Wind noise detection method, apparatus, and earphone
By using dual microphones in the headphones for multi-level wind noise detection, combining the detection of feedforward microphones and call microphones, the problems of high resource consumption and insufficient accuracy in headphone wind noise detection are solved, achieving efficient wind noise detection and improved battery life.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- XIAOMI TECH (WUHAN) CO LTD
- Filing Date
- 2023-02-23
- Publication Date
- 2026-07-14
AI Technical Summary
In existing technologies, headphones suffer from high computational resource consumption and insufficient detection accuracy when detecting wind noise. In particular, single-microphone detection schemes have frequent misjudgments, while dual-microphone detection schemes have high power consumption and serious unnecessary resource waste.
A dual-microphone headset is used. The feedforward microphone is used for primary wind noise detection, and the call microphone is used for secondary wind noise detection if a suspected wind noise signal is detected. By combining single-microphone and dual-microphone detection schemes, the computing resources consumed by continuous detection are reduced and the detection accuracy is improved.
It effectively reduces the computational resource consumption of wind noise detection, increases the battery life of headphones, and improves the accuracy of wind noise detection through a multi-level detection method, reducing the possibility of false detection.
Smart Images
Figure CN116320867B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the fields of audio signal processing technology and headphone technology, and in particular to a wind noise detection method, device and headphone. Background Technology
[0002] For students, professionals, and artists, headphones have become an indispensable part of their work and life. Features such as adaptive sound compensation, active noise cancellation, and spatial audio are highly sought after. Active noise cancellation, in particular, is becoming an increasingly important factor for many when choosing headphones. However, wind noise is unavoidable during headphone use and can significantly impact the user experience, such as reducing call quality and music playback quality. Therefore, detecting wind noise in the headphone's environment has become a key research area in this field. Summary of the Invention
[0003] To overcome the problems existing in related technologies, this disclosure provides a wind noise detection method, device, and headphones.
[0004] According to a first aspect of the present disclosure, a wind noise detection method is provided, applied to an earphone, the earphone including a first signal collector and a second signal collector, the method comprising:
[0005] Acquire the first audio signal collected by the first signal collector;
[0006] Based on the first audio signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located;
[0007] If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, the second audio signal collected by the second signal collector is acquired.
[0008] Based on the first audio signal and the second audio signal, determine whether there is wind noise in the environment where the headphones are located.
[0009] In some embodiments of this disclosure, determining whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal includes: performing a filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determining whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal and the sub-band signal.
[0010] In some embodiments of this disclosure, determining whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal and the sub-band signal includes: determining a first energy of the first audio signal; determining a second energy of the sub-band signal; determining that there is a suspected wind noise signal in the environment where the headphones are located when the first energy satisfies a first condition and the second energy satisfies a second condition; or determining that there is no suspected wind noise signal in the environment where the headphones are located when the first energy does not satisfy the first condition and / or the second energy does not satisfy the second condition.
[0011] In some embodiments of this disclosure, determining whether there is wind noise in the environment where the headphones are located based on the first audio signal and the second audio signal includes: determining the Pearson correlation coefficient between the first audio signal and the second audio signal; determining that there is no wind noise in the environment where the headphones are located if the Pearson correlation coefficient is greater than or equal to a first threshold; or determining that there is wind noise in the environment where the headphones are located if the Pearson correlation coefficient is less than or equal to the first threshold.
[0012] In some embodiments of this disclosure, the method further includes: if it is determined that there is no suspected wind noise signal in the environment where the headphones are located, returning to the step of acquiring the first audio signal collected by the first signal collector.
[0013] In some embodiments of this disclosure, the method further includes: when it is determined that there is wind noise in the environment where the headphones are located, determining the intensity of the wind noise signal in the environment where the headphones are located based on the first audio signal and the second audio signal; determining a corresponding noise reduction coefficient based on the intensity of the wind noise signal, wherein the noise reduction coefficient is used to assist the headphones in performing corresponding noise reduction processing.
