A hearing aid system and method capable of automatically adjusting the volume according to the environment

Abstract

The present invention discloses a hearing aid system and method capable of automatically adjusting the volume according to the environment. The method includes: collecting environmental noise data through at least one microphone of the hearing aid; performing a fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extracting the frequency components and their energy spectrum E = |F| 2 ; calculating the overall sound pressure level (SPL) of the environmental noise based on the frequency domain feature F and the energy spectrum E; performing adaptive compensation according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,..., c k}, and calculating the required gain G; adjusting the output volume of the hearing aid through a digital signal processor based on the gain G. The present invention has the following advantages: real-time adaptability, which can improve user comfort, enhance sound recognition ability, and adapt to diverse usage scenarios.

Description

Technical Field

[0001] The present invention belongs to the field of computer system engineering, and particularly relates to a hearing aid system and method capable of automatically adjusting the volume according to the environment. Background Art

[0002] In modern society, with the aging of the population and the increase in environmental noise, hearing impairment has gradually become a common health problem. According to the statistics of the World Health Organization, approximately 466 million people worldwide are affected by hearing loss to varying degrees. As the main device for improving hearing, the technological development and application of hearing aids have also received attention. Traditional hearing aids usually rely on static gain settings, lack adaptability, and fail to effectively cope with complex and changing environmental sound conditions.

[0003] Environmental noise is one of the key factors affecting people's hearing experience. People have different sound requirements in different environments (such as noisy streets, quiet libraries, or noisy restaurants). Therefore, hearing aids need to be dynamically adjusted according to the real-time environmental noise situation to provide the best hearing experience. However, traditional hearing aids cannot adapt to these changes in real time, resulting in users still feeling discomfort or unable to effectively hear important sounds, such as conversations or alarm sounds, in noisy environments.

[0004] To improve this problem, in recent years, researchers have begun to explore dynamic gain adjustment technologies based on environmental noise. Summary of the Invention

[0005] In view of the defects existing in the above-mentioned prior art, the present invention provides a method for automatically adjusting the volume according to the environment, including the following steps:

[0006] Step S101: Collect environmental noise data through at least one microphone of the hearing aid to generate a sound feature vector V = {v1, v2,..., v n}, where v i represents the i-th sound feature;

[0007] Step S103: Perform a fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extract the frequency components and their energy spectrum E = |F| 2 ;

[0008] Step S105: Calculate the overall sound pressure level (SPL) of the environmental noise according to the frequency domain feature F and the energy spectrum E;

[0009] Step S107: According to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,..., c kPerform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula

[0010]

[0011] , where C i represents the user's hearing response at frequency f i , N is the number of frequency components, E i is the energy spectrum of the i-th frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the environmental sound signal intensity at time t, H(t) is the user's hearing curve response function at time t, M is the number of frequency components, ω j is the weight of the j-th frequency component, f j is the frequency of the j-th frequency component, τ is the threshold of the user's hearing sensitivity, and α is the slope parameter of the logistic regression function;

[0012] Step S109: Adjust the output volume of the hearing aid based on the gain G through a digital signal processor.

[0013] Among them, the step S103 also includes performing a wavelet transform on the sound feature vector V to obtain multi-scale frequency domain features W = {w1, w2,..., w p}, to achieve sensitive capture of instantaneous noise changes.

[0014] Among them, the overall sound pressure level SPL is calculated using the following formula in step S105

[0015] where N is the number of frequency components, E i is the energy spectrum of the i-th frequency component.

[0016] Among them, in step S107, it is expressed by the following formula where M is the number of selected frequencies, C i is the value of C at the i-th frequency component.

[0017] Among them, in step S107, S(t) = |X(t)|, where X(t) is the complex form of the audio signal at time t, and |X(t)| is its amplitude.

[0018] Among them, in step S107, H(t) = C(f0 + Δf·t), where f0 is the initial frequency and Δf is the frequency change rate.

[0019] Among them, the hearing curve C of the user in step S107 is generated from the hearing test data fed back by the user, and is specifically implemented through the following steps:

[0020] Conduct a hearing test on the user to obtain the hearing thresholds of the user at different frequencies;

[0021] Construct the hearing curve C of the user by linear interpolation to smooth the changes in hearing thresholds at different frequencies.

