Hearing aid system and method capable of automatically adjusting volume according to environment

Abstract

The invention discloses a hearing aid system and method capable of automatically adjusting volume according to environment. The method comprises the following steps: collecting environment noise data through at least one microphone of a hearing aid; performing fast Fourier transform (FFT) on the sound feature vector V to calculate a frequency feature F = {f1, f2,..., fm}, and extracting a frequency component and an energy spectrum E = F2 thereof; calculating the total sound pressure level SPL of the environmental noise according to the frequency domain feature F and the energy spectrum E; adaptive compensation is carried out according to the total sound pressure level SPL and a hearing curve C = {c1, c2,..., ck} of a user, and a needed gain G is calculated; and based on the gain G, adjusting the output volume of the hearing aid through a digital signal processor. The method has the following advantages that real-time adaptability is achieved, the comfort level of the user can be improved, the voice recognition capacity is enhanced, and the method adapts to diversified use scenes.

Description

Technical Field

[0001] The present invention belongs to the field of computer system engineering, and in particular 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 of environmental noise, hearing impairment has gradually become a common health problem. According to statistics from the World Health Organization, about 466 million people in the world 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 that affect people's hearing experience. People have different needs for sound in different environments (such as noisy streets, quiet libraries, or bustling restaurants). Therefore, hearing aids need to dynamically adjust according to the real-time environmental noise conditions to provide the best hearing experience. However, traditional hearing aids cannot adapt to these changes in real time, resulting in users still feeling uncomfortable or unable to effectively hear important sounds, such as conversations or alarms, in noisy environments.

[0004] In order to improve this problem, researchers have begun to explore dynamic gain adjustment technology based on environmental noise in recent years. Summary of the invention

[0005] In view of the defects in the above-mentioned prior art, the present invention provides a method for automatically adjusting the volume according to the environment, comprising 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 fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2, ..., f m}, and extract the frequency component and its energy spectrum E = |F| 2 ;

[0008] Step S105, calculating the overall sound pressure level SPL of the ambient 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 k} Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula

[0010]

[0011] , where C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function;

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

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

[0014] 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] Wherein, 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] 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] In step S107, H(t)=C(f0+Δf·t), where f0 is the initial frequency and Δf is the frequency change rate.

[0019] The hearing curve C of the user in step S107 is generated by hearing test data fed back by the user, which is specifically achieved by the following steps:

[0020] Conduct hearing tests on users to obtain their hearing thresholds at different frequencies;

[0021] The user's hearing curve C is constructed by linear interpolation to smooth the changes in hearing thresholds at different frequencies.

[0022] The step of constructing the user's hearing curve C by linear interpolation specifically includes:

[0023] Enter the known frequency and hearing threshold, and set the value range of f to [f1,f k ];

[0024] For each frequency f that needs to be interpolated, find fi and fi+1;

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

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

[0027] The basic idea of ​​linear interpolation is that for any two known points (f i , t i ) and (f i+1 , t i+1 ) through these two points to estimate the point between them, and t(f) is calculated using the following formula:

[0028] where t(f) is the estimated hearing threshold at frequency f.

[0029] The present invention also proposes a hearing aid system that can automatically adjust the volume according to the environment, comprising:

[0030] At least one microphone 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;

[0031] The frequency characteristic analysis module is used to perform fast Fourier transform FFT on the sound characteristic vector V to calculate the frequency characteristic F={f1, f2, ..., f m}, and extract the frequency component and its energy spectrum E = |F| 2 ;

[0032] 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 characteristics F and the energy spectrum E;

[0033] The gain calculation module is used to calculate the gain according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ..., c k} performs adaptive compensation and calculates the required gain G, wherein the gain G is calculated using the following formula:

[0034]

[0035] , where C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function;

[0036] A digital signal processor is used to control the hearing aid output volume based on the gain G.

[0037] Compared with the prior art, the present invention has the following advantages:

[0038] Traditional hearing aids usually use fixed gain settings and cannot adapt to different environmental conditions in real time. This may cause users to not be able to hear important sounds clearly in noisy environments, or feel that the volume is too loud in quiet environments. Through the automatic adjustment mechanism of the present invention, the hearing aid can monitor the ambient noise in real time and dynamically adjust the volume according to the sound pressure level (SPL) of the current environment, ensuring that users can get the best hearing experience in various environments.

[0039] By using Fast Fourier Transform (FFT) to analyze the characteristics of ambient sound, the present invention can accurately identify the main sound components. Combined 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 hearing fatigue and discomfort caused by noise interference.

