CN115802267A - Automatic calibration method and system for acoustic characteristics of hearing aid - Google Patents
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Abstract
The embodiment of the invention provides an automatic calibration method and system for acoustic characteristics of a hearing aid, wherein the method comprises the following steps: respectively carrying out online testing on the gold sample hearing aid and the hearing aid to be tested under the same background, respectively comparing the SPK curve and the MIC curve obtained by the two tests to obtain a difference value curve in a comparison result to form a difference value sequence, selecting a preset number of frequency points, and determining a standard amplitude value and a standard phase based on the positions of the frequency points; determining initial filter parameters according to the detection parameters, sequentially taking the parameters as iteration factors to iterate, calculating iteration amplitude and iteration phase after each iteration, comparing the iteration amplitude and the iteration phase with standard amplitude and standard phase, and taking the comparison result as a convergence result; and writing the parameters after iterative convergence into the hearing aid to be detected to finish automatic calibration. By adopting the method, the difference of the sensitivity can be compensated through calibrating the gain of the chip, so that the acoustic characteristic effect of mass production hearing aids is consistent with the research and development effect, and the consistency of the acoustic effect of the hearing aids is ensured.
Description
Technical Field
The invention relates to the technical field of hearing aids, in particular to an automatic calibration method and system for acoustic characteristics of a hearing aid.
Background
At present, a large number of hearing aids exist in the market, microphones, loudspeakers and cavities of one hearing aid are determined, however, in the mass production stage and during mass hearing aid production, incoming materials of the microphones and the loudspeakers cannot ensure the consistency of incoming materials of each batch, certain sensitivity differences exist among the microphones and the loudspeakers, most of the hearing aids are manually assembled, and the cavities of the hearing aids are influenced to a certain extent along with the assembly, so that the acoustic characteristics of the hearing aids are influenced;
because the chip of audiphone is batch production, acquiescence gain is unchangeable, because sensitivity of microphone, loudspeaker in batches can't be accomplished unanimously, in the test process, though can adjust the gain effect of audiphone through adjusting microphone gain, the regulation of gain is limited all the time, because the gain is direct action on the microphone passageway, it can influence the audiphone acoustic characteristic of full frequency channel to adjust the gain, can't adjust to some frequency points, frequency channel, just lead to the audiphone acoustic test's yield not ideal all the time.
Disclosure of Invention
In view of the problems in the prior art, embodiments of the present invention provide a method and a system for automatically calibrating acoustic characteristics of a hearing aid.
The embodiment of the invention provides an automatic calibration method for acoustic characteristics of a hearing aid, which comprises the following steps:
carrying out online test on the golden hearing aid and the Bluetooth adapter under a preset test background, and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test;
connecting the hearing aid to be detected and the Bluetooth adapter on line, setting the test background to perform the on-line test, acquiring an SPK (sinusoidal pulse code) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference curve in a comparison result;
sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining the standard parameters based on the positions of the frequency points;
determining the frequency, the gain and the quality factor of an initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation;
and writing the frequency, the gain and the quality factor after the iterative convergence into the hearing aid to be detected to finish automatic calibration.
In one embodiment, the method further comprises:
and obtaining an amplitude difference function by taking the difference between the iteration amplitude and the standard amplitude after each iteration, obtaining a phase difference function by taking the difference between the iteration phase and the standard phase after each iteration, obtaining a difference function by combining the amplitude difference function and the phase difference function, and taking the result of the difference function approaching 0 as the convergence result of the iteration.
In one embodiment, the method further comprises:
based on the standard filter, calculating corresponding optimal frequency points;
based on the optimal frequency point, calculating the optimal gain under the optimal frequency point;
calculating an optimal quality factor based on the optimal frequency point and the optimal gain, and combining the optimal frequency point, the optimal gain and the optimal quality factor to obtain a group of iterative filters;
and superposing the amplitude and the phase corresponding to the group of iterative filters to the difference function to finish one iteration.
