Composite man-machine interaction electronic musical instrument general control unit and embedded system
By constructing a dual-fusion classification model for electronic musical instruments, combining instrument pressure dwell parameters and performance environment characteristics, the problem of the simplicity of existing electronic musical instrument control algorithms is solved, achieving more efficient audio correction and music quality improvement.
Patent Information
- Application Number
- CN202511441097.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-10-10
- Publication Date
- 2026-01-02
AI Technical Summary
Existing machine learning control and correction algorithms for electronic musical instruments are too simplistic, with disorganized data sources, and cannot effectively handle the timbre, pitch, and accompaniment of electronic musical instruments, thus limiting their application and the improvement of music quality.
A general-purpose control unit and embedded system for electronic musical instruments with composite human-computer interaction are adopted. By fusing multimodal coefficients through instrument pressure dwell parameters, performance environment characteristics and instrument functional indicators, a dual-fusion classification model for electronic musical instrument control is constructed for audio correction.
It has improved the accuracy of audio correction and the quality of music for electronic musical instruments, expanded their application scope, and promoted the popularization of electronic music.
Smart Images
Figure CN121260132A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The system of the present application belongs to the technical field of new information technology service for electronic musical instruments, and particularly relates to a composite human-computer interaction electronic musical instrument general control unit and embedded system. BACKGROUND
[0002] At present, a digital piano, also known as an electronic piano, is an electronic musical instrument that simulates the sound and feeling of a traditional piano. The electronic piano has various functions and characteristics, making it very popular in music education and family entertainment. In the composition of the electronic piano, a plurality of keyboards are usually included, with the same number of keys as a standard acoustic piano. Force sensors are arranged on the keyboard to detect the force of the performer's key pressing, to simulate the dynamic response of the acoustic piano. Touch technology such as weighted keyboard, hammer action, etc. is provided to simulate the touch and feedback of the acoustic piano. The internal sound generator processes tone, effect and audio signals, stores digital audio samples of different tone and pitch. And configure the sound source, set the built-in speaker and earphone jack, set the pedal with the sustain function. However, the prior art adjusts the control parameters during the performance process, so that the performance of the performer is more in line with the standard demonstration performance in terms of tone, pitch and accompaniment playing, and the performance effect of the performer is optimized, but the model used is too basic, and the data used is too fuzzy, which cannot be well standardized and corrected. In addition, the main function of the electronic piano is to help the performer learn, so it mainly judges the performance errors and optimization of the performer through the model.
[0003] Therefore, the existing machine learning control correction algorithm of the electronic musical instrument is too simple, the data source is relatively messy, and it is difficult to obtain relevant specific parameter data to process electronic musical instrument general control features, construct an electronic musical instrument control fusion classification model, improve model training efficiency, enhance audio correction methods to improve music quality, assist in improving electronic music performance quality, and promote electronic music promotion. SUMMARY
[0004] To solve the above technical problems, the present application provides a composite human-computer interaction electronic musical instrument general control unit and embedded system.
[0005] In a first aspect of the present application, a composite human-computer interaction electronic musical instrument general control unit and embedded system is provided, which comprises a musical instrument pressure residence parameter acquisition module, a performance environment feature access module, a musical instrument function data storage unit module, an electronic musical instrument control double fusion classification model construction module, and an electronic musical instrument general control and embedded control module:
[0006] The musical instrument pressure stay parameter acquisition module: obtains the musical instrument pressure stay parameter through an electronic musical instrument upload sensor;
[0007] The performance environment feature access module: obtains the performance environment feature through networking;
[0008] The musical instrument function data storage unit module: obtains the musical instrument function index feature based on the musical instrument function data storage unit;
[0009] The electronic musical instrument control double fusion classification model construction module: performs multi-modal coefficient fusion processing based on the musical instrument pressure stay parameter, the performance environment feature, and the musical instrument function index to obtain an electronic musical instrument general control feature, and constructs an electronic musical instrument control double fusion classification model based on the electronic musical instrument general control feature and the audio correction method;
[0010] The electronic musical instrument general control and embedded control module: based on the electronic musical instrument control double fusion classification model, outputs the audio current correction method for the electronic musical instrument played by different persons in different environments.
