server receives the user's basic information and initializes the user data, which includes the user's name, current singing ability, goals, progress record, and emotional information.

[1686] Step 3:

[1687] The user uploads the singing audio file to the device, which receives the audio file and saves it in the specified directory.

[1688] Step 4:

[1689] The server reads the saved audio file and analyzes the audio data using an audio analysis library. Specifically, it extracts pitch and amplitude features from the audio data and calculates the average pitch value and stability.

[1690] Step 5:

[1691] The server evaluates the user's current singing ability based on the analysis results and records the evaluation results in the user's data, including average pitch, sense of rhythm, and vocal accuracy.

[1692] Step 6:

[1693] The server identifies the user's goals (e.g., expanding the high range, introducing vibrato, improving vocal technique) based on user data and compares them with the user's current abilities.

[1694] Step 7:

[1695] The server then generates a customized practice plan based on the comparison results, including specific exercises (e.g., high-pitched notes, vibrato, vocalization).

[1696] Step 8:

[1697] The user sings in real time, and the device captures their voice and facial expressions. The captured voice data is saved as a temporary file, and the facial expression data is processed for emotion recognition.

[1698] Step 9:

[1699] The device analyzes the user's facial expressions and voice tone to activate the emotion engine, which identifies the user's emotional state (e.g., tension, relaxation, joy, sadness).

[1700] Step 10:

[1701] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user. The feedback includes pitch accuracy, rhythmic stability, and vocal accuracy, as well as emotional advice. For example, if the user is nervous, the server will provide advice such as "Try relaxing and taking a breather."

[1702] Step 11:

[1703] The server tracks the user's practice progress and records each milestone, and the progress achieved is stored in the user's data, allowing the user to view their own progress.

[1704] Step 12:

[1705] The server stores all progress data and practice history in formats such as JSON for future analysis and reference.

[1706] Example 2

[1707] 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."

[1708] Conventional singing practice systems have difficulty accurately assessing a user's singing ability when practicing independently at home, and they lack the feedback needed to maintain motivation. This makes it difficult to effectively improve singing ability and provide an optimal practice plan for each user. Furthermore, since feedback does not take emotions into account, it is difficult to respond to fluctuations in performance due to the user's psychological state. Therefore, a new system for improving singing ability and maintaining motivation is needed.

[1709] 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.

[1710] In this invention, the server includes means for capturing a user's voice, means for analyzing the captured voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for recognizing the user's emotions and providing feedback or advice based on the emotions, and means for tracking the user's progress and recording achieved milestones, thereby enabling users to efficiently and effectively improve their singing ability at home and receive appropriate feedback to maintain their motivation.

[1711] "User" refers to an individual who uses the system to practice singing.

[1712] "Voice acquisition means" refers to a device or function for recording the user's voice and inputting it into the system.

[1713] "Audio analysis means" refers to software or algorithms used to analyze acquired audio data and evaluate singing characteristics such as pitch and amplitude.

[1714] "Customized practice plan generation means" refers to a device or function that creates an individually tailored practice menu based on the user's singing ability evaluation and goals.

[1715] The "real-time voice analysis means" refers to a function for instantly analyzing voice data when a user sings in real time.

[1716] "Feedback providing means" refers to a device or function that provides advice or guidance to the user in real time or at a later time based on the results of voice analysis.

[1717] "Emotion recognition means" refers to a device or software that identifies and analyzes the user's current emotions from their facial expressions and tone of voice.

[1718] "Emotion-based feedback means" refers to a function for providing appropriate advice and support to users based on emotion recognition results.

[1719] "Progress Tracking Measures" refers to devices or software that store a user's practice records and continuously track milestone achievements.

[1720] "Milestone recording means" refers to a function that allows a user to record important goals and achievements achieved during practice.

[1721] "Progress data storage means" refers to a device or function that accumulates data about a user's practice and stores it for future reference and analysis.

[1722] The "means for providing a practice menu for improving skills" refers to a function for providing a specific practice menu for the user to improve a specific singing skill based on the analyzed voice data.

[1723] This invention is a system that provides a virtual voice training service that combines an AI voice analysis tool and an emotion engine for individuals who want to improve their singing ability. It includes functions to support users' singing practice at home and keep them motivated.

