Frequency response calibration parameter determination method and frequency response calibration method

Abstract

The embodiment of the invention provides a method for determining frequency response calibration parameters. The method comprises the following steps: acquiring frequency response big data of a plurality of candidate devices; determining a target frequency response value matched with the preset interested frequency point based on the frequency response big data; selecting a part of frequency points from the interested frequency points as center frequency points to be subjected to frequency response calibration; determining a calibration gain value matched with each center frequency point according to the initial frequency response value and the target frequency response value of the target candidate device based on each center frequency point; calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; and under the condition that the dispersion of the calibrated frequency response values of the plurality of candidate devices is smaller than a preset threshold value, or the number of cyclic operations reaches a preset number threshold value, taking the center frequency point corresponding to the minimum dispersion, and the target frequency response value and the random quality factor matched with the center frequency point as frequency response calibration parameters.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of terminal technology, and more particularly to a method for determining frequency response calibration parameters, a frequency response calibration method, and an electronic device. Background Art

[0002] With the development of internet technology, the demand for terminal products is growing. Currently, many terminal devices are equipped with sound-generating devices to enable voice communication or audio playback. When sound signals are played through these sound-generating devices, their frequency response affects the sound quality of the terminal devices.

[0003] When the frequency response performance of the sound-emitting device to the sound signal fluctuates, or deviates from the standard frequency response curve, the user's hearing experience will be inconsistent, affecting the user experience. Summary of the Invention

[0004] To address the above technical issues, the present application provides a method for determining frequency response calibration parameters and a frequency response calibration method. The method comprises obtaining frequency response big data for multiple candidate devices; determining target frequency response values that match preset frequency points of interest based on the frequency response big data; and looping through the following operations until the dispersion of the calibrated frequency response values is less than a preset dispersion threshold, or the number of loop operations reaches a preset number threshold: selecting at least some frequency points from the preset frequency points of interest as center frequency points for frequency response calibration; determining calibration gain values that match each center frequency point based on the initial frequency response values and target frequency response values of the target candidate devices at each center frequency point; calibrating the initial frequency response values of the target candidate devices based on the calibration gain values to obtain calibrated frequency response values; calculating the number of loop operations and the dispersion of the calibrated frequency response values of the multiple candidate devices; and, if the dispersion of the calibrated frequency response values is less than the preset dispersion threshold, or the number of loop operations reaches the preset number threshold, using the center frequency point corresponding to the minimum dispersion, the target frequency response value that matches the center frequency point, and the random quality factor as frequency response calibration parameters.

[0005] In a first aspect, an embodiment of the present application provides a method for determining frequency response calibration parameters, comprising: obtaining initial frequency response values of a plurality of candidate devices based on preset frequency points of interest to obtain frequency response big data; determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data; looping the following operations until the discreteness of the calibrated frequency response value is less than a preset discreteness threshold, or the number of loop operations reaches a preset number threshold: selecting some frequency points from the frequency points of interest as center frequency points to be subjected to frequency response calibration; determining a target frequency response value matching each of the frequency points of interest based on the initial frequency response value and the target frequency response value of the target candidate device based on each of the center frequency points. a calibration gain value matched to each of the center frequency points, the target candidate device including any candidate device from the multiple candidate devices; calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; calculating the number of loop operations and the discreteness of the calibrated frequency response values of the multiple candidate devices; and when the discreteness of the calibrated frequency response value is less than a preset discreteness threshold or the number of loop operations reaches a preset number threshold, using the center frequency point corresponding to the minimum discreteness, the target frequency response value matched to the center frequency point, and the random quality factor as the frequency response calibration parameters.

[0006] In this embodiment of the present application, the same frequency band division parameters can be used for all devices to be calibrated. Frequency response calibration parameters can be pushed to the devices to be calibrated as version update parameters, while the devices to be calibrated only need to store their own frequency response data. Pushing frequency response calibration parameters as version update parameters effectively decouples frequency response calibration from production line operations, effectively improving production line efficiency while ensuring that all devices are simultaneously updated with the latest frequency response calibration parameters.

[0007] By continuously collecting frequency response big data in the project, we can optimize the calibration frequency band division and target frequency response value, which will help improve the accuracy of frequency response calibration and ensure the consistency of frequency response performance of different sound-emitting devices.

[0008] According to the first aspect, determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data includes: calculating an average of the initial frequency response values of the multiple candidate devices based on each of the frequency points of interest; and adjusting the average of the initial frequency response values based on a preset calibration gain range to obtain the target frequency response value matching each of the frequency points of interest.

[0009] According to the first aspect, or any implementation manner of the first aspect above, the selecting of some frequency points from the frequency points of interest as the center frequency points to be subjected to frequency response calibration includes: setting N candidate calibration frequency bands, each of the N candidate calibration frequency bands having a corresponding preset importance level, where N is an integer greater than 1; and randomly selecting N frequency points from the frequency points of interest as the center frequency points to be subjected to frequency response calibration based on a preset frequency point spacing threshold and the importance level corresponding to each of the candidate calibration frequency bands.

[0010] According to the first aspect, or any implementation of the first aspect above, determining the calibration gain value that matches each of the center frequency points based on the initial frequency response value and the target frequency response value of the target candidate device based on each of the center frequency points includes: calculating the difference between the initial frequency response value and the target frequency response value of the target candidate device based on each of the center frequency points, and using the difference as the calibration gain value that matches the corresponding center frequency point.

[0011] According to the first aspect, or any implementation manner of the first aspect above, calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value includes: determining N initial calibration frequency bands according to each of the center frequency points and the random quality factor matching each of the center frequency points; when there is an overlapping frequency band in the N initial calibration frequency bands, updating the random quality factor and / or the center frequency point corresponding to the overlapping frequency band, and re-determining the corresponding initial calibration frequency band according to the updated random quality factor and / or the updated center frequency point until the N initial calibration frequency bands do not overlap with each other; generating N target calibration frequency bands according to the band cutoff frequencies of adjacent frequency bands in the N non-overlapping initial calibration frequency bands; constructing a calibration filter according to each of the target calibration frequency bands and the calibration gain value matching each of the target calibration frequency bands; and using the calibration filter to calibrate the initial frequency response value of the target candidate device to obtain the calibrated frequency response value.

[0012] According to the first aspect, or any implementation method of the first aspect above, N target calibration frequency bands are generated based on the frequency band cutoff frequencies of adjacent frequency bands in the N non-overlapping initial calibration frequency bands, including: for the i-th initial calibration frequency band and the i+1-th initial calibration frequency band in the N initial calibration frequency bands, the average of the right cutoff frequency of the i-th initial calibration frequency band and the left cutoff frequency of the i+1-th initial calibration frequency band is used as the adjusted frequency band cutoff frequency, i is an integer and 1≤i≤N-1; and the N target calibration frequency bands are generated based on the adjusted frequency band cutoff frequencies.

[0013] According to the first aspect, or any implementation of the first aspect above, the method also includes: using the preset minimum frequency band cutoff frequency as the left cutoff frequency of the first target calibration frequency band among the N target calibration frequency bands; and using the preset maximum frequency band cutoff frequency as the right cutoff frequency of the Nth target calibration frequency band among the N target calibration frequency bands.

[0014] According to the first aspect, or any implementation manner of the first aspect above, obtaining the initial frequency response values of multiple candidate devices based on preset frequency points of interest includes: using each of the candidate devices to play a test audio signal to obtain a frequency response curve matching each of the candidate devices, the frequency response curve indicating the initial frequency response value of the candidate device based on the frequency points of interest; using the calibration filter to calibrate the initial frequency response value of the target candidate device to obtain the calibrated frequency response value includes: using the calibration filter to calibrate the frequency response curve matching the target candidate device, the calibrated frequency response curve indicating the calibrated frequency response value of the target candidate device.

[0015] According to the first aspect, or any implementation of the first aspect above, the test audio signal is a full-frequency domain scanning signal.

[0016] According to the first aspect, or any implementation of the first aspect above, the use of the calibration filter to calibrate the frequency response curve matching the target candidate device includes: determining a candidate frequency point matching the frequency point of interest based on a preset mapping relationship; and using the calibration filter to calibrate the frequency response curve according to the calibration gain value of the target candidate device based on the candidate frequency point, to obtain the calibrated frequency response curve.

