TEOAE feedback signal generation method and device based on software simulation

Abstract

The present application discloses a method and device for generating TEOAE feedback signals based on software simulation, which belongs to the field of acoustic signal processing technology, including: preprocessing the audio signal received by the audio input device, and determining the intensity of the stimulus signal according to the preprocessed audio signal; searching for the feedback intensity value matching the intensity of the stimulus signal in a preset feedback intensity relationship table; calculating the output signal value intensity according to the feedback intensity value, and setting the waveform type and waveform parameters of the output signal; generating an output signal, and evaluating the feedback effect according to the output signal; if the evaluation result shows that the feedback effect does not reach the set target, adjusting the feedback intensity relationship table and the waveform parameters and re-evaluating the feedback effect until the feedback effect reaches the set target. The present application can generate a TEOAE feedback signal containing a specific frequency component, and adjust the SNR value of the frequency point according to user needs, thereby improving the accuracy and reliability of the hearing test.

Description

Technical Field

[0001] The present application relates to the technical field of acoustic signal processing, and in particular to a method and device for generating a TEOAE feedback signal based on software simulation. Background Art

[0002] Hearing health assessment plays a vital role in modern medicine, and transient evoked otoacustic emission (TEOAE), as a non-invasive and efficient hearing test method, has been widely used in newborn hearing screening, hearing impairment diagnosis, and hearing rehabilitation effect evaluation. The TEOAE test assesses the functional status of the cochlea by sending short sound stimulation to the cochlea of ​​the subject and detecting the resulting weak sound response, namely the TEOAE feedback signal.

[0003] However, the existing TEOAE testing technology has the following shortcomings:

[0004] 1. Existing TEOAE detection equipment mainly relies on hardware to achieve signal detection and feedback. The limitation of hardware performance makes it impossible to provide accurate feedback signals. This inaccuracy may lead to inaccurate hearing test results.

[0005] 2. Most existing equipment uses fixed test parameters and cannot flexibly adjust the signal-to-noise ratio (SNR) value of the frequency point according to the requirements of the setter. SNR is a key indicator for measuring signal quality. It reflects the ratio between signal strength and background noise strength. In TEOAE testing, SNR values ​​at different frequency points have different importance for assessing hearing health. Therefore, this limitation greatly limits the flexibility and customizability of hearing tests.

[0006] In addition, the existing technology lacks an effective means to verify the performance of the Derived Nonlinearity Response (DNLR) algorithm. The DNLR algorithm is a technology used to process otoacoustic emission signals and plays an important role in TEOAE measurements, especially in eliminating stimulus artifacts. However, the existing technology does not provide a clear solution to determine whether the DNLR algorithm can correctly process signals of different intensities. Summary of the invention

[0007] The purpose of the present application is to provide a method and device for generating TEOAE feedback signals based on software simulation, so as to solve the problem in the prior art that TEOAE detection equipment cannot provide accurate feedback signals, which may lead to inaccurate hearing test results.

[0008] Another object of the present application is to provide a method and device for generating a TEOAE feedback signal based on software simulation, so as to solve the problem that most TEOAE detection equipment in the prior art adopts fixed test parameters and cannot flexibly adjust the signal-to-noise ratio of the frequency point according to the requirements of the setter.

[0009] Another object of the present application is to provide a method and device for generating TEOAE feedback signals based on software simulation, so as to solve the problem in the prior art of lacking an effective method for verifying the performance of the nonlinear differential averaging method.

[0010] To achieve the above objectives, this application adopts the following technical solutions:

[0011] In a first aspect of the present application, a method for generating a TEOAE feedback signal based on software simulation is provided, comprising the following steps:

[0012] Preprocessing the audio signal received by the audio input device, and determining the intensity of the stimulation signal according to the preprocessed audio signal;

[0013] Obtaining a preset feedback intensity relationship table, and searching the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table;

[0014] Calculating the output signal value strength according to the feedback strength value, and setting the waveform type and waveform parameters of the output signal based on the output signal value strength;

[0015] generating an output signal according to the waveform type and waveform parameters, and evaluating the feedback effect according to the output signal;

[0016] If the evaluation result shows that the feedback effect does not reach the set target, the feedback intensity relationship table and the waveform parameters are adjusted and the feedback effect is re-evaluated until the feedback effect reaches the set target.

