Cooking appliance and method for operating a cooking appliance

Abstract

The application provides an oil fume exhaustor abnormal sound masking method and system based on an audio injection method, which is applied to an oil fume exhaustor control system and comprises the following steps: acquiring audio data of the oil fume exhaustor during operation; judging whether the oil fume exhaustor has abnormal sound during operation based on a comparison result of the audio data and preset audio data in a target dimension; the target dimension comprises a single frequency peak value difference, a frequency band deviation and an overall sound pressure level difference; if the oil fume exhaustor has abnormal sound, performing parameter optimization on parameters of a preset control sound based on the comparison result and a annoyance degree prediction model to obtain an optimized control sound; the parameters of the preset control sound comprise a frequency component, a frequency band range and a sound pressure level; and masking the abnormal sound of the oil fume exhaustor during operation based on the optimized control sound. The application alleviates the technical problem that the abnormal sound during actual operation cannot be effectively improved in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of range hood noise reduction, and in particular to a range hood abnormal sound masking method and system based on an audio injection method. BACKGROUND

[0002] When the range hood is running, abnormal sound problems may occur due to certain uncertain factors, affecting the user experience. How to effectively identify abnormal sound characteristic signals and how to process abnormal sound to improve user auditory perception are important problems in current range hood technology. Currently, for the abnormal sound problem of the range hood during operation, optimization is generally performed during the product structure design stage, and the abnormal sound problem in actual operation cannot be effectively improved. SUMMARY

[0003] Therefore, the purpose of the present application is to provide a range hood abnormal sound masking method and system based on an audio injection method to alleviate the technical problem that the abnormal sound problem in actual operation cannot be effectively improved in the prior art.

[0004] In a first aspect, the present application provides a range hood abnormal sound masking method based on an audio injection method, applied to a range hood control system, including: obtaining audio data of the range hood during operation; based on a comparison result of the audio data and preset audio data in a target dimension, determining whether the range hood during operation has abnormal sound; the target dimension includes single frequency peak value difference, frequency band deviation, and overall sound pressure level difference; if there is abnormal sound, based on the comparison result and a annoyance degree prediction model, optimizing parameters of a preset control sound to obtain an optimized control sound; the parameters of the preset control sound include frequency components, frequency band range, and sound pressure level; based on the optimized control sound, masking the abnormal sound of the range hood during operation.

[0005] Further, obtaining audio data of the range hood during operation includes: obtaining audio time domain data of the range hood during operation; converting the audio time domain data into audio data in the frequency domain through Fourier transform.

[0006] Further, based on the comparison result of the audio data and the preset audio data in the target dimension, it is determined whether the range hood has abnormal sound during operation, including: calculating the single frequency peak difference, the frequency band deviation and the overall sound pressure level difference of the audio data and the preset audio data respectively; the single frequency peak difference is the difference between the frequency peak of the audio data and the frequency peak of the preset audio data; the frequency band deviation is the difference between the frequency band energy of the audio data and the frequency band energy of the preset audio data; the overall sound pressure level difference is the difference between the sound pressure level of the audio data and the sound pressure level of the preset audio data; it is determined whether the single frequency peak difference is greater than the preset frequency difference value, or the frequency band deviation is greater than the preset frequency band energy difference value, or the overall sound pressure level difference is greater than the preset sound pressure level difference value; if so, it is determined that the range hood has abnormal sound during operation.

[0007] Further, based on the comparison result and the annoyance prediction model, the parameters of the preset control sound are optimized to obtain the optimized control sound, including: a synthesis step: synthesizing the preset control sound and the audio data to obtain the synthesized superimposed sound; using the annoyance prediction model to predict and score the synthesized superimposed sound to obtain the annoyance value; it is determined whether the annoyance value is less than the preset annoyance value; if not, the parameters of the preset control sound are optimized based on the comparison result, and the synthesis step is returned until the annoyance value is greater than or equal to the preset annoyance value, and the optimized control sound is obtained.

[0008] Further, based on the comparison result, the parameters of the preset control sound are optimized, including: if the single frequency peak difference is greater than the preset frequency difference value, the frequency component of the preset control sound is optimized; if the frequency band deviation is greater than the preset frequency band energy difference value, the frequency band range of the preset control sound is optimized; if the overall sound pressure level difference is greater than the preset sound pressure level difference value, the sound pressure level of the preset control sound is optimized.