[0017] According to the first aspect, or any implementation of the first aspect above, the calculating the discreteness of the calibrated frequency response values of multiple candidate devices includes: calculating the variance of the calibrated frequency response curves of the multiple candidate devices; and performing weighted summation on the variances corresponding to each of the frequency points of interest according to a preset attention level matching each of the frequency points of interest, the weighted summation result indicating the discreteness of the calibrated frequency response values, wherein the attention level is a weight value assigned according to a contribution value of the corresponding frequency point of interest to the loudness in the ear.

[0018] According to the first aspect, or any implementation of the first aspect above, the method further includes: sending the frequency response calibration parameter as a version update parameter to the device to be calibrated.

[0019] In a second aspect, an embodiment of the present application provides a frequency response calibration method, which is applied to a device to be calibrated, the method comprising: receiving version update parameters, the version update parameters comprising a center frequency point and a random quality factor based on the center frequency point and a target frequency response value; in response to the received version update parameters, obtaining locally stored frequency response data, the frequency response data comprising an initial frequency response value of the device to be calibrated based on each of the center frequency points; determining a calibration gain value matching each of the center frequency points based on the initial frequency response value and the target frequency response value based on each of the center frequency points; constructing a calibration filter based on the center frequency point and the random quality factor and the calibration gain value matching the center frequency point; and using the calibration filter, calibrating the frequency response value of the device to be calibrated for the audio signal to be played to obtain a calibrated audio signal.

[0020] According to the second aspect, determining the calibration gain value matching each of the center frequency points based on the initial frequency response value and the target frequency response value based on each of the center frequency points includes: calculating the difference between the initial frequency response value of the device to be calibrated based on each of the center frequency points and the target frequency response value, and using the difference as the calibration gain value of the device to be calibrated based on the corresponding center frequency point.

[0021] According to the second aspect, or any implementation method of the second aspect above, the calibration filter is constructed according to the center frequency point and the random quality factor and the calibration gain value matching the center frequency point, including: determining N initial calibration frequency bands according to each of the center frequency points and the random quality factor matching each of the center frequency points; when there is an overlapping frequency band in the N initial calibration frequency bands, updating the random quality factor and / or the center frequency point corresponding to the overlapping frequency band, and re-determining the corresponding initial calibration frequency band according to the updated random quality factor and / or the updated center frequency point until the N initial calibration frequency bands do not overlap with each other; generating N target calibration frequency bands according to the band cutoff frequencies of adjacent frequency bands in the N non-overlapping initial calibration frequency bands; and constructing a calibration filter according to each of the target calibration frequency bands and the calibration gain value matching each of the target calibration frequency bands.

[0022] According to the second aspect, or any implementation of the second aspect above, the using the calibration filter to calibrate the frequency response value of the device to be calibrated for the audio signal to be played to obtain a calibrated audio signal includes: performing a Fourier transform on the audio signal to be played played by the device to be calibrated to obtain a converted frequency domain signal; and using the calibration filter to calibrate the converted frequency domain signal to obtain the calibrated audio signal.

[0023] In a third aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored on the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: obtaining initial frequency response values of multiple candidate devices based on preset frequency points of interest to obtain frequency response big data; determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data; looping the following operations until the discreteness of the calibrated frequency response value is less than a preset discreteness threshold, or the number of loop operations reaches a preset number threshold: selecting some frequency points from the frequency points of interest as the center frequency points to be calibrated; and performing the following operations based on the frequency response big data. The target candidate device determines a calibration gain value matching each center frequency point based on the initial frequency response value and the target frequency response value of each center frequency point, and the target candidate device includes any candidate device among the multiple candidate devices; calibrates the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; calculates the number of loop operations and the discreteness of the calibrated frequency response values of the multiple candidate devices; and when the discreteness of the calibrated frequency response value is less than a preset discreteness threshold or the number of loop operations reaches a preset number threshold, uses the center frequency point corresponding to the minimum discreteness, the target frequency response value matching the center frequency point, and the random quality factor as the frequency response calibration parameters.

[0024] In a fourth aspect, an embodiment of the present application provides an electronic device, comprising: one or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored on the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: receiving version update parameters, the version update parameters including a center frequency point and a random quality factor and a target frequency response value based on the center frequency point; in response to the received version update parameters, obtaining locally stored frequency response data, the frequency response data including an initial frequency response value of the device to be calibrated based on each of the center frequency points; determining a calibration gain value matching each of the center frequency points based on the initial frequency response value and the target frequency response value based on each of the center frequency points; constructing a calibration filter based on each of the center frequency points and the calibration gain value matching each of the center frequency points; using the calibration filter, calibrating the frequency response value of the device to be calibrated for the audio signal to be played to obtain a calibrated audio signal.

[0025] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising a computer program, which, when run on an electronic device, enables the electronic device to execute instructions of a method in any possible implementation of the first aspect, or instructions of a method in any possible implementation of the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The figure schematically shows a user holding a mobile phone for voice communication;

[0027] Figure 2 The diagram schematically shows the distribution of the sound-generating components of a mobile phone;

[0028] Figure 3 A schematic diagram schematically shows the frequency response curves of devices with the same specifications;

[0029] Figure 4 The structure diagram of a frequency response calibration system is schematically shown;

[0030] Figure 5 A flow chart of a method for determining frequency response calibration parameters is schematically shown;

[0031] Figure 6 A schematic diagram schematically shows the weight distribution corresponding to the frequency points;

[0032] Figure 7 is a schematic diagram of the hardware structure of an electronic device shown as an example;

[0033] Figure 8 is a software structure block diagram of an illustrative electronic device;

[0034] Figure 9 A schematic diagram of a frequency response calibration process is schematically shown;

[0035] Figure 10 The diagram schematically shows the frequency response calibration process during a call. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0037] The term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0038] In the description and claims of the embodiments of this application, the terms "first" and "second" are used to distinguish different objects, rather than to describe a specific order of objects. For example, the terms "first target object" and "second target object" are used to distinguish different objects, rather than to describe a specific order of objects.

[0039] In the embodiments of this application, words such as "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplarily" or "for example" is intended to present the relevant concepts in a concrete manner.

[0040] In the description of the embodiments of this application, unless otherwise specified, "multiple" means two or more. For example, "multiple processing units" means two or more processing units; "multiple systems" means two or more systems.

[0041] Voice communication or audio playback has become an important feature of electronic devices, such as mobile phones. For example, when an electronic device provides voice communication to a user, its sound-generating device converts electrical audio signals from other devices into sound signals and outputs them. For example, the sound-generating device can be a mobile phone receiver, which is also the speaker used to produce audio during voice communication.

[0042] Figure 1 The following diagram schematically shows a user holding a mobile phone for voice communication. Figure 1 As shown, when a user is using mobile phone 101 for voice communication, the sound outlet of handset 102 is close to the user's auricle. Handset 102 is used to play the voice signal of the other user during the voice communication. If the sound outlet of handset 102 is not covered by the user's auricle, the sound emitted by the sound outlet may be heard by other users, resulting in the leakage of the voice communication content.

[0043] Figure 2The diagram schematically shows the distribution of the sound-emitting components of a mobile phone. Private calls are a highly-regarded mobile phone call feature. In a private call scenario, two sound-emitting components may be provided in the mobile phone to offset call leakage. As shown in 2A, the two sound-emitting components may be a handset and a ceramic sound generator. The handset can emit sound through the handset sound hole or the handset sound slit, and the ceramic sound generator can emit sound by pushing the screen. As shown in 2B, both sound-emitting components may be handsets. The mobile phone is provided with handset 1 and handset 2. Handset 1 emits sound from the handset 1 sound slit through the handset 1 pipe, and handset 2 emits sound from the handset 2 sound hole through the handset 2 pipe.

[0044] Figure 2 The sound-generating devices and structural layout are only for demonstration and explanation, and do not limit the application scenarios of the embodiments of the present application.

[0045] In related technologies, to address the issue of receiver sound leakage, a first sound signal can be played through a certain sound-generating device in the phone, and a second sound signal can be played through another sound-generating device while the user is using the phone for voice communication. The second sound signal and the first sound signal have opposite phases at the location of the sound leakage. Because the second sound signal and the first sound signal have opposite phases, the two corresponding sound waves cancel each other out during propagation, effectively reducing receiver sound leakage and minimizing the leakage of voice communication content. In other words, the problem of receiver sound leakage can be effectively alleviated by using dual-unit hardware to emit opposite-phase sound waves for cancellation.