[0014] In some embodiments of this disclosure, determining the intensity of wind noise signal present in the environment where the headphones are located based on the first audio signal and the second audio signal includes: performing a short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal acquisition device; performing a short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal acquisition device; determining the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal based on the first time-frequency representation and the second time-frequency representation; and determining the intensity of wind noise signal present in the environment where the headphones are located based on the correlation coefficient.
[0015] In some embodiments of this disclosure, the first signal collector is a feedforward microphone; the second signal collector is a call microphone.
[0016] According to a second aspect of the present disclosure, a wind noise detection device is provided, disposed in an earphone, the earphone including a first signal collector and a second signal collector, the device comprising:
[0017] The first acquisition module is used to acquire the first audio signal acquired by the first signal acquisition device;
[0018] The first determining module is used to determine, based on the first audio signal, whether there is a suspected wind noise signal in the environment where the headphones are located;
[0019] The second acquisition module is used to acquire the second audio signal collected by the second signal collector when it is determined that there is a suspected wind noise signal in the environment where the headphones are located.
[0020] The second determining module is used to determine whether there is wind noise in the environment where the headphones are located, based on the first audio signal and the second audio signal.
[0021] In some embodiments of this disclosure, the first determining module is specifically used to: perform a filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determine whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal and the sub-band signal.
[0022] In some embodiments of this disclosure, the first determining module is specifically used to: determine a first energy of the first audio signal; determine a second energy of the sub-band signal; determine that there is a suspected wind noise signal in the environment where the headphones are located when the first energy satisfies a first condition and the second energy satisfies a second condition; or, determine that there is no suspected wind noise signal in the environment where the headphones are located when the first energy does not satisfy the first condition and / or the second energy does not satisfy the second condition.
[0023] In some embodiments of this disclosure, the second determining module is specifically used to: determine the Pearson correlation coefficient between the first audio signal and the second audio signal; if the Pearson correlation coefficient is greater than or equal to a first threshold, determine that there is no wind noise in the environment where the headphones are located; or, if the Pearson correlation coefficient is less than or equal to the first threshold, determine that there is wind noise in the environment where the headphones are located.
[0024] In some embodiments of this disclosure, the first acquisition module is further configured to: acquire the first audio signal collected by the first signal collector when it is determined that there is no suspected wind noise signal in the environment where the headphones are located.
[0025] In some embodiments of this disclosure, the device further includes a third determining module; wherein the third determining module is configured to: determine the intensity of the wind noise signal present in the environment where the headphones are located, based on the first audio signal and the second audio signal, when it is determined that wind noise exists in the environment where the headphones are located; and determine a corresponding noise reduction coefficient based on the intensity of the wind noise signal, wherein the noise reduction coefficient is used to assist the headphones in performing corresponding noise reduction processing.
[0026] In some embodiments of this disclosure, the third determining module is specifically used to: perform a short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal acquisition device; perform a short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal acquisition device; determine the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal based on the first time-frequency representation and the second time-frequency representation; and determine the intensity of the wind noise signal present in the environment where the headphones are located based on the correlation coefficient.
[0027] In some embodiments of this disclosure, the first signal collector is a feedforward microphone; the second signal collector is a call microphone.
[0028] According to a third aspect of the present disclosure, an earphone is provided, comprising:
[0029] First signal acquisition unit and second signal acquisition unit;
[0030] processor;
[0031] A memory for storing processor-executable instructions; wherein the instructions are executed by the processor to enable the processor to perform the method described in the first aspect above.
[0032] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in the first aspect above.