In one embodiment, the method further comprises:
setting the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected through a Trial run, connecting the set hearing aid to be detected with the Bluetooth adapter, and setting the test background to perform the on-line test;
acquiring curve data obtained by performing online test on a set hearing aid to be detected, comparing the curve data with curve data obtained by performing online test on a golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range;
and when the estimated difference curve is within a preset threshold range, writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration.
In one embodiment, the method further comprises:
and placing the golden hearing aid and the Bluetooth adapter at a designated position of the closed test box, connecting the golden hearing aid to the coupler, and closing the closed test box before the online test.
The embodiment of the invention provides an automatic calibration system for acoustic characteristics of a hearing aid, which comprises:
the first testing module is used for carrying out online testing on the golden hearing aid and the Bluetooth adapter under a preset testing background and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a testing result after the online testing is qualified, wherein the online testing comprises an SPK test and an MIC test;
the second testing module is used for connecting the hearing aid to be tested with the Bluetooth adapter on line, setting the testing background for carrying out the on-line testing, acquiring an SPK (sinusoidal pulse keying) testing curve, an MIC (microphone) testing curve and testing parameters of the hearing aid to be tested, and respectively comparing the SPK standard curve with the SPK testing curve, the MIC standard curve with the MIC testing curve to obtain a difference value curve in a comparison result;
the frequency point module is used for sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining the standard parameters based on the positions of the frequency points;
the iteration module is used for determining the frequency, the gain and the quality factor of the initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation;
and the calibration module is used for writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration.
In one embodiment, the system further comprises:
and the second iteration module is used for obtaining an amplitude difference value function by taking the difference between the iteration amplitude value after each iteration and the standard amplitude value, obtaining a phase difference value function by taking the difference between the iteration phase value after each iteration and the standard phase value, obtaining a difference value function by combining the amplitude difference value function and the phase difference value function, and taking the result of the difference value function approaching 0 as the convergence result of the iteration.
In one embodiment, the system further comprises:
the third testing module is used for setting the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be tested through a Trial run, connecting the set hearing aid to be tested with the Bluetooth adapter, and setting the testing background to perform the on-line testing;
the comparison module is used for acquiring curve data obtained by performing online testing on the set hearing aid to be detected, comparing the curve data with curve data obtained by performing online testing on a golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range;
and the writing module is used for writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration when the estimated difference curve is within a preset threshold range.
An embodiment of the present invention provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for automatic calibration of acoustic properties of a hearing aid when executing the program.
Embodiments of the present invention provide a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described method for automatic calibration of acoustic properties of a hearing aid.
The embodiment of the invention provides an automatic calibration method and system for acoustic characteristics of a hearing aid, which are characterized in that a golden hearing aid and a Bluetooth adapter are subjected to online test under a preset test background, and an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified are obtained, wherein the online test comprises an SPK test and an MIC test; connecting the hearing aid to be detected and the Bluetooth adapter on line, setting a test background for on-line test, acquiring an SPK (sinusoidal pulse keying) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference value curve in a comparison result; sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining standard parameters based on the positions of the frequency points; determining the frequency, the gain and the quality factor of an initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation; and writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration. Therefore, the gain of the chip can be calibrated, the difference of the sensitivity can be compensated, the acoustic characteristic effect of mass production hearing aids is consistent with the research and development effect, and the acoustic effect consistency of the hearing aids is ensured.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart of a method for automatic calibration of acoustic properties of a hearing aid according to an embodiment of the present invention;
FIG. 2 is a flow chart of a sequential fitting loop for amplitude and phase in an embodiment of the invention;
FIG. 3 is a flow chart of an iterative process for parameter adjustment in an embodiment of the present invention;
fig. 4 is a block diagram of an apparatus for automatic calibration of the acoustic properties of a hearing aid according to an embodiment of the invention;
fig. 5 is a schematic structural diagram of an electronic device in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of a method for automatically calibrating acoustic characteristics of a hearing aid according to an embodiment of the present invention, and as shown in fig. 1, the embodiment of the present invention provides a method for automatically calibrating acoustic characteristics of a hearing aid, including:
and S101, performing online test on the golden hearing aid and the Bluetooth adapter under a preset test background, and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test.