[0046] To facilitate mass production, electronic equipment hardware currently uses a modular production approach. For example, by testing the speakers of individual prototypes to obtain frequency response curves, the speaker coefficients are calculated using a sound field reproduction control algorithm and then applied to all devices' speakers.

[0047] Figure 3 The following diagram shows the frequency response curves of devices with the same specifications. Due to differences in material batches and hardware of terminal devices, the frequency response performance of devices with the same specifications produced by the same manufacturer may be inconsistent. Figure 3 As shown, the frequency response curves for devices with the same specifications can vary by as much as 10dB. This shows that even devices with the same specifications can have inconsistent frequency response performance. If the sound device parameters obtained from individual prototype tests are applied to other devices in bulk, the frequency response performance of the sound device may degrade.

[0048] Calibrating the frequency response performance of a sound-generating device to ensure that its frequency response curve to the sound signal is consistent can be an effective way to improve the applicability of calibration parameters.

[0049] Electronic devices may include mobile phones, tablet computers, smart watches, laptops, smart homes, in-vehicle devices, virtual-reality fusion devices, augmented reality devices, netbooks, etc.

[0050] Embodiments of the present application provide a scheme for determining frequency response calibration parameters, applicable to a calibration device. In this scheme, the calibration device obtains initial frequency response values of multiple candidate devices based on preset frequency points of interest to obtain frequency response data. Based on the frequency response data, a target frequency response value matching each frequency point of interest is determined. Next, the following operations are performed repeatedly until the dispersion of the calibrated frequency response values is less than a preset dispersion threshold, or the number of loop operations reaches a preset threshold: Selecting a subset of frequency points from the frequency points of interest as center frequencies for frequency response calibration; Determining calibration gain values matching each center frequency point based on the initial frequency response values and target frequency response values of target candidate devices at each center frequency point, where the target candidate device includes any candidate device from the multiple candidate devices. Calibrating the initial frequency response values of the target candidate devices based on the calibration gain values to obtain calibrated frequency response values. Next, the number of loop operations and the dispersion of the calibrated frequency response values of the multiple candidate devices are calculated. If the dispersion of the calibrated frequency response values is less than the preset dispersion threshold, or the number of loop operations reaches the preset threshold, the target frequency response values based on each center frequency point are used as frequency response calibration parameters.

[0051] The embodiments of this application can eliminate the need for frequency response calibration and optimization during the production phase, effectively saving production time and improving production efficiency. Furthermore, they can effectively prevent incorrect or inappropriate calibration results from being hard-coded into electronic devices during the production phase, potentially impacting their subsequent frequency response performance, reducing their audio playback performance, and negatively impacting the user experience.

[0052] By continuously collecting frequency response big data in the project, we can optimize the calibration frequency band division and target frequency response value, which will help improve the accuracy of frequency response calibration and ensure the consistency of frequency response performance of different sound-emitting devices.

[0053] Figure 4 The schematic diagram of the structure of a frequency response calibration system is shown schematically. Figure 4As shown, the frequency response calibration system may include an electronic device and a calibration parameter optimization system. The calibration parameter optimization system may include a calibration device and a plurality of candidate devices. When it is necessary to calibrate the frequency response performance of the sound-emitting device in the electronic device, the calibration device pushes the frequency response calibration parameters as version update parameters to the electronic device. The frequency response calibration parameters include, for example, a center frequency point and a target frequency response value and a random quality factor that match the center frequency point. The target frequency response value may be determined based on the frequency response big data obtained by the calibration device. After the electronic device to be calibrated obtains the frequency response calibration parameters, the electronic device may store the frequency response calibration parameters in a local non-volatile storage device, so that the electronic device can perform consistency verification on the frequency response performance of the sound-emitting device during the voice communication process or the audio signal playback process, thereby making the frequency response curves of the sound-emitting device in the electronic device consistent.

[0054] The calibration device may include a frequency response big data acquisition module, a calibration parameter determination module, and a calibration control module. The frequency response big data acquisition module is used to obtain frequency response curves of multiple candidate devices for a test audio signal to obtain frequency response big data. The calibration parameter determination module is used to determine target frequency response values that match each frequency point of interest based on the initial frequency response values of the multiple candidate devices indicated by the frequency response big data and based on preset frequency points of interest. The calibration parameter determination module is also used to determine frequency response calibration parameters based on the target frequency response values that match each frequency point of interest. The calibration control module is used to establish a communication connection with the electronic device to be calibrated. For example, the calibration control module can send version update parameters to the electronic device, or it can also be used to receive a frequency response calibration request sent by the electronic device.

[0055] Figure 5 The flow chart of a method for determining frequency response calibration parameters is schematically shown. The method for determining frequency response calibration parameters is applicable to a calibration device, which includes, for example, a frequency response big data acquisition module, a calibration parameter determination module, and a calibration control module. The calibration parameter determination module includes, for example, a frequency response calibration parameter determination module, a loop control module, a filter construction module, and a filter calibration module. Figure 5 As shown, the process of determining the frequency response calibration parameters includes, for example, operations S101 to S111.

[0056] The following is a schematic description of the implementation process of each operation in the process of determining the frequency response calibration parameters.

[0057] In operation S101 , a frequency response big data acquisition module acquires initial frequency response values of a plurality of candidate devices based on preset frequency points of interest to obtain frequency response big data.

[0058] Exemplarily, multiple candidate devices are used to play a test audio signal to obtain a frequency response curve matching each candidate device. For example, the test audio signal may be played through the speakers of the multiple candidate devices, and the test audio signal may be a full-frequency sweep signal. The frequency response big data acquisition module calculates the frequency response based on the test audio signal played by each candidate device, obtaining the initial frequency response value of each candidate device based on the frequency point.

[0059] For example, Table 1 schematically shows the initial frequency response values of candidate devices based on frequency points.

[0060] Table 1

[0061] frequency 200 212 224 236 … 8500 9000 9500 10000 Frequency Response 51.2 52.8 54 55.5 … 101.3 102 102.2 103

[0062] Optionally, a curve may be drawn based on the initial frequency response value of each candidate device at a frequency point to obtain a frequency response curve.

[0063] There is no one-to-one correspondence between frequency points, but there can be a preset mapping relationship between the two. For example, Freq represents a frequency point, and FreqIdx represents the adjacent frequency point corresponding to Freq. The preset mapping relationship between FreqIdx and Freq can be expressed by formula (1):

[0064]

[0065] The round function is used to round a value to a specified number of digits. N / / 2 represents the integer quotient of N divided by 2.

[0066] If a 1024-point FFT transform is used, the mapping relationship between the frequency point Freq and the frequency point FreqIdx can be shown in Table 2:

[0067] Table 2

[0068] frequency 200 212 224 236 … 8500 9000 9500 10000 Frequency 4 5 5 5 182 192 203 214

[0069] In operation S102 , a frequency response calibration parameter determination module determines a target frequency response value that matches each frequency point of interest based on the frequency response big data.

[0070] Exemplarily, the frequency response calibration parameter determination module calculates the average of initial frequency response values of multiple candidate components based on each frequency point of interest, and adjusts the average of the initial frequency response values based on a preset calibration gain range to obtain a target frequency response value that matches each frequency point of interest.

[0071] The frequency response calibration parameter determination module can use the mean of the initial frequency response values of multiple candidate devices at each frequency point of interest as the target frequency response value matching the corresponding frequency point of interest. The module can also adjust the mean of the initial frequency response values as needed within a preset calibration gain range to obtain a target frequency response value matching each frequency point of interest. For example, the mean of the initial frequency response values can be adjusted based on in-ear hearing requirements to obtain a target frequency response value that better meets the user's hearing requirements.

[0072] In operation S103 , the loop control module determines whether the dispersion of the calibrated frequency response value is less than a preset dispersion threshold, or whether the number of loop operations reaches a preset number threshold.

[0073] When the dispersion of the frequency response value after calibration is less than the preset dispersion threshold, or the number of loop operations reaches the preset number threshold, operation S108 is performed.

[0074] If the dispersion of the calibrated frequency response value is greater than or equal to the preset dispersion threshold, and the number of loop operations does not reach the preset number threshold, operation S104 is performed.

