Earphone noise reduction method and device, wearable device and computer readable storage medium

Abstract

The embodiment of the application provides a kind of earphone noise reduction method, device, wearable device and computer readable storage medium, belong to the field of noise reduction, the method comprises: detecting environmental noise;When the environmental noise is less than or equal to the first preset noise threshold, the ear canal parameter of user is acquired;According to the ear canal parameter, matching noise reduction filter parameter;According to the noise reduction filter parameter, the noise reduction processing in ear canal is carried out.In the environment of environmental noise less than the first preset noise threshold, ear canal adaptive detection function will be started, automatically detect the ear canal parameter of user, and automatically match noise reduction filter parameter, improve the effect of noise reduction, so that user can experience more suitable noise reduction effect.

Description

Technical Field

[0001] This application relates to the field of noise reduction technology, and in particular to a method, apparatus, wearable device and computer-readable storage medium for headphone noise reduction. Background Technology

[0002] Existing noise-canceling headphones can automatically detect the user's activity status and location, such as an office, gym, or coffee shop, by enabling adaptive sound control. They can automatically switch between preset ambient sound and noise cancellation schemes. In the existing scheme, an ambient noise level of less than 70dB SPL is defined as an office environment, and a preset active noise cancellation (ANC) filter parameter is used. However, there is no further subdivision to match the most suitable noise cancellation filter parameter, resulting in relatively poor noise cancellation performance. Summary of the Invention

[0003] To address the aforementioned technical problems, embodiments of this application provide a headphone noise reduction method, apparatus, wearable device, and computer-readable storage medium.

[0004] In a first aspect, embodiments of this application provide a headphone noise reduction method, the method comprising:

[0005] Detecting environmental noise;

[0006] When the ambient noise is less than or equal to a first preset noise threshold, the user's ear canal parameters are obtained.

[0007] Match the noise reduction filter parameters according to the ear canal parameters;

[0008] Noise reduction processing is performed in the ear canal based on the noise reduction filter parameters.

[0009] In one embodiment, the ear canal parameters include: a passive noise reduction curve in the ear canal, and the noise reduction filter parameters include: target feedforward filter parameters;

[0010] The step of matching noise reduction filter parameters according to the ear canal parameters includes:

[0011] The target feedforward filter parameters are generated based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value.

[0012] In one embodiment, generating target feedforward filter parameters based on the passive noise reduction curve in the ear canal and the deepest noise reduction effect value includes:

[0013] Adjust the feedforward filter parameters according to the passive noise reduction curve of the ear canal and the deepest noise reduction effect value to perform noise reduction processing;

[0014] Detect the current residual noise level in the user's ear canal;

[0015] Determine whether the difference between the current residual noise value and the residual noise value of the target model is less than or equal to a second preset noise threshold;

[0016] If the difference is less than or equal to the second preset noise threshold, then the current feedforward filter parameters are determined as the target feedforward filter parameters;

[0017] If the difference is greater than the second preset noise threshold, the feedforward filter parameters of the headphones are adjusted until the difference between the residual noise value in the user's ear canal and the residual noise value of the target model is less than the second preset noise threshold, and the current feedforward filter parameters are determined as the target feedforward filter parameters.

[0018] In one embodiment, obtaining the residual noise value of the target model includes:

[0019] Obtain the objective noise reduction curve;

[0020] The residual noise value of the target model is determined based on the maximum noise reduction depth of the objective noise reduction curve.

[0021] In one embodiment, the feedforward filter parameters include frequency points and gain values; adjusting the feedforward filter parameters according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value includes:

[0022] The frequency point and the gain value are adjusted according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value.

[0023] In one embodiment, when the ambient noise is greater than the first preset noise threshold, the target environment in which the user is located is determined based on the ambient noise.

[0024] Obtain the target active noise reduction parameters that match the target environment;

[0025] Noise reduction processing is performed based on the target active noise reduction parameters.