[0022] Among them, the construction of the hearing curve C of the user by linear interpolation specifically includes:

[0023] Input the known frequencies and hearing thresholds, and set the value range of f as [f1, f k ;

[0024] Find fi and fi+1 for each frequency f to be interpolated;

[0025] Calculate t(f) using the interpolation formula;

[0026] The obtained t(f) forms a smooth hearing curve C of the user.

[0027] Among them, the basic idea of linear interpolation is that for any two known points (f i , t i ) and (f i+1 , t i+1 ), the straight line passing through these two points is used to estimate the points between them, and the following formula is used to calculate t(f):

[0028] where t(f) is the estimated hearing threshold at frequency f. The present invention also proposes a hearing aid system that can automatically adjust the volume according to the environment, including

[0029] At least one microphone, which is used to collect environmental noise data and generate a sound feature vector V = {v1, v2,..., v n}, where v i represents the i-th sound feature;

[0030] A frequency feature analysis module, which is used to perform a fast Fourier transform FFT on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extract the frequency components and their energy spectrum E = |F| 2 ;

[0031] An overall sound pressure level calculation module, which is used to calculate the overall sound pressure level SPL of the environmental noise according to the frequency domain feature F and the energy spectrum E;

[0032] A gain calculation module, which is used to perform adaptive compensation according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,..., c k}, and calculate the required gain G, where the gain G is calculated using the following formula

[0033]

[0034] , where C i represents the user's hearing response at frequency f i , N is the number of frequency components, E i is the energy spectrum of the i-th frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the environmental sound signal intensity at time t, H(t) is the user's hearing curve response function at time t, M is the number of frequency components, ω j is the weight of the j-th frequency component, f j is the frequency of the j-th frequency component, τ is the threshold of the user's hearing sensitivity, and α is the slope parameter of the logistic regression function;

[0035] A digital signal processor, which is used to control the output volume of the hearing aid based on the gain G.

[0036] Compared with the prior art, the present invention has the following advantages:

[0037] Traditional hearing aids usually use fixed gain settings and cannot adapt to different environmental conditions in real time. This results in the user may not be able to clearly hear important sounds in a noisy environment, or feel the volume is too loud in a quiet environment. Through the automatic adjustment mechanism of the present invention, the hearing aid can monitor the environmental noise in real time and dynamically adjust the volume according to the sound pressure level (SPL) of the current environment, ensuring that the user can obtain the best hearing experience in various environments.

[0038] By using the fast Fourier transform (FFT) to analyze the environmental sound characteristics, the present invention can accurately identify the main sound components. Combining with the user's personalized hearing curve, the hearing aid can perform adaptive compensation according to the user's hearing sensitivity. This personalized gain adjustment significantly improves the user's comfort and reduces the hearing fatigue and discomfort caused by noise interference.

[0039] The present invention not only focuses on the overall sound pressure level of environmental noise, but also optimizes the sound enhancement within a specific frequency range by extracting frequency components and their energy spectra. By precisely calculating the user's hearing response at different frequencies, the hearing aid can more effectively amplify important sounds (such as conversations, alarm sounds, etc.), enhancing the user's ability to recognize sounds in the surrounding environment. This is particularly important for users who need to maintain communication in complex environments.

[0040] Due to the diversity of environmental noise, traditional hearing aids often struggle to meet the audio requirements of various scenarios. Through the gain adjustment mechanism of this solution, the hearing aid can quickly adapt to different scenarios (such as restaurants, streets, meeting rooms, etc.). This flexibility ensures that users can enjoy clear sound in different environments, no longer being limited to specific usage occasions. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present disclosure will become readily understood. In the drawings, several embodiments of the present disclosure are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0042] Figure 1 is a flowchart showing a method for automatically adjusting the volume according to the environment according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0043] In order to make the objects, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0044] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "the", and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. "Plural" generally includes at least two.

[0045] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present invention to describe..., these... should not be limited to these terms. These terms are only used to distinguish.... For example, without departing from the scope of the embodiments of the present invention, the first... may also be referred to as the second..., and similarly, the second... may also be referred to as the first....

[0046] It should be understood that the term "and / or" used herein is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Additionally, the character " / " in this text generally indicates that the associated objects before and after are in an "or" relationship.

[0047] Depending on the context, the words "if" or "when" as used herein can be interpreted as "when...", "while...", "in response to determining", or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined", "in response to determining", "when detecting (stated condition or event)", or "in response to detecting (stated condition or event)".

