MIDI cloud music system with intelligent analysis and teaching functions and teaching method

Abstract

The invention relates to an MIDI cloud music system with intelligent analysis and teaching functions and a teaching method, and relates to the technical field of musical instruments. The system comprises a user terminal module which obtains playing data and uploads the playing data to a cloud end; the cloud server module is used for analyzing the MIDI data and generating feedback information and accompaniment data; the intelligent analysis and feedback module performs analysis according to the playing pitch, rhythm and strength, and generates error correction prompts, playing suggestions and visual comparison data; the automatic arrangement and accompaniment module generates an accompaniment track and an arrangement structure according to the selected music style, rhythm and playing characteristics, and sends the track and the structure to the user terminal module for playing; the personalized teaching management module is used for dynamically adjusting teaching contents and difficulty levels and pushing teaching resources according to the learning progress and the playing level; and the database module is used for storing playing records, intelligent analysis results, automatic arrangement information and personalized teaching resources. The application has the effect of improving the application value of the cloud music system and the user experience.

Description

Technical Field

[0001] The present application relates to the technical field of musical instruments, and in particular to a MIDI cloud music system and teaching method with intelligent analysis and teaching functions. Background Art

[0002] In recent years, with the rapid growth of music education and performance needs, MIDI technology has been widely used; MIDI technology is a universal electronic communication protocol that can exchange performance data between electronic musical instruments and computing devices. Through the MIDI protocol, users can realize data transmission, performance synchronization and remote control between musical instruments, thereby promoting the development of new models such as online music education, remote performance interaction and creative collaboration; in order to further improve the application effect of MIDI technology in remote music education, some systems have combined MIDI devices with cloud technology to form MIDI cloud music systems and teaching methods. These systems process and synchronously transmit MIDI data through cloud servers, realizing the sharing of music education resources among multiple regions.

[0003] However, the existing MIDI cloud music system and teaching method still have certain limitations in technical implementation. The relevant technology discloses a MIDI cloud music system and teaching method, which aims to interconnect devices with MIDI IN / OUT interfaces into cloud devices through MIDI smart cloud devices to achieve remote instrument teaching, music interaction and educational resource sharing. However, the system still has the following shortcomings: (1) It lacks intelligent analysis and feedback functions and cannot provide users with performance suggestions; (2) It does not support automatic arrangement and accompaniment functions, and the user experience is relatively simple; (3) The system design fails to dynamically adjust the difficulty according to the user's practice progress, making it difficult to meet personalized teaching needs. Therefore, in response to the above technical problems, there is an urgent need for a MIDI cloud music system with intelligent functions to further enhance the application value and user experience of the system. Summary of the invention

[0004] In order to enhance the application value and user experience of the MIDI cloud music system, the present application provides a MIDI cloud music system and a teaching method with intelligent analysis and teaching functions.

[0005] In the first aspect, the present application provides a MIDI cloud music system with intelligent analysis and teaching functions, which adopts the following technical solutions: A MIDI cloud music system with intelligent analysis and teaching functions, the system comprising: A user terminal module, used to obtain user performance data and upload the performance data to the cloud via the network; A cloud server module is connected to the user terminal module for parsing, storing and distributing the received MIDI data, and generating real-time feedback information and accompaniment data in combination with an intelligent analysis algorithm; An intelligent analysis and feedback module, which is preset in the cloud server module, is used to perform real-time analysis based on the user's playing pitch, rhythm, and strength, and generate error correction prompts, playing suggestions, and visual comparison data based on the analysis results; The automatic arrangement and accompaniment module is preset in the cloud server module, and is used to automatically generate an accompaniment track and an arrangement structure according to the music style, beat and performance characteristics selected by the user, and send the corresponding accompaniment track and arrangement structure to the user terminal module for playback; A personalized teaching management module communicates and interacts with the intelligent analysis and feedback module and the automatic arrangement and accompaniment module to dynamically adjust the teaching content and difficulty level according to the user's learning progress and performance level, and push corresponding teaching resources; A database module, which is in communication with the cloud server module and is used to store user performance records, intelligent analysis results, automatic arrangement information, and personalized teaching resources; Preferably, the user terminal module includes: MIDI interface unit, used to connect electronic musical instruments and collect MIDI signals; A local processing unit, used for locally buffering the user's performance data in an unstable network environment, and uploading the data to the cloud server module after the network is restored; The human-computer interaction unit is used to present real-time performance scoring, error correction suggestions, dynamic music score display and accompaniment playback interface to the user, and receive user instructions for adjusting practice difficulty, music style selection and accompaniment style modification.