[0009] In a second aspect, the embodiments of the present application also provide an oil fume exhaustor abnormal sound masking system based on an audio injection method, applied to an oil fume exhaustor control system, comprising an acquisition module, a judgment module, an optimization module and a masking module; the acquisition module is configured to acquire audio data of the oil fume exhaustor during operation; the judgment module is configured to judge whether the oil fume exhaustor has abnormal sound during operation based on a comparison result of the audio data and preset audio data in a target dimension; the target dimension includes single frequency peak difference, frequency band deviation and overall sound pressure level difference; the optimization module is configured to, if there is abnormal sound, perform parameter optimization on parameters of a preset control sound based on the comparison result and a annoyance prediction model to obtain an optimized control sound; the parameters of the preset control sound include frequency component, frequency band range and sound pressure level; and the masking module is configured to mask the abnormal sound of the oil fume exhaustor during operation based on the optimized control sound.

[0010] Further, the judgment module is further configured to: calculate single frequency peak difference, frequency band deviation and overall sound pressure level difference of the audio data and the preset audio data respectively; the single frequency peak difference is a difference value of a frequency peak of the audio data and a frequency peak of the preset audio data; the frequency band deviation is a difference value of a frequency band energy of the audio data and a frequency band energy of the preset audio data; and the overall sound pressure level difference is a difference value of a sound pressure level of the audio data and a sound pressure level of the preset audio data; judge whether the single frequency peak difference is greater than a preset frequency difference value, or the frequency band deviation is greater than a preset frequency band energy difference value, or the overall sound pressure level difference is greater than a preset sound pressure level difference value; and if yes, judge that the oil fume exhaustor has abnormal sound during operation.

[0011] Further, the optimization module is further configured to: a synthesis step of synthesizing the preset control sound and the audio data to obtain a synthesized superimposed sound; predicting and scoring the synthesized superimposed sound by using the annoyance prediction model to obtain an annoyance value; judging whether the annoyance value is less than a preset annoyance value; if no, performing parameter optimization on the preset control sound based on the comparison result and returning to the synthesis step until the annoyance value is greater than or equal to the preset annoyance value to obtain the optimized control sound; and performing parameter optimization on the preset control sound based on the comparison result, including: if the single frequency peak difference is greater than the preset frequency difference value, optimizing the frequency component of the preset control sound; if the frequency band deviation is greater than the preset frequency band energy difference value, optimizing the frequency band range of the preset control sound; and if the overall sound pressure level difference is greater than the preset sound pressure level difference value, optimizing the sound pressure level of the preset control sound.

[0012] In a third aspect, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method of the first aspect when executing the computer program.

[0013] In a fourth aspect, a computer readable medium having non-volatile program code executable by a processor is provided, and the program code causes the processor to perform the method of the first aspect.

[0014] The present application provides an audio injection method based range hood abnormal sound masking method and system, which utilizes spectrum analysis to identify abnormal sound from three dimensions of single frequency peak difference, frequency band deviation, and overall sound pressure level difference, and optimizes the regulated sound, so as to improve the technical effect of masking abnormal sound and alleviate the technical problem that the existing technology cannot effectively improve the abnormal sound in actual operation. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the specific embodiments of the present application or the technical solutions in the prior art, the drawings needed in the specific embodiments or the prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can obtain other drawings according to these drawings without creative labor.

[0016] Figure 1 A flowchart of an audio injection method based range hood abnormal sound masking method provided by an embodiment of the present application;

[0017] Figure 2 A flowchart of another audio injection method based range hood abnormal sound masking method provided by an embodiment of the present application;

[0018] Figure 3 A schematic diagram of an audio injection method based range hood abnormal sound masking system provided by an embodiment of the present application. DETAILED DESCRIPTION

[0019] The technical solutions of the present application will be described below in conjunction with the drawings, obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0020] Embodiment one:

[0021] Figure 1A flowchart of a range hood abnormal sound masking method based on an audio injection method is provided according to an embodiment of the present application, and the method is applied to a range hood control system. As shown in Figure 1 The method specifically includes the following steps:

[0022] Step S102, audio data of the range hood during operation is acquired.