[0075] In operation S104 , the filter construction module selects at least some frequency points from the preset frequency points of interest as central frequency points for frequency response calibration.

[0076] Exemplarily, the filter construction module sets N candidate calibration frequency bands, each of the N candidate calibration frequency bands having a corresponding preset importance level, where N is an integer greater than 1. Based on the importance level corresponding to each candidate calibration frequency band, the candidate calibration frequency bands can be divided into important frequency bands, unimportant frequency bands, attention frequency bands, and unattention frequency bands.

[0077] Next, the filter construction module may randomly select N frequency points from the frequency points of interest as the center frequency points to be calibrated according to a preset frequency point spacing threshold and the importance level corresponding to each candidate calibration frequency band.

[0078] For example, the number of preset frequency points of interest is M, the number of candidate calibration frequency bands is N, N<<M, and the filter construction module randomly selects N frequency points from the M preset frequency points of interest as the center frequency point Fc to be calibrated. The search space of Fc is In order to prevent the search space of Fc from being too large, the search space of Fc can be constrained and the search results that do not meet the constraints can be eliminated.

[0079] As an optional method, the filter construction module can constrain the search space of Fc according to a preset frequency point spacing threshold and the importance level corresponding to each candidate calibration frequency band. For example, when the selected center frequency point appears in an unconcerned frequency band, or the number of points appearing in an unimportant frequency band exceeds a preset number threshold, the current random selection result is eliminated, and the operation of randomly selecting at least some frequency points from the preset frequency points of interest is returned. For another example, when the frequency point spacing of the selected center frequency point is less than a preset minimum frequency point spacing threshold (indicating that the frequency point distribution is overly concentrated), or is greater than a preset maximum frequency point spacing threshold (indicating that the frequency point distribution is overly sparse), the current random selection result is eliminated, and the operation of randomly selecting at least some frequency points from the preset frequency points of interest is returned.

[0080] In operation S105 , the filter construction module determines a calibration gain value matching each center frequency point according to an initial frequency response value and a target frequency response value of a target candidate device based on each center frequency point, where the target candidate device includes any candidate device from among the plurality of candidate devices.

[0081] Exemplarily, the filter construction module calculates the difference between the initial frequency response value of the target candidate device based on each center frequency point and the target frequency response value, and uses the difference as the calibration gain value matching the corresponding center frequency point. The target candidate device can be any candidate device among multiple candidate devices.

[0082] For example, the calibration gain value Gain that matches the center frequency point Fc can be expressed using formula (2): Fc :

[0083]

[0084] Indicates the target frequency response value that matches the center frequency point Fc, FR Fc Indicates the initial frequency response value of the candidate device based on the center frequency point Fc.

[0085] In operation S106 , the filter construction module constructs a calibration filter according to the center frequency point and the calibration gain value and random quality factor that match the center frequency point.

[0086] Exemplarily, the filter construction module determines N initial calibration frequency bands based on each center frequency point and a random quality factor matching each center frequency point. If there is an overlapping frequency band among the N initial calibration frequency bands, the random quality factor and / or center frequency point corresponding to the overlapping frequency band is updated, and the corresponding initial calibration frequency band is re-determined based on the updated random quality factor and / or updated center frequency point until the N initial calibration frequency bands do not overlap.

[0087] If the N initial calibration frequency bands do not overlap, the filter construction module generates N target calibration frequency bands based on the cutoff frequencies of adjacent frequency bands in the N initial calibration frequency bands. The filter construction module then constructs a calibration filter based on each target calibration frequency band and a calibration gain value that matches each target calibration frequency band.

[0088] The filter construction module determines N initial calibration frequency bands based on the center frequency point Fc and the random quality factor Q that matches the center frequency point Fc. The center frequency point Fc corresponds to the center frequency of the initial calibration frequency band, and the ratio of the center frequency point Fc to the random quality factor Q constitutes the bandwidth of the initial calibration frequency band.

[0089] For example, Table 3 schematically shows the corresponding relationship between the initial calibration frequency band, the center frequency point Fc, and the random quality factor Q:

[0090] Table 3

[0091]

[0092] The right cutoff frequency 7200 of the N-1th initial calibration frequency band is greater than the left cutoff frequency 7000 of the Nth initial calibration frequency band. Therefore, the N-1th initial calibration frequency band and the Nth initial calibration frequency band overlap. The random quality factor and / or center frequency point corresponding to the overlapping frequency band is updated, and the corresponding initial calibration frequency band is re-determined based on the updated random quality factor and / or updated center frequency point until the N initial calibration frequency bands do not overlap.

[0093] For example, Table 4 schematically shows a relationship diagram between the target calibration frequency band and the initial calibration frequency band.

[0094] Table 4

[0095]

[0096] The filter construction module updates the random quality factors corresponding to the N-1th initial calibration frequency band and the Nth initial calibration frequency band, respectively. For example, the random quality factor corresponding to the N-1th initial calibration frequency band is updated from 5 to 6, and the random quality factor corresponding to the Nth initial calibration frequency band is updated from 8 to 10.

[0097] When the N initial calibration frequency bands do not overlap with each other, for the i-th initial calibration frequency band and the i+1-th initial calibration frequency band among the N initial calibration frequency bands, the average of the right cutoff frequency of the i-th initial calibration frequency band and the left cutoff frequency of the i+1-th initial calibration frequency band is used as the adjusted frequency band cutoff frequency, where i is an integer and 1≤i≤N-1.

[0098] The filter construction module generates N target calibration frequency bands according to the adjusted frequency band cutoff frequencies. Exemplarily, when generating the target calibration frequency bands, the filter construction module may use the adjusted frequency band cutoff frequencies as the frequency band cutoff frequencies of the target calibration frequency bands.

[0099] As an optional manner, the filter construction module may further use a preset minimum frequency band cutoff frequency as the left cutoff frequency of the first target calibration frequency band among the N target calibration frequency bands, and use a preset maximum frequency band cutoff frequency as the right cutoff frequency of the Nth target calibration frequency band among the N target calibration frequency bands.

[0100] Taking initial calibration bands 1 and 2 as an example, the right cutoff frequency of initial calibration band 1 is 300, and the left cutoff frequency of initial calibration band 2 is 350. The average of the right cutoff frequency of initial calibration band 1 and the left cutoff frequency of initial calibration band 2, 325, is used as the adjusted band cutoff frequency. The adjusted band cutoff frequency constitutes the band cutoff frequency of the target calibration band.

[0101] In addition, as shown in Table 4, the preset minimum frequency band cutoff frequency 0 is used as the left cutoff frequency of the first target calibration frequency band, and the preset maximum frequency band cutoff frequency 24000 is used as the right cutoff frequency of the Nth target calibration frequency band.

[0102] The filter construction module constructs a calibration filter according to each target calibration frequency band and a calibration gain value matching each target calibration frequency band.

[0103] In operation S107 , the filter calibration module calibrates the initial frequency response value of the target candidate device using the calibration filter to obtain a calibrated frequency response value.

[0104] Exemplarily, the filter calibration module uses the constructed calibration filter to calibrate a frequency response curve that matches the target candidate device, and the calibrated frequency response curve indicates a calibrated frequency response value of the target candidate device.

[0105] There is no one-to-one correspondence between frequency points, but there can be a preset mapping relationship between the two. The filter calibration module can calibrate the frequency response curve using the calibration filter based on the preset mapping relationship to obtain a calibrated frequency response curve.

[0106] In operation S108 , the loop control module sends a loop termination notification to the filter construction module.

[0107] The loop control module calculates the variance of the calibrated frequency response values of multiple candidate devices and weights the variances corresponding to each frequency point of interest based on the preset attention level matched to each frequency point of interest. The weighted sum indicates the dispersion of the calibrated frequency response values. The attention level is a weight assigned based on the contribution of the corresponding frequency point of interest to the in-ear loudness.

[0108] Figure 6 The diagram schematically shows the weight distribution corresponding to the frequency points. Figure 6 As shown, curve 6A is the 40 Phon equal loudness curve. An equal loudness curve is a curve that equalizes the subjective perception of loudness (loudness level) of a sound, as determined through subjective measurement. Curve 6A shows that the sound pressure level within the medium wave range is at a relatively low level on the entire curve, indicating that the human ear is sensitive to medium wave sounds. Outside the medium wave range, the equal loudness curve tilts upward on both the short and long wave sides, indicating that the human ear is less sensitive to short and long wave sounds.