[1724] System Overview

[1725] To use the system, users enter basic information (such as their name, current singing ability, and goals). This information is used to personalize the system. The user uploads an audio file of their singing, and the audio data is analyzed to evaluate the user's current singing ability. A customized practice plan is then generated based on the evaluation and goals.

[1726] Analysis of audio data

[1727] The user records their singing as an audio file and uploads it to the device. The device receives the audio file and saves it in a specified directory. A dedicated library such as Librosa is used to analyze the saved audio file. The server reads and analyzes the audio file, extracting pitch (height) and amplitude characteristics from the audio data. The average pitch value and stability are then calculated to evaluate the user's current singing ability.

[1728] Generate a customized practice plan

[1729] The server compares the user's singing ability assessment results with pre-set goals, and based on the results, identifies necessary practice items and generates a customized practice menu, including how to extend high notes, vibrato control, and vocal technique.

[1730] Emotional Recognition and Feedback

[1731] The user sings in real time and the device captures the audio. When the device captures the live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and vocal tone. The server analyzes the audio and emotional data in real time. The system provides the user with immediate feedback, including pitch accuracy, sense of rhythm, and vocal accuracy, as well as advice based on the user's emotions.

[1732] Progress Tracking and Data Storage

[1733] The server records the user's practice progress and saves the milestones achieved, allowing the user to visually confirm their own growth. Progress data is saved in JSON format or similar for future reference and analysis.

[1734] Specific examples

[1735] For example, if User B wants to improve his singing ability and motivation, he will use the system as follows:

[1736] 1. User B enters basic information (name, current pitch, goal, etc.) when logging in for the first time.

[1737] 2. User B uploads the audio file of his singing.

[1738] 3. The server analyzes the audio file and calculates the current pitch (e.g., 200).

[1739] 4. User B's target pitch is set to 300.

[1740] 5. The server generates a customized practice plan, recommending high-pitched practice.

[1741] 6. User B sings in real time, and the device recognizes emotions from live voice and facial expressions.

[1742] 7. The server analyzes the voice and emotion data in real time and provides emotion-based feedback to User B. For example, it may provide advice such as "Try to relax and take a deep breath."

[1743] 8. User B's progress is recorded and goal achievement is tracked periodically. All data is saved so User B can review it later.

[1744] Prompt Sentence Examples

[1745] "Analyzes audio files sung by users, extracts pitch and amplitude characteristics, and evaluates the user's singing ability."

[1746] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1747] Step 1:

[1748] User

[1749] When a user logs in for the first time, they enter basic information such as their name, current singing ability, and goals. This data is used to personalize the system. The information is sent to the server and saved as a user profile.

[1750] Input: Basic information such as name, current singing ability, goals, etc.

[1751] Output: User profile (e.g., JSON format)

[1752] Step 2:

[1753] User

[1754] Users record themselves singing and upload the audio file to the system, preferably in MP3 or WAV format.

[1755] Input: Recorded audio file

[1756] Output: Uploaded audio file

[1757] Step 3:

[1758] Terminal

[1759] The device receives the audio file uploaded by the user and saves it in the specified directory. At this time, it checks the integrity of the file and returns an error message if the file is incomplete.

[1760] Input: Uploaded audio file

[1761] Output: Saved audio file

[1762] Step 4:

[1763] server

[1764] The server reads the saved audio file and analyzes the audio data using a dedicated library such as Librosa. The analysis items include pitch (height) and amplitude (strength). The average pitch and stability are calculated to evaluate the user's singing ability.

[1765] Input: Saved audio file

[1766] Output: Singing ability evaluation results (average pitch, amplitude, stability, etc.)

[1767] Step 5:

[1768] server

[1769] The server compares the user's singing ability assessment results with pre-set goals. Based on the results, it identifies necessary practice items and generates a customized practice plan, suggesting, for example, how to extend the high range, control vibrato, and vocal techniques.

[1770] Input: Singing ability assessment results, user goals

[1771] Output: Customized practice plan

[1772] Step 6:

[1773] User

[1774] The user sings in real time and the device captures the voice.