[0033] The technical solution provided by the embodiments of this disclosure can include the following beneficial effects: A first audio signal is acquired by a first signal acquisition device to determine whether a suspected wind noise signal exists, i.e., a first-level wind noise judgment is performed. If a suspected wind noise signal is determined to exist, a second audio signal is acquired by a second signal acquisition device. Based on the first and second audio signals, it is determined whether wind noise exists in the environment where the headphones are located, i.e., a second-level wind noise judgment is performed. This disclosure combines a single-microphone detection scheme and a dual-microphone detection scheme, eliminating the need for continuous dual-microphone detection, significantly reducing computational resource consumption, and increasing the headphone's battery life. Furthermore, this disclosure employs a multi-level detection method, which can effectively ensure the accuracy of wind noise detection and reduce the possibility of false wind noise detection to a certain extent.
[0034] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description
[0035] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.
[0036] Figure 1 This is a flowchart illustrating a wind noise detection method according to an exemplary embodiment.
[0037] Figure 2 This is a flowchart illustrating another wind noise detection method according to an exemplary embodiment.
[0038] Figure 3 This is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment.
[0039] Figure 4 This is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment.
[0040] Figure 5 This is a schematic diagram of the structure of a wind noise detection device according to an exemplary embodiment.
[0041] Figure 6 This is a schematic diagram of the structure of another wind noise detection device according to an exemplary embodiment.
[0042] Figure 7 This is a block diagram illustrating an earphone according to an exemplary embodiment. Detailed Implementation
[0043] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.
[0044] In active noise cancellation technology, wind noise detection algorithms are a crucial component. Related technologies include single-microphone detection schemes and dual-microphone detection schemes for determining the presence of wind noise. Single-microphone detection has poor performance and is prone to false positives. Dual-microphone detection schemes use the correlation between two microphone signals to detect wind noise in the environment where the headphones are located. However, dual-microphone detection requires two data streams, resulting in significant power consumption. Furthermore, wind noise scenarios are relatively rare compared to non-wind noise scenarios, and continuous dual-microphone detection leads to unnecessary loss of computing resources, posing a significant challenge to the battery life of some wireless headphones.
[0045] This disclosure provides a wind noise detection method, device, and earphone to reduce the consumption of computing resources when detecting wind noise, while ensuring the accuracy of wind noise detection.
[0046] Figure 1 This is a flowchart illustrating a wind noise detection method according to an exemplary embodiment. It should be noted that this wind noise detection method is applied to headphones. The headphones include a first signal acquisition unit and a second signal acquisition unit. For example... Figure 1 As shown, the wind noise detection method may include the following steps.
[0047] Step 101: Obtain the first audio signal collected by the first signal collector.
[0048] It should be noted that the earphones described in this disclosure are earphones equipped with dual microphones. Optionally, in some embodiments of this disclosure, the first signal acquisition device may be a feedforward microphone to acquire ambient noise audio. As an example, the earphones may be TWS true wireless earphones, wired earphones, etc.
[0049] Step 102: Based on the first audio signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
[0050] It should be noted that the first signal acquisition device can collect noise from the external environment, i.e., the first audio signal. In other words, based on the first audio signal collected by the first signal acquisition device, a first-level wind noise judgment is performed on the wind noise signal in the environment. As one possible implementation, the presence of suspected wind noise signals in the environment where the headphones are located can be determined based on whether the first audio signal meets preset conditions.
[0051] Step 103: If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, acquire the second audio signal collected by the second signal acquisition device.
[0052] In some embodiments of this disclosure, the second signal collector can be a call microphone to collect call audio. If a suspected wind noise signal is detected, a second audio signal is collected based on the second signal collector to perform a secondary wind noise judgment. This eliminates the need for continuous dual-microphone detection, significantly reducing computational resource consumption.
[0053] Step 104: Determine whether there is wind noise in the environment where the headphones are located based on the first audio signal and the second audio signal.
[0054] As one possible approach, the correlation between the first and second audio signals can be used to determine whether wind noise exists in the environment where the headphones are located.