[0026] In one embodiment, obtaining the target active noise reduction parameters that match the target environment includes:

[0027] Obtain the target noise frequency band corresponding to the target environment;

[0028] Determine the maximum noise reduction depth for the target noise frequency band;

[0029] The target active noise reduction parameters are determined based on the maximum noise reduction depth.

[0030] Secondly, embodiments of this application provide a headphone noise reduction device, the headphone noise reduction device comprising:

[0031] The detection module is used to detect environmental noise;

[0032] The acquisition module is used to acquire the user's ear canal parameters when the ambient noise is less than or equal to a first preset noise threshold;

[0033] The matching module is used to match the noise reduction filter parameters according to the ear canal parameters;

[0034] The noise reduction module is used to perform noise reduction processing within the ear canal according to the noise reduction filter parameters.

[0035] Thirdly, embodiments of this application provide a wearable device, including a memory and a processor, wherein the memory is used to store a computer program, and the computer program executes the headphone noise reduction method provided in the first aspect when the processor is running.

[0036] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when run on a processor, executes the headphone noise reduction method provided in the first aspect.

[0037] The headphone noise reduction method, apparatus, wearable device, and computer-readable storage medium provided in this application detect ambient noise when a user is wearing headphones; when the ambient noise is less than or equal to a first preset noise threshold, the user's ear canal parameters are acquired; target feedforward filter parameters are generated based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value; and noise reduction processing is performed in the ear canal based on the target feedforward filter parameters. In environments where the ambient noise is less than the first preset noise threshold, an adaptive detection function in the ear canal is activated to automatically detect the user's passive noise reduction curve of the ear canal and automatically match the target feedforward filter parameters, improving the noise reduction effect and allowing the user to experience a more suitable noise reduction effect. Attached Figure Description

[0038] To more clearly illustrate the technical solutions of this application, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be considered as a limitation on the scope of protection of this application. In the various drawings, similar components are numbered similarly.

[0039] Figure 1 A flowchart of the headphone noise reduction method provided in an embodiment of this application is shown;

[0040] Figure 2 Another schematic flowchart of the headphone noise reduction method provided in this application embodiment is shown;

[0041] Figure 3 Another schematic flowchart of the headphone noise reduction method provided in this application embodiment is shown;

[0042] Figure 4 A schematic diagram of the headphone noise reduction device provided in an embodiment of this application is shown.

[0043] Icons: 400 - Headphone noise cancellation device; 401 - Detection module; 402 - Acquisition module; 403 - Matching module; 404 - Noise cancellation module. Detailed Implementation

[0044] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0045] The components of this application, typically described and illustrated in the accompanying drawings, can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0046] In the following, the terms “comprising,” “having,” and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as excluding, firstly, the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations thereof.

[0047] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0048] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0049] This application provides a method for noise reduction in headphones.

[0050] See Figure 1 Noise cancellation methods for headphones include:

[0051] Step S101: Detect ambient noise.

[0052] As an example, when a user puts the headphones on their ears, the headphones automatically detect that the user is wearing them. At this point, the headphones automatically initiate the first detection step, namely, activating the environmental detection function. This environmental detection function uses a single feedforward microphone (FF MIC) on the headphones to detect ambient noise and determine whether the detected ambient noise is less than 70 dBSPL in order to proceed to the next detection mode.

[0053] It should be noted that, depending on the capabilities of the headphone microphone, the threshold for ambient noise can be set to other values, such as 60 / 50dB. In addition, the threshold for ambient noise can also be adjusted according to the actual power consumption, which is not restricted here.

[0054] Step S102: When the ambient noise is less than or equal to a first preset noise threshold, obtain the user's ear canal parameters.

[0055] Since existing technologies generally classify ambient noise levels below 70 dBSPL as office environments and lack more accurate noise reduction solutions, this embodiment, to provide a more suitable noise reduction solution, can set the first preset noise threshold to 70 dBSPL. Alternatively, it can be set to other noise values; no restriction is placed here. Each user has a corresponding ear canal parameter. Based on the user's personalized ear canal parameter, subsequent noise reduction adjustments can be made for the individual user. For example, the user's ear canal parameter can be an ear canal passive noise reduction curve.