[0023] Optionally, in the embodiment of the present application, the audio time domain data of the range hood during operation is first acquired; then the audio time domain data is converted into audio data in the frequency domain through Fourier transform.

[0024] Optionally, in the embodiment of the present application, the audio time domain data is audio time domain data collected by an audio collection device in the range hood control system at a preset time length and a preset sampling frequency.

[0025] Step S104, based on a comparison result of the audio data and preset audio data in a target dimension, it is determined whether there is an abnormal sound during the operation of the range hood; the target dimension includes a single frequency peak value difference, a frequency band deviation degree and an overall sound pressure level difference.

[0026] The preset audio data is noise frequency domain data of the range hood during operation when leaving the factory.

[0027] Step S106, if there is an abnormal sound, based on the comparison result and a annoyance degree prediction model, parameters of a preset control sound are optimized to obtain an optimized control sound; the parameters of the preset control sound include a frequency component, a frequency band range and a sound pressure level.

[0028] Step S108, based on the optimized control sound, the abnormal sound during the operation of the range hood is masked.

[0029] Specifically, the range hood control module plays the optimized control sound through the audio playing module to mask the abnormal sound.

[0030] The present application provides a range hood abnormal sound masking method based on an audio injection method, which utilizes spectrum analysis to identify the abnormal sound from three dimensions of a single frequency peak value difference, a frequency band deviation degree and an overall sound pressure level difference, and optimizes the control sound, so as to improve the technical effect of masking the abnormal sound and alleviate the technical problem that the existing technology cannot effectively improve the abnormal sound in actual operation.

[0031] Specifically, step S104 further includes the following steps:

[0032] Step S1041, respectively calculating the single frequency peak difference, the frequency band deviation and the overall sound pressure level difference of the audio data and the preset audio data; the single frequency peak difference is the difference between the frequency peak of the audio data and the frequency peak of the preset audio data; the frequency band deviation is the difference between the frequency band energy of the audio data and the frequency band energy of the preset audio data; the overall sound pressure level difference is the difference between the sound pressure level of the audio data and the sound pressure level of the preset audio data.

[0033] Step S1042, judging whether the single frequency peak difference is greater than the preset frequency difference value, or the frequency band deviation is greater than the preset frequency band energy difference value, or the overall sound pressure level difference is greater than the preset sound pressure level difference value; if yes, it is judged that the range hood has abnormal sound when running.

[0034] Specifically, the noise of the range hood is composed of broadband noise and line spectrum noise, and the frequency energy is mainly concentrated in the low frequency, mainly from 200Hz to 1000Hz. The abnormal sound is shown in the frequency domain, which is the single frequency peak value and the specific frequency band energy, wherein:

[0035] Single frequency peak difference F: the difference between the frequency peak of the preset audio data B and the audio data A of the range hood, F=B frequency peak-A frequency peak, if the single frequency peak difference F is greater than the allowed frequency difference value Δf (i.e. the preset frequency difference value), it is judged that there is an abnormal sound problem, which needs to be optimized by the control sound, and the frequency component of the control sound is optimized by the built-in control algorithm of the range hood to synthesize a new control sound.

[0036] Frequency band deviation D: the difference between the frequency band energy of the preset audio data B and the audio data A of the range hood, D=B frequency band energy-A frequency band energy, the frequency band is selected as 1 / 3 octave, if the frequency band deviation D is greater than the allowed frequency band energy difference value Δd (i.e. the preset frequency band energy difference value), it is judged that there is an abnormal sound problem, which needs to be optimized by the control sound, and the frequency band range of the control sound is optimized by the built-in control algorithm of the range hood to synthesize a new control sound.

[0037] Overall sound pressure level difference S: the difference between the sound pressure level of the preset audio data B and the audio data A of the range hood, S=B sound pressure level-A sound pressure level, if the overall sound pressure level difference S is greater than the allowed sound pressure level difference value Δd (i.e. the preset sound pressure level difference value), it is judged that the masking effect of the control sound is weak, which needs to be optimized by the control sound. The sound pressure level of the control sound is optimized by the built-in control algorithm of the range hood to synthesize a new control sound.