[0017] Preferably, the step of preprocessing the audio signal received by the audio input device and determining the intensity of the stimulation signal according to the preprocessed audio signal comprises:

[0018] Collecting audio signals received by an audio input device and converting the audio signals into digital signals;

[0019] Filtering the digital signal, and extracting a first signal strength from the filtered digital signal;

[0020] It is determined whether the first signal strength exceeds a set threshold, and if so, the stimulation signal strength is extracted from the filtered digital signal.

[0021] Preferably, the step of setting the waveform type and waveform parameters of the output signal based on the output signal value strength includes:

[0022] A matching output signal waveform is selected according to the output signal value strength, and waveform parameters are set. The waveform parameters include sampling frequency, signal duration, frequency component list, and frequency component strength list.

[0023] Preferably, generating an output signal according to the waveform type and waveform parameters comprises:

[0024] Calculating the number of sampling points within the signal duration according to the sampling frequency and the signal duration, and generating a time axis based on the number of sampling points;

[0025] A mathematical expression of an output signal is determined according to the waveform type, and corresponding data in the time axis, frequency component list and intensity list are input into the mathematical expression to obtain an output signal.

[0026] Preferably, the step of evaluating the feedback effect according to the output signal comprises:

[0027] Inputting the output signal into an audio playback device for playback to obtain a sound signal;

[0028] Performing spectrum analysis on the acoustic signal using fast Fourier transform to obtain spectrum data, and extracting initial signal values ​​of each frequency component from the spectrum data;

[0029] The deviation between each initial signal value and its corresponding expected output value is calculated, and the feedback effect is determined based on the calculation result.

[0030] Preferably, the step of determining the feedback effect according to the calculation result comprises:

[0031] When the deviations between the initial signal values ​​and their corresponding expected output values ​​are not all within the set range, it is determined that the feedback effect does not reach the set target, and the frequency components corresponding to the initial signal values ​​whose deviations exceed the set range are taken as the objects to be adjusted.

[0032] Preferably, the adjusting the feedback intensity relationship table and the waveform parameters and re-evaluating the feedback effect comprises:

[0033] Optimizing the initial signal value of the frequency component to be adjusted according to the deviation, and adjusting the feedback intensity value corresponding to the frequency component to be adjusted in the feedback intensity relationship table and the signal duration, frequency component list and frequency component intensity list in the waveform parameters according to the optimized signal value;

[0034] The output signal is recalculated according to the adjustment result, and the feedback effect is evaluated based on the new output signal.

[0035] In a second aspect of the present application, a TEOAE feedback signal generating device based on software simulation is provided, comprising:

[0036] A preprocessing module, used to preprocess the audio signal received by the audio input device, and determine the intensity of the stimulation signal according to the preprocessed audio signal;

[0037] A search module, used to obtain a preset feedback intensity relationship table, and search the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table;

[0038] A setting module, used to calculate the output signal value strength according to the feedback strength value, and set the waveform type and waveform parameters of the output signal based on the output signal value strength;

[0039] An evaluation module, used to generate an output signal according to the waveform type and waveform parameters, and to evaluate the feedback effect according to the output signal;

[0040] The adjustment module is used to adjust the feedback intensity relationship table and waveform parameters and re-evaluate the feedback effect if the evaluation result shows that the feedback effect does not reach the set target, until the feedback effect reaches the set target.

[0041] According to a third aspect of the present application, an electronic device is provided, comprising a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement a TEOAE feedback signal generation method based on software simulation as described in any one of the above.

[0042] In a fourth aspect of the present application, a computer-readable storage medium storing a computer program is provided, wherein the computer program enables a computer to implement a TEOAE feedback signal generation method based on software simulation as described in any one of the above when executed.

[0043] This application has the following beneficial effects:

[0044] 1. This application uses scientific and reasonable threshold settings to ensure that feedback is triggered only when the signal strength reaches a certain level, effectively avoiding false triggering or missed triggering, thereby improving the accuracy and reliability of signal recognition. Different thresholds can also be set to verify the response of the device under different signal strengths, thereby verifying the eligibility of the DNLR algorithm, ensuring the reliability of the TEOAE detection device in actual applications, and improving users' trust in the TEOAE detection device.