Specifically, the golden hearing aid provides a hearing aid standard sample for a manufacturer or a business, meets various data requirements of the hearing aid, then performs an online test on the golden hearing aid and a bluetooth adapter in a preset test background, for example, the golden hearing aid is placed in a closed test box to prevent other sound interference, then is connected to a coupler, is turned on and enters a pairing mode to be online connected with the bluetooth adapter, then closes the closed test box, and performs an online test in a speaker mode (SPK test) and an online test in a microphone mode (MIC test) on the golden hearing aid respectively, wherein the online test results after the online test is qualified include an SPK standard curve (frequency response curve FR) in the speaker mode, an MIC standard curve (frequency response curve FR) in the microphone mode and related standard parameters, wherein the related standard parameters may include related physical parameters of the golden hearing aid, including AD Gain, input max, HT reference, tput, IO diff and the like, and may further include related parameters of corresponding filters in the curves, such as frequency, gain, quality factor and the like of the filters.
And S102, connecting the hearing aid to be detected with the Bluetooth adapter, setting the test background to perform the online test, acquiring an SPK (sinusoidal pulse keying) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve respectively to obtain a difference curve in a comparison result.
Specifically, a hearing aid to be tested, which needs to be calibrated, is arranged under the same test background as a gold-sample hearing aid, and is subjected to online test with a bluetooth adapter, wherein the online test comprises an SPK test and an MIC test, an SPK detection curve, an MIC detection curve and corresponding detection parameters of the hearing aid to be tested are obtained, the SPK standard curve, the SPK detection curve, the MIC standard curve and the MIC detection curve are compared respectively, response errors between the hearing aid to be tested and the gold-sample hearing aid under the SPK test and the MIC test are obtained, a difference curve is obtained according to the corresponding errors, and the difference curve of the SPK test and the difference curve of the MIC test can be included.
And S103, sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining the standard parameters based on the positions of the frequency points.
Specifically, difference values in a difference value curve are sequentially formed into a difference value sequence from large to small, wherein the difference value sequence value is the sequence of Frequency points in the difference value curve, the difference value is the absolute value of the difference between the Frequency responses of the golden hearing aid and the hearing aid to be detected, then a corresponding number of Frequency points are selected from the difference value sequence according to the number of filters, the selected sequence follows the sequence of the difference value sequence, wherein filter data can be determined according to calibration precision or can be set manually, the corresponding positions of the curves of the golden hearing aid corresponding to the Frequency point positions can be determined based on the positions of the Frequency points, then standard parameters are combined to determine the standard filters corresponding to the positions and the standard amplitude values and the standard phases corresponding to the standard filters, and the standard filters can comprise corresponding parameters (Frequency, gain and quality factor Q).
And step S104, determining the frequency, the gain and the quality factor of the initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors to iterate, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iterative calculation.
Specifically, an initial filter and corresponding parameters of the hearing aid to be tested can be determined according to the relevant parameters of the hearing aid to be tested: and the frequency, the gain and the quality factor are used as iteration factors to be iterated in sequence, the iteration amplitude and the iteration phase of the initial filter are calculated after each iteration and are compared with the standard amplitude and the standard phase, and the purpose of comparison is to make the initial filter and the standard filter consistent, namely, the comparison result is used as the convergence result of the iterative calculation.