[0038] Specifically, step S106 further includes the following steps:

[0039] Synthesis step S1061, synthesizing the preset control sound and the audio data to obtain the synthesized superimposed sound;

[0040] Step S1062, the annoyance degree prediction model is used to predict and score the superimposed sound after synthesis, and an annoyance degree value is obtained;

[0041] Step S1063, it is judged whether the annoyance degree value is less than a preset annoyance degree value; if not, the preset control sound is optimized based on the comparison result, and the synthesis step S1061 is returned until the annoyance degree value is greater than or equal to the preset annoyance degree value, and the optimized control sound is obtained.

[0042] Among them, the parameter optimization of the preset control sound based on the comparison result comprises:

[0043] If the single frequency peak value difference is greater than the preset frequency difference value, the frequency component of the preset control sound is optimized; if the frequency band deviation degree is greater than the preset frequency band energy difference value, the frequency band range of the preset control sound is optimized; if the overall sound pressure level difference is greater than the preset sound pressure level difference value, the sound pressure level of the preset control sound is optimized.

[0044] In the embodiment of the application, the updated control sound is synthesized with the collected audio time domain data M, and the annoyance degree of the synthesized superimposed sound is predicted by the annoyance degree prediction model. If the score K is greater than the allowable annoyance degree value Δk (i.e. the preset annoyance degree value), the control sound needs to be adaptively optimized, and after optimization, the annoyance degree prediction score is again performed until the score is within the allowable range.

[0045] The annoyance degree prediction model: in the development process of the audio injection function, 80% of the data obtained from the subjective evaluation experiment is selected for regression modeling, and the remaining 20% of the data is used for prediction evaluation to form an annoyance degree prediction model, which can simplify the evaluation process of the same type of superimposed sound.

[0046] Adaptive optimization of control sound: realized by the deep learning algorithm formed in the development stage of the audio injection function.

[0047] Finally, the update of the control sound database is completed, and the optimization is completed. After completion, the audio injection effect can mask the abnormal sound, so that the user's listening experience is improved. Figure 2 A flowchart of another range hood abnormal sound masking method based on the audio injection method according to the embodiment of the application.

[0048] As can be seen from the above description, the embodiment of the application provides a range hood abnormal sound masking method based on the audio injection method, which identifies the abnormal sound by analyzing the frequency domain data of the noise collected when the range hood is working, optimizes the corresponding parameters of the control sound, and finally updates the control sound database through the superimposed sound annoyance degree prediction model and the deep learning control sound adaptive optimization algorithm to realize the masking of the abnormal sound, thereby improving the user's listening experience.

[0049] The method provided by the embodiment of the application utilizes spectrum analysis to identify the abnormal sound from three dimensions of single frequency peak difference F, frequency band deviation D and overall sound pressure level difference S, and optimizes the control sound, so that the effect of masking the abnormal sound is achieved. When the range hood generates abnormal sound, the staff cannot effectively solve the problem of the abnormal sound in real time. Based on a large number of mathematical modeling with high accuracy in the early stage, the adaptive optimization of the control sound is achieved, and the abnormal sound is masked. In addition, the method provided by the embodiment of the application is realized by installing an audio acquisition device in the range hood, and the working noise of the range hood is collected and compared with the target sound, so as to provide the hardware device necessary in the process.

[0050] Embodiment two:

[0051] Figure 3 A schematic diagram of a range hood abnormal sound masking system based on an audio injection method according to the embodiment of the application is shown in the figure. The system is applied to a range hood control system. As shown in the figure, the system comprises an acquisition module 10, a judgment module 20, an optimization module 30 and a masking module 40. Figure 1

[0052] Specifically, the acquisition module 10 is configured to acquire audio data of the range hood when the range hood is running.

[0053] Optionally, the acquisition module 10 is further configured to: acquire audio time domain data of the range hood when the range hood is running; and convert the audio time domain data into audio data in the frequency domain through Fourier transform.

[0054] The judgment module 20 is configured to judge whether the range hood has abnormal sound when the range hood is running based on a comparison result of the audio data and preset audio data in a target dimension. The target dimension comprises single frequency peak difference, frequency band deviation and overall sound pressure level difference.