[0006] Preferably, the intelligent analysis and feedback module includes: The music feature extraction unit is used to extract the pitch, strength, speed and sustain parameters in the performance data, and generate matching information in combination with the existing music score standard data; An error detection and correction unit, for automatically detecting rhythm deviation, pitch error, excessive force, or weak force performance problems based on the parameters of the music feature extraction unit and comparing them with a preset correct model, and giving specific correction suggestions; The real-time scoring and incentive unit is used to score the user's current performance results and generate visual charts, and to enhance the user's interest in practice through periodic performance analysis and reward mechanisms.

[0007] Preferably, the automatic arrangement and accompaniment module includes: Accompaniment style library, used to store accompaniment styles of various music genres; The arrangement logic generation unit is used to automatically arrange and combine accompaniment tracks based on the music style and performance repertoire selected by the user, and to make real-time adjustments to chords, beats, and instrumentation according to the user's performance data; The collaborative performance control unit is used to generate a fused accompaniment track according to the performance style and speed of each user when multiple people perform collaboratively remotely, and transmit the accompaniment track in separate tracks, so as to ensure the synchronization and coordination of the performances of multiple parties.

[0008] Preferably, it also includes a multi-party interaction unit, which is used for real-time performance collaboration, music discussion and performance result sharing among users in different regions, and realizes multi-person online interaction and instant communication through the cloud server module; when multiple users are connected to the cloud server module at the same time, the multi-party interaction unit coordinates the collection and playback order of MIDI data of each party, and automatically generates a fusion accompaniment audio track and comprehensive performance analysis results according to the system's collaborative performance control unit.

[0009] Preferably, the system further comprises: Cross-platform access module, used to support various types of terminal devices, using a unified cloud communication protocol to achieve standardized transmission of MIDI data; The security encryption and disaster recovery unit is used to encrypt the user's real-time performance data, teaching videos and interactive information, and establish a redundant backup and disaster recovery mechanism in the cloud server module to ensure the stability and security of long-term online music teaching and interaction.

[0010] A music teaching method using a MIDI cloud music system with intelligent analysis and teaching functions as described above, comprising the following steps: S1: Data collection, obtaining the user's MIDI performance data through the user terminal module, and uploading the MIDI performance data to the cloud server module; S2: Intelligent analysis, in which the intelligent analysis and feedback module in the cloud server module extracts music features and detects errors from the MIDI performance data, and generates performance error correction prompts, real-time scores, and visual charts; S3: Automatic arrangement and accompaniment generation, the automatic arrangement and accompaniment module dynamically generates the corresponding arrangement structure and accompaniment track according to the style, beat and actual performance of the performance; S4: Personalized difficulty adjustment. The personalized teaching management module automatically matches and recommends difficulty levels based on the user's historical performance data and scoring results, and pushes etudes and teaching resources suitable for the user's current level; S5: Feedback and presentation. The cloud server module sends the intelligent analysis feedback, arrangement and accompaniment information, and difficulty adjustment suggestions to the user terminal module at the same time, so that the user can refer to it in the visual interface and perform the next round of performance and practice.

[0011] Preferably, the error detection in S2 includes: Establish a standard music score database and corresponding music score matching model; Dividing the user MIDI data into a plurality of note segments and matching them with the correct note sequences in the standard music score database; The degree of deviation of the note segment in pitch, duration and intensity is determined based on the matching result, and the determination result is sent to the error detection and correction unit for automatic correction and suggestion.

[0012] Preferably, S3 further includes: Select user-specified and system-recommended music styles from the accompaniment style library; Constructing a basic accompaniment track according to the harmony trend, beat characteristics and music structure information of the music style; The actual beat, strength and rhythm changes of the user during the performance are obtained, and the arrangement structure and expression form of the basic accompaniment audio track are adjusted in real time to ensure the flexibility and adaptability of the accompaniment.

[0013] Preferably, the S4 further includes: According to the scoring results of the user's recent performances and the distribution of error types, the user's current ability index is calculated through a dynamic weight algorithm; According to the ability index, automatically recommend several repertoire lists that match the user's level, and formulate short-term and long-term practice plans for the user based on a preset skill growth path; After the user continues to practice and completes the specified goals, the ability index is updated in real time, and the difficulty is repositioned and resources are reallocated based on the latest results to continuously match the teaching content suitable for the user's stage.