[0109] The curve shown in 6B is the weight distribution curve corresponding to the frequency points. Frequency points within the focus frequency range have higher weight values. The focus frequency range can be the frequency range of the frequency points that the human ear is most sensitive to. The higher the weight value corresponding to the frequency point, the higher the corresponding attention level. The weight value can be determined based on the contribution value of the corresponding frequency point to the loudness in the ear. Assigning weights based on the contribution value to the loudness in the ear can improve the consistency of devices in the frequency band sensitive to the human ear and better control sound leakage in the frequency band sensitive to the human ear.

[0110] The loop control module sends a loop termination notification to the filter construction module when the discreteness of the frequency response value after calibration is less than a preset discreteness threshold, or when the number of loop operations reaches a preset number threshold.

[0111] In operation S109 , the filter construction module sends the center frequency point information corresponding to the minimum discreteness to the frequency response calibration parameter determination module.

[0112] In operation S110 , the frequency response calibration parameter determination module uses the center frequency point corresponding to the minimum dispersion, the random quality factor matching the center frequency point, and the target frequency response value as frequency response calibration parameters.

[0113] In operation S111 , the calibration control module generates version update parameters based on the acquired frequency response calibration parameters.

[0114] Frequency response calibration parameters can be used to perform calibration compensation when an electronic device plays an audio signal, thereby reducing the difference between the frequency response curve of the played audio signal and the standard frequency response curve, which is beneficial to improving the audio playback performance of the electronic device and enhancing the user's listening experience.

[0115] Based on frequency response big data, the target frequency response value and calibration gain value based on the center frequency point are determined. A center frequency point is randomly selected from the preset frequency points of interest, and the frequency band to be calibrated is divided according to each center frequency point and the random quality factor that matches each center frequency point. Based on the discreteness of the calibrated frequency response value, the operation of randomly selecting the center frequency point and dividing the frequency band to be calibrated is repeated until the discreteness of the calibrated frequency response value is less than the preset discreteness threshold. This can effectively ensure the accuracy of the determined frequency response calibration parameters, help improve the frequency response calibration accuracy, and effectively ensure the consistency of the frequency response performance of different sound-generating components of the electronic device.

[0116] For electronic equipment to be calibrated:

[0117] In order to better understand the embodiment of the present application, the structure of the electronic device 100 according to the embodiment of the present application is introduced below.

[0118] like Figure 7 FIG is a schematic diagram showing the structure of an electronic device 100. Figure 7 Figure 1 shows a schematic diagram of the structure of electronic device 100. Optionally, electronic device 100 can be referred to as a terminal or a terminal device. Specifically, the product form factor can be a smart terminal, such as a mobile phone, tablet, DV, smartwatch, smart wearable device, portable computer, laptop computer, smart speaker, or other product. Specifically, the functional modules involved in this application can be deployed on the DSP chip of the relevant device, specifically as an application or software therein. A frequency response calibration function can be provided through software installation or upgrade, as well as through hardware invocation and coordination.

[0119] It should be understood that Figure 7 The illustrated electronic device 100 is merely one example of an electronic device, and the electronic device 100 may have more or fewer components than shown in the drawings, may combine two or more components, or may have a different configuration of components. Figure 7 The various components shown in the drawings may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and / or application specific integrated circuits.

[0120] The electronic device 100 may include: a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display 194, and a subscriber identification module (SIM) card interface 195. The sensor module 180 may include a pressure sensor, a gyroscope sensor, an acceleration sensor, a temperature sensor, a motion sensor, an air pressure sensor, a magnetic sensor, a distance sensor, a proximity light sensor, a fingerprint sensor, a touch sensor, an ambient light sensor, a bone conduction sensor, etc.

[0121] The processor 110 may include one or more processing units, for example, an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU). The different processing units may be independent devices or integrated into one or more processors.

[0122] The controller may be the nerve center and command center of the electronic device 100. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[0123] The processor 110 may further include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory.

[0124] The USB interface 130 is an interface that complies with USB standard specifications, and specifically may be a Mini USB interface, a Micro USB interface, a USB Type C interface, etc.

[0125] The charging management module 140 is configured to receive charging input from a charger. The charger can be either a wireless charger or a wired charger. While charging the battery 142, the charging management module 140 can also power the electronic device through the power management module 141. The power management module 141 is configured to connect the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140 and provides power to the processor 110, the internal memory 121, the external memory, the display 194, the camera 193, and the wireless communication module 160.

[0126] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor, the baseband processor, and the like.

[0127] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization.

[0128] The mobile communication module 150 can provide wireless communication solutions including 2G / 3G / 4G / 5G applied to the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), and the like.

[0129] The wireless communication module 160 can provide wireless communication solutions for application on the electronic device 100, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication technology (NFC), infrared technology (IR), etc.

[0130] In some embodiments, antenna 1 of electronic device 100 is coupled to mobile communication module 150 , and antenna 2 is coupled to wireless communication module 160 , so that electronic device 100 can communicate with the network and other devices through wireless communication technology.

[0131] The electronic device 100 can implement audio functions, such as voice communication function, audio playback function, etc., through the speaker 171, earpiece (ie, receiver) 172, microphone 173 and application processor in the audio module 170.

[0132] The audio module 170 is used to convert digital audio signals into analog audio signals for output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be provided in the processor 110, or some functional modules of the audio module 170 can be provided in the processor 110.

[0133] Speaker 171, also known as a "horn," is used to convert audio electrical signals into sound signals. Earpiece (i.e., receiver) 172 is used to convert audio electrical signals into sound signals. Microphone 173, also known as a "microphone," is used to convert sound signals into electrical signals.

[0134] The electronic device 100 implements display functions through a GPU, a display screen 194 , an application processor, etc. The processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

[0135] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. In some embodiments, the electronic device 100 may include one or N display screens 194, where N is a positive integer greater than one.

[0136] The electronic device 100 can implement a shooting function through an ISP, a camera 193, a video codec, a GPU, a display screen 194, and an application processor.

[0137] The ISP is used to process data fed back by the camera 193. For example, when taking a photo, the shutter is opened, and light is transmitted through the lens to the camera's photosensitive element. The light signal is converted into an electrical signal, which is then transmitted to the ISP for processing and converted into an image visible to the naked eye.

[0138] The camera 193 is used to capture still images or videos. The object generates an optical image through the lens and projects it onto the photosensitive element. The photosensitive element can be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the light signal into an electrical signal, and then passes the electrical signal to the ISP for conversion into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. The DSP converts the digital image signal into an image signal in a standard RGB, YUV or other format. In some embodiments, the electronic device 100 may include 1 or N cameras 193, where N is a positive integer greater than 1.

[0139] Among them, the camera 193 can be located in the edge area of the electronic device, can be an under-screen camera, or can be a liftable camera. The camera 193 can include a rear camera, and can also include a rear camera. The embodiment of the present application does not limit the specific position and form of the camera 193. The electronic device 100 can include cameras with one or more focal lengths. For example, cameras with different focal lengths can include a telephoto camera, a wide-angle camera, an ultra-wide-angle camera, or a panoramic camera.

[0140] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The external memory card communicates with the processor 110 through the external memory interface 120 to implement a data storage function.

[0141] The software system of the electronic device 100 may adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a microservice architecture, or a cloud architecture. In the embodiment of the present invention, the Android system with a layered architecture is used as an example to illustrate the software structure of the electronic device 100.

[0142] like Figure 8 This is an illustrative block diagram of the software structure of electronic device 100. The layered architecture of electronic device 100 divides the software into several layers, each with distinct roles and responsibilities. Layers communicate with each other via software interfaces. In some embodiments, the Android system is divided into five layers: application layer, application framework layer, Android runtime layer, system layer, and kernel layer, from top to bottom.

[0143] The application layer may include a series of application packages, which may include calls, address books, messages, music, gallery, etc. In an embodiment of the present application, the application layer may also install a calibration application. In some embodiments, the calibration application may receive the frequency response calibration parameters of the calibration device, and after receiving the frequency response calibration parameters, obtain the frequency response data stored locally in the electronic device, the frequency response data including the initial frequency response value of the electronic device based on each center frequency point. The calibration application is also used to calibrate the frequency response value of the electronic device for the test audio signal based on the frequency response calibration parameters and the frequency response data, and obtain the calibrated device frequency response value.