[0055] Optionally, in some embodiments of this disclosure, if it is determined that there is no suspected wind noise signal in the environment where the headphones are located, the process can return to the step of acquiring the first audio signal collected by the first signal collector, continue to collect audio signals, and detect wind noise in the environment where the headphones are located.
[0056] According to the wind noise detection method of this disclosure, a first audio signal is acquired by a first signal acquisition device to determine whether a suspected wind noise signal exists, i.e., a first-level wind noise judgment is performed. If a suspected wind noise signal is determined to exist, a second audio signal is acquired by a second signal acquisition device. Based on the first and second audio signals, it is determined whether wind noise exists in the environment where the headphones are located, i.e., a second-level wind noise judgment is performed. This disclosure combines a single-microphone detection scheme and a dual-microphone detection scheme, eliminating the need for continuous dual-microphone detection, significantly reducing computational resource consumption and increasing the headphone's battery life. Furthermore, this disclosure employs a multi-level detection method, which effectively ensures the accuracy of wind noise detection and reduces the possibility of false wind noise detection to a certain extent.
[0057] Figure 2 This is a flowchart illustrating another wind noise detection method according to an exemplary embodiment. Figure 1 As shown, the wind noise detection method may include the following steps.
[0058] Step 201: Obtain the first audio signal collected by the first signal collector.
[0059] Step 202: Filter the first audio signal to obtain the filtered sub-band signal.
[0060] As an example, the first audio signal can be filtered using formula (1) to obtain the sub-band signal after filtering.
[0061]
[0062] In the formula, x(t) is the first audio signal, and y(t) is the sub-band signal after filtering. For bandpass filtering, l is the lower cutoff frequency of the passband, and h is the upper cutoff frequency of the passband. Optionally, in some embodiments of this disclosure, l = 100Hz and h = 500Hz can be set.
[0063] Step 203: Based on the first audio signal and the sub-band signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
[0064] In some embodiments of this disclosure, the presence of suspected wind noise in the environment where the headphones are located can be determined based on whether the energy of the first audio signal and the energy of the sub-band signal meet preset conditions. As one possible implementation, the first energy E1 of the first audio signal can be determined with reference to formula (2), and the second energy E2 of the sub-band signal can be determined with reference to formula (3).
[0065]
[0066]
[0067] Where N is the number of sampling points, x(i) is the first audio signal of the i-th sampling point, and y(i) is the sub-band signal of the i-th sampling point.
[0068] If the first energy E1 satisfies the first condition and the second energy E2 satisfies the second condition, it is determined that a suspected wind noise signal exists in the environment where the headphones are located. If the first energy E1 does not satisfy the first condition, or the second energy E2 does not satisfy the second condition, or both the first energy E1 and the second energy E2 do not satisfy the second condition, it is determined that no suspected wind noise signal exists in the environment where the headphones are located. The first condition is that the first energy E1 is greater than or equal to a first threshold T1, and the second condition is that the second energy E2 is greater than or equal to a second threshold E2. T1 and T2 are judgment thresholds set according to the actual situation.
[0069] Step 204: If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, acquire the second audio signal collected by the second signal acquisition device.
[0070] Step 205: Determine whether there is wind noise in the environment where the headphones are located based on the first audio signal and the second audio signal.
[0071] It should be noted that, in the embodiments of this disclosure, steps 204-205 can be implemented in any of the embodiments of this disclosure, and this disclosure does not limit them.
[0072] According to the wind noise detection method of this disclosure, a first audio signal is acquired by a first signal acquisition device, and the first audio signal is filtered. The presence of a suspected wind noise signal is determined based on the first audio signal and the filtered sub-band signal, i.e., a first-level wind noise judgment is performed, improving the detection accuracy of suspected wind noise signals. If a suspected wind noise signal is determined to exist, a second audio signal is acquired by a second signal acquisition device. The presence of wind noise in the environment where the headphones are located is determined based on the first and second audio signals, i.e., a second-level wind noise judgment is performed. This disclosure combines a single-microphone detection scheme and a dual-microphone detection scheme, eliminating the need for continuous dual-microphone detection, significantly reducing computational resource consumption, and increasing the headphone's battery life. Furthermore, this disclosure employs a multi-level detection method, which can improve the accuracy of wind noise detection and reduce the possibility of false wind noise detection to a certain extent.