[0056] As an example, when the ambient noise detected by the headphone's FF MIC is less than a first preset noise threshold (e.g., 70 dBSPL), an adaptive detection function within the ear canal is activated. Because everyone's ear canal is different, this is reflected in noise-canceling headphones, meaning the ear canal parameters are different. For example, a passive noise cancellation curve can be used to characterize a user's ear canal features. Since noise cancellation effectiveness heavily relies on passive noise cancellation, theoretically, each person has a filter that best suits their own ear canal. Therefore, by obtaining the user's passive noise cancellation curve, the noise cancellation filter parameters that best suit the user can be obtained.

[0057] Step S103: Match the noise reduction filter parameters according to the ear canal parameters.

[0058] In this embodiment, the noise reduction filter parameters can be the target feedforward filter parameters. Noise reduction filter parameters matched based on the user's individual ear canal parameters are more adaptable to the user's individual ear canal characteristics and improve the noise reduction effect.

[0059] In one embodiment, step S103 includes:

[0060] The target feedforward filter parameters are generated based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value.

[0061] In this embodiment, the passive noise reduction curve in the ear canal is the noise reduction value of each frequency point automatically calculated by the headphone device. Since the calculation of the passive noise reduction curve in the ear canal is a large amount of work and takes a long time, the usual practice is to set a certain frequency range and set the maximum noise reduction value of that frequency range. This makes it easier for the system to automatically calculate and identify the passive noise reduction curve in the ear canal.

[0062] In this embodiment, the maximum noise reduction effect value can be set according to the requirements defined by the actual product, generally not exceeding 50dB; considering the waterbed effect, 40dB is recommended as the optimal value.

[0063] See Figure 2 Step S103 includes:

[0064] Step S1031: Adjust the parameters of the feedforward filter according to the passive noise reduction curve of the ear canal and the deepest noise reduction effect value to perform noise reduction processing.

[0065] In one embodiment, the feedforward filter parameters include frequency points and gain values; adjusting the feedforward filter parameters according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value includes:

[0066] The frequency point and the gain value are adjusted according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value.

[0067] Step S1032: Detect the current residual noise value in the user's ear canal.

[0068] In this embodiment, when the ambient noise is less than a first preset noise threshold, the single feedback microphone (FB MIC) will automatically start to obtain the current residual noise value in the ear canal.

[0069] Step S1033: Determine whether the difference between the current residual noise value and the target model residual noise value is less than or equal to the second preset noise threshold.

[0070] In this embodiment, the second preset noise threshold can be a relatively small noise value, for example, 1 dB. If the difference is less than or equal to the second preset noise threshold, it indicates that the current residual noise value is close to the residual noise value of the target model, and the feedforward filter parameters are determined to be the most suitable at this time. If the difference is greater than the second preset noise threshold, it indicates that the difference between the current residual noise value and the residual noise value of the target model is relatively large, and the feedforward filter parameters need to be adjusted until the difference between the detected residual noise value and the residual noise value of the target model is less than or equal to the second preset noise threshold.

[0071] In one embodiment, obtaining the residual noise value of the target model includes:

[0072] Obtain the objective noise reduction curve;

[0073] The residual noise value of the target model is determined based on the maximum noise reduction depth of the objective noise reduction curve.

[0074] In one implementation, the maximum noise reduction depth of the objective noise reduction curve can be matched with that of the Soundcheck and simulated artificial head testing system to obtain the residual noise value of the target model; for example, the maximum noise reduction depth within 200Hz reaches 40dB.

[0075] Step S1034: If the difference is less than or equal to the second preset noise threshold, then the current feedforward filter parameters are determined as the target feedforward filter parameters.