[0144] The application framework layer provides application programming interfaces (APIs) and programming frameworks for applications in the application layer, including various components and services to support developers' Android development. The application framework layer includes some predefined functions. Figure 8 As shown, the application framework layer may include a window manager, a resource manager, a content provider, a notification manager, a screen management service, and the like.

[0145] The window manager is used to manage window programs. The window manager can obtain the display screen size, determine whether there is a status bar, lock the screen, take screenshots, etc.

[0146] The resource manager can provide various resources for applications, such as localized strings, icons, images, layout files, video files, etc.

[0147] The system layer includes the system library and the Android Runtime. The system library can include multiple functional modules, such as the image rendering library, image synthesis library, function library, and media library. The image rendering library can provide image processing functions to help meet various image processing requirements.

[0148] In the embodiment of the present application, the application framework layer may include some predefined functions. Figure 8 As shown, the application framework layer is equipped with an audio playback management service. The audio playback management service can be used to initialize the audio and video player, obtain the current audio volume, adjust the audio playback volume, add sound effects, etc.

[0149] The Android runtime consists of core libraries and a virtual machine (VM). The runtime is responsible for scheduling and management of the Android system. The core libraries consist of two parts: one containing the Java language's callable functions and the other the Android core library. The application layer and the application framework layer run in the VM, which executes the Java files in the application and framework layers as binary files. The VM is responsible for managing object lifecycles, stack management, thread management, security and exception management, and garbage collection.

[0150] The HAL layer provides HALs corresponding to different hardware modules of electronic devices, such as AudioHAL, CameraHAL, WiFi HAL, smart PA control HAL, and information storage HAL.

[0151] The Audio HAL can correspond to audio output devices (such as speakers and screen sound devices) through the audio driver of the kernel layer. When a mobile phone is equipped with multiple audio output devices (such as multiple speakers or screen sound devices), the multiple audio output devices correspond to multiple audio drivers of the kernel layer.

[0152] The smart PA control HAL (HAL) interfaces with the smart PA hardware circuit via the smart PA algorithm in the DSP. For example, when the smart PA control HAL receives a calibration instruction from a calibration application in the application layer, it can control the smart PA algorithm to play audio signals. When the smart PA control HAL receives a call instruction from a call application or a music playback instruction from a music application in the application layer, it can control the smart PA algorithm to play the other party's voice signal or the audio signal corresponding to the music. Furthermore, the smart PA control HAL can also control the activation of smart PA hardware circuits (such as the hardware circuit of the screen sound device (smart PA0)) via I2C signals to play audio signals through the screen sound device.

[0153] The information storage HAL corresponds to the electronic device's non-volatile storage medium (e.g., memory) and is used to store frequency response calibration parameters calculated by the electronic device or calibration device in the electronic device's non-volatile storage medium. For example, when the electronic device receives the frequency response calibration parameters calculated by the calibration device, the information storage HAL may store the frequency response calibration parameters in the electronic device's non-volatile storage medium. Frequency response calibration is used to reduce the difference between the frequency response curve of the actual audio signal played and the standard frequency response curve, thereby improving the applicability of the frequency response calibration parameters.

[0154] The kernel layer is located below the HAL and is a layer between hardware and software. In addition to including audio drivers, the kernel layer may also include display drivers, camera drivers, sensor drivers, etc., which are not limited in this embodiment of the present application.

[0155] The hardware circuit is located below the kernel layer. In an embodiment of the present application, the hardware circuit may include a digital signal processing (DSP) chip, in which a smart PA algorithm module, an audio algorithm module, etc. may run.

[0156] The smart PA algorithm module includes a filter calibration module. When the smart PA control HAL receives the frequency response calibration parameters sent by the calibration application, the information storage HAL checks whether frequency response data is stored in the non-volatile storage device. If the information storage HAL detects frequency response data, it sends the frequency response data to the filter calibration module. The filter calibration module constructs a calibration filter based on the frequency response calibration parameters and the locally stored frequency response data. The filter calibration module also uses the calibration filter to calibrate the frequency response value of the electronic device for the audio signal to be played, generating a calibrated audio signal.

[0157] It is understandable that Figure 8 The components included in the illustrated system framework layer, system library, and runtime layer do not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or may combine or split certain components, or arrange the components differently.

[0158] Figure 9 The following schematic diagram shows a frequency response calibration process. Figure 9 As shown, the calibration application in the application layer receives frequency response calibration parameters, which include the center frequency point, a target frequency response value based on the center frequency point, and a random quality factor. The calibration application sends the frequency response calibration parameters to the smart PA control HAL in the HAL layer and sends a frequency response calibration instruction to the information storage HAL. The smart PA control HAL passes the received frequency response calibration parameters to the smart PA algorithm in the DSP chip, for example, to the filter construction module in the smart PA algorithm. After receiving the frequency response calibration instruction, the information storage HAL checks whether frequency response data is stored in the non-volatile storage device. The frequency response data includes the initial frequency response values of the device to be calibrated based on each center frequency point. If locally stored frequency response data is detected, the information storage HAL sends the frequency response data to the filter construction module in the smart PA algorithm.

[0159] The filter construction module determines a calibration gain value that matches each center frequency point based on the initial frequency response value and the target frequency response value at each center frequency point. Exemplarily, the filter construction module calculates the difference between the initial frequency response value and the target frequency response value of the device to be calibrated at each center frequency point and uses the difference as the calibration gain value for the device to be calibrated at the corresponding center frequency point.

[0160] The filter construction module constructs a calibration filter based on each center frequency point, a random quality factor matching each center frequency point, and a calibration gain value. Exemplarily, the filter construction module determines N initial calibration frequency bands based on each center frequency point and the random quality factor matching each center frequency point. If there are overlapping frequency bands among the N initial calibration frequency bands, the filter construction module updates the random quality factor and / or center frequency point corresponding to the overlapping frequency band, and re-determines the corresponding initial calibration frequency band based on the updated random quality factor and / or updated center frequency point, until the N initial calibration frequency bands do not overlap.

[0161] In the case that the N initial calibration frequency bands do not overlap with each other, the filter construction module generates N target calibration frequency bands according to frequency band cutoff frequencies of adjacent frequency bands in the N initial calibration frequency bands.

[0162] As an optional method, for the i-th initial calibration frequency band and the i+1-th initial calibration frequency band among the N initial calibration frequency bands, the average of the right cutoff frequency of the i-th initial calibration frequency band and the left cutoff frequency of the i+1-th initial calibration frequency band is used as the adjusted frequency band cutoff frequency, where i is an integer and 1≤i≤N-1.

[0163] The filter construction module generates N target calibration frequency bands according to the adjusted frequency band cutoff frequencies. Exemplarily, when generating the target calibration frequency bands, the filter construction module may use the adjusted frequency band cutoff frequencies as the frequency band cutoff frequencies of the target calibration frequency bands.

[0164] The filter construction module constructs a calibration filter according to each target calibration frequency band and a calibration gain value matching each target calibration frequency band, and sends the constructed calibration filter to the frequency response calibration module.

[0165] When the audio application is ready to play an audio signal, the audio application sends the audio signal to be played to the smart PA control HAL, and the smart PA control HAL passes the audio signal to be played to the frequency response calibration module in the smart PA algorithm.

[0166] The frequency response calibration module uses a calibration filter to calibrate the frequency response of the audio signal being played. For example, the frequency response calibration module performs a Fourier transform on the audio signal to obtain a converted frequency domain signal. The frequency response calibration module uses the calibration filter to calibrate the converted frequency domain signal to obtain a calibrated audio signal. The frequency response calibration module transmits the calibrated audio signal to the sound-generating device, which then plays the calibrated audio signal.

[0167] In the embodiment of the present application, the device to be calibrated may be, for example, a sound-generating device in an electronic device, and the sound-generating device may include, for example, a speaker, an earpiece, a screen sound-generating device, etc., which is not limited in this embodiment.

[0168] The filter calibration module sends the calibrated device frequency response value to the capacitive device parameter determination module, which determines the capacitive device parameters suitable for the device to be calibrated (such as the sound-generating device) based on the calibrated device frequency response value.