[0014] In summary, the present application includes at least one of the following beneficial technical effects: 1. This application combines the cloud server module with the intelligent analysis and feedback module to analyze the performance data uploaded by users in real time and generate error correction prompts and personalized feedback. Compared with the existing technology, this application effectively shortens the feedback cycle between learners and teachers and improves the timeliness and pertinence of music education; 2. The automatic arrangement and accompaniment module of the present application can generate a real-time adaptive accompaniment track according to the actual performance of the user, and dynamically adjust the performance beat and intensity. This function not only enhances the user's performance experience, but also meets the diverse needs of single-person practice or multi-person collaborative performance, which is a breakthrough in the traditional fixed accompaniment mode; 3. Through the personalized teaching management module, this application can generate an ability index based on the user's performance data, and push repertoire and teaching resources that match the user's current level and learning progress, further optimizing the learning path planning. Compared with the unified teaching method in the prior art, this application truly achieves the goal of "teaching students in accordance with their aptitude." BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a structural schematic diagram of a MIDI cloud music system with intelligent analysis and teaching functions according to an embodiment of the present application.

[0016] Figure 2 It is a functional diagram of the intelligent analysis and feedback module of an embodiment of the present application.

[0017] Figure 3 It is a workflow diagram of the automatic arrangement and accompaniment module of an embodiment of the present application. DETAILED DESCRIPTION

[0018] The following is combined with Figure 1-3 This application is described in further detail.

[0019] The embodiment of the present application discloses a MIDI cloud music system with intelligent analysis and teaching functions, which uses a cloud server to analyze the received user performance data and provides a variety of real-time feedback based on the analysis results, including intelligent analysis and error correction prompts, dynamic difficulty adjustment, and automatic arrangement and accompaniment. Figure 1 The system of this application mainly includes the following modules: user terminal module, cloud server module, intelligent analysis and feedback module, automatic arrangement and accompaniment module, personalized teaching management module, database module, multi-party interaction unit and cross-platform access module; data communication and linkage are achieved between each module through wired or wireless networks (such as the Internet, local area network or 5G / 4G network, etc.).

[0020] 1. User terminal module Used to obtain user performance data and upload the performance data to the cloud via the network.

[0021] In the specific implementation process, the user terminal module can adopt a variety of hardware forms, such as the MIDI interface of the electronic musical instrument or an external MIDI interface device, and can also be used in combination with a mobile terminal (such as a smart phone, tablet computer) or a computer (desktop, notebook, etc.).

[0022] Specifically, the user terminal module includes a MIDI interface unit, which is first responsible for receiving MIDI performance data from electronic musical instruments, including but not limited to pitch, strength, rhythm, control information, etc.; the user terminal module also includes a local processing unit, which can upload data to the cloud server module in real time when the network is stable, and locally cache the data when the network is unstable or disconnected, and perform batch uploading after the network is restored.

[0023] The user terminal module also includes a human-computer interaction unit, which is used to present real-time performance scores, error correction suggestions, dynamic music score display and accompaniment playback interface to the user, and receive user instructions for adjusting practice difficulty, music style selection and accompaniment style modification, and present error correction suggestions, performance scores, dynamic music score display and system-generated automatic accompaniment and other information to the user in a visual manner to meet the user's interactive needs during the learning and performance process.

[0024] 2. Cloud server module It is connected to the user terminal module in communication, and is used to parse, store and distribute the received MIDI data, and generate real-time feedback information and accompaniment data in combination with the intelligent analysis algorithm.

[0025] During the specific implementation process, the cloud server module is the core management and computing platform of the system, with high-performance data processing and storage capabilities. It connects with the database module to parse, analyze and record the MIDI data uploaded by users.

[0026] Multiple functional modules can be loaded simultaneously in the cloud server module, such as intelligent analysis and feedback module, automatic arrangement and accompaniment module, personalized teaching management module, etc., to collaboratively support music teaching and performance activities for multiple users and multiple scenarios.

[0027] A secure encryption and disaster recovery mechanism is used between the cloud server module and the user terminal module to ensure the security and reliability of data information during transmission, storage and processing.

[0028] 3. Intelligent analysis and feedback module It is preset in the cloud server module and is used to perform real-time analysis based on the user's playing pitch, rhythm, and strength, and generate error correction prompts, performance suggestions, and visual comparison data based on the analysis results.

[0029] In the specific implementation process, the intelligent analysis and feedback module includes a music feature extraction unit, an error detection and correction unit, and a real-time scoring and incentive unit.

[0030] The music feature extraction unit is used to extract the pitch, strength, speed and sustain parameters in the performance data, and generate matching information in combination with the existing music score standard data; The error detection and correction unit is used to automatically detect rhythm deviation, pitch error, excessive force, and weak force performance problems based on the parameters of the music feature extraction unit after comparing them with the preset correct model, and give specific correction suggestions; The real-time scoring and incentive unit is used to score the user's current performance results and generate visual charts, and to enhance the user's interest in practice through periodic performance analysis and reward mechanisms.