[0055] The optimization module 30 is configured to, if the range hood has abnormal sound, perform parameter optimization on parameters of a preset control sound based on the comparison result and a annoyance degree prediction model, to obtain an optimized control sound. The parameters of the preset control sound comprise frequency component, frequency band range and sound pressure level.

[0056] The masking module 40 is configured to mask the abnormal sound of the range hood when the range hood is running based on the optimized control sound.

[0057] The application provides a range hood abnormal sound masking system based on an audio injection method. The abnormal sound is identified from three dimensions of single frequency peak difference, frequency band deviation and overall sound pressure level difference through spectrum analysis, and the control sound is optimized, so that the technical effect of improving the masking of the abnormal sound is achieved, and the technical problem that the abnormal sound in actual operation cannot be effectively improved in the prior art is solved.

[0058] Specifically, the judgment module 20 is further configured to:​

[0059] respectively, the single frequency peak value difference, the frequency band deviation and the overall sound pressure level difference of the audio data and the preset audio data are calculated, the single frequency peak value difference is the difference between the frequency peak value of the audio data and the frequency peak value of the preset audio data, the frequency band deviation is the difference between the frequency band energy of the audio data and the frequency band energy of the preset audio data, and the overall sound pressure level difference is the difference between the sound pressure level of the audio data and the sound pressure level of the preset audio data.

[0060] It is judged whether the single frequency peak value difference is greater than a preset frequency difference value, or the frequency band deviation is greater than a preset frequency band energy difference value, or the overall sound pressure level difference is greater than a preset sound pressure level difference value.

[0061] If yes, it is judged that the range hood has abnormal noise during operation.

[0062] Specifically, the optimization module 30 is further configured to:

[0063] a synthesis step of synthesizing the preset control sound and the audio data to obtain a synthesized superimposed sound.

[0064] The synthesized superimposed sound is predicted and scored by using the annoyance prediction model to obtain an annoyance value.

[0065] It is judged whether the annoyance value is less than a preset annoyance value.

[0066] If no, the preset control sound is parameter-optimized based on the comparison result, and the synthesis step is returned until the annoyance value is greater than or equal to the preset annoyance value, and an optimized control sound is obtained.

[0067] The preset control sound is parameter-optimized based on the comparison result, including:

[0068] If the single frequency peak value difference is greater than the preset frequency difference value, the frequency component of the preset control sound is optimized, if the frequency band deviation is greater than the preset frequency band energy difference value, the frequency band range of the preset control sound is optimized, and if the overall sound pressure level difference is greater than the preset sound pressure level difference value, the sound pressure level of the preset control sound is optimized.

[0069] The embodiment of the present application also provides an electronic device, including a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to realize the steps of the method in the above-mentioned embodiment one.

[0070] The embodiment of the present application also provides a computer readable medium with non-volatile program code executable by a processor, and the program code makes the processor execute the method in the above-mentioned embodiment one.

[0071] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions recorded in the above embodiments can be modified, or some or all of the technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for masking abnormal noise in a range hood based on audio injection, characterized in that, Applications in range hood control systems; including: Acquire audio data of the range hood during operation; Based on the comparison results between the audio data and the preset audio data in the target dimension, it is determined whether the range hood has any abnormal noise during operation; the target dimension includes single frequency peak difference, frequency band deviation, and overall sound pressure level difference; the preset audio data is the noise frequency domain data of the range hood at the time of manufacture; the single frequency peak difference is the difference between the frequency peak value of the audio data and the frequency peak value of the preset audio data; the frequency band deviation is the difference between the frequency band energy of the audio data and the frequency band energy of the preset audio data; the overall sound pressure level difference is the difference between the sound pressure level of the audio data and the sound pressure level of the preset audio data; The process of determining whether there is an abnormal sound includes: Calculate the single-frequency peak difference, frequency band deviation, and overall sound pressure level difference between the audio data and the preset audio data, respectively. Determine whether the single frequency peak difference is greater than a preset frequency difference, or whether the frequency band deviation is greater than a preset frequency band energy difference, or whether the overall sound pressure level difference is greater than a preset sound pressure level difference. If so, it is determined that the range hood is making abnormal noise during operation; If abnormal noise is present, the parameters of the preset control sound are optimized based on the comparison results and the annoyance prediction model to obtain the optimized control sound; the parameters of the preset control sound include frequency components, frequency band range and sound pressure level; Based on the optimized control sound, abnormal noises during the operation of the range hood are masked.