[0045] 2. This application optimizes the signal recognition process to ensure that the TEOAE detection equipment can work stably in practical applications and will not cause erroneous results due to false triggering or missed triggering.

[0046] 3. In this application, users can customize the feedback intensity relationship table and waveform parameters according to their needs, which meets different test requirements and improves the adaptability and flexibility of TEOAE detection equipment.

[0047] 4. The present application can generate a composite signal containing multiple frequency components, which can be applied to more complex test scenarios, such as the detection of TEOAE test equipment, thereby improving the test capability and application scope of TEOAE detection equipment.

[0048] 5. This application has a feedback adjustment mechanism, which enables users to adjust the feedback intensity relationship table and waveform parameters according to the effect evaluation results, thereby optimizing the feedback effect and improving the adaptability and optimization capabilities of the device. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0050] Figure 1 It is a flowchart of a method for generating a TEOAE feedback signal based on software simulation provided in an embodiment of the present application;

[0051] Figure 2 It is a structural schematic diagram of a TEOAE feedback signal generating device based on software simulation provided in an embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of an electronic device for implementing a TEOAE feedback signal generation method based on software simulation provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] To make the technical solution of the present application clearer, the present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The terms "first", "second", etc. in the claims and specification of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances. This is only to describe the distinction method used when describing objects with the same attributes in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that a process, method, system, product or device containing a series of units is not necessarily limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or devices.

[0054] Example 1

[0055] Figure 1 FIG. 1 is a flow chart of a method for generating a TEOAE feedback signal based on software simulation provided in this embodiment. Figure 1 The method for generating TEOAE feedback signals based on software simulation can be executed by a computer or a server, or software on a computer or a server, and specifically includes the following steps:

[0056] S110, preprocessing the audio signal received by the audio input device, and determining the intensity of the stimulation signal according to the preprocessed audio signal;

[0057] S120, obtaining a preset feedback intensity relationship table, and searching the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table;

[0058] S130, calculating the output signal value strength according to the feedback strength value, and setting the waveform type and waveform parameters of the output signal based on the output signal value strength;

[0059] S140, generating an output signal according to the waveform type and waveform parameters, and evaluating the feedback effect according to the output signal;

[0060] S150: If the evaluation result shows that the feedback effect does not reach the set target, the feedback intensity relationship table and the waveform parameters are adjusted and the feedback effect is re-evaluated until the feedback effect reaches the set target.

[0061] This embodiment generates a feedback signal containing specific frequency components by simulating the response of the human ear to the TEOAE stimulation signal, which not only realizes scientific and reasonable threshold setting to ensure that feedback is triggered only when the signal strength reaches a certain level, thereby effectively avoiding false triggering or missed triggering and improving the accuracy and reliability of signal recognition, but also allows users to customize the feedback intensity relationship table and waveform parameters according to their needs, meeting different test requirements and improving the adaptability and flexibility of TEOAE detection equipment. At the same time, it also has a feedback adjustment mechanism, allowing users to adjust the feedback intensity relationship table and waveform parameters according to the feedback effect evaluation results, thereby optimizing the feedback effect and improving the adaptability and optimization ability of the equipment.

[0062] Furthermore, preprocessing the audio signal received by the audio input device and determining the intensity of the stimulation signal according to the preprocessed audio signal includes:

[0063] Collect the audio signal received by the audio input device and convert the audio signal into a digital signal;

[0064] Filtering the digital signal, and extracting a first signal strength from the filtered digital signal;

[0065] It is determined whether the first signal strength exceeds a set threshold, and if so, the stimulation signal strength is extracted from the filtered digital signal.

[0066] First, an audio input device is connected to a collection device. Preferably, the audio input device is a microphone. The collection device is used to collect the audio signal received by the microphone in real time, and the audio signal is converted into a digital signal. Then, the converted digital signal is filtered to remove noise and interference and improve signal quality. The filtered digital signal is then feature extracted to obtain a first signal strength. Preferably, the peak equivalent sound pressure level (peSPL) is calculated based on the filtered digital signal. PeSPL is a measurement method of sound signal strength, especially when processing short-term sound signals. Therefore, in this embodiment, obtaining the first signal strength is essentially calculating peSPL.