In addition, the iterative process may be that an amplitude difference function is obtained by subtracting the standard amplitude from the iterative amplitude after each iteration, a phase difference function is obtained by subtracting the standard phase from the iterative phase after each iteration, a difference function is obtained by combining the amplitude difference function and the phase difference function, and then a result of the difference function approaches 0 as a convergence result of the iterative calculation, which may specifically include:
1. initial filter for obtaining hearing aid to be tested
Then, each filter parameter, namely frequency Fc, gain and quality factor Q, is adjusted to be consistent with the target filter, but because any parameter is modified to influence the amplitude and phase at the same time, a cyclic convergence mode is adopted when the optimal filter parameter is calculated, only one of the amplitude and the phase is fitted each time, then the other one is fitted, and after the cycle is repeated for a certain number of times, the corresponding Fc, gain and Q of which the amplitude and the phase are relatively converged to the minimum can be obtained. The flow is shown in fig. 2, and fig. 2 is a flow chart of a fitting cycle for the amplitude and the phase in sequence in this embodiment;
2. calculating fitting amplitude and fitting phase (iterative amplitude and iterative phase) through Fc, gain and Q after each fitting, and then combining the fitting amplitude and the fitting phase with a target (standard) filter
The amplitude value and the phase value are differentiated to obtain an amplitude difference value function and a phase difference value function which are respectively defined as
、
. This function is a ternary function with respect to Fc, gain and Q, which is differentiable at any point. Calculating optimal filter parameters i.e. finding min: (
) And min (
) Corresponding Fc, gain and Q wherein the fitted amplitude valuesThe process of summing the phase function is actually solving the following equation:
3. in the final implementation process, the difference function F (Gain, Q) is actually unknown, so that the direct solving of the formula cannot be implemented, and thus min (F (Gain, Q)) is approached in a gradient descending manner, so that the formula is deformed as follows:
wherein, alpha is learning rate, and
defined as the rate of return (hr),
negative value, alpha and
negative correlation, as the yield is larger, that is, closer to 0, i.e., closer to min (G (Fc, gain, Q)), the variation of Fc, gain, and Q is smaller, so α is smaller.
Since 3 parameters need to be adjusted, each parameter is calculated one by one in the adjustment process, as shown in fig. 3, fig. 3 is a flowchart of an iterative process for parameter adjustment in this embodiment;
4. obtaining G1 through an initial original curve, obtaining F2 through a single iteration mode of Fc or Gain or Q, and calculating the yield
And obtaining a learning rate alpha 1, so as to obtain a parameter corresponding to G3, substituting the parameter into a new yield and a new learning rate, continuously executing the operation until the yield is less than a certain value, considering that the optimal Fc or Gain or Q of the frequency point is obtained, repeating the operation on the 3 parameters, and finally obtaining the optimal filter parameters Fc, gain and Q.
And S105, writing the frequency, the gain and the quality factor after the iterative convergence into the hearing aid to be detected to finish automatic calibration.
Specifically, the calibration effect of the hearing aid is tested by writing the filter parameters including frequency, gain and quality factor after iterative convergence into the hearing aid, and when the calibration effect of the hearing aid meets the preset requirement, the automatic calibration of the hearing aid is completed.
In addition, the frequency, the gain and the quality factor after iterative convergence can be set to enter the hearing aid to be detected through the Trial run, so that whether the calibration is successful or not can be judged in advance through the step of the Trial run before the parameters are written, then the set hearing aid to be detected and the Bluetooth adapter are connected, and a test background is set for on-line testing; acquiring curve data obtained by performing online test on a set hearing aid to be detected, comparing the curve data with curve data obtained by performing online test on a golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range, wherein the preset threshold range can be used for judging whether the discrete condition of the curve meets a standard requirement, the standard requirement can be used for obtaining an acceptance standard of the hearing aid according to the type of the hearing aid, and then the acceptance standard is determined; and when the estimated difference curve is within the preset threshold range, the automatic calibration is accurate, and if the calibration is successful, the frequency, the gain and the quality factor after iterative convergence are written into the hearing aid to be detected to finish the automatic calibration.
The embodiment of the invention provides an automatic calibration method for acoustic characteristics of a hearing aid, which comprises the steps of carrying out online test on a golden hearing aid and a Bluetooth adapter under a preset test background, and obtaining an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test; connecting the hearing aid to be detected and the Bluetooth adapter on line, setting a test background for on-line test, acquiring an SPK (sinusoidal pulse keying) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference value curve in a comparison result; sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining standard parameters based on the positions of the frequency points; determining the frequency, the gain and the quality factor of an initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation; and writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration. Therefore, the gain of the chip can be calibrated, the difference of the sensitivity can be compensated, the acoustic characteristic effect of mass production hearing aids is consistent with the research and development effect, and the acoustic effect consistency of the hearing aids is ensured.