[0031] The intelligent analysis and feedback module can perform multi-dimensional analysis of the user's MIDI performance data, such as pitch, rhythm, dynamics, sustain, interval relationship, etc., and compare it with the standard music scores or models pre-stored in the database to quickly identify wrong notes, beat deviations or dynamic control problems that occur during the user's performance.

[0032] Based on the analysis results, the intelligent analysis and feedback module will generate error correction suggestions, performance demonstrations or improvement measures, and send them to the user terminal module for display through the cloud server module. This can help users know their performance defects at the first time and make targeted corrections in subsequent practice or performance.

[0033] At the same time, the intelligent analysis and feedback module will give a comprehensive score to the user's overall performance quality and present it to the user in the form of charts, etc., and combine it with a reward mechanism to enhance learning motivation.

[0034] 4. Automatic arrangement and accompaniment module It is preset in the cloud server module and is used to automatically generate accompaniment tracks and arrangement structures according to the style, beat and performance characteristics selected by the user, and send the corresponding accompaniment tracks and arrangement structures to the user terminal module for playback.

[0035] In the specific implementation process, the automatic arrangement and accompaniment module is used to provide users with flexible and diverse accompaniment generation and automatic arrangement functions. The module includes an accompaniment style library, an arrangement logic generation unit, and a collaborative performance control unit.

[0036] The accompaniment style library is used to store accompaniment styles of various music genres; the accompaniment style library pre-stores accompaniment templates and instrumentation settings of various common or classic music styles, such as pop, rock, classical, jazz, folk, etc. Users can directly select the required style, or the system can automatically recommend the most suitable style based on the user's performance.

[0037] The arrangement logic generation unit is used to automatically arrange and combine accompaniment tracks based on the music style and performance repertoire selected by the user, and to make real-time adjustments to chords, beats, and instrumentation according to the user's performance data; after obtaining the user's performance repertoire, performance speed, strength, and music style selection, the arrangement logic generation unit automatically arranges or generates adaptive harmony trends and beat characteristics in combination with existing templates, and can refine and dynamically adjust the accompaniment track according to the real-time performance data to ensure the harmony and consistency of the accompaniment with the user's real-time performance.

[0038] The collaborative performance control unit is used to generate a fused accompaniment track based on the performance style and speed of each user when multiple people are performing collaboratively remotely, and transmit the accompaniment track in separate tracks, so as to ensure the synchronization and coordination of the performances of multiple parties; in the scenario of multiple people performing collaboratively remotely, the collaborative performance control unit can integrate the performance speeds and styles of multiple users, and automatically fuse them to generate one or more complete ensemble accompaniment tracks, so as to realize remote ensemble or band rehearsal.

[0039] 5. Personalized teaching management module It communicates and interacts with the intelligent analysis and feedback module, and the automatic arrangement and accompaniment module to dynamically adjust the teaching content and difficulty level according to the user's learning progress and performance level, and push corresponding teaching resources.

[0040] In the specific implementation process, the personalized teaching management module focuses on the user's learning process and difficulty matching. By reading the historical scores and error distribution of users' multiple performances in the database, the module can calculate the user's current ability index (including but not limited to; pitch accuracy, rhythm stability, dynamic control, etc.), and recommend songs and teaching resources suitable for the user's level based on the preset skill growth path.

[0041] After the user has trained multiple times and achieved improvement, the system can automatically update his / her ability index and adjust the difficulty of the recommended pieces in real time, allowing the user to gradually improve his / her playing skills.

[0042] The personalized teaching management module also supports setting teaching goals based on user preferences, such as focusing on strengthening left-right hand coordination, specific style of performance or improvisation skills, etc.

[0043] 6. Database Module It is connected to the cloud server module to store user performance records, intelligent analysis results, automatic arrangement information and personalized teaching resources.

[0044] The database module is connected to the cloud server module and is used to store users' performance data, intelligent analysis results, accompaniment style library information, teaching resources and other content.

[0045] In order to meet the diverse needs of users at different levels and types, the database can simultaneously retain a variety of standard music scores and models and keep them updated in a timely manner.

[0046] The database module is equipped with disaster recovery backup and security encryption mechanisms to ensure the reliability and confidentiality of user data.