[0011] Further, the musical instrument pressure stay parameter includes a performance pressing force, a maximum contact area, and a pressing contact time.
[0012] Further, the performance environment feature includes an electronic musical instrument performance environment temperature, a performance environment noise, and a performance environment humidity.
[0013] Further, the musical instrument function index feature includes a musical instrument note response time, a pitch accuracy, and a complex tone condition.
[0014] Further, the multi-modal coefficient fusion is a coefficient processing chain combination of the musical instrument pressure stay parameter, the performance environment feature, and the musical instrument function index with the size of the space occupied by the performance electronic musical instrument as a coefficient to obtain an electronic musical instrument general control feature.
[0015] Further, the electronic musical instrument control double fusion classification model adopts a double fusion Fisher criterion classifier model based on double models using data conditions to correct classification results.
[0016] Further, the double fusion Fisher criterion classifier model based on double models using data conditions to correct classification results.
[0017] A composite human-computer interaction electronic musical instrument general control unit and an embedded method are also provided, and the method comprises:
[0018] The instrument pressure staying parameter is acquired through an electronic musical instrument upload sensor, the performance environment features are acquired through networking, the instrument function index features are acquired based on an instrument function data storage unit, and the audio correction method for improving the music quality is acquired according to a tuner;
[0019] The electronic musical instrument general control features are obtained through multi-modal coefficient fusion processing based on the instrument pressure staying parameter, the performance environment features and the instrument function index;
[0020] The electronic musical instrument control double fusion classification model is constructed based on the electronic musical instrument general control features and the audio correction method;
[0021] The audio current correction method output of the electronic musical instrument under the performance of different persons in different environments is based on the electronic musical instrument control double fusion classification model.
[0022] Further, the instrument pressure staying parameter includes performance pressing force, maximum contact area and pressing contact time.
[0023] Further, the performance environment features include electronic musical instrument performance environment temperature, performance environment noise and performance environment humidity.
[0024] Therefore, the beneficial effects of the present application are that the electronic musical instrument general control features are obtained through processing of the instrument pressure staying parameter, performance environment features and instrument function index features acquired through sensors, and the audio correction method for improving the music quality is acquired, the electronic musical instrument control double fusion classification model is constructed by using the electronic musical instrument general control features and the audio correction method, the double fusion classification model is constructed by comprehensively processing the player, performance scene and main function features of the electronic musical instrument, the double fusion classification model weight distribution is performed after the double model training is performed according to the data, the fusion classification is performed, the model training efficiency is improved, the audio correction method for improving the music quality is enhanced, the use range of the electronic musical instrument is greatly reduced, the music quality under the performance of the electronic musical instrument is improved, the electronic music performance quality is improved, the model further improves the accurate acquisition of the audio correction method, and the electronic music promotion is promoted.
[0025] More embodiments and improvement effects of the present application will be further introduced in combination with the drawings and specific embodiments. BRIEF DESCRIPTION OF DRAWINGS
[0026] Figure 1 is a composite human-computer interaction electronic musical instrument general control unit and embedded method flowchart of the present application;
[0027] Figure 2 is a composite human-computer interaction electronic musical instrument general control unit and embedded system schematic diagram of the present application;
[0028] Figure 3is an example diagram of an electronic musical instrument in the embodiment of the present application;
[0029] Figure 4 is a schematic diagram of an electronic musical instrument function index in the embodiment of the present application;
[0030] Figure 5 is a schematic diagram of an electronic device structure for implementing the method of the present application in the embodiment of the present application. DETAILED DESCRIPTION
[0031] The application will be further described below in conjunction with the drawings and specific embodiments, and the linear discriminant analysis model used in the present application is an improvement of the linear discriminant model in the application scenario of general control of composite human-computer interaction electronic musical instruments.
[0032] As Figure 2 indicated, the control unit and embedded system applied to general control of electronic musical instruments of the present application belong to the emerging software and new information technology service technical field of electronic musical instruments, and therefore belong to the emerging software and new information technology service industry.