[0067] The threshold of signal strength is set according to actual needs to determine whether to trigger feedback. Preferably, in this embodiment, the threshold is set to 75dB peSPL. It should be noted here that the basic idea of ​​the nonlinear differential averaging method DNLR is that when the stimulus signal intensity is weak, the acoustic intensity of the TEOAE feedback signal increases with the increase of the stimulus signal intensity; when the stimulus signal intensity increases to about 70dB peSPL, the acoustic intensity of the TEOAE feedback signal tends to saturation and no longer increases with the increase of the stimulus signal intensity. The DNLR algorithm is the only way to eliminate artifacts. At present, all devices that implement TEOAE testing cannot do without this algorithm. Therefore, only if the threshold is set scientifically and reasonably can false triggering or missed triggering be effectively avoided. Of course, different thresholds can also be set to verify the response of the TEOAE detection equipment under different signal intensities, and then determine whether the DNLR algorithm can correctly process the signal.

[0068] The obtained first signal strength is compared with the set threshold. If the first signal strength exceeds the set threshold, it means that feedback will be triggered, that is, there is a stimulation signal in the filtered digital signal, and the stimulation signal is extracted from the filtered digital signal to obtain the stimulation signal strength.

[0069] When multiple different thresholds are set, if the stimulus signal is judged to exist in the filtered digital signal at a high threshold, but not at a low threshold, the DNLR algorithm is judged to be qualified because it can correctly process signals of different intensities. By verifying the legitimacy of the DNLR algorithm, the reliability of TEOAE detection equipment in practical applications can be ensured, thereby improving users' trust in the equipment.

[0070] Next, obtain a preset feedback intensity relationship table, which can also be user-defined, and contains different stimulus signal intensities and their corresponding feedback intensity values. According to the extracted stimulus signal intensity, find the corresponding feedback intensity value in the table. After finding it, calculate the output signal value intensity according to the feedback intensity value found. Specifically, correct the feedback intensity value to obtain the output signal value intensity, and then select the appropriate output waveform type according to the output signal value intensity and actual needs, and set the corresponding waveform parameters. In the process of generating TEOAE feedback signals, the final output is a signal, but this signal is usually represented in the form of a waveform. Specifically, the output signal is a time series, representing the sound pressure values ​​at different time points. This time series can be visualized as a waveform graph, or it can be saved as an audio file (such as a WAV file) for further use or playback.

[0071] The waveform parameters include sampling frequency (sampling_rate), signal duration (duration), frequency component list (frequencies) and intensity list (amplitudes) of corresponding frequency components. Preferably, in this embodiment, the output waveform type is a sine waveform, the sampling frequency is 64000 Hz, the signal duration is 0.008 seconds, the frequency component list is [1000, 1500, 2000, 3000, 4000] Hz, and the elements represent the frequency components contained in the signal. The intensity list of the frequency components is [0.9, 0.05, 0.05, 0.05, 0.05], and the elements represent the intensity of the frequency components. The sampling frequency is a system setting and cannot be changed. The signal duration, frequency component list and frequency component intensity list can all be adjusted to meet the detection requirements of the TEOAE detection equipment.

[0072] Further, generating an output signal according to the waveform type and the waveform parameters includes:

[0073] Calculate the number of sampling points within the signal duration according to the sampling frequency and the signal duration, and generate a time axis based on the number of sampling points;

[0074] A mathematical expression of an output signal is determined according to the waveform type, and corresponding data in the time axis, frequency component list and intensity list are input into the mathematical expression to obtain an output signal.

[0075] The number of sampling points within the signal duration is calculated according to the sampling frequency and the signal duration. Specifically, the number of sampling points = sampling frequency * signal duration. A time axis is generated using the linspace function in the Numpy library. The length of the time axis is the number of sampling points within the signal duration. Numpy is a library in the programming language Python, which provides a large number of mathematical functions and operations, especially operations on arrays (multidimensional arrays). In the Numpy library, the linspace function is used to generate an arithmetic progression that is evenly distributed between the specified starting value (start) and the ending value (stop) and contains a specified number of samples. In simple terms, the linspace function generates a one-dimensional array between the starting value and the ending value at equal intervals. The number of elements in the array is specified by the user. At the same time, a zero array (signal) with the same length as the time axis is created to store the generated signal values.