[0169] During normal use of an electronic device, when an audio-related application (such as a call application or a music application) runs in response to a user operation, the smart PA control HAL issues an audio playback instruction. The smart PA control HAL receives the audio playback instruction, and the information storage HAL detects whether the frequency response calibration parameters are stored in the non-volatile storage device. If the information storage HAL detects the frequency response calibration parameters, the information storage HAL obtains the frequency response calibration parameters from the non-volatile storage medium and sends the frequency response calibration parameters to the filter calibration module. In response to the received frequency response calibration parameters, the filter calibration module determines the filter type, center frequency, frequency response gain and other parameters based on the frequency response calibration parameters. In addition, the filter calibration module can also convert the audio signal to be played into a frequency domain signal, and use the multi-band filter in the filter calibration module to calibrate the frequency domain gain, and send the calibrated audio signal to the smart PA hardware circuit, so that the sound-generating device of the electronic device plays the calibrated audio signal.

[0170] Figure 10 The following diagram schematically shows the frequency response calibration process during a call. Figure 10 As shown in the figure, during a call, the call application sends a frequency response calibration instruction to the smart PA control HAL by calling the call service in the system service layer. The smart PA control HAL obtains the frequency response calibration parameters, which include the optimized center frequency point Fc, the random quality factor Q that matches the center frequency point Fc, and the target frequency response value. The smart PA control HAL can also obtain the locally stored frequency response data from the non-volatile storage medium. The frequency response data includes the initial frequency response value FR that matches the center frequency point Fc. The smart PA control HAL sends the initial frequency response value FR, the random quality factor Q based on the center frequency point Fc, and the target frequency response value to the privacy call algorithm in the call downlink HAL.

[0171] The filter calibration module in the privacy call algorithm is based on the initial frequency response value FR and the target frequency response value of each center frequency point Fc. Determine the calibration gain value that matches each center frequency point Fc. For example, the filter calibration module calculates the initial frequency response value FR based on each center frequency point Fc. Fc and target frequency response value The filter calibration module constructs a calibration filter based on the center frequency point Fc and the calibration gain value and random quality factor that match the center frequency point Fc.

[0172] During a call, the call application invokes the call service in the system service layer and issues a call instruction to the call downlink HAL. The call algorithm in the call downlink HAL generates a call audio signal. The call algorithm sends the call audio signal to the filter calibration module in the privacy call algorithm. The filter calibration module uses the constructed calibration filter to calibrate the frequency response of the call audio signal, generating a calibrated audio signal. The call downlink HAL then drives sound generators 1 and 2 in the smart PA hardware circuit to generate sound.

[0173] It is understandable that, in order to implement the above functions, the electronic device includes hardware and / or software modules that perform the corresponding functions. In combination with the algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application in combination with the embodiments, but such implementation should not be considered to be beyond the scope of this application.

[0174] All relevant contents of each step involved in the above method embodiment can be referred to the functional description of the corresponding functional module and will not be repeated here.

[0175] This embodiment further provides an electronic device, comprising: one or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: obtaining initial frequency response values of multiple candidate devices based on preset frequency points of interest to obtain frequency response big data; determining a target frequency response value matching each frequency point of interest based on the frequency response big data; and looping the following operations until the discreteness of the calibrated frequency response value is less than a preset discreteness threshold, or the number of loop operations reaches a preset number threshold: selecting some frequency points from the frequency points of interest as the center frequency points to be calibrated. point; determining a calibration gain value matching each center frequency point according to an initial frequency response value and a target frequency response value of the target candidate device based on each center frequency point, the target candidate device including any candidate device from a plurality of candidate devices; calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; calculating the number of loop operations and the discreteness of the calibrated frequency response values of the plurality of candidate devices; and when the discreteness of the calibrated frequency response value is less than a preset discreteness threshold, or the number of loop operations reaches a preset number threshold, using the center frequency point corresponding to the minimum discreteness, the random quality factor matching the center frequency point, and the target frequency response value as frequency response calibration parameters.

[0176] This embodiment also provides an electronic device, comprising: one or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: receiving version update parameters, the version update parameters including a center frequency point and a random quality factor and a target frequency response value based on the center frequency point; in response to the received version update parameters, obtaining locally stored frequency response data, the frequency response data including an initial frequency response value of the device to be calibrated based on each center frequency point; determining a calibration gain value matching each center frequency point based on the initial frequency response value and the target frequency response value based on each center frequency point; constructing a calibration filter based on the random quality factor and the calibration gain value matching each center frequency point; using the calibration filter, calibrating the frequency response value of the device to be calibrated for the audio signal to be played, to obtain a calibrated audio signal.

[0177] This embodiment further provides a computer storage medium having computer instructions stored therein. When the computer instructions are executed on an electronic device, the electronic device executes the above-mentioned related method steps to implement the frequency response calibration parameter determination method and frequency response calibration method in the above-mentioned embodiment.

[0178] This embodiment further provides a computer program product. When the computer program product is run on a computer, it causes the computer to execute the above-mentioned related steps to implement the method for determining frequency response calibration parameters and the frequency response calibration method in the above-mentioned embodiment.

[0179] In addition, an embodiment of the present application further provides a device, which may be a chip, component, or module. The device may include a connected processor and memory; wherein the memory is used to store computer-executable instructions. When the device is running, the processor may execute the computer-executable instructions stored in the memory to enable the chip to perform the frequency response calibration parameter determination method and frequency response calibration method in the above-mentioned method embodiments.

[0180] Among them, the electronic device, computer storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0181] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0182] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0183] Units described as separate components may or may not be physically separate, and components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0184] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0185] Any content of each embodiment of this application, as well as any content of the same embodiment, can be freely combined. Any combination of the above content is within the scope of this application.

[0186] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0187] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0188] The steps of the method or algorithm described in conjunction with the disclosure of the embodiments of the present application can be implemented in a hardware manner, or can be implemented by a processor executing a software instruction. The software instruction can be composed of corresponding software modules, and the software module can be stored in a random access memory (Random Access Memory, RAM), a flash memory, a read-only memory (Read Only Memory, ROM), an erasable programmable read-only memory (Erasable Programmable ROM, EPROM), an electrically erasable programmable read-only memory (Electrically EPROM, EEPROM), a register, a hard disk, a mobile hard disk, a read-only compact disc (CD-ROM) or any other form of storage medium well known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and can write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an ASIC.

[0189] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0190] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A method for determining frequency response calibration parameters, characterized in that: include: Obtaining initial frequency response values of multiple candidate devices based on preset frequency points of interest to obtain frequency response big data; Determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data; The following operations are performed cyclically until the dispersion of the frequency response value after calibration is less than the preset dispersion threshold, or the number of cyclic operations reaches the preset threshold: Selecting some frequency points from the frequency points of interest as central frequency points to be calibrated; determining, according to the initial frequency response value and the target frequency response value of the target candidate device based on each of the center frequency points, a calibration gain value matching each of the center frequency points, the target candidate device including any candidate device among the plurality of candidate devices; calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; Calculating the number of cycle operations and the dispersion of the calibrated frequency response values of the plurality of candidate devices; as well as When the dispersion of the calibrated frequency response value is less than a preset dispersion threshold, or the number of loop operations reaches a preset number threshold, the center frequency point corresponding to the minimum dispersion, and the target frequency response value and random quality factor matching the center frequency point are used as the frequency response calibration parameters.

2. The method according to claim 1, characterized in that Determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data includes: Calculating an average of the initial frequency response values of the plurality of candidate devices based on the respective frequency points of interest; and Based on a preset calibration gain interval, the mean of the initial frequency response values is adjusted to obtain the target frequency response value matching each of the frequency points of interest.

3. The method according to claim 1, characterized in that The selecting of some frequency points from the frequency points of interest as the center frequency points to be subjected to the frequency response calibration comprises: Setting N candidate calibration frequency bands, each candidate calibration frequency band in the N candidate calibration frequency bands having a corresponding preset importance level, where N is an integer greater than 1; and According to a preset frequency point spacing threshold and the importance level corresponding to each of the candidate calibration frequency bands, N frequency points are randomly selected from the frequency points of interest to serve as the central frequency points for frequency response calibration.