[0033] In a first aspect of the present application, a general control unit and embedded system of composite human-computer interaction electronic musical instruments are provided, which include a musical instrument pressure residence parameter acquisition module, a performance environment feature access module, a musical instrument function data storage unit module, an electronic musical instrument control double fusion classification model construction module, and an electronic musical instrument general control and embedded control module:
[0034] The musical instrument pressure residence parameter acquisition module acquires musical instrument pressure residence parameters through an electronic musical instrument sensor;
[0035] The performance environment feature access module acquires performance environment features through networking;
[0036] The musical instrument function data storage unit module acquires musical instrument function index features based on a musical instrument function data storage unit;
[0037] The electronic musical instrument control double fusion classification model construction module performs multi-modal coefficient fusion processing based on the musical instrument pressure residence parameters, the performance environment features, and the musical instrument function indexes to obtain electronic musical instrument general control features, and constructs an electronic musical instrument control double fusion classification model based on the electronic musical instrument general control features and the audio correction method;
[0038] The electronic musical instrument general control and embedded control module outputs an audio current correction method for electronic musical instruments played by different people in different environments based on the electronic musical instrument control double fusion classification model.
[0039] The electronic musical instrument in the present embodiment can be an electronic piano, an electronic violin, or an electronic drum.
[0040] Further, the instrument pressure staying parameters include playing pressing strength, maximum contact area and pressing contact time.
[0041] The electronic musical instrument in the embodiment is an electronic piano, and the sensor installed on each key measures the gravity of each playing pressing of the performer on the key during playing to obtain the playing pressing strength, obtains the maximum contact area of the performer with the key during each pressing, and obtains the pressing contact time of the performer during each pressing of the key.
[0042] For the electronic piano, the pressing data during playing can be converted into volume or timbre change. The electronic piano itself is provided with a corresponding strength sensor, and therefore, it is extremely simple to obtain the instrument pressure staying parameters. In an embodiment of the present application, according to the playing key strength of a conventional electronic piano, the range of the playing pressing strength is usually 30-100 grams. In the embodiment, the maximum contact area range is expanded to 0.8 square centimeters to 2 square centimeters to consider the suitability for children. The pressing contact time is increased to 1-50 milliseconds to consider that some high notes need to be pressed for a long time, compared to the key pressing time of 1-20 milliseconds in the conventional strength detection.
[0043] In the embodiment, the vector of the instrument pressure staying parameters is (playing pressing strength, maximum contact area, pressing contact time). In order to ensure the consistency of subsequent data processing of the double fusion classification model, the dimensional processing of the vector data is performed, and the subsequent data processing remains consistent in the dimensional processing.
[0044] Further, the playing environment features include electronic musical instrument playing environment temperature, playing environment noise and playing environment humidity.
[0045] As shown in the following table, temperature and humidity, as basic parameters affecting electronic musical instruments, have multidimensional effects on the timbre performance of electronic musical instruments. The effects are reflected not only in the change of physical characteristics of the electronic musical instrument equipment, but also in the change of sound propagation characteristics. Although electronic musical instruments are not as sensitive to environmental temperature and humidity as traditional wooden musical instruments, the performance of precise electronic components and mechanical parts is still significantly restricted by environmental conditions, thereby affecting the final timbre output quality.
[0046] Environmental parameter Affected component Physical change Low temperature Conductive rubber key Increased hardness, decreased elasticity Crystal oscillator Frequency drift High temperature Power amplifier Thermal protection activation Electrolytic capacitor Capacity change, increased ESR High humidity Circuit board Decreased insulation resistance Metallic contact Accelerated oxidation Low humidity Plastic housing Static electricity accumulation
[0047] And the noise problem faced by electronic musical instruments in the performance environment constitutes an often overlooked but crucial timbre influencing factor. Unlike traditional acoustic musical instruments, electronic musical instruments rely heavily on clean power supply and low-noise electromagnetic environment to achieve the designed timbre quality. Various forms of noise interference can invade the audio signal chain through various channels, causing different degrees of timbre degradation, from subtle tone changes to serious audible noise interference.
[0048] In this embodiment, the feature vector of the performance environment feature is composed of the electronic musical instrument performance environment temperature, the performance environment noise, and the performance environment humidity by removing the dimension chain connection, such as one performance environment feature represented as (electronic musical instrument performance environment temperature, performance environment noise, performance environment humidity), which can be specifically represented as (22, 15, 35%), and the vector values correspond to the corresponding feature vector values.
[0049] Further, the instrument function index feature includes the note response time, the pitch accuracy, and the complex sound condition of the electronic musical instrument.