[0048] It should also be noted that the term "comprising", "including", or any other variant thereof is intended to cover non-exclusive inclusion, such that a commodity or device comprising a series of elements not only includes those elements but also includes other elements not explicitly listed, or elements inherent to such commodity or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the commodity or device comprising the said element.

[0049] The optional embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0050] Embodiment 1

[0051] As Figure 1 shown, the present invention discloses a method for automatically adjusting the volume according to the environment, including the following steps:

[0052] Step S101: Collect environmental noise data through at least one microphone of a hearing aid to generate a sound feature vector V = {v1, v2,..., v n}, where v i represents the i-th sound feature;

[0053] Step S103: Perform a fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extract the frequency components and their energy spectrum E = |F| 2 ;

[0054] Step S105: Calculate the overall sound pressure level (SPL) of the environmental noise according to the frequency domain feature F and the energy spectrum E;

[0055] Step S107: Perform adaptive compensation according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,..., c k}, and calculate the required gain G, where the gain G is calculated using the following formula

[0056]

[0057] , where C i represents the user's hearing response at frequency f i , N is the number of frequency components, E i is the energy spectrum of the i-th frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the environmental sound signal intensity at time t, H(t) is the user's hearing curve response function at time t, M is the number of frequency components, ω j is the weight of the j-th frequency component, f j is the frequency of the j-th frequency component, τ is the threshold of the user's hearing sensitivity, and α is the slope parameter of the logistic regression function;

[0058] Step S109: Based on the gain G, adjust the output volume of the hearing aid through a digital signal processor.

[0059] Embodiment 2

[0060] A method for automatically adjusting the volume according to the environment proposed by the present invention includes the following steps:

[0061] Step S101: Collect environmental noise data through at least one microphone of the hearing aid to generate a sound feature vector V = {v1, v2,..., v n}, where v i represents the i-th sound feature;

[0062] Step S103: Perform a fast Fourier transform FFT on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extract the frequency components and their energy spectrum E = |F| 2 ;

[0063] Step S105: Calculate the overall sound pressure level SPL of the environmental noise according to the frequency domain feature F and the energy spectrum E;

[0064] Step S107: Perform adaptive compensation according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,...,, c k}, and calculate the required gain G, where the gain G is calculated using the following formula

[0065]

[0066] , where C i represents the user's hearing response at frequency f i , N is the number of frequency components, E i is the energy spectrum of the i-th frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the environmental sound signal intensity at time t, H(t) is the user's hearing curve response function at time t, M is the number of frequency components, ω j is the weight of the j-th frequency component, f j is the frequency of the j-th frequency component, τ is the threshold of the user's hearing sensitivity, and α is the slope parameter of the logistic regression function;

[0067] where, SPL ref usually depends on the standard environmental noise level and can be obtained through environmental measurement devices or historical data. ω j is usually determined according to the user's hearing characteristics and the spectral distribution of the environmental noise and may be set through user feedback or empirical values. τ is usually obtained through the user's hearing test and represents the user's hearing sensitivity at a specific frequency. α is the slope parameter of the logistic regression function, which is used to adjust the response of the gain to frequency changes and is usually obtained through data analysis or machine learning model optimization.

[0068] Step S109: Based on the gain G, adjust the output volume of the hearing aid through a digital signal processor.

[0069] where, step S103 further includes performing a wavelet transform on the sound feature vector V to obtain multi-scale frequency domain features W = {w1, w2,..., w p}, to achieve sensitive capture of instantaneous noise changes.

[0070] In one embodiment, the wavelet transform extracts features by convolving the signal with a set of wavelet functions. Commonly used wavelet functions include Haar wavelets, Daubechies wavelets, etc. The wavelet transform can be divided into discrete wavelet transform (DWT) and continuous wavelet transform (CWT), and discrete wavelet transform is used here.

[0071] The output of the wavelet transform is the representation of the signal at different scales and positions. The formula for discrete wavelet transform can be expressed as:

[0072] where, W j，k is the coefficient of the wavelet transform, representing the feature at the j-th scale and the k-th position; ψ j，k[n] is a wavelet function, usually expressed as: ψ j，k [n] = 2 -2j ψ(2 -j (n - k)), where ψ(t) is the mother wavelet, j is the scale factor, and k is the position parameter.

[0073] By performing wavelet transform on the sound feature vector V, multi-scale frequency domain features W can be obtained, expressed as: W = {w1, w2,..., w p}}, specifically, ω i can be obtained by sampling the wavelet coefficients at different scales j and positions k: where j i and k i correspond to the scale and position of the i-th feature respectively.