[0047] 7. Multi-party interactive unit It is used for real-time performance collaboration, music discussion and performance result sharing among users in different regions, and realizes multi-person online interaction and instant communication through the cloud server module; when multiple users are connected to the cloud server module at the same time, the multi-party interaction unit coordinates the collection and playback order of MIDI data of all parties, and automatically generates fusion accompaniment audio tracks and comprehensive performance analysis results according to the system's collaborative performance control unit.

[0048] In the specific implementation process, the multi-party interactive unit can provide an online interactive environment for multiple users in different geographical locations in the cloud server module, including text, voice or video discussion, and real-time performance data synchronization.

[0049] When multiple users are connected to the cloud, the system can integrate and playback the performance data of multiple parties through the multi-party interaction unit, and cooperate with the collaborative performance control unit to generate fusion accompaniment, thereby supporting application scenarios such as band rehearsals, teacher-student interactions, or multi-person teaching.

[0050] 8. Cross-platform access module A cross-platform access module that supports multiple types of terminal devices and uses a unified cloud communication protocol to achieve standardized transmission of MIDI data.

[0051] In the specific implementation process, the cross-platform access module is designed to support various types of terminal devices to meet the user's flexible and convenient use needs. The module adopts a unified cloud communication protocol and data standard to uniformly process and transmit MIDI data collected by different hardware platforms.

[0052] Regardless of whether the user uses a smart phone, tablet computer, laptop computer or dedicated electronic musical instrument terminal, the user can obtain the same music teaching and performance services on the cloud server module provided by the present invention.

[0053] Through the functional coordination of the above modules, the MIDI cloud music system of the present invention can not only realize remote instrument teaching and music interaction, but also solve the problems of the lack of intelligent analysis, real-time feedback, automatic arrangement and accompaniment, multi-party collaborative performance and personalized teaching in the prior art, bringing users a better and more efficient music learning and performance experience.

[0054] The system of the present application also includes a security encryption and disaster recovery unit, which is used to encrypt the user's real-time performance data, teaching videos and interactive information, and establish a redundant backup and disaster recovery mechanism in the cloud server module to ensure the stability and security of long-term online music teaching and interaction.

[0055] The implementation principle of a MIDI cloud music system with intelligent analysis and teaching functions in an embodiment of the present application is as follows: the present application can analyze the performance data uploaded by the user in real time and generate error correction prompts and personalized feedback through the combination of a cloud server module and an intelligent analysis and feedback module. Compared with the prior art, the present application effectively shortens the feedback cycle between learners and teachers, and improves the timeliness and pertinence of music education; the automatic arrangement and accompaniment module of the present application can generate a real-time adaptive accompaniment track according to the actual performance of the user, and dynamically adjust the performance beat and intensity. This function not only enhances the user's performance experience, but also meets the diverse needs of single-player practice or multi-player collaborative performance, which is a breakthrough in the traditional fixed accompaniment mode; the present application can generate an ability index based on the user's performance data through a personalized teaching management module, and push tracks and teaching resources that meet the user's current level and learning progress, further optimizing the learning path planning. Compared with the unified teaching method in the prior art, the present application truly achieves the goal of "teaching students in accordance with their aptitude."

[0056] The present application also provides a music teaching method based on the above-mentioned MIDI cloud music system with intelligent analysis and teaching functions, comprising the following steps: S1: Data collection, obtaining the user's MIDI performance data through the user terminal module, and uploading the MIDI performance data to the cloud server module; S2: Intelligent analysis, in which the intelligent analysis and feedback module in the cloud server module extracts music features and detects errors from the MIDI performance data, and generates performance error correction prompts, real-time scores, and visual charts; S21: Error detection, establishing a standard music score database and a corresponding music score matching model; Dividing the user MIDI data into a plurality of note segments and matching them with the correct note sequences in the standard music score database; Determine the degree of deviation of the note segment in pitch, duration, and intensity according to the matching result, and send the determination result to the error detection and correction unit for automatic correction and suggestion; S3: Automatic arrangement and accompaniment generation, the automatic arrangement and accompaniment module dynamically generates the corresponding arrangement structure and accompaniment track according to the style, beat and actual performance of the performance; S31: Selecting a music style specified by the user and recommended by the system from the accompaniment style library; Constructing a basic accompaniment track according to the harmony trend, beat characteristics and music structure information of the music style; Acquire the actual beat, strength and rhythm changes of the user during the performance, and adjust the arrangement structure and expression form of the basic accompaniment audio track in real time to ensure the flexibility and adaptability of the accompaniment; S4: Personalized difficulty adjustment. The personalized teaching management module automatically matches and recommends difficulty levels based on the user's historical performance data and scoring results, and pushes etudes and teaching resources suitable for the user's current level; S41: Calculate the user's current ability index through a dynamic weight algorithm based on the scoring results of the user's recent multiple performances and the distribution of error types; According to the ability index, automatically recommend several repertoire lists that match the user's level, and formulate short-term and long-term practice plans for the user based on a preset skill growth path; After the user continues to practice and completes the specified goals, the ability index is updated in real time, and the difficulty is repositioned and resources are reallocated according to the latest results, and the teaching content suitable for the user's stage is continuously matched; S5: Feedback and presentation. The cloud server module sends the intelligent analysis feedback, arrangement and accompaniment information, and difficulty adjustment suggestions to the user terminal module at the same time, so that the user can refer to it in the visual interface and perform the next round of performance and practice.