[0076] In this embodiment, if the difference is less than or equal to the second preset noise threshold, it means that the current residual noise value is close to the residual noise value of the target model. It is determined that the feedforward filter parameters at this time are the most suitable, and the current feedforward filter parameters are determined as the target feedforward filter parameters for noise reduction processing.

[0077] As an example, if the first preset noise threshold is 70dB, and the current ambient noise is 60dB, which is less than 70dB, the noise recognition will be inaccurate due to the low noise level, and existing technologies cannot achieve precise noise reduction. The headphone noise reduction method provided in this embodiment, based on ear canal parameters and the approximate noise level of the current environment, can determine a noise reduction range. For example, if the current ambient noise is 60dB, which falls within the 50dB-70dB noise reduction range, a noise reduction depth of 20dB-40dB can be applied to achieve a noise reduction effect that maintains a perceived sound level of around 30dB.

[0078] Step S1035: If the difference is greater than the second preset noise threshold, the feedforward filter parameters of the headphones are adjusted until the difference between the residual noise value in the user's ear canal and the residual noise value of the target model is less than the first preset noise threshold, and the current feedforward filter parameters are determined as the target feedforward filter parameters.

[0079] In this embodiment, when the difference is greater than the second preset noise threshold, it indicates that the current residual noise value is significantly different from the residual noise value of the target model. The system will automatically adjust the value of the FF filter below 2kHz. The feedforward filter parameters include frequency point, GAIN value, etc., and perform noise reduction processing in real time according to the adjusted feedforward filter parameters. The residual noise value in the ear canal is detected in real time, and the detected residual noise value is compared with the residual noise value of the target model until the residual noise value in the ear canal obtained by FBMIC is close to the residual noise value of the target model. The automatic adjustment of feedforward filter parameters stops, and the system will automatically solidify the feedforward filter parameters at this time and automatically embed them into the program. The solidified feedforward filter parameters are used for noise reduction processing in the ear canal in sequence.

[0080] Step S104: Perform noise reduction processing in the ear canal according to the noise reduction filter parameters.

[0081] In this embodiment, when the ambient noise is less than the first preset noise threshold, the adaptive detection function inside the ear canal will be activated to automatically detect the user's passive noise reduction curve in the ear canal and automatically match the target feedforward filter parameters to improve the noise reduction effect and enable the user to experience a more suitable noise reduction effect.

[0082] See Figure 3 The method further includes:

[0083] Step S105: When the ambient noise is greater than the first preset noise threshold, determine the target environment where the user is located based on the ambient noise.

[0084] In this embodiment, the environment can be classified into corresponding types based on noise level or signal spectrum. For example, the signal spectrum of the environmental noise can be obtained, and the target environment of the user can be determined based on the signal spectrum.

[0085] As an example, when the ambient noise detected by the FF MIC on the headphone device is greater than or equal to a first preset noise threshold, the FFT detection function is activated. The signal spectrum is obtained based on the picked-up ambient noise, and the specific user's living environment is automatically identified based on the signal spectrum. Different ambient noises correspond to different noise frequency bands. For example, the signal spectrum of ambient noise in an airplane cabin environment is <200 Hz, the signal spectrum of ambient noise in a subway environment is between 400 and 1000 Hz, and the signal spectrum of ambient noise in a restaurant and coffee shop is between 200 Hz and 400 Hz.

[0086] In this embodiment, the signal spectrum corresponding to various environments can be obtained in advance. When the signal spectrum corresponding to the user's environment is detected, the target environment of the user can be determined by querying the correspondence between the signal spectrum and the environment.

[0087] Step S106: Obtain the target active noise reduction parameters that match the target environment.

[0088] In this embodiment, after the headphone device automatically identifies the user's target environment, the system will select the appropriate active noise cancellation (ANC) filter parameter from a set of preset ANC filter parameters. For example, the preset ANC filter parameters can be specifically set for deeper frequency bands within 200 Hz, 400–1000 Hz, and 200–400 Hz, respectively.

