Pipa playing intelligent error correction system based on AI acoustic analysis
The intelligent error correction system based on AI acoustic analysis identifies and corrects pipa playing errors in real time, solving the problems of teacher shortage and lack of feedback in traditional teaching, improving learning efficiency, supporting personalized teaching, and promoting the modernization of pipa art.
Patent Information
- Application Number
- CN202511312657.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-15
- Publication Date
- 2025-11-21
AI Technical Summary
Traditional pipa teaching relies heavily on the teacher's subjective experience. With a shortage of qualified teachers and limited class time, and a lack of immediate feedback after class, learners find it difficult to identify and correct errors such as intonation deviations, unstable rhythms, and improper techniques. Incorrect playing habits are easily solidified into muscle memory, requiring a significant investment of time to correct.
Employing an AI-based intelligent error correction system, including audio acquisition, feature extraction, AI analysis, and feedback modules, it identifies and corrects performance errors in real time, providing visual and audible error correction guidance. Combined with a score alignment module, it offers learners 24/7 instant feedback and personalized practice suggestions.
It enables instant and accurate identification and correction of performance errors, preventing errors from becoming muscle memory, greatly improving practice efficiency, lowering the threshold for self-learning, providing personalized teaching support, and promoting the modern inheritance of pipa art.
Smart Images
Figure CN120998162A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The application relates to the technical field of intelligent teaching systems, in particular to an AI acoustic analysis-based intelligent error correction system for pipa playing. BACKGROUND
[0002] As one of the most representative traditional plucked string instruments in China, the pipa is known for its rich expressiveness and complex playing techniques. The process of learning the pipa is extremely long and difficult, and learners need to go through long-term and repeated practice to master accurate pitch, rhythm, and dozens of unique playing techniques such as wheel fingers, shaking fingers, and sweeping, etc. In this process, it is crucial to discover and correct errors in practice in a timely and accurate manner.
[0003] In traditional pipa teaching, learners' playing errors need to rely on professional teachers to make judgments through auditory recognition and visual observation. However, professional teacher resources are scarce and teaching time is limited, and learners often lack real-time error correction guidance during after-school independent practice. A large number of error playing habits are easily solidified, and more time cost is needed for subsequent correction. For example, when beginners practice pressing the strings, if the finger pressing position deviates from the reasonable range of the peg, and lacks real-time feedback, the learner may continue to repeat the error action, making it difficult to correct the muscle memory. Therefore, we propose an AI acoustic analysis-based intelligent error correction system for pipa playing to solve the above problems. SUMMARY
[0004] In view of the deficiencies of the prior art, the present application provides an AI acoustic analysis-based intelligent error correction system for pipa playing, which solves the problem that traditional pipa teaching is highly dependent on teachers' subjective experience, and there is a shortage of teachers, limited class hours, and a lack of immediate feedback during after-school practice. Learners are difficult to discover errors such as pitch deviation, unstable rhythm, and improper technique application on their own during unguided practice, leading to repeated reinforcement of error playing habits and the formation of stubborn muscle memory. When the errors are corrected at the next class, not only is the efficiency low, but even more time cost is required to correct them.
[0005] To achieve the above purpose, the present application realizes the following technical scheme: an AI acoustic analysis-based intelligent error correction system for pipa playing, comprising:
[0006] An audio acquisition module for real-time acquisition and preprocessing of pipa audio signals of a player;
[0007] A feature extraction module connected with the audio acquisition module for extracting time-domain and frequency-domain acoustic features related to playing errors from the preprocessed audio signals;
[0008] The AI analysis module is connected to the feature extraction module and has a pre-trained pipa playing error recognition model built into it. The AI analysis module is used to receive the acoustic features and analyze them based on the pipa playing error recognition model, and output analysis results including error type, error occurrence time and error severity.
[0009] The feedback module, connected to the AI analysis module, is used to generate and output real-time, visual, or audible error correction guidance information to the user terminal based on the analysis results.
[0010] Preferably, the acoustic features include: pitch sequence, intensity envelope, note start point, note duration, spectral centroid, and Mel frequency cepstral coefficients.
[0011] Preferably, the pipa playing error identification model in the AI analysis module is a neural network model based on deep learning, and its training data contains a large number of pipa audio samples labeled with correct and various types of incorrect playing; the error types include at least one of pitch error, rhythm error, and technique error.
[0012] Preferably, the technique errors include errors in the evenness of the tremolo, errors in the frequency and stability of the tremolo, errors in the clarity and balance of the sweeping strokes, errors in pitch caused by deviations in the position of the pressed notes, and errors in the inconsistent timbre of the plucking strokes.