[0057] In addition, the present application also provides specific embodiments under the following three implementation scenarios. Example

[0058] Reference Figure 1-3 , the single-person remote instrument teaching scenario is as follows: 1. Environment Construction The user uses an electronic piano with a MIDI interface at home and connects it to a personal computer through a dedicated MIDI adapter cable. The personal computer is installed with the user terminal module software provided by the present invention and has a stable Internet connection.

[0059] The cloud server module is located in the remote computer room and is equipped with intelligent analysis and feedback modules, automatic arrangement and accompaniment modules, and personalized teaching management modules, and is connected to the database module in real time.

[0060] 2. First time use and login After the user registers and logs into the system, the user terminal module automatically detects the MIDI output port of the electronic piano in the background and completes the initialization settings. The user can check the instrument connection status, select the music to be learned or practiced, and adjust the difficulty and accompaniment style in the system interface.

[0061] 3. Teaching process When the user plays the target song, the MIDI data output by the electronic piano is uploaded to the cloud server module through the user terminal module. If the network is disconnected, the user terminal module will cache it and upload it again after the network is restored to ensure data integrity.

[0062] The intelligent analysis and feedback module identifies, compares and analyzes every note played by the user, and quickly generates error correction prompts when errors are found. The real-time scoring and incentive unit gives instant scores or evaluations to prompt users of performance quality and progress.

[0063] At the same time, the automatic arrangement and accompaniment module automatically generates suitable arrangement and accompaniment tracks based on the selected style according to the user's current song selection, playing speed and strength, etc. The generated accompaniment is transmitted back to the user terminal module by the cloud server module, and seamlessly cooperates with the user's real-time performance or blends into the background music.

[0064] If the user encounters problems during performance, the visual interface of the user terminal module will display the prompt color, location and correction measures of the erroneous notes, helping the user to make targeted improvements or repeat practice.

[0065] 4. Dynamic push of difficulty and teaching resources After monitoring the user's performance for multiple times, the personalized teaching management module will summarize the user's performance scores and common error types, and determine whether the teaching difficulty needs to be adjusted based on the user's ability index. For example, if the user has significant deviations in pitch or rhythm accuracy, the system will automatically recommend basic rhythm exercises or slow mode; if the user's level is high, the system will push more complex works and provide advanced technique demonstrations.

[0066] The system can also provide additional music theory explanations or performance technique video links based on the user's learning progress to ensure that the user grows in both performance skills and theoretical knowledge simultaneously.

[0067] 5. Practice results and data summary After the user completes this practice, all performance data will be stored in the database module by the system for subsequent query and comparison. The user can view his or her progress charts, error statistics, and ability index growth records in different time periods in the system.

[0068] Through this embodiment, users can obtain high-quality teaching feedback and targeted guidance without the presence of professional teachers, which greatly improves learning efficiency and performance pleasure. Example

[0069] Reference Figure 1-3 , the multi-user remote collaborative performance scenario is as follows: 1. Environment Construction Two users perform using their own electronic musical instruments at different locations, and each user is connected to the same cloud server module via a user terminal module.

[0070] The multi-party interaction unit establishes a virtual collaboration space for multiple users in the cloud server module at the same time, and all MIDI data can be synchronously processed and distributed through the cloud.

[0071] 2. Collaborative performance process User A plays the main melody, and user B plays the secondary melody or accompaniment part. The performance data of the two are uploaded to the cloud via the user terminal module.

[0072] The collaborative performance control unit in the cloud server module merges the two performance data and automatically generates an ensemble background track based on the corresponding accompaniment style template and preset rules; if a difference in performance speed is detected between the two users, the system will automatically make fine adjustments or prompts while ensuring no distortion, so as to maintain the synchronization and coordination of the overall performance.