[0076] Based on the selected output waveform type, for each frequency component, a corresponding mathematical expression is used to generate a signal. In this embodiment, the output waveform type is a sine waveform, and a sine function is used to generate a signal. Specifically:

[0077] sifnal+=amp*sin(2*π*f req *t),

[0078] Among them, sifnal+ means adding the signal value corresponding to each frequency component in the frequency component list to the zero array signal, amp is an array variable, in which each element corresponds to the intensity of a frequency component. The array can be used to control the intensity of a specific frequency component individually to generate a single frequency signal, thereby completing the test of a single frequency component, or to control the intensity of multiple frequency components at the same time to generate a composite signal, thereby combining to complete the test of multiple frequency components, f req represents the frequency of the frequency component, and t represents the time point on the time axis. By generating a composite signal containing multiple frequency components, it can be applied to more complex test scenarios, thus increasing the application range of TEOAE detection equipment.

[0079] Furthermore, the feedback effect is evaluated according to the output signal, including:

[0080] Input the output signal into an audio playback device for playback to obtain a sound signal;

[0081] The acoustic signal is processed by using fast Fourier transform to obtain spectrum data, and the initial signal value of each frequency component is extracted from the spectrum data;

[0082] The deviation between each initial signal value and its corresponding expected output value is calculated, and the feedback effect is determined based on the calculation result.

[0083] The calculated output waveform is output to an audio playback device. Preferably, the audio playback device is a speaker, which emits sound and controls the sound according to demand, such as volume. The sound signal in the speaker is then collected through a microphone or other acoustic sensor, while ensuring that the collected sound signal can accurately reflect the acoustic environment in the speaker. Through the sound control function, the output sound can be controlled according to demand to achieve the expected effect, thereby improving the practicality and user experience of the TEOAE detection equipment.

[0084] The collected sound signal is subjected to spectrum analysis using Fast Fourier Transform (FFT) to obtain spectrum data. FFT is a mathematical transformation that converts time domain signals into frequency domain signals. It can provide the intensity distribution of the signal at different frequencies. The initial signal value of each frequency component, namely the spectrum signal value, is calculated based on the obtained spectrum data. In essence, it refers to determining and quantifying the intensity (or amplitude) corresponding to each frequency component from the spectrum data of the signal. The spectrum is a distribution diagram that describes various frequency components in the signal and their corresponding intensity (or amplitude). In the spectrum diagram, the horizontal axis represents the frequency component, and the vertical axis represents the intensity (or amplitude) of the corresponding frequency component. Then, the deviation of each spectrum signal value from its corresponding expected output value is calculated. Preferably, E i =H i -H i set, where E i represents the ith frequency error, H i represents the i-th spectrum signal value, H i set represents the expected output value corresponding to the i-th frequency component, i takes 1000 Hz, 1500 Hz, 2000 Hz, 3000 Hz and 4000 Hz respectively, and the feedback effect is evaluated according to the deviation.

[0085] Further, the feedback intensity relationship table and waveform parameters are adjusted and the feedback effect is re-evaluated, including:

[0086] Optimize the initial signal value of the frequency component to be adjusted according to the deviation, and adjust the feedback intensity corresponding to the frequency component to be adjusted in the feedback intensity relationship table and the signal duration and intensity list of the frequency component in the waveform parameters according to the optimized signal value;

[0087] The output signal is recalculated according to the adjustment result, and the feedback effect is evaluated based on the new output signal.

[0088] If the obtained deviation exceeds the set range, it is determined that the feedback effect does not reach the set target. Preferably, the set range is E iLess than ±1dB, and the frequency components corresponding to the initial signal values ​​whose deviations exceed the set range are taken as objects to be adjusted, and the initial signal values ​​of each object to be adjusted are optimized. Specifically, for each object to be adjusted, if its deviation is positive and too large, it is considered that its signal value is too large, and the signals of these frequency components are weakened; if its deviation is negative and too large, it is considered that its signal value is too small, and the signals of these frequency components are enhanced. The optimization process may require multiple iterations until a satisfactory output effect is achieved.

[0089] According to the optimized spectrum signal value, the feedback intensity in the feedback intensity relationship table and the signal duration, frequency component list and frequency component intensity list in the waveform parameters are adjusted.

[0090] After all adjustments are completed, re-evaluate the feedback effect to determine whether the feedback effect has reached the set target. If the effect is still not good, repeat the parameter adjustment and feedback effect evaluation steps until the feedback effect reaches the set target.