[0074] Through wavelet transform, instantaneous noise changes can be effectively captured. For example, when analyzing environmental noise, instantaneous high-frequency noise changes can be identified through changes in the wavelet coefficients W. By setting appropriate thresholds, these wavelet coefficients can be further processed to remove noise or extract specific features.

[0075] Among them, in the step S105, the overall sound pressure level SPL is calculated using the following formula

[0076] where N is the number of frequency components, and E i is the energy spectrum of the i-th frequency component.

[0077] Among them, in the step S107, it is expressed by the following formula where M is the number of selected frequencies, and C i is the value of C at the i-th frequency component.

[0078] Among them, in the step S107, S(t) = |X(t)|, where X(t) is the complex form of the audio signal at time t, and |X(t)| is its amplitude.

[0079] Among them, in the step S107, H(t) = C(f0 + Δf·t), where f0 is the initial frequency and Δf is the frequency change rate.

[0080] Among them, in the step S107, the user's hearing curve C is generated from the hearing test data feedback by the user, and is specifically implemented through the following steps:

[0081] Conduct a user hearing test to obtain the user's hearing thresholds at different frequencies;

[0082] Construct the user's hearing curve C by linear interpolation to smooth the changes in hearing thresholds at different frequencies.

[0083] Among them, constructing the user's hearing curve C by the linear interpolation method specifically includes:

[0084] Input the known frequency and hearing threshold, and set the value range of f as [f1, f k ;

[0085] Find fi and fi + 1 for each frequency f to be interpolated;

[0086] Calculate t(f) using the interpolation formula;

[0087] The obtained t(f) forms a smooth user hearing curve C.

[0088] Among them, the basic idea of linear interpolation is that for any two known points (f i , t i ) and (f i+1 , t i+1 ), the straight line passing through these two points is used to estimate the points between them. Then, the following formula is used to calculate t(f):

[0089] Where t(f) is the estimated hearing threshold at frequency f. In a certain embodiment, assume the user's hearing test data is as follows:

[0090] · f = {1000, 2000, 4000}

[0091] · T = {30, 20, 10} (corresponding hearing thresholds)

[0092] If you want to estimate the hearing threshold at 1500 Hz:

[0093] · Interpolate between f1 = 1000 Hz and f2 = 2000 Hz:

[0094] · Then

[0095] · Therefore, t(1500) = 25 dB.

[0096] Embodiment III

[0097] The present invention also proposes a hearing aid system that can automatically adjust the volume according to the environment,

[0098] At least one microphone, which is used to collect environmental noise data and generate a sound feature vector V = {v1, v2,..., v n}, where v i represents the i-th sound feature;

[0099] A frequency feature analysis module, which is used to perform a fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2,..., f m}, and extract the frequency components and their energy spectrum E = |F| 2 ;

[0100] An overall sound pressure level calculation module, which is used to calculate the overall sound pressure level SPL of the ambient noise according to the frequency domain feature F and the energy spectrum E;

[0101] A gain calculation module, which is used to perform adaptive compensation according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2,..., c k} to calculate the required gain G, and the gain G is calculated using the following formula

[0102]

[0103] , where C i represents the user's hearing response at frequency f i , N is the number of frequency components, E i is the energy spectrum of the i-th frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the intensity of the ambient sound signal at time t, H(t) is the user's hearing curve response function at time t, M is the number of frequency components, ω j is the weight of the j-th frequency component, f j is the frequency of the j-th frequency component, τ is the threshold of the user's hearing sensitivity, and α is the slope parameter of the logistic regression function;

[0104] A digital signal processor, which is used to control the output volume of the hearing aid based on the gain G.

[0105] Example 4

[0106] The present disclosure embodiment provides a non-volatile computer storage medium, and the computer storage medium stores computer-executable instructions, and these computer-executable instructions can execute the method steps described in the above embodiments.

[0107] It should be noted that the above-mentioned computer-readable medium in the present disclosure may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which the computer-readable program code is carried. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable signal medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0108] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist separately and not be assembled into the electronic device.

[0109] The computer program code for performing the operations of the present disclosure may be written in one or more programming languages or combinations thereof. The above-mentioned programming languages include object-oriented programming languages - such as Java, Smalltalk, C++, and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or it may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0110] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0111] The units involved in the embodiments described in the present disclosure can be implemented in software or in hardware. Among them, the name of the unit does not constitute a limitation on the unit itself in some cases.