[0073] The intelligent analysis and feedback module can score or correct the performance quality of user A and user B respectively, and present it in the interface of the multi-party interaction unit. The two users can discuss the key points of the performance in real time, modify the performance method in time or rehearse again.

[0074] 3. Ensemble results storage and playback After the collaborative performance is completed, the system will store all ensemble data (including the performance tracks of the two users and the fusion accompaniment tracks generated by the automatic arrangement and accompaniment modules) in the database at the same time. Users can log in to the system at any time afterwards to play back and listen to their own performance results, and they can also share these results with other members or instructors for comments.

[0075] Through this embodiment, multiple people can conduct remote band rehearsals or ensemble practices across regions, and obtain accompaniment support and personalized teaching guidance from the system, helping the orchestra or group to still conduct ensemble activities efficiently even when the venue is limited. Example

[0076] Reference Figure 1-3 , examples of intelligent analysis and personalized growth paths are as follows: 1. User data recording and modeling In the system of the present invention, each user will be bound to a unique account and establish a unique ability index model. The model integrates the scoring results of the user's past performances (such as pitch score, rhythm score, overall performance fluency, etc.), and can be classified and managed according to different music styles and repertoire types, so that the system can accurately determine the user's areas of expertise and weaknesses.

[0077] 2. Intelligent analysis and progress tracking The intelligent analysis and feedback module continuously extracts the user's performance characteristics during each performance and calculates the corresponding indicators such as accuracy, stability, and timbre control. The system derives the user's current ability index based on these indicators and the weight algorithm. If the user's performance in a certain indicator is significantly improved after multiple performances, the system will give visual or text praise to stimulate the user's enthusiasm for continued practice.

[0078] If the system detects that the user repeatedly makes mistakes in certain specific aspects, it will push special practice tracks or teaching videos for this problem through the personalized teaching management module, allowing the user to make up for the shortcomings first and then proceed to more difficult track training.

[0079] 3. Growth path planning and implementation Based on the user's historical data and latest performance, the personalized teaching management module will dynamically adjust their growth path. For example, if the user has a high level of mastery of pop music styles, the system can automatically recommend some advanced pieces or suggest trying basic transition exercises related to jazz and classical styles to expand their musical horizons; if it is detected that the user's control over difficult classical pieces is still insufficient, segmented practice or simplified music scores will be given priority in the short term.

[0080] The system also supports setting stage goals, such as mastering a difficult piece of music within a month. When users achieve their goals, the system will give special achievement rewards or marks through real-time scoring and incentive units to enhance their satisfaction.

[0081] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A MIDI cloud music system with intelligent analysis and teaching functions, characterized by: The system comprises: A user terminal module, used to obtain user performance data and upload the performance data to the cloud via the network; A cloud server module is connected to the user terminal module for parsing, storing and distributing the received MIDI data, and generating real-time feedback information and accompaniment data in combination with an intelligent analysis algorithm; An intelligent analysis and feedback module, which is preset in the cloud server module, is used to perform real-time analysis based on the user's playing pitch, rhythm, and strength, and generate error correction prompts, playing suggestions, and visual comparison data based on the analysis results; The automatic arrangement and accompaniment module is preset in the cloud server module, and is used to automatically generate an accompaniment track and an arrangement structure according to the music style, beat and performance characteristics selected by the user, and send the corresponding accompaniment track and arrangement structure to the user terminal module for playback; A personalized teaching management module communicates and interacts with the intelligent analysis and feedback module and the automatic arrangement and accompaniment module to dynamically adjust the teaching content and difficulty level according to the user's learning progress and performance level, and push corresponding teaching resources; A database module, which is in communication with the cloud server module and is used to store user performance records, intelligent analysis results, automatic arrangement information, and personalized teaching resources; After receiving the real-time feedback, accompaniment information and difficulty adjustment suggestions sent by the cloud server module, the user terminal module provides the user with a visual, multimedia performance guidance interface to achieve remote instrument teaching, music interaction and educational resource sharing.

2. A MIDI cloud music system with intelligent analysis and teaching functions according to claim 1, characterized in that: The user terminal module comprises: MIDI interface unit, used to connect electronic musical instruments and collect MIDI signals; A local processing unit, used for locally buffering the user's performance data in an unstable network environment, and uploading the data to the cloud server module after the network is restored; The human-computer interaction unit is used to present real-time performance scoring, error correction suggestions, dynamic music score display and accompaniment playback interface to the user, and receive user instructions for adjusting practice difficulty, music style selection and accompaniment style modification.