[1775] Input: Real-time singing voice

[1776] Output: Captured live audio

[1777] Step 7:

[1778] Terminal

[1779] When the device captures live audio, it activates an emotion engine that recognizes emotions from the user's facial expressions and tone of voice, and emotional data is also acquired at the same time.

[1780] Input: Live captured audio, facial expression data

[1781] Output: Emotion data

[1782] Step 8:

[1783] server

[1784] The server analyzes the voice and emotion data in real time and provides immediate feedback to the user, such as feedback on pitch accuracy and rhythm, along with emotion-based advice, such as "Try relaxing and taking a deep breath."

[1785] Input: Real-time voice data, emotion data

[1786] Output: Feedback (advice based on pitch accuracy, rhythm, and emotion)

[1787] Step 9:

[1788] server

[1789] The server records the user's practice progress and reports achieved milestones. The progress data is stored in JSON format for the user to refer to later.

[1790] Input: Practice progress information

[1791] Output: Progress data (JSON format) and milestones achieved

[1792] The above is the specific processing flow of this program.

[1793] (Application example 2)

[1794] 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."

[1795] Currently, there is a lack of effective systems for managing the stress and improving the skills of robot operators in factories. Conventional methods make it difficult to accurately grasp the emotional state of operators, which often results in delayed response when stress accumulates. Furthermore, training plans for skill improvement are difficult to individually optimize, and feedback tailored to each operator's skills and emotions is not provided. Therefore, a system that can more efficiently manage stress for robot operators and improve their skills is needed.

[1796] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring the user's voice, means for analyzing the acquired voice and evaluating the user's current singing ability, means for generating a customized practice plan based on the user's goals, means for analyzing the user's voice in real time and providing feedback, means for tracking the user's progress and recording achieved milestones, means for analyzing the user's facial expressions and recognizing emotions, and means for customizing practice plans and feedback based on the user's voice and emotional data. This makes it possible to grasp the operator's stress level in real time and provide feedback accordingly. Furthermore, by providing a customized practice plan based on each operator's skill improvement, efficient skill improvement is possible.

[1797] The "means for acquiring user's voice" is a device or software for capturing the voice uttered by the robot operator and storing it as digital data.

[1798] "Means for analyzing the captured audio and assessing the user's current singing ability" refers to software or algorithms that analyze the captured audio data and assess the operator's skill level and stress level based on the content of the data.

[1799] "Means for generating a customized practice plan based on the user's goals" refers to software or a system for creating optimal practice menus and tasks according to the goals set by the operator.

[1800] "Means for analyzing the user's voice in real time and providing feedback" refers to a device or software that analyzes the operator's voice in real time and immediately provides suggestions for improvement or advice based on the results.

[1801] "Means for tracking user progress and recording achieved milestones" refers to a system for tracking the progress of operators' practice and work, and recording data on goals and milestones achieved.

[1802] "Means for analyzing the user's facial expressions and recognizing emotions" refers to software or algorithms that use a camera to capture the operator's facial expressions and identify emotions using image analysis technology.

[1803] "Means for customizing practice plans and feedback based on the user's voice and emotional data" refers to a system that creates and provides practice plans and feedback optimized for each operator based on acquired and analyzed voice and emotional data.

[1804] System Overview

[1805] The system is designed to help manage stress and improve the skills of robot operators in factories. Its main components include voice data acquisition and analysis, facial expression analysis, real-time feedback, and progress management. The system combines hardware such as a head-mounted display (HMD) and webcam with software such as OpenCV, librosa, and Keras.

[1806] Acquisition and analysis of audio data

[1807] User

[1808] The robot operator inputs voice using a microphone built into the head-mounted display (HMD), which allows voice data to be acquired in real time during operation.

[1809] Terminal

[1810] The device saves the captured voice data, which is then analyzed using a voice analysis library such as librosa to extract features for evaluating the user's skill level and stress level.

[1811] server

[1812] The server analyzes the audio data to assess the operator's skill level and stress level, using functions to extract pitch and amplitude characteristics, and generates a customized practice plan based on the analysis results.

[1813] Facial Expression Analysis and Emotion Recognition

[1814] User

[1815] The robot operator captures facial expressions using a camera built into the head-mounted display.