2. The method according to claim 1, characterized in that, Acquire audio data of the range hood during operation, including: Acquire the audio time-domain data of the range hood during operation; The audio time-domain data is converted into frequency-domain audio data through Fourier transform.

3. The method according to claim 1, characterized in that, Based on the comparison results and the annoyance prediction model, the parameters of the preset control sound are optimized to obtain the optimized control sound, including: Synthesis step: The preset control sound is synthesized with the audio data to obtain the synthesized superimposed sound; Annoyance level prediction model is used to predict and score the synthesized superimposed sound to obtain an annoyance level value; Determine whether the annoyance level is less than a preset annoyance level; If not, then the preset control sound is optimized based on the comparison results, and the process returns to the synthesis step until the annoyance value is greater than or equal to the preset annoyance value, thus obtaining the optimized control sound.

4. The method according to claim 3, characterized in that, Based on the comparison results, the parameters of the preset controlled sound are optimized, including: If the single-frequency peak difference is greater than the preset frequency difference, then the frequency components of the preset controlled sound are optimized. If the frequency band deviation is greater than the preset frequency band energy difference, then the frequency band range of the preset control sound is optimized; If the overall sound pressure level difference is greater than the preset sound pressure level difference value, then the sound pressure level of the preset control sound is optimized.

5. A noise masking system for range hoods based on audio injection method, characterized in that, It is applied to the control system of a range hood; it includes: an acquisition module, a judgment module, an optimization module, and a masking module; among which, The acquisition module is used to acquire audio data of the range hood during operation; The judgment module is used to determine whether the range hood has abnormal noise during operation based on the comparison results of the audio data and the preset audio data in the target dimension; the target dimension includes single frequency peak difference, frequency band deviation and overall sound pressure level difference; the preset audio data is the noise frequency domain data of the range hood when it is running at the factory; The judgment module is also used for: Calculate the single-frequency peak difference, frequency band deviation, and overall sound pressure level difference between the audio data and the preset audio data, respectively; the single-frequency peak difference is the difference between the frequency peak value of the audio data and the frequency peak value of the preset audio data; the frequency band deviation is the difference between the frequency band energy of the audio data and the frequency band energy of the preset audio data; the overall sound pressure level difference is the difference between the sound pressure level of the audio data and the sound pressure level of the preset audio data. Determine whether the single frequency peak difference is greater than a preset frequency difference, or whether the frequency band deviation is greater than a preset frequency band energy difference, or whether the overall sound pressure level difference is greater than a preset sound pressure level difference. If so, it is determined that the range hood is making abnormal noise during operation; The optimization module is used to optimize the parameters of the preset control sound based on the comparison results and the annoyance prediction model if there is an abnormal sound, so as to obtain the optimized control sound; the parameters of the preset control sound include frequency components, frequency band range and sound pressure level. The masking module is used to mask abnormal noises during the operation of the range hood based on the optimized control sound.

6. The system according to claim 5, characterized in that, The optimization module is also used for: Synthesis step: The preset control sound is synthesized with the audio data to obtain the synthesized superimposed sound; Annoyance level prediction model is used to predict and score the synthesized superimposed sound to obtain an annoyance level value; Determine whether the annoyance level is less than a preset annoyance level; If not, then the preset control sound is optimized based on the comparison results, and the synthesis step is returned until the annoyance value is greater than or equal to the preset annoyance value, and the optimized control sound is obtained. Based on the comparison results, the parameters of the preset controlled sound are optimized, including: If the single-frequency peak difference is greater than the preset frequency difference, then the frequency components of the preset controlled sound are optimized. If the frequency band deviation is greater than the preset frequency band energy difference, then the frequency band range of the preset control sound is optimized; If the overall sound pressure level difference is greater than the preset sound pressure level difference value, then the sound pressure level of the preset control sound is optimized.

7. 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 computer program, it implements the steps of the method described in any one of claims 1 to 4.

8. A computer-readable medium having processor-executable non-volatile program code, characterized in that, The program code causes the processor to execute the method according to any one of claims 1-4.

Images