3. A MIDI cloud music system with intelligent analysis and teaching functions according to claim 1, characterized in that: The intelligent analysis and feedback module includes: The music feature extraction unit is used to extract the pitch, strength, speed and sustain parameters in the performance data, and generate matching information in combination with the existing music score standard data; An error detection and correction unit, for automatically detecting rhythm deviation, pitch error, excessive force, or weak force performance problems based on the parameters of the music feature extraction unit and comparing them with a preset correct model, and giving specific correction suggestions; The real-time scoring and incentive unit is used to score the user's current performance results and generate visual charts, and to enhance the user's interest in practice through periodic performance analysis and reward mechanisms.

4. The MIDI cloud music system with intelligent analysis and teaching functions according to claim 1, characterized in that: The automatic arrangement and accompaniment module comprises: Accompaniment style library, used to store accompaniment styles of various music genres; The arrangement logic generation unit is used to automatically arrange and combine accompaniment tracks based on the music style and performance repertoire selected by the user, and to make real-time adjustments to chords, beats, and instrumentation according to the user's performance data; The collaborative performance control unit is used to generate a fused accompaniment track according to the performance style and speed of each user when multiple people perform collaboratively remotely, and transmit the accompaniment track in separate tracks, so as to ensure the synchronization and coordination of the performances of multiple parties.

5. A MIDI cloud music system with intelligent analysis and teaching functions according to claim 4, characterized in that: It also includes a multi-party interaction unit for real-time performance collaboration, music discussion and performance result sharing among users in different regions, and realizes multi-person online interaction and instant communication through the cloud server module; When multiple users are connected to the cloud server module at the same time, the multi-party interactive unit coordinates the collection and playback order of MIDI data from all parties, and automatically generates a fusion accompaniment track and a comprehensive performance analysis result according to the system's collaborative performance control unit.

6. The MIDI cloud music system with intelligent analysis and teaching functions according to claim 1, characterized in that: The system further comprises: Cross-platform access module, used to support various types of terminal devices, using a unified cloud communication protocol to achieve standardized transmission of MIDI data; The security encryption and disaster recovery unit is used to encrypt the user's real-time performance data, teaching videos and interactive information, and establish a redundant backup and disaster recovery mechanism in the cloud server module to ensure the stability and security of long-term online music teaching and interaction.

7. A music teaching method using the MIDI cloud music system as described in any one of claims 1 to 6, characterized in that: The steps include: S1: Data collection, obtaining the user's MIDI performance data through the user terminal module, and uploading the MIDI performance data to the cloud server module; S2: Intelligent analysis, in which the intelligent analysis and feedback module in the cloud server module extracts music features and detects errors from the MIDI performance data, and generates performance error correction prompts, real-time scores, and visual charts; S3: Automatic arrangement and accompaniment generation, the automatic arrangement and accompaniment module dynamically generates the corresponding arrangement structure and accompaniment track according to the style, beat and actual performance of the performance; S4: Personalized difficulty adjustment. The personalized teaching management module automatically matches and recommends difficulty levels based on the user's historical performance data and scoring results, and pushes etudes and teaching resources suitable for the user's current level; S5: Feedback and presentation. The cloud server module sends the intelligent analysis feedback, arrangement and accompaniment information, and difficulty adjustment suggestions to the user terminal module at the same time, so that the user can refer to it in the visual interface and perform the next round of performance and practice.

8. The music teaching method according to claim 7, characterized in that: The error detection in S2 includes: Establish a standard music score database and corresponding music score matching model; Dividing the user MIDI data into a plurality of note segments and matching them with the correct note sequences in the standard music score database; The degree of deviation of the note segment in pitch, duration and intensity is determined based on the matching result, and the determination result is sent to the error detection and correction unit for automatic correction and suggestion.

9. The music teaching method according to claim 7, characterized in that: The S3 further includes: Select user-specified and system-recommended music styles from the accompaniment style library; Constructing a basic accompaniment track according to the harmony trend, beat characteristics and music structure information of the music style; The actual beat, strength and rhythm changes of the user during the performance are obtained, and the arrangement structure and expression form of the basic accompaniment audio track are adjusted in real time to ensure the flexibility and adaptability of the accompaniment.

10. The music teaching method according to claim 7, characterized in that: The S4 further comprises: According to the scoring results of the user's recent performances and the distribution of error types, the user's current ability index is calculated through a dynamic weight algorithm; According to the ability index, automatically recommend several repertoire lists that match the user's level, and formulate short-term and long-term practice plans for the user based on a preset skill growth path; After the user continues to practice and completes the specified goals, the ability index is updated in real time, and the difficulty is repositioned and resources are reallocated based on the latest results to continuously match the teaching content suitable for the user's stage.

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