[1816] Terminal

[1817] The device recognizes emotions from captured facial expression data. It uses OpenCV to detect faces and inputs them into an emotion recognition model built with Keras to analyze the operator's emotional state in real time.

[1818] server

[1819] The server generates feedback based on the analyzed voice and emotional data, providing advice and suggestions for improvement in real time according to the operator's emotional state.

[1820] Tracking progress and providing feedback

[1821] server

[1822] The server tracks the operators' progress and records the milestones they achieve, allowing them to visually confirm their progress in improving their skills and managing stress. The progress data is saved in JSON format or similar for future reference and analysis.

[1823] Specific examples

[1824] For example, when Robot Operator A uses the system, the process goes through the following steps:

[1825] 1. Operator A puts on the head-mounted display and begins capturing voice and facial expressions.

[1826] 2. The audio data acquired by the device is analyzed using librosa, and features such as pitch and amplitude are extracted.

[1827] 3. Based on the analysis results, the server evaluates Operator A's current skill level and stress state.

[1828] 4. At the same time, the device analyzes the facial expression data captured by the camera using OpenCV and Keras to recognize the emotional state.

[1829] 5. The server generates real-time feedback based on the voice and emotion data. For example, if Operator A is nervous, the server will provide advice such as "Relax."

[1830] 6. The server records Operator A's progress data so that it can be reviewed later.

[1831] Example prompts to input to a generative AI model:

[1832] "Operator A's audio and video analysis has confirmed that he has a high stress level. Please generate feedback and a training plan based on his emotional state."

[1833] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1834] Step 1:

[1835] The user puts on the head-mounted display and starts capturing voice. The user's voice is picked up by a microphone and saved as digital data. This digital data becomes the input data for voice analysis.

[1836] Step 2:

[1837] The voice data acquired by the device is read using the librosa library. Using librosa, features such as pitch and amplitude characteristics are extracted from the voice data. These features become the output data for voice analysis.

[1838] Step 3:

[1839] The server receives the features of the voice data sent from the device and evaluates the operator's skill level and stress level. The evaluation results become the input data for generating a practice plan.

[1840] Step 4:

[1841] The user captures their facial expressions using a camera built into the head-mounted display, and this video data becomes the input data for emotion recognition.

[1842] Step 5:

[1843] The facial expression data captured by the device is analyzed using OpenCV to detect the face. The detected facial features are input into a Keras emotion recognition model to recognize the user's emotional state. The emotion recognition results are used as input data for generating feedback.

[1844] Step 6:

[1845] The server integrates the results of the voice data evaluation and emotion recognition, and generates appropriate feedback in real time, which is then presented to the user.

[1846] Step 7:

[1847] The server tracks user progress and records milestones achieved, and this progress data is stored in a format such as JSON for future reference and analysis.

[1848] Step 8:

[1849] The server uses a generative AI model to generate prompts based on the input data and presents them to the user, providing feedback and practice plans according to their emotional state.These prompts allow users to visualize their progress.

[1850] 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.

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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.

[1856] 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).

[1857] 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.

[1858] 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."

[1859] 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.

[1860] 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).

[1861] 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.

[1862] 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.

[1863] 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.

[1864] 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.

[1865] 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.

[1866] 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.

[1867] 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.

[1868] 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.

[1869] 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, in order to avoid confusion and to 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.

[1870] 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.

[1871] The following is further disclosed regarding the above embodiment.

[1872] (Claim 1)

[1873] means for acquiring a user's voice;

[1874] means for analyzing the captured voice and assessing the user's current singing ability;

[1875] means for generating a customized exercise plan based on the user's goals;

[1876] a means for analyzing the user's voice in real time and providing feedback;

[1877] a means of tracking the user's progress and recording milestones achieved;

[1878] A system including:

[1879] (Claim 2)

[1880] 10. The system of claim 1, further comprising means for storing the user's progress data and storing it in a format available for future reference and analysis.

[1881] (Claim 3)

[1882] 10. The system of claim 1, further comprising means for providing a specific practice menu for improving skills such as how to extend the high range, vibrato control, and vocal technique of the user based on the analyzed voice data.