Fig. 4 is a diagram illustrating an automatic calibration system for acoustic characteristics of a hearing aid according to an embodiment of the present invention, including: a first testing module S201, a second testing module S202, a frequency point module S203, an iteration module S204, and a calibration module S205, wherein:
the first testing module S201 is configured to perform an online test on the golden hearing aid and the bluetooth adapter under a preset testing background, and obtain an SPK standard curve, an MIC standard curve, and standard parameters in a test result after the online test is qualified, where the online test includes an SPK test and an MIC test.
And the second testing module S202 is used for connecting the hearing aid to be tested with the Bluetooth adapter, setting the testing background for online testing, acquiring the SPK testing curve, the MIC testing curve and the testing parameters of the hearing aid to be tested, and respectively comparing the SPK standard curve, the SPK testing curve, the MIC standard curve and the MIC testing curve to obtain a difference value curve in a comparison result.
And the frequency point module S203 is configured to sequentially form a difference value sequence according to the difference values in the difference value curve from large to small, select a corresponding number of frequency points from the difference value sequence according to the preset number of filters, and determine, based on the positions of the frequency points, the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter in combination with the standard parameters.
And the iteration module S204 is used for determining the frequency, the gain and the quality factor of the initial filter according to the detection parameters, sequentially performing iteration by using the frequency, the gain and the quality factor as iteration factors, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and using the comparison result as the convergence result of the iterative calculation.
And the calibration module S205 is configured to write the iteratively converged frequency, gain, and quality factor into the hearing aid to be tested to complete automatic calibration.
In one embodiment, the system further comprises:
and the second iteration module is used for obtaining an amplitude difference value function by making a difference between the iteration amplitude value after each iteration and the standard amplitude value, obtaining a phase difference value function by making a difference between the iteration phase value after each iteration and the standard phase value, obtaining a difference value function by combining the amplitude difference value function and the phase difference value function, and taking the result of the difference value function approaching 0 as the convergence result of the iteration.
In one embodiment, the system further comprises:
and the third testing module is used for setting the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be tested through a Trial run, connecting the set hearing aid to be tested with the Bluetooth adapter, and setting the testing background to carry out the on-line testing.
And the comparison module is used for acquiring curve data obtained by performing online test on the set hearing aid to be detected, comparing the curve data with the curve data obtained by performing online test on the golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range.
And the writing module is used for writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration when the estimated difference curve is within a preset threshold range.
The specific definition of the system for automatic calibration of the acoustic properties of a hearing aid may be found in the above definition of the method for automatic calibration of the acoustic properties of a hearing aid and will not be described in detail here. The various modules in the above described automatic calibration system for the acoustic properties of a hearing aid may be implemented in whole or in part by software, hardware and combinations thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
Fig. 5 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 5: a processor (processor) 301, a memory (memory) 302, a communication Interface (Communications Interface) 303 and a communication bus 304, wherein the processor 301, the memory 302 and the communication Interface 303 complete communication with each other through the communication bus 304. The processor 301 may call logic instructions in the memory 302 to perform the following method: performing online test on the golden hearing aid and the Bluetooth adapter under a preset test background, and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test; connecting the hearing aid to be detected and the Bluetooth adapter on line, setting a test background for on-line test, obtaining an SPK test curve, an MIC test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference value curve in a comparison result; sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining standard parameters based on the positions of the frequency points; determining the frequency, the gain and the quality factor of the initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation; and writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration.