[0013] Preferably, the error correction guidance information output by the feedback module includes: highlighting the error location in the form of a waveform or spectrum on the user terminal interface, describing the error type in text, providing standard performance example audio, and providing targeted practice suggestions.
[0014] Preferably, it also includes;
[0015] The music score input module is used to receive or select the target music score to practice;
[0016] The music score and audio alignment module is connected to the music score input module and the AI analysis module. It is used to perform real-time alignment and matching of the audio signal acquired by the audio acquisition module with the standard note sequence of the target music score, and to provide analysis context for the AI analysis module.
[0017] Preferably, the AI analysis module compares the extracted acoustic features with the standard expected features of the corresponding notes in the target score based on the alignment information provided by the score and audio alignment module, thereby identifying deviations and judging them as errors.
[0018] Preferably, the system is also integrated into a mobile terminal application, and the audio acquisition module is a built-in or external microphone of the mobile terminal.
[0019] The present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it realizes the function of an intelligent error correction system for pipa playing based on AI acoustic analysis.
[0020] The present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the function of an intelligent error correction system for pipa playing based on AI acoustic analysis.
[0021] Beneficial effects
[0022] This invention provides an intelligent error correction system for pipa performance based on AI acoustic analysis. Compared with existing technologies, it has the following advantages:
[0023] This AI-based intelligent error correction system for pipa performance effectively solves the core problems of scarce teacher resources and lack of real-time guidance for after-class practice in traditional pipa teaching. By simulating the teacher's auditory judgment through AI technology, it provides learners with real-time feedback around the clock, intervening immediately when errors occur to prevent incorrect playing habits from becoming muscle memory. The system can objectively and accurately identify technical defects such as pitch, rhythm, evenness of tremolo, and stability of finger tremolo, and transforms abstract errors into visual waveform highlights and text prompts. Combined with standard example audio and targeted practice suggestions, it significantly lowers the self-learning threshold and improves practice efficiency. At the same time, it provides data support for personalized teaching by generating detailed practice reports, which has positive significance for the inheritance of pipa art and the modernization of teaching. Attached Figure Description
[0024] Figure 1 This is a connection block diagram of the intelligent error correction system for pipa playing based on AI acoustic analysis according to the present invention;
[0025] Figure 2 This is a connection diagram of the electronic device of the present invention. Detailed Implementation
[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0027] like Figure 1 As shown:
[0028] The intelligent error correction system for pipa performance based on AI acoustic analysis includes:
[0029] The audio acquisition module is used to acquire and preprocess the pipa audio signal of the performer in real time through the microphone, such as noise reduction and normalization.
[0030] The feature extraction module, connected to the audio acquisition module, is used to extract time-domain and frequency-domain acoustic features related to performance errors from the preprocessed audio signal. The acoustic features include: pitch sequence, intensity envelope, note start point, note duration, spectral centroid, and Mel frequency cepstral coefficients.
[0031] The AI analysis module, connected to the feature extraction module, contains a pre-trained pipa performance error recognition model. This module receives acoustic features and analyzes them based on the model, outputting results including error type, time of occurrence, and severity. The model is a deep learning-based neural network model, and its training data includes numerous pipa audio samples labeled with correct and various types of errors. Error types include at least one of pitch, rhythm, and technique errors. Technique errors include errors in evenness of tremolo, frequency and stability of tremolo, clarity and dynamic balance of sweeping strokes, pitch errors caused by finger placement deviations, and inconsistent tone during plucking.
[0032] The feedback module, connected to the AI analysis module, is used to generate and output real-time, visual, or audible error correction guidance information to the user terminal based on the analysis results. The error correction guidance information output by the feedback module includes: highlighting the error location in the form of waveform or spectrum on the user terminal interface, describing the error type in text, providing standard performance example audio, and providing targeted practice suggestions.
[0033] It also includes a music score input module for receiving or selecting the target music score to practice;
[0034] The music score and audio alignment module is connected to the music score input module and the AI analysis module. It is used to perform real-time alignment and matching of the audio signal acquired by the audio acquisition module with the standard note sequence of the target music score, providing analysis context for the AI analysis module. Based on the alignment information provided by the music score and audio alignment module, the AI analysis module compares the extracted acoustic features with the standard expected features of the corresponding notes in the target music score, thereby identifying deviations and judging them as errors. The system is also integrated into the mobile terminal application. The audio acquisition module is the built-in or external microphone of the mobile terminal.