[0089] In one embodiment, step S106 includes:

[0090] Obtain the target noise frequency band corresponding to the target environment;

[0091] Determine the maximum noise reduction depth for the target noise frequency band;

[0092] The target active noise reduction parameters are determined based on the maximum noise reduction depth.

[0093] In this embodiment, the multiple preset ANC filter parameters are set as follows: based on the concentrated frequency bands of different noise distributions, the gain (GAIN) value of the ANC filter parameters within that frequency band is set to be larger. For example, for noise below 200 Hz, a peak (PEAK) point can be set in the ANC filter parameters, and the GAIN value can be set to a positive value, for example, +8 dB. It should be noted that the actual number of PEAK points and the magnitude of the GAIN value within this 200 Hz range can be obtained by testing the noise reduction objective curve using acoustic detection (Soundcheck) and a simulated artificial head testing system. Exemplarily, the maximum noise reduction depth is used as the standard within 200 Hz, where the maximum noise reduction depth is 40 dB. The noise reduction depth in other frequency bands can be slightly reduced, thereby providing the user with a better noise reduction effect. In this embodiment, the target active noise reduction parameter is the target ANC filter parameter, which is determined based on the maximum noise reduction depth.

[0094] Step S107: Perform noise reduction processing based on the target active noise reduction parameters.

[0095] As an example, the target active noise reduction parameters are target ANC filter parameters, and noise reduction processing is performed based on the target ANC filter parameters. This allows for the identification of different environmental noises above a first preset noise threshold, and the matching of corresponding ANC filter parameters, thereby improving the noise reduction effect for the corresponding environment.

[0096] To further clarify, the method also includes:

[0097] The ambient noise is detected at preset time intervals.

[0098] In this embodiment, considering that users may move from different living noise environments to other living noise environments, the ambient noise is detected at preset time intervals, realizing a real-time ambient noise detection function. Exemplarily, the FF MIC re-detects the ambient noise every few seconds and uses an A-weighted method to identify the living noise environment, thereby achieving continuous noise detection and allowing users to intelligently experience the most suitable noise reduction effect.

[0099] Existing noise reduction solutions lack adaptive detection within the ear canal and adaptive ANC filter parameter matching. Furthermore, the environment noise level is below 70 dBSPL, which is typically set to an office environment. The existing microphones can only recognize environments with noise levels above 60 dBSPL, and cannot accurately identify environments with lower noise levels. Therefore, existing intelligent noise reduction solutions cannot provide users with more precise and effective noise reduction.

[0100] In this embodiment, when the ambient noise is less than or equal to a first preset noise threshold (e.g., 70 dB SPL), the adaptive detection function inside the ear canal is automatically activated. This function automatically detects the user's passive noise reduction curve in the ear canal and automatically matches the target feedforward filter parameters to improve the noise reduction effect. This allows the user to experience a more suitable noise reduction effect and also enables real-time detection of ambient noise. For example, when a user walks from a shopping mall to a subway station, the real-time detection function can automatically identify the user's living environment and match the corresponding ANC filter parameters to provide a more accurate noise reduction solution and improve the noise reduction effect.

[0101] The headphone noise reduction method provided in this embodiment detects ambient noise; when the ambient noise is less than or equal to a first preset noise threshold, it acquires the user's ear canal parameters; it matches noise reduction filter parameters according to the ear canal parameters; and it performs noise reduction processing within the ear canal according to the noise reduction filter parameters. In environments where the ambient noise is less than the first preset noise threshold, an adaptive detection function within the ear canal is activated to automatically detect the user's ear canal parameters and automatically match the noise reduction filter parameters, improving the noise reduction effect and allowing the user to experience a more suitable noise reduction effect.

[0102] In addition, this application provides a headphone noise reduction device.

[0103] like Figure 4 As shown, the headphone noise cancellation device 400 includes:

[0104] Detection module 401 is used to detect ambient noise when it detects that a user is wearing headphones;

[0105] The acquisition module 402 is used to acquire the user's ear canal parameters when the ambient noise is less than or equal to a first preset noise threshold.