[0050] The electronic musical instrument general control system is aimed at the performance adjustment control of a single electronic musical instrument, so the performance test index can verify the audio correction of the electronic musical instrument, and by quantifying the electronic musical instrument function index parameter data, the audio correction method of the electronic musical instrument general control unit and the embedded system can be objectively obtained. The electronic musical instrument control system performance test index has multiple items, but in this application, only the note response time, the pitch accuracy, and the complex sound condition are selected as the deterministic quantitative indexes that can make the model output stable in model construction.
[0051] In this embodiment, the instrument function index feature is also obtained by chain splicing of each feature, and one of the instrument function index features can be represented as (note response time, pitch accuracy, complex sound condition), wherein the complex sound condition is valued by whether the electronic musical instrument has a burst or distortion, and the value is 1 if there is no burst or distortion, and 0 otherwise. The note response time is valued according to the response time value, and the response time of the electronic musical instrument to the keyboard is generally less than 10 ms, so in one embodiment of the application, the note response time of the tested electronic musical instrument can be taken as 8 ms. The pitch accuracy is measured by an audio analyzer, and the value is set according to the error, and the error is generally less than or equal to 2%, and in one embodiment of the application, the value can be taken as 0.87%. Therefore, the specific instrument function index feature of the application can be represented as (8, 0.87%, 1).
[0052] Furthermore, the multimodal coefficient fusion uses the space occupied by the electronic instrument during performance as a coefficient to chain the pressure dwell parameters of the instrument, the performance environment characteristics, and the instrument functional indicators to obtain general control features for the electronic instrument. To reduce data bias and achieve consistency in the input model training feature data, the influence of the performance space on the overall sound quality output of the electronic instrument is corrected using the model input features. The general control features for the electronic instrument are expressed as (…). Instrument pressure dwell parameters Characteristics of the performance environment (Musical instrument functional index characteristics), where To determine the ratio of the optimal playing space to the actual playing space for electronic musical instruments, the formula for calculating the space size coefficient for playing electronic musical instruments is as follows:
[0053]
[0054] In the formula, 'a' represents the space occupied by the electronic instrument. For actual performance space, To ensure the optimal playing space for electronic musical instruments, and to guarantee that 'a' is a positive value, its absolute value is taken.
[0055] In this embodiment, the optimal playing space for the electronic keyboard is 50m³.
[0056] Furthermore, the electronic musical instrument control dual-fusion classification model adopts a dual-fusion Fisher criterion classifier model based on dual-model data to correct the classification results.
[0057] Furthermore, the dual-fusion Fisher criterion classifier model, which corrects the classification results based on data conditions using a dual-model approach, is calculated using the following formula:
[0058]
[0059] In the formula, The method for correcting the output audio. The normal vector of the Fisher criterion classifier model trained using n sets of data is perpendicular to the hyperplane. The normal vector perpendicular to the hyperplane of the Fisher criterion classifier model trained using Nn sets of data is obtained through the initial model construction. For general control features of electronic musical instruments, N, N is the total number of data used to train the model, n is the number of data used to train the first Fisher criterion classifier model, and N-n is the number of data used to train the second Fisher criterion classifier model. To ensure the formation of the training model and to ensure that one of the models is trained with as much data as possible and the other model is trained with as little data as possible, according to the data model fusion principle, a large data model generally has stronger generalization ability, but may ignore the subtle patterns of a specific task, while a small data model focuses on the key features of classification, so the fusion can improve the sensitivity of the general control of electronic musical instruments in specific scenarios. Therefore, the value range of n is set, and the model trained with a small amount of data is used to classify the fusion of the judgment value of the model trained with a large amount of data.
[0060] As shown in the related client device, Figure 5 Generally, a microcomputer is used to realize the functions and implement the audio correction method in the embodiment.
[0061] In the embodiment, the audio correction method is set according to the value of The specific parameters of the audio correction method are set, including adjustment of the filter element and automatic adjustment of the transformer parameters. In an embodiment of the application, the automatic adjustment of the parameters can be performed according to the relationship between the corresponding value and a threshold value such as 1.5. Here, it is a conventional selection of model classification, and will not be described here.