[0040] The present invention not only focuses on the overall sound pressure level of ambient noise, but also optimizes the sound enhancement within a specific frequency range by extracting frequency components and their energy spectra. By accurately calculating the user's hearing response at different frequencies, the hearing aid can more effectively amplify important sounds (such as conversations, alarms, etc.) and enhance the user's ability to recognize sounds in the surrounding environment. This is especially important for users who need to maintain communication in complex environments.

[0041] Due to the diversity of environmental noise, traditional hearing aids often have difficulty meeting the audio needs of various scenarios. Through the gain adjustment mechanism of this solution, hearing aids can quickly adapt to different scenarios (such as restaurants, streets, conference rooms, etc.). This flexibility ensures that users can enjoy clear sound in different environments and are no longer limited to specific usage occasions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] By reading the detailed description below with reference to the accompanying drawings, the above and other purposes, features and advantages of the exemplary embodiments of the present disclosure will become readily understood. In the accompanying drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0043] Figure 1 The flowchart of a method for automatically adjusting volume according to an environment according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme 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 part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] 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", "said" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings, and "multiple" generally includes at least two.

[0046] It should be understood that although the terms first, second, third, etc. may be used to describe ... in the embodiments of the present invention, 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 ....

[0047] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0048] As used herein, the words "if" and "if" may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0049] It should also be noted that the term "includes", "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, so that a commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprising a ..." do not exclude the existence of other identical elements in the commodity or device including the elements.

[0050] The optional embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0051] Embodiment 1

[0052] like Figure 1 As shown, the present invention discloses a method for automatically adjusting volume according to the environment, comprising the following steps:

[0053] 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;

[0054] Step S103: Perform fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2, ..., f m}, and extract the frequency component and its energy spectrum E = |F| 2 ;

[0055] Step S105, calculating the overall sound pressure level SPL of the ambient noise according to the frequency domain feature F and the energy spectrum E;

[0056] Step S107: According to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ..., c k} Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula

[0057]

[0058] , where C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function;

[0059] Step S109: Based on the gain G, adjust the output volume of the hearing aid through a digital signal processor.

[0060] Embodiment 2

[0061] The present invention provides a method for automatically adjusting volume according to the environment, comprising the following steps:

[0062] 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;

[0063] Step S103: Perform fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2, ..., f m}, and extract the frequency component and its energy spectrum E = |F| 2 ;

[0064] Step S105, calculating the overall sound pressure level SPL of the ambient noise according to the frequency domain feature F and the energy spectrum E;

[0065] Step S107: According to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ... c k} Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula

[0066]

[0067] , where C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function;

[0068] Among them, SPL ref Usually depends on the standard environmental noise level, which can be obtained through environmental measurement equipment or historical data. j It is usually determined based on the user's hearing characteristics and the spectral distribution of the ambient 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 gain response to frequency changes and is usually obtained through data analysis or machine learning model optimization.

[0069] Step S109: Based on the gain G, adjust the output volume of the hearing aid through a digital signal processor.

[0070] Wherein, the step S103 further includes performing a wavelet transform on the sound feature vector V to obtain a multi-scale frequency domain feature W={w1, w2, ..., w p}, to achieve sensitive capture of instantaneous noise changes.

[0071] In one embodiment, the wavelet transform extracts features by convolving the signal with a set of wavelet functions. Commonly used wavelet functions include Haar wavelet, Daubechies wavelet, etc. Wavelet transform can be divided into discrete wavelet transform (DWT) and continuous wavelet transform (CWT), and discrete wavelet transform is used here.

[0072] The output of the wavelet transform is the representation of the signal at different scales and locations. The formula for discrete wavelet transform can be expressed as:

[0073] Among them, W j，k is the coefficient of the wavelet transform, representing the features at the jth scale and the kth position; ψ j，k[n] is the wavelet function, usually expressed as: ψ j，k [n] = 2 -2j ψ(2 -j (nk)), where ψ(t) is the mother wavelet, j is the scale factor, and k is the location parameter.

[0074] By performing wavelet transform on the sound feature vector V, we can obtain the multi-scale frequency domain feature W, which is expressed as: W = {w1, w2, ..., w p}, specifically, w i It can be obtained by sampling the wavelet coefficients at different scales j and positions k: where j i and k i They correspond to the scale and position of the i-th feature respectively.

[0075] Wavelet transform can effectively capture instantaneous noise changes. For example, when analyzing environmental noise, instantaneous high-frequency noise changes can be identified by the changes in the wavelet coefficients W. By setting appropriate thresholds, these wavelet coefficients can be further processed to remove noise or extract specific features.

[0076] The overall sound pressure level SPL is calculated using the following formula in step S105:

[0077] Where N is the number of frequency components, E i is the energy spectrum of the i-th frequency component.