Furthermore, the logic instructions in the memory 302 may be implemented in software functional units and stored in a computer readable storage medium when sold or used as a stand-alone product. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the transmission method provided in the foregoing embodiments when executed by a processor, for example, the method includes: performing online test on the golden hearing aid and the Bluetooth adapter under a preset test background, and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test; connecting the hearing aid to be detected and the Bluetooth adapter on line, setting a test background for on-line test, acquiring an SPK (sinusoidal pulse keying) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference value curve in a comparison result; sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining standard parameters based on the positions of the frequency points; determining the frequency, the gain and the quality factor of an initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation; and writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for automatic calibration of acoustic properties of a hearing aid, comprising:
performing online test on the golden hearing aid and the Bluetooth adapter under a preset test background, and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a test result after the online test is qualified, wherein the online test comprises an SPK test and an MIC test;
connecting the hearing aid to be detected and the Bluetooth adapter on line, setting the test background to perform the on-line test, acquiring an SPK (sinusoidal pulse code) test curve, an MIC (microphone) test curve and test parameters of the hearing aid to be detected, and respectively comparing the SPK standard curve with the SPK test curve, the MIC standard curve with the MIC test curve to obtain a difference curve in a comparison result;
sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining a corresponding standard filter and a standard amplitude value and a standard phase corresponding to the standard filter by combining the standard parameters based on the positions of the frequency points;
determining the frequency, the gain and the quality factor of an initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation;
and writing the frequency, the gain and the quality factor after the iterative convergence into the hearing aid to be detected to finish automatic calibration.
2. The method for automatic calibration of acoustic characteristics of a hearing aid according to claim 1, wherein said calculating an iterative magnitude and an iterative phase of said initial filter after each iteration, comparing said iterative magnitude and said iterative phase with said standard magnitude and standard phase, and using the result of the comparison as a convergence result of said iterative calculation comprises:
and obtaining an amplitude difference value function by taking the difference between the iteration amplitude and the standard amplitude after each iteration, obtaining a phase difference value function by taking the difference between the iteration phase and the standard phase after each iteration, obtaining a difference value function by combining the amplitude difference value function and the phase difference value function, and taking the result of the difference value function approaching 0 as the convergence result of the iteration.
3. Method for automatic calibration of acoustic properties of a hearing aid according to claim 2, wherein each iteration comprises
Based on the standard filter, calculating a corresponding optimal frequency point;
based on the optimal frequency point, calculating the optimal gain under the optimal frequency point;
calculating an optimal quality factor based on the optimal frequency point and the optimal gain, and combining the optimal frequency point, the optimal gain and the optimal quality factor to obtain a group of iterative filters;
and superposing the amplitude and the phase corresponding to the group of iterative filters to the difference function to complete one iteration.
4. The method for automatically calibrating the acoustic characteristics of a hearing aid according to claim 1, wherein said writing the iteratively converged frequencies, gains, and quality factors into the hearing aid under test for automatic calibration comprises:
setting the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected through a Trial run, connecting the set hearing aid to be detected with the Bluetooth adapter, and setting the test background to perform the on-line test;
acquiring curve data obtained by performing online testing on a set hearing aid to be detected, comparing the curve data with curve data obtained by performing online testing on a golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range;
and when the estimated difference value curve is within a preset threshold range, writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration.
5. The method for automatic calibration of acoustic properties of a hearing aid according to claim 1, wherein said test context comprises:
and placing the golden hearing aid and the Bluetooth adapter at the specified positions of the closed test box, connecting the golden hearing aid to the coupler, and closing the closed test box before the online test.