[0062] A composite human-computer interaction electronic musical instrument general control unit and an embedded method are also provided, the method comprising:
[0063] The instrument pressure retention parameter is obtained through the electronic musical instrument sensor, the performance environment features are obtained through networking, the instrument function index features are obtained based on the instrument function data storage unit, and the audio correction method for improving the quality of the music is obtained according to the tuner;
[0064] The multi-modal coefficient fusion processing is performed based on the instrument pressure retention parameter, the performance environment features, and the instrument function index to obtain the electronic musical instrument general control features;
[0065] The electronic musical instrument control double-fusion classification model is constructed based on the electronic musical instrument general control features and the audio correction method;
[0066] Based on the electronic musical instrument control double-fusion classification model, the output of the audio current correction method for the electronic musical instrument played by different people in different environments is obtained.
[0067] The electronic musical instrument in the embodiment can be an electronic piano, an electronic violin, or an electronic drum.
[0068] Further, the instrument pressure staying parameters include playing pressing strength, maximum contact area and pressing contact time.
[0069] The electronic musical instrument in the embodiment is a piano, and the sensor installed on each key measures the gravity of each playing pressing of the player on the key to obtain the playing pressing strength, obtains the maximum contact area of the player with the key during each pressing, and obtains the pressing contact time of the player pressing the key each time.
[0070] For the piano, the pressing data during playing can be converted into volume or timbre changes. The piano itself has a corresponding strength sensor, so it is very simple to obtain the instrument pressure staying parameters. In an embodiment of the present application, according to the playing key strength of a conventional piano, the playing pressing strength is usually 30-100 grams. In the embodiment, the maximum contact area is expanded to 0.8 square centimeters to 2 square centimeters to consider the suitability for children. The pressing contact time is increased to 1-50 milliseconds compared to the conventional strength detection key time of 1-20 milliseconds to consider that some high notes need to be pressed for a long time.
[0071] In the embodiment, the vector representation of the instrument pressure staying parameters is (playing pressing strength, maximum contact area, pressing contact time). To ensure the consistency of subsequent double fusion classification model data processing, the vector data is processed to remove the dimension, and the subsequent data processing remains consistent in removing the dimension.
[0072] Further, the playing environment features include electronic musical instrument playing environment temperature, playing environment noise and playing environment humidity.
[0073] Temperature and humidity are basic parameters that affect electronic musical instruments and have multidimensional effects on the timbre performance of electronic musical instruments. Such effects are reflected not only in the physical property changes of electronic musical instrument equipment, but also in the changes in sound propagation characteristics. Although electronic musical instruments are not as sensitive to environmental temperature and humidity as traditional wooden musical instruments, the performance of precise electronic components and mechanical parts is still significantly restricted by environmental conditions, which in turn affects the final timbre output quality.
[0074] The noise problem faced by electronic musical instruments in the playing environment constitutes an important timbre influencing factor that is often overlooked. Unlike traditional acoustic musical instruments, electronic musical instruments highly depend on clean power supply and low-noise electromagnetic environment to achieve the designed timbre quality. Various forms of noise interference can invade the audio signal chain through various ways, causing different degrees of timbre degradation, from subtle sound quality changes to serious audible noise interference.
[0075] In this embodiment, the feature vector of the performance environment feature is composed of the electronic musical instrument performance environment temperature, performance environment noise and performance environment humidity by removing the dimension chain link, such as one of the performance environment features is represented as (electronic musical instrument performance environment temperature, performance environment noise, performance environment humidity), which can be specifically represented as (22, 15, 35%), and the vector value corresponds to the corresponding feature vector value.
[0076] Therefore, the beneficial effects of the present application are that the electronic musical instrument general control features are obtained by processing the musical instrument pressure retention parameters, performance environment features and musical instrument function index features obtained by sensors, and the audio correction method for improving the music quality is obtained, and the electronic musical instrument control double fusion classification model is constructed by using the electronic musical instrument general control features and the audio correction method. The present application comprehensively processes the main function features of the player, the performance scene and the electronic musical instrument to construct the double fusion classification fusion model, and the double fusion classification model weight distribution is allocated according to the double model training data, and then the fusion classification is performed, the model training efficiency is improved, the audio correction method for improving the music quality is enhanced, the use range of the electronic musical instrument is greatly reduced, the music quality under the performance scene of the electronic musical instrument is improved, the electronic music performance quality is improved, and the model further improves the accurate acquisition of the audio correction method, and promotes the popularization of electronic music.