[0073] Figure 3 This is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment. For example... Figure 3 As shown, the wind noise detection method may include the following steps.
[0074] Step 301: Obtain the first audio signal collected by the first signal collector.
[0075] Step 302: Based on the first audio signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
[0076] Step 303: If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, the second audio signal collected by the second signal acquisition device is obtained.
[0077] Step 304: Determine the Pearson correlation coefficient between the first audio signal and the second audio signal.
[0078] As an example, the Pearson correlation coefficient C between the first audio signal and the second audio signal can be determined by referring to formula (4).
[0079]
[0080] Where x(i) is the first audio signal at the i-th sampling point. Let x(t) be the average value of the first audio signal, and z(i) be the second audio signal at the i-th sampling point. Let z(t) be the average value of the second audio signal, and N be the number of sampling points.
[0081] Step 305: If the Pearson correlation coefficient is greater than the first threshold C0, it is determined that there is no wind noise in the environment where the headphones are located. The first threshold C0 is preset.
[0082] Step 306: If the Pearson correlation coefficient is less than or equal to the first threshold C0, it is determined that there is wind noise in the environment where the headphones are located.
[0083] Optionally, in other embodiments of this disclosure, it can be determined that there is no wind noise in the environment where the headphones are located if the Pearson correlation coefficient is greater than or equal to a first threshold, and that there is wind noise in the environment where the headphones are located if the Pearson correlation coefficient is less than the first threshold.
[0084] It should be noted that, in the embodiments of this disclosure, steps 301-303 can be implemented in any of the embodiments of this disclosure, and this disclosure does not limit them.
[0085] According to the wind noise detection method of this disclosure, a first audio signal is acquired by a first signal acquisition device to determine whether there is a suspected wind noise signal, i.e., a first-level wind noise judgment is performed. If a suspected wind noise signal is determined to exist, a second audio signal is acquired by a second signal acquisition device. Based on the Pearson correlation coefficient between the first and second audio signals, it is determined whether there is wind noise in the environment where the headphones are located, i.e., a second-level wind noise judgment is performed, thus improving the accuracy of wind noise detection. This disclosure combines a single-microphone detection scheme and a dual-microphone detection scheme, eliminating the need for continuous dual-microphone detection, significantly reducing computational resource consumption and increasing the headphone's battery life. Furthermore, this disclosure employs a multi-level detection method to further reduce the possibility of false wind noise detection.
[0086] It should be noted that, in order to optimize the user experience of the headphones, in some embodiments of this disclosure, when it is determined that there is wind noise in the environment where the headphones are located, targeted adaptation can be performed based on the detected wind noise signal to assist the headphones in performing corresponding noise reduction processing, so as to avoid causing abrupt changes in the listening experience. Figure 4 This is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment. For example... Figure 4 As shown, the wind noise detection method may include the following steps.
[0087] Step 401: Obtain the first audio signal collected by the first signal collector.
[0088] Step 402: Based on the first audio signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
[0089] Step 403: If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, the second audio signal collected by the second signal collector is acquired.
[0090] Step 404: Determine whether there is wind noise in the environment where the headphones are located based on the first audio signal and the second audio signal.
[0091] Step 405: If it is determined that there is wind noise in the environment where the headphones are located, determine the intensity of the wind noise signal in the environment where the headphones are located based on the first audio signal and the second audio signal.
[0092] Optionally, in some embodiments of this disclosure, a short-time Fourier transform can be performed on the first audio signal to obtain a first time-frequency representation X1(λ,μ) of the first signal acquisition device. A short-time