6. A system for automatic calibration of acoustic properties of a hearing aid, the system comprising:
the first testing module is used for carrying out online testing on the golden hearing aid and the Bluetooth adapter under a preset testing background and acquiring an SPK standard curve, an MIC standard curve and standard parameters in a testing result after the online testing is qualified, wherein the online testing comprises an SPK test and an MIC test;
the second testing module is used for connecting the hearing aid to be tested with the Bluetooth adapter on line, setting the testing background for carrying out the on-line testing, acquiring an SPK (sinusoidal pulse keying) testing curve, an MIC (microphone) testing curve and testing parameters of the hearing aid to be tested, and respectively comparing the SPK standard curve with the SPK testing curve, the MIC standard curve with the MIC testing curve to obtain a difference value curve in a comparison result;
the frequency point module is used for sequentially forming a difference value sequence according to the difference values in the difference value curve from large to small, selecting a corresponding number of frequency points from the difference value sequence according to the number of preset filters, and determining the corresponding standard filter and the standard amplitude and the standard phase corresponding to the standard filter by combining the standard parameters based on the positions of the frequency points;
the iteration module is used for determining the frequency, the gain and the quality factor of the initial filter according to the detection parameters, sequentially taking the frequency, the gain and the quality factor as iteration factors for iteration, calculating the iteration amplitude and the iteration phase of the initial filter after each iteration, comparing the iteration amplitude and the iteration phase with the standard amplitude and the standard phase, and taking the comparison result as the convergence result of the iteration calculation;
and the calibration module is used for writing the frequency, the gain and the quality factor after the iterative convergence into the hearing aid to be detected to finish automatic calibration.
7. The system for automatic calibration of acoustic properties of a hearing aid according to claim 6, wherein said system further comprises:
and the second iteration module is used for obtaining an amplitude difference value function by making a difference between the iteration amplitude value after each iteration and the standard amplitude value, obtaining a phase difference value function by making a difference between the iteration phase value after each iteration and the standard phase value, obtaining a difference value function by combining the amplitude difference value function and the phase difference value function, and taking the result of the difference value function approaching 0 as the convergence result of the iteration.
8. The system for automatic calibration of acoustic properties of a hearing aid according to claim 6, wherein said system further comprises:
the third testing module is used for setting the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be tested through a Trial run, connecting the set hearing aid to be tested with the Bluetooth adapter, and setting the testing background to perform the on-line testing;
the comparison module is used for acquiring curve data obtained by performing online testing on the set hearing aid to be detected, comparing the curve data with curve data obtained by performing online testing on a golden sample hearing aid to obtain an estimated difference curve, and detecting whether the estimated difference curve is within a preset threshold range;
and the writing module is used for writing the frequency, the gain and the quality factor after iterative convergence into the hearing aid to be detected to finish automatic calibration when the estimated difference curve is within a preset threshold range.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, carries out the steps of the method for automatic calibration of acoustic properties of a hearing aid according to any one of claims 1 to 5.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of a method for automatic calibration of acoustic properties of a hearing aid according to any one of claims 1 to 5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116249062A (en) * | 2023-05-08 | 2023-06-09 | 深圳市英唐数码科技有限公司 | Hearing-aid equipment state intelligent quality inspection method, system and medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112118525A (en) * | 2020-09-15 | 2020-12-22 | 杭州兆华电子有限公司 | Automatic change intelligent TWS bluetooth headset test system |
| CN114760567A (en) * | 2022-04-26 | 2022-07-15 | 歌尔股份有限公司 | Method, device and equipment for calibrating sound quality effect of earphone and storage medium |
| CN115604628A (en) * | 2022-12-12 | 2023-01-13 | 杭州兆华电子股份有限公司（Cn） | Filter calibration method and device based on earphone loudspeaker frequency response |
-
2023
- 2023-02-09 CN CN202310089660.0A patent/CN115802267A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112118525A (en) * | 2020-09-15 | 2020-12-22 | 杭州兆华电子有限公司 | Automatic change intelligent TWS bluetooth headset test system |
| CN114760567A (en) * | 2022-04-26 | 2022-07-15 | 歌尔股份有限公司 | Method, device and equipment for calibrating sound quality effect of earphone and storage medium |
| CN115604628A (en) * | 2022-12-12 | 2023-01-13 | 杭州兆华电子股份有限公司（Cn） | Filter calibration method and device based on earphone loudspeaker frequency response |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116249062A (en) * | 2023-05-08 | 2023-06-09 | 深圳市英唐数码科技有限公司 | Hearing-aid equipment state intelligent quality inspection method, system and medium |
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