[0091] The TEOAE detection equipment is equipped with a feedback adjustment mechanism, which enables users to adjust the feedback intensity relationship table and waveform parameters according to the effect evaluation results, thereby optimizing the feedback effect and improving the adaptability and optimization capabilities of the equipment.

[0092] Example 2

[0093] Figure 2 FIG. 1 is a schematic diagram of a structure of a TEOAE feedback signal generating device based on software simulation provided in this embodiment. Figure 2 As shown, the TEOAE feedback signal generating device based on software simulation includes:

[0094] A preprocessing module, used to preprocess the audio signal received by the audio input device, and determine the intensity of the stimulation signal according to the preprocessed audio signal;

[0095] A search module, used to obtain a preset feedback intensity relationship table, and search the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table;

[0096] A setting module, used to calculate the output signal value strength according to the feedback strength value, and set the waveform type and waveform parameters of the output signal based on the output signal value strength;

[0097] An evaluation module, used for generating an output signal according to a waveform type and waveform parameters, and performing feedback effect evaluation according to the output signal;

[0098] The adjustment module is used to adjust the feedback intensity relationship table and waveform parameters and re-evaluate the feedback effect if the evaluation result shows that the feedback effect does not reach the set target, until the feedback effect reaches the set target.

[0099] This embodiment is used to implement the methods provided by all the above embodiments, and has the corresponding beneficial effects of the above methods. For technical details not fully described in this embodiment, please refer to the methods provided by all the above embodiments of this application.

[0100] Example 3

[0101] Figure 3 is a schematic diagram of the structure of an electronic device provided in this embodiment. Figure 3 As shown, the electronic device includes a memory 301 and a processor 302, wherein the memory 301 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 302 to implement the above-mentioned TEOAE feedback signal generation method based on software simulation.

[0102] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the electronic device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0103] A computer-readable storage medium storing a computer program, wherein the computer program enables a computer to implement a TEOAE feedback signal generation method based on software simulation as described above when executed.

[0104] Exemplarily, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the memory 301 and executed by the processor 302, and the input interface 305 and the output interface 306 complete the I / O interface transmission of data to complete the present application. One or more modules / units may be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device.

[0105] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may include, but is not limited to, a memory 301 and a processor 302. Those skilled in the art may understand that this embodiment is only an example of a computer device and does not constitute a limitation on the computer device. The computer device may include more or fewer components, or a combination of certain components, or different components. For example, the computer device may also include an input device 307, a network access device, a bus, etc.

[0106] The processor 302 may be a central processing unit (CPU), or other general-purpose processors 302, digital signal processors 302 (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor 302 may be a microprocessor 302, or the processor 302 may be any conventional processor 302, etc.

[0107] The memory 301 may be an internal storage unit of a computer device, such as a hard disk or memory of the computer device. The memory 301 may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Furthermore, the memory 301 may include both an internal storage unit of the computer device and an external storage device. The memory 301 is used to store computer programs and other programs and data required by the computer device. The memory 301 may also be used to temporarily store in the output device 308. The aforementioned storage media include various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory ROM 303, a random access memory RAM 304, a disk or an optical disk.

[0108] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for generating TEOAE feedback signals based on software simulation, characterized in that: The following steps are involved: Preprocessing the audio signal received by the audio input device, and determining the intensity of the stimulation signal according to the preprocessed audio signal; Obtaining a preset feedback intensity relationship table, and searching the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table; Calculating the output signal value strength according to the feedback strength value, and setting the waveform type and waveform parameters of the output signal based on the output signal value strength, wherein the waveform parameters include sampling frequency, signal duration, frequency component list and frequency component strength list; generating an output signal according to the waveform type and waveform parameters, and evaluating the feedback effect according to the output signal; If the evaluation result shows that the feedback effect does not reach the set target, the feedback intensity relationship table and the waveform parameters are adjusted and the feedback effect is re-evaluated until the feedback effect reaches the set target; Wherein, the evaluating of feedback effect according to the output signal comprises: Inputting the output signal into an audio playback device for playback to obtain a sound signal; Performing spectrum analysis on the acoustic signal using fast Fourier transform to obtain spectrum data, and extracting initial signal values ​​of each frequency component from the spectrum data; Calculate the deviation between each initial signal value and its corresponding expected output value, and determine the feedback effect based on the calculation result, including: When the deviations between the initial signal values ​​and the corresponding expected output values ​​are not all within the set range, it is determined that the feedback effect does not reach the set target, and the frequency components corresponding to the initial signal values ​​whose deviations exceed the set range are taken as the objects to be adjusted; The adjusting the feedback intensity relationship table and the waveform parameters and re-evaluating the feedback effect includes: Optimizing the initial signal value of the frequency component to be adjusted according to the deviation, and adjusting the feedback intensity value corresponding to the frequency component to be adjusted in the feedback intensity relationship table and the signal duration, frequency component list and frequency component intensity list in the waveform parameters according to the optimized signal value; The output signal is recalculated according to the adjustment result, and the feedback effect is evaluated based on the new output signal.