[0106] Matching module 403 is used to match noise reduction filter parameters according to the ear canal parameters;

[0107] The noise reduction module 404 is used to perform noise reduction processing in the ear canal according to the noise reduction filter parameters.

[0108] In one embodiment, the ear canal parameters include: a passive noise reduction curve in the ear canal, and the noise reduction filter parameters include: target feedforward filter parameters;

[0109] The matching module 403 is also used to generate target feedforward filter parameters based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value.

[0110] In one embodiment, the matching module 403 is further configured to adjust the feedforward filter parameters according to the passive noise reduction curve of the ear canal and the deepest noise reduction effect value, so as to perform noise reduction processing.

[0111] Detect the current residual noise level in the user's ear canal;

[0112] Determine whether the difference between the current residual noise value and the residual noise value of the target model is less than or equal to a second preset noise threshold;

[0113] If the difference is less than or equal to the second preset noise threshold, then the current feedforward filter parameters are determined as the target feedforward filter parameters.

[0114] If the difference is greater than the second preset noise threshold, the feedforward filter parameters of the headphones are adjusted until the difference between the residual noise value in the user's ear canal and the residual noise value of the target model is less than the second preset noise threshold, and the current feedforward filter parameters are determined as the target feedforward filter parameters.

[0115] In one embodiment, the headphone noise cancellation device 400 further includes:

[0116] The first processing module is used to obtain the objective noise reduction curve;

[0117] The residual noise value of the target model is determined based on the maximum noise reduction depth of the aforementioned objective noise reduction curve. 。

[0118] In one embodiment, the feedforward filter parameters include frequency point and gain value; the matching module 403 is further configured to adjust the frequency point and gain value according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value.

[0119] In one embodiment, the headphone noise cancellation device 400 further includes:

[0120] The second processing module is used to determine the target environment where the user is located based on the environmental noise when the environmental noise is greater than the first preset noise threshold.

[0121] Obtain the target active noise reduction parameters that match the target environment;

[0122] Noise reduction processing is performed based on the target active noise reduction parameters.

[0123] In one embodiment, the second processing module is further configured to acquire the target noise frequency band corresponding to the target environment;

[0124] Determine the maximum noise reduction depth for the target noise frequency band;

[0125] The target active noise reduction parameters are determined based on the maximum noise reduction depth.

[0126] The headphone noise reduction device 400 provided in this embodiment can implement the headphone noise reduction method provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0127] The headphone noise cancellation device provided in this embodiment detects ambient noise; when the ambient noise is less than or equal to a first preset noise threshold, it acquires the user's ear canal parameters; it matches noise cancellation filter parameters according to the ear canal parameters; and it performs noise cancellation processing within the ear canal according to the noise cancellation filter parameters. In environments where the ambient noise is less than the first preset noise threshold, an adaptive detection function within the ear canal is activated, automatically detecting the user's ear canal parameters and automatically matching the noise cancellation filter parameters to improve the noise cancellation effect, allowing the user to experience a more suitable noise cancellation effect.

[0128] In addition, this application provides a wearable device, including a memory and a processor, wherein the memory stores a computer program, and the computer program executes the headphone noise reduction method provided in Embodiment 1 when it is run on the processor.

[0129] In this embodiment, the wearable device can be an earphone device, which can be a wired earphone or a wireless earphone, and there is no limitation on this.

[0130] The headphone device provided in this embodiment can implement the headphone noise reduction method provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0131] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the headphone noise reduction method provided in Embodiment 1.

[0132] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0133] The computer-readable storage medium provided in this embodiment can implement the headphone noise reduction method provided in Embodiment 1. To avoid repetition, it will not be described again here.

[0134] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal that includes that element.