[0112] The preferred embodiments of the present invention are described above to make the spirit of the present invention clearer and easier to understand, and are not intended to limit the present invention. Any modifications, substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope defined by the appended claims of the present invention.

Claims

1. A method for automatically adjusting volume according to the environment, characterized in that: The following steps are involved: Step S101: Collect environmental noise data through at least one microphone of the hearing aid to generate a sound feature vector ,in Indicates The sound characteristics, The value range is 1~n; Step S103: Perform fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature , and extract the frequency components and their energy spectra ; Step S105: according to the frequency domain characteristics and energy spectrum Calculate the overall sound pressure level SPL of the ambient noise; Step S107: according to the overall sound pressure level SPL and the hearing curve of the user Perform adaptive compensation and calculate the required gain G, wherein the gain G is calculated using the following formula: , where N is the total number of all calculated frequency components, E i is the energy spectrum of the ith frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the ambient sound signal strength at time t, H(t) is the user's hearing curve response function at time t, M is the number of selected frequencies in the overall sound pressure level calculation, ω j is the weight of the jth frequency component, f j is the frequency of the jth frequency component, τ is the threshold of the user's hearing sensitivity, α is the slope parameter of the logistic regression function, and m=n; Step S109: Based on the gain G, adjust the output volume of the hearing aid through a digital signal processor.

2. The method according to claim 1, characterized in that: The step S103 also includes performing a wavelet transform on the sound feature vector V to obtain multi-scale frequency domain features. , among which, sensitive capture of instantaneous noise changes is achieved.

3. The method according to claim 1, characterized in that: In step S105, the overall sound pressure level SPL is calculated using the following formula: , where N is the total number of all calculated frequency components, E i is the energy spectrum of the i-th frequency component.

4. The method according to claim 1, characterized in that: In step S107, the following formula is used to express , where M is the number of frequencies selected in the overall sound pressure level calculation.

5. The method according to claim 1, characterized in that: In step S107 ,in is the complex form of the audio signal at time t, is its amplitude.

6. The method according to claim 1, characterized in that: In step S107 , where f0 is the initial frequency and Δf is the rate of frequency change.

7. The method according to claim 1, characterized in that: The hearing curve C of the user in step S107 is generated by the hearing test data fed back by the user, which is specifically achieved by the following steps: Conduct hearing tests on users to obtain their hearing thresholds at different frequencies; The user's hearing curve C is constructed by linear interpolation to smooth the changes in hearing thresholds at different frequencies.

8. The method according to claim 7, characterized in that: The method of constructing the user's hearing curve C by linear interpolation specifically includes: Enter the known frequency and hearing threshold, and set the value range of f to [f1,f k ]; For each frequency f that needs to be interpolated, find f i and f i+1 , where the value range of i is 1~k; Calculate t(f) using the interpolation formula; The obtained t(f) forms a smooth user hearing curve C.

9. The method according to claim 8, characterized in that The basic idea of ​​linear interpolation is that for any two known points The straight line passing through these two points is used to estimate the point between them, and t(f) is calculated using the following formula: , where t(f) is the estimated hearing threshold at frequency f.

10. A hearing aid system capable of automatically adjusting the volume according to the environment, comprising: At least one microphone, which is used to collect environmental noise data and generate sound feature vectors ,in Indicates The sound characteristics, The value range is 1~n; The frequency feature analysis module is used to perform fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature. , and extract the frequency components and their energy spectra ; The overall sound pressure level calculation module is used to calculate the sound pressure level according to the frequency domain characteristics. and energy spectrum Calculate the overall sound pressure level SPL of the ambient noise; A gain calculation module is used to calculate the gain according to the overall sound pressure level SPL and the user's hearing curve Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula: , where N is the total number of all calculated frequency components, E i is the energy spectrum of the ith frequency component, SPL ref is the reference sound pressure level, H avg is the average response of the user's hearing curve at frequency f, T is the upper limit of the time interval, S(t) is the ambient sound signal strength at time t, H(t) is the user's hearing curve response function at time t, M is the number of selected frequencies in the overall sound pressure level calculation, ω j is the weight of the jth frequency component, f j is the frequency of the jth frequency component, τ is the threshold of the user's hearing sensitivity, α is the slope parameter of the logistic regression function, and m=n; A digital signal processor is used to control the hearing aid output volume based on the gain G.

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