[0035] like Figure 2As shown, an electronic device includes a memory, a processor, a communication bus, and a communication interface. The communication bus is used to connect and communicate with the processor, the memory, and the communication interface. The communication interface is used to interact with external image acquisition devices and terminal devices to receive raw image data or send recognition results. The memory is used to store computer programs. The processor is used to execute the computer programs stored in the memory to realize the function of an AI-based acoustic analysis-based intelligent error correction system for pipa playing.
[0036] A computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the functions of the aforementioned intelligent error correction system for pipa playing based on AI acoustic analysis. The storage medium includes, but is not limited to, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, etc.
[0037] This solution effectively addresses the core challenges of scarce teacher resources and lack of real-time guidance for after-class practice in traditional pipa teaching. By using AI technology to simulate a teacher's auditory judgment, it provides learners with real-time feedback around the clock, intervening immediately when errors occur to prevent incorrect playing habits from becoming muscle memory. The system can objectively and accurately identify technical defects such as pitch, rhythm, evenness of tremolo, and stability of finger movements, transforming abstract errors into visual waveform highlights and text prompts. Combined with standard example audio and targeted practice suggestions, it significantly lowers the self-learning threshold and improves practice efficiency. Furthermore, by generating detailed practice reports, it provides data support for personalized teaching, which has positive significance for the inheritance of pipa art and the modernization of teaching.
[0038] Working principle: The user launches the APP, selects the piece to practice, the system loads the corresponding sheet music, the user begins to play, the audio acquisition module continuously records, the feature extraction module calculates acoustic features in real time, the sheet music and audio alignment module continuously matches the current playing position with the sheet music, the AI analysis module compares the features of the current note with the ideal feature range of the note specified in the sheet music, and once a deviation exceeds the threshold, it is immediately judged as an error. The feedback module immediately provides a visual prompt on the screen, and can also choose to play an audio prompt. After the practice is completed, the system can generate a complete practice report, summarizing all the errors and improvement suggestions for this practice.
[0039] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A pipa playing intelligent error correction system based on AI acoustic analysis, characterized in that: include: The audio acquisition module is used to acquire and preprocess the pipa audio signal of the performer in real time; The feature extraction module, connected to the audio acquisition module, is used to extract time-domain and frequency-domain acoustic features related to performance errors from the preprocessed audio signal. The AI analysis module is connected to the feature extraction module and has a pre-trained pipa playing error recognition model built into it. The AI analysis module is used to receive the acoustic features and analyze them based on the pipa playing error recognition model, and output analysis results including error type, error occurrence time and error severity. The feedback module, connected to the AI analysis module, is used to generate and output real-time, visual, or audible error correction guidance information to the user terminal based on the analysis results.
2. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 1, characterized in that: The acoustic features include: pitch sequence, intensity envelope, note start point, note duration, spectral centroid, and Mel frequency cepstral coefficients.
3. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 2, characterized in that: The pipa performance error identification model in the AI analysis module is a neural network model based on deep learning. Its training data contains a large number of pipa audio samples labeled with correct and various types of incorrect performances. The error types include at least one of pitch error, rhythm error, and technique error.
4. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 3, characterized in that: The technical errors mentioned include errors in the evenness of the tremolo, errors in the frequency and stability of the tremolo, errors in the clarity and balance of the sweeping strokes, errors in pitch caused by deviations in the position of the pressed notes, and errors in the consistency of the timbre of the plucking strokes.
5. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 1, characterized in that: The error correction guidance information output by the feedback module includes: highlighting the error location in the form of a waveform or spectrum on the user terminal interface, describing the error type in text, providing standard performance example audio, and providing targeted practice suggestions.
6. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 1, characterized in that: Also includes; The music score input module is used to receive or select the target music score to practice; The music score and audio alignment module is connected to the music score input module and the AI analysis module. It is used to perform real-time alignment and matching of the audio signal acquired by the audio acquisition module with the standard note sequence of the target music score, and to provide analysis context for the AI analysis module.
7. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 1, characterized in that: The AI analysis module, based on the alignment information provided by the score and audio alignment module, compares the extracted acoustic features with the standard expected features of the corresponding notes in the target score, thereby identifying deviations and judging them as errors.
8. The intelligent error correction system for pipa performance based on AI acoustic analysis according to claim 1, characterized in that: The system is also integrated into a mobile terminal application, and the audio acquisition module is a built-in or external microphone of the mobile terminal.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the functions of the system as described in any one of claims 1-8.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the functionality of the system as described in any one of claims 1-8.