[0135] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0136] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for noise reduction in headphones, characterized in that, The method includes: Detecting environmental noise; When the ambient noise is less than or equal to a first preset noise threshold, the user's ear canal parameters are obtained. Match the noise reduction filter parameters according to the ear canal parameters; Noise reduction processing is performed in the ear canal according to the noise reduction filter parameters; The ear canal parameters include: the passive noise reduction curve of the ear canal; the noise reduction filter parameters include: the target feedforward filter parameters. The step of matching noise reduction filter parameters according to the ear canal parameters includes: Target feedforward filter parameters are generated based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value. The step of generating target feedforward filter parameters based on the passive noise reduction curve in the ear canal and the deepest noise reduction effect value includes: Adjust the feedforward filter parameters according to the passive noise reduction curve of the ear canal and the deepest noise reduction effect value to perform noise reduction processing; Detect the current residual noise level in the user's ear canal; Determine whether the difference between the current residual noise value and the residual noise value of the target model is less than or equal to a second preset noise threshold; If the difference is greater than the second preset noise threshold, the feedforward filter parameters of the headphones are adjusted until the difference between the residual noise value in the user's ear canal and the residual noise value of the target model is less than the second preset noise threshold, and the current feedforward filter parameters are determined as the target feedforward filter parameters.

2. The method according to claim 1, characterized in that, The step of generating target feedforward filter parameters based on the passive noise reduction curve in the ear canal and the deepest noise reduction effect value also includes: If the difference is less than or equal to the second preset noise threshold, then the current feedforward filter parameters are determined as the target feedforward filter parameters.

3. The method according to claim 2, characterized in that, The acquisition of the residual noise value of the target model includes: Obtain the objective noise reduction curve; The residual noise value of the target model is determined based on the maximum noise reduction depth of the objective noise reduction curve.

4. The method according to claim 2, characterized in that, The feedforward filter parameters include frequency points and gain values; adjusting the feedforward filter parameters according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value includes: The frequency point and the gain value are adjusted according to the passive noise reduction curve in the ear canal and the deepest noise reduction effect value.

5. The method according to claim 1, characterized in that, The method further includes: When the ambient noise is greater than the first preset noise threshold, the target environment in which the user is located is determined based on the ambient noise. Obtain the target active noise reduction parameters that match the target environment; Noise reduction processing is performed based on the target active noise reduction parameters.

6. The method according to claim 5, characterized in that, The step of obtaining the target active noise reduction parameters that match the target environment includes: Obtain the target noise frequency band corresponding to the target environment; Determine the maximum noise reduction depth for the target noise frequency band; The target active noise reduction parameters are determined based on the maximum noise reduction depth.

7. A headphone noise reduction device, characterized in that, The device includes: The detection module is used to detect environmental noise; The acquisition module is used to acquire the user's ear canal parameters when the ambient noise is less than or equal to a first preset noise threshold; The matching module is used to match the noise reduction filter parameters according to the ear canal parameters; The noise reduction module is used to perform noise reduction processing in the ear canal according to the noise reduction filter parameters; The ear canal parameters include: the passive noise reduction curve of the ear canal; the noise reduction filter parameters include: the target feedforward filter parameters. The matching module is also used to generate target feedforward filter parameters based on the passive noise reduction curve of the ear canal and the deepest noise reduction effect value; Adjust the feedforward filter parameters according to the passive noise reduction curve of the ear canal and the deepest noise reduction effect value to perform noise reduction processing; Detect the current residual noise level in the user's ear canal; Determine whether the difference between the current residual noise value and the residual noise value of the target model is less than or equal to a second preset noise threshold; If the difference is greater than the second preset noise threshold, the feedforward filter parameters of the headphones are adjusted until the difference between the residual noise value in the user's ear canal and the residual noise value of the target model is less than the second preset noise threshold, and the current feedforward filter parameters are determined as the target feedforward filter parameters.

8. A wearable device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program that executes the headphone noise reduction method according to any one of claims 1 to 6 when the processor is running.

9. A computer-readable storage medium, characterized in that, It stores a computer program that, when run on a processor, executes the headphone noise reduction method according to any one of claims 1 to 6.

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