[1883] "Example 1"

[1884] (Claim 1)

[1885] means for acquiring a user's voice;

[1886] means for analyzing the captured voice and assessing the user's current singing ability;

[1887] means for generating a customized exercise plan based on the user's goals;

[1888] a means for analyzing the user's voice in real time and providing feedback;

[1889] a means of tracking the user's progress and recording milestones achieved;

[1890] A means for extracting pitch and amplitude characteristics from the user's voice data and evaluating the user's current ability based on the analysis results;

[1891] A system including:

[1892] (Claim 2)

[1893] 10. The system of claim 1, further comprising means for storing the user's progress data and storing it in a format available for future reference and analysis.

[1894] (Claim 3)

[1895] 10. The system of claim 1, further comprising means for providing a specific practice menu for improving skills such as how to extend the high range, vibrato control, and vocal technique of the user based on the analyzed voice data.

[1896] "Application Example 1"

[1897] New Claims

[1898] (Claim 1)

[1899] means for acquiring a user's voice;

[1900] means for analyzing the captured voice and assessing the user's current singing ability;

[1901] means for generating a customized exercise plan based on the user's goals;

[1902] a means for analyzing the user's voice in real time and providing feedback;

[1903] a means of tracking the user's progress and recording milestones achieved;

[1904] means for processing singing data based on user input and providing a generated practice plan;

[1905] means for analyzing a user's voice data to extract pitch and amplitude characteristics;

[1906] A system including:

[1907] (Claim 2)

[1908] a means for storing user progress data and storing it in a format that is available for future reference and analysis;

[1909] 10. The system of claim 1, further comprising means for analyzing the user's practice audio and using a generative AI model to evaluate singing ability and customize a practice plan.

[1910] (Claim 3)

[1911] A means for providing specific practice menus based on the analyzed voice data to improve skills such as how to extend the user's high range, vibrato control, and vocal technique; and

[1912] 10. The system of claim 1, further comprising means for a user to input prompt sentences to the generative AI model to obtain a customized practice plan.

[1913] "Example 2: Combining Emotion Engines"

[1914] (Claim 1)

[1915] means for acquiring a user's voice;

[1916] means for analyzing the captured voice and assessing the user's current singing ability;

[1917] means for generating a customized exercise plan based on the user's goals;

[1918] a means for analyzing the user's voice in real time and providing feedback;

[1919] a means for recognizing a user's emotions and providing feedback or advice based on the emotions;

[1920] a means of tracking the user's progress and recording milestones achieved;

[1921] A system including:

[1922] (Claim 2)

[1923] 10. The system of claim 1, further comprising means for storing the user's progress data in a format available for future reference and analysis.

[1924] (Claim 3)

[1925] The system of claim 1, further comprising means for providing a specific practice menu for improving the user's skills such as how to extend the high range, vibrato control, and vocal technique based on the analyzed voice data.

[1926] "Application example 2 when combining emotion engines"

[1927] (Claim 1)

[1928] means for acquiring a user's voice;

[1929] means for analyzing the captured voice and assessing the user's current singing ability;

[1930] means for generating a customized exercise plan based on the user's goals;

[1931] a means for analyzing the user's voice in real time and providing feedback;

[1932] a means of tracking the user's progress and recording milestones achieved;

[1933] means for analyzing a user's facial expression and recognizing emotions;

[1934] A means to customize practice plans and feedback based on the user's voice and emotional data;

[1935] A system including:

[1936] (Claim 2)

[1937] 10. The system of claim 1, further comprising means for storing the user's progress data and storing it in a format available for future reference and analysis.

[1938] (Claim 3)

[1939] 10. The system of claim 1, further comprising means for providing a specific practice menu for improving skills such as how to extend the high range, vibrato control, and vocal technique of the user based on the analyzed voice data. [Explanation of symbols]

[1940] 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 acquiring a user's voice; means for analyzing the captured voice and assessing the user's current singing ability; means for generating a customized exercise plan based on the user's goals; a means for analyzing the user's voice in real time and providing feedback; a means of tracking the user's progress and recording milestones achieved; A system including:

2. 10. The system of claim 1, further comprising means for storing user progress data and storing it in a format available for future reference and analysis.

3. The system of claim 1, further comprising means for providing a specific practice menu for improving the user's skills such as how to extend the high range, vibrato control, and vocal technique based on the analyzed voice data.

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