2. A method for generating TEOAE feedback signals based on software simulation according to claim 1, characterized in that: The step of preprocessing the audio signal received by the audio input device and determining the intensity of the stimulation signal according to the preprocessed audio signal comprises: Collecting audio signals received by an audio input device and converting the audio signals into digital signals; Filtering the digital signal, and extracting a first signal strength from the filtered digital signal; It is determined whether the first signal strength exceeds a set threshold, and if so, the stimulation signal strength is extracted from the filtered digital signal.

3. A method for generating TEOAE feedback signals based on software simulation according to claim 1, characterized in that: The step of setting the waveform type and waveform parameters of the output signal based on the output signal value strength includes: A matching output signal waveform is selected according to the output signal value strength, and waveform parameters are set.

4. A method for generating TEOAE feedback signals based on software simulation according to claim 3, characterized in that: The generating an output signal according to the waveform type and the waveform parameters comprises: Calculating the number of sampling points within the signal duration according to the sampling frequency and the signal duration, and generating a time axis based on the number of sampling points; A mathematical expression of an output signal is determined according to the waveform type, and corresponding data in the time axis, frequency component list and intensity list are input into the mathematical expression to obtain an output signal.

5. A TEOAE feedback signal generating device based on software simulation, characterized in that: include: A preprocessing module, used to preprocess the audio signal received by the audio input device, and determine the intensity of the stimulation signal according to the preprocessed audio signal; A search module, used to obtain a preset feedback intensity relationship table, and search the feedback intensity value matching the stimulation signal intensity in the feedback intensity relationship table; A setting module, used to calculate the output signal value strength according to the feedback strength value, and set the waveform type and waveform parameters of the output signal based on the output signal value strength, wherein the waveform parameters include sampling frequency, signal duration, frequency component list and frequency component strength list; An evaluation module, used to generate an output signal according to the waveform type and waveform parameters, and to evaluate the feedback effect according to the output signal; An adjustment module, for adjusting the feedback intensity relationship table and the waveform parameters and re-evaluating the feedback effect if the evaluation result shows that the feedback effect does not reach the set target, until the feedback effect reaches the set target; The evaluation module performs feedback effect evaluation according to the output signal, including: Inputting the output signal into an audio playback device for playback to obtain a sound signal; Performing spectrum analysis on the acoustic signal using fast Fourier transform to obtain spectrum data, and extracting initial signal values ​​of each frequency component from the spectrum data; Calculate the deviation between each initial signal value and its corresponding expected output value, and determine the feedback effect based on the calculation result, including: When the deviations between the initial signal values ​​and the corresponding expected output values ​​are not all within the set range, it is determined that the feedback effect does not reach the set target, and the frequency components corresponding to the initial signal values ​​whose deviations exceed the set range are taken as the objects to be adjusted; The adjusting module adjusts the feedback intensity relationship table and waveform parameters and re-evaluates the feedback effect, including: Optimizing the initial signal value of the frequency component to be adjusted according to the deviation, and adjusting the feedback intensity value corresponding to the frequency component to be adjusted in the feedback intensity relationship table and the signal duration, frequency component list and frequency component intensity list in the waveform parameters according to the optimized signal value; The output signal is recalculated according to the adjustment result, and the feedback effect is evaluated based on the new output signal.

6. An electronic device, characterized in that: It comprises a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement a TEOAE feedback signal generation method based on software simulation as described in any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables a computer to implement a method for generating a TEOAE feedback signal based on software simulation as claimed in any one of claims 1 to 4 when executed.

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