[0078] Wherein, 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.

[0079] 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.

[0080] In step S107, H(t)=C(f0+Δf·t), where f0 is the initial frequency and Δf is the frequency change rate.

[0081] The hearing curve C of the user in step S107 is generated by hearing test data fed back by the user, which is specifically achieved by the following steps:

[0082] Conduct hearing tests on users to obtain their hearing thresholds at different frequencies;

[0083] The user's hearing curve C is constructed by linear interpolation to smooth the changes in hearing thresholds at different frequencies.

[0084] The step of constructing the user's hearing curve C by linear interpolation specifically includes:

[0085] Enter the known frequency and hearing threshold, and set the value range of f to [f1,f k ];

[0086] For each frequency f that needs to be interpolated, find fi and fi+1;

[0087] Calculate t(f) using the interpolation formula;

[0088] The obtained t(f) forms a smooth user hearing curve C.

[0089] The basic idea of ​​linear interpolation is that for any two known points (f i , t i ) and (f i+1 , t i+1 ) through these two points to estimate the point between them, and t(f) is calculated using the following formula:

[0090] where t(f) is the estimated hearing threshold at frequency f.

[0091] In one embodiment, it is assumed that the user's hearing test data is as follows:

[0092] f = {1000, 2000, 4000}

[0093] T = {30, 20, 10} (corresponding hearing threshold)

[0094] If you want to estimate the hearing threshold at a frequency of 1500 Hz:

[0095] Interpolate between f1 = 1000 Hz and f2 = 2000 Hz:

[0096] · but

[0097] ·

[0098] Therefore, t(1500)=25dB.

[0099] Embodiment 3

[0100] The present invention also proposes a hearing aid system that can automatically adjust the volume according to the environment.

[0101] At least one microphone 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;

[0102] The frequency characteristic analysis module is used to perform fast Fourier transform FFT on the sound characteristic vector V to calculate the frequency characteristic F={f1, f2, ..., f m}, and extract the frequency component and its energy spectrum E = |F| 2 ;

[0103] 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 characteristics F and the energy spectrum E;

[0104] A gain calculation module is used to calculate the gain according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ..., c k} Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula

[0105]

[0106] , where C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function;

[0107] A digital signal processor is used to control the hearing aid output volume based on the gain G.

[0108] Embodiment 4

[0109] An embodiment of the present disclosure provides a non-volatile computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the method steps described in the above embodiment.

[0110] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with 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, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0111] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0112] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (AN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0113] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0114] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0115] The above introduces the preferred embodiments of the present invention, which is intended to make the spirit of the present invention clearer and easier to understand, but is not intended to limit the present invention. All modifications, substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection outlined by the claims attached to 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 V = {υ1,υ2, ...,υ n }, where υ i represents the i-th sound feature; Step S103: Perform fast Fourier transform (FFT) on the sound feature vector V to calculate the frequency feature F = {f1, f2, ..., f m }, and extract the frequency component and its energy spectrum E = |F| 2 ; Step S105, calculating the overall sound pressure level SPL of the ambient noise according to the frequency domain feature F and the energy spectrum E; Step S107: According to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ..., c k } Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula ， Among them, C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function; 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 further includes performing a wavelet transform on the sound feature vector V to obtain a multi-scale frequency domain feature W={ω1, ω2, ..., ω p }, to achieve sensitive capture of instantaneous noise changes.

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 number of 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 selected frequencies.

5. The method according to claim 1, characterized in that: 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.

6. The method according to claim 1, characterized in that: In step S107, H(t)=C(f0+Δf·t), wherein f0 is the initial frequency and Δf is the frequency change rate.

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 fi and fi+1; 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 (f i , t i ) and (f i+1 , t i+1 ) through these two points 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 is used to collect environmental noise data and generate a sound feature vector V = {υ1,υ2, ...,υ n }, where υ i represents the i-th sound feature; The frequency characteristic analysis module is used to perform fast Fourier transform FFT on the sound characteristic vector V to calculate the frequency characteristic F={f1, f2, ..., f m }, and extract the frequency component and its energy spectrum E = |F| 2 ; 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 characteristics F and the energy spectrum E; A gain calculation module is used to calculate the gain according to the overall sound pressure level SPL and the user's hearing curve C = {c1, c2, ..., c k } Perform adaptive compensation and calculate the required gain G, where the gain G is calculated using the following formula ， Among them, C i Indicates that the user is at frequency f i The hearing response under the condition of 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 frequency components, and w 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, and α is the slope parameter of the logistic regression function; A digital signal processor is used to control the hearing aid output volume based on the gain G.

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