4. The method according to claim 1, wherein The step of determining a calibration gain value matching each of the center frequency points based on the initial frequency response value and the target frequency response value of each of the center frequency points according to the target candidate device includes: The difference between the initial frequency response value of the target candidate device based on each center frequency point and the target frequency response value is calculated, and the difference is used as the calibration gain value matched with the corresponding center frequency point.

5. The method according to claim 1, wherein The step of calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value includes: Determining N initial calibration frequency bands according to each of the center frequency points and a random quality factor matched with each of the center frequency points; If there is an overlapping frequency band among the N initial calibration frequency bands, updating the random quality factor and / or the center frequency point corresponding to the overlapping frequency band, and re-determining the corresponding initial calibration frequency band according to the updated random quality factor and / or the updated center frequency point until the N initial calibration frequency bands do not overlap with each other; Generating N target calibration frequency bands according to frequency band cutoff frequencies of adjacent frequency bands in the N initial calibration frequency bands that do not overlap with each other; constructing a calibration filter according to each of the target calibration frequency bands and the calibration gain value matched with each of the target calibration frequency bands; and The initial frequency response value of the target candidate device is calibrated using the calibration filter to obtain the calibrated frequency response value.

6. The method according to claim 5, characterized in that Generating N target calibration frequency bands according to frequency band cutoff frequencies of adjacent frequency bands in the N non-overlapping initial calibration frequency bands includes: For an i-th initial calibration frequency band and an (i+1)-th initial calibration frequency band among the N initial calibration frequency bands, taking an average of a right cutoff frequency of the i-th initial calibration frequency band and a left cutoff frequency of the (i+1)-th initial calibration frequency band as the adjusted frequency band cutoff frequency, where i is an integer and 1≤i≤N-1; and The N target calibration frequency bands are generated according to the adjusted frequency band cutoff frequencies.

7. The method according to claim 6, characterized in that The method further comprises: Using the preset minimum frequency band cutoff frequency as the left cutoff frequency of the first target calibration frequency band among the N target calibration frequency bands; and The preset maximum frequency band cutoff frequency is used as the right cutoff frequency of the Nth target calibration frequency band among the N target calibration frequency bands.

8. The method according to claim 5, characterized in that The obtaining of initial frequency response values of a plurality of candidate devices based on preset frequency points of interest includes: Playing a test audio signal using each candidate device to obtain a frequency response curve matching each candidate device, wherein the frequency response curve indicates an initial frequency response value of the candidate device based on the frequency point of interest; The step of calibrating the initial frequency response value of the target candidate device by using the calibration filter to obtain the calibrated frequency response value includes: The frequency response curve matching the target candidate device is calibrated using the calibration filter, and the calibrated frequency response curve indicates the calibrated frequency response value of the target candidate device.

9. The method according to claim 8, characterized in that The test audio signal is a full-frequency domain scanning signal.

10. The method according to claim 8, characterized in that The step of calibrating the frequency response curve matching the target candidate device by using the calibration filter includes: Determining a candidate frequency point that matches the frequency point of interest based on a preset mapping relationship; The frequency response curve is calibrated using the calibration filter according to the calibration gain value of the target candidate component based on the candidate frequency point to obtain the calibrated frequency response curve.

11. The method according to claim 8, characterized in that The calculating the dispersion of the calibrated frequency response values of the plurality of candidate devices includes: calculating variances of the calibrated frequency response curves of the plurality of candidate devices; According to the preset attention level matched with each of the frequency points of interest, the variances corresponding to the frequency points of interest are weighted and summed, and the weighted summation result indicates the dispersion of the frequency response value after calibration, The attention level is a weight value assigned according to the contribution value of the corresponding frequency point of interest to the loudness in the ear.

12. The method according to claim 1, characterized in that The method further comprises: The frequency response calibration parameters are sent to the device to be calibrated as version update parameters.

13. A frequency response calibration method, applied to a device to be calibrated, characterized in that: The method comprises: receiving version update parameters, wherein the version update parameters include a center frequency point, a random quality factor based on the center frequency point, and a target frequency response value; In response to the received version update parameter, locally stored frequency response data is acquired, where the frequency response data includes initial frequency response values of the device to be calibrated based on each of the center frequency points; determining a calibration gain value matching each of the center frequency points according to the initial frequency response value based on each of the center frequency points and the target frequency response value; Constructing a calibration filter according to the center frequency point, the random quality factor matched with the center frequency point, and the calibration gain value; The calibration filter is used to calibrate the frequency response value of the device to be calibrated for the audio signal to be played, thereby obtaining a calibrated audio signal.

14. The method according to claim 13, characterized in that The step of determining a calibration gain value matching each of the center frequency points based on the initial frequency response value and the target frequency response value of each of the center frequency points includes: The difference between the initial frequency response value of the device to be calibrated based on each center frequency point and the target frequency response value is calculated, and the difference is used as the calibration gain value of the device to be calibrated based on the corresponding center frequency point.

15. The method according to claim 13, characterized in that The constructing a calibration filter according to the center frequency point, the random quality factor matched with the center frequency point, and the calibration gain value includes: Determining N initial calibration frequency bands according to each of the center frequency points and a random quality factor matched with each of the center frequency points; If there is an overlapping frequency band among the N initial calibration frequency bands, updating the random quality factor and / or the center frequency point corresponding to the overlapping frequency band, and re-determining the corresponding initial calibration frequency band according to the updated random quality factor and / or the updated center frequency point until the N initial calibration frequency bands do not overlap with each other; generating N target calibration frequency bands according to frequency band cutoff frequencies of adjacent frequency bands in the N initial calibration frequency bands that do not overlap with each other; and A calibration filter is constructed according to each of the target calibration frequency bands and the calibration gain value matched with each of the target calibration frequency bands.

16. The method according to claim 13, characterized in that The method of calibrating the frequency response value of the device to be calibrated with respect to the audio signal to be played by using the calibration filter to obtain a calibrated audio signal includes: Performing Fourier transform on the audio signal to be played by the device to be calibrated to obtain a converted frequency domain signal; and The converted frequency domain signal is calibrated using the calibration filter to obtain the calibrated audio signal.

17. An electronic device, characterized in that: include: One or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored on the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: Obtaining initial frequency response values of multiple candidate devices based on preset frequency points of interest to obtain frequency response big data; Determining a target frequency response value matching each of the frequency points of interest based on the frequency response big data; The following operations are performed cyclically until the dispersion of the frequency response value after calibration is less than the preset dispersion threshold, or the number of cyclic operations reaches the preset threshold: Selecting some frequency points from the frequency points of interest as central frequency points to be calibrated; determining, according to the initial frequency response value and the target frequency response value of the target candidate device based on each of the center frequency points, a calibration gain value matching each of the center frequency points, the target candidate device including any candidate device among the plurality of candidate devices; calibrating the initial frequency response value of the target candidate device according to the calibration gain value to obtain a calibrated frequency response value; Calculating the number of cycle operations and the dispersion of the calibrated frequency response values of the plurality of candidate devices; as well as When the dispersion of the calibrated frequency response value is less than a preset dispersion threshold, or the number of loop operations reaches a preset number threshold, the center frequency point corresponding to the minimum dispersion, and the target frequency response value and random quality factor matching the center frequency point are used as the frequency response calibration parameters.

18. An electronic device, characterized in that: include: One or more processors, a memory, and one or more computer programs, wherein the one or more computer programs are stored on the memory, and when the computer programs are executed by the one or more processors, the electronic device performs the following steps: receiving version update parameters, wherein the version update parameters include a center frequency point, a random quality factor based on the center frequency point, and a target frequency response value; In response to the received version update parameter, locally stored frequency response data is acquired, where the frequency response data includes initial frequency response values of the device to be calibrated based on each of the center frequency points; determining a calibration gain value matching each of the center frequency points according to the initial frequency response value based on each of the center frequency points and the target frequency response value; Constructing a calibration filter according to the center frequency point, the random quality factor matched with the center frequency point, and the calibration gain value; The calibration filter is used to calibrate the frequency response value of the device to be calibrated for the audio signal to be played, thereby obtaining a calibrated audio signal.

19. A computer-readable storage medium, characterized in that The method comprises a computer program, which, when executed on an electronic device, causes the electronic device to execute the method for determining frequency response calibration parameters according to any one of claims 1 to 12, or the frequency response calibration method according to any one of claims 13 to 16.

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