[0077] Of course, it can be understood that each embodiment of the present application can realize one of the effects, and the combination of multiple embodiments of the present application can realize all the effects described above, but it is not required that each embodiment of the present application realizes all the advantages and effects described above, because each embodiment of the present application can constitute a separate technical solution and make one or more contributions to the prior art, each embodiment of the present application is not affected, and the scheme can still be implemented by deleting one embodiment.
[0078] The part of the module structure of the present application which is not specifically clear is subject to the content recorded in the prior art. The prior art mentioned in the foregoing background art part and the specific embodiment part of the present application can be used as a part of the present application to understand the meaning of part of the technical features or parameters.
Claims
1. A composite human-computer interaction electronic musical instrument general control unit and embedded system, the system comprising a musical instrument pressure dwell parameter acquisition module, a performance environment feature storage module, a musical instrument function data storage unit module, an electronic musical instrument control dual-fusion classification model construction module, and an electronic musical instrument general control and embedded control module, characterized in that: The instrument pressure dwell parameter acquisition module acquires the instrument pressure dwell parameter through a sensor on the electronic instrument. The performance environment feature storage module acquires performance environment features via a network connection. The musical instrument function data storage unit module: acquires musical instrument function index features based on the musical instrument function data storage unit; The electronic musical instrument control dual-fusion classification model construction module: Based on the instrument pressure dwell parameters, the performance environment characteristics, and the instrument function indicators, multimodal coefficient fusion processing is performed to obtain general control features of electronic musical instruments; and based on the general control features of electronic musical instruments and the audio correction method, an electronic musical instrument control dual-fusion classification model is constructed. The general control and embedded control module for electronic musical instruments: based on the dual fusion classification model for electronic musical instrument control, it outputs the current audio correction method for electronic musical instruments played by different people in different environments.
2. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 1, characterized in that: The instrument pressure dwell parameters include the playing pressure intensity, the maximum contact area, and the pressing contact time.
3. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 1, characterized in that: The performance environment characteristics include the temperature, noise, and humidity of the electronic instrument performance environment.
4. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 2 or 3, characterized in that: The functional characteristics of the musical instruments include the note response time, pitch accuracy, and polyphony of electronic musical instruments.
5. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 4, characterized in that: The multimodal coefficient fusion is a process that combines the instrument pressure dwell parameters, the performance environment characteristics, and the instrument functional indicators with the space occupied by the electronic instrument as the coefficient to obtain the general control characteristics of the electronic instrument.
6. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 5, characterized in that: The electronic musical instrument control dual-fusion classification model adopts a dual-fusion Fisher criterion classifier model based on dual models that correct classification results using data conditions.
7. The composite human-computer interaction electronic musical instrument universal control unit and embedded system as described in claim 6, characterized in that: The dual-fusion Fisher criterion classifier model is based on dual models that use data to correct classification results.
8. A universal control unit for electronic musical instruments with composite human-computer interaction and an embedded method, characterized in that, The method includes: The instrument pressure dwell parameters are obtained by sensors on the electronic instrument, and the characteristics of the playing environment are obtained by networking. The instrument function index characteristics are obtained based on the instrument function data storage unit, and the audio correction methods to improve the quality of the music are obtained by the tuner. Based on the instrument pressure dwell parameters, the performance environment characteristics, and the instrument functional indicators, multimodal coefficient fusion processing is performed to obtain the general control characteristics of electronic musical instruments; A dual-fusion classification model for electronic musical instrument control is constructed based on the general control features of the electronic musical instruments and the audio correction method. Based on the aforementioned dual-fusion classification model for electronic musical instrument control, the current audio correction method is output for electronic musical instruments played by different people in different environments.
9. The composite human-computer interaction electronic musical instrument universal control unit and embedded method as described in claim 1, characterized in that: The instrument pressure dwell parameters include the playing pressure intensity, the maximum contact area, and the pressing contact time.
10. The composite human-computer interaction electronic musical instrument universal control unit and embedded method as described in claim 1, characterized in that: The performance environment characteristics include the temperature, noise, and humidity of the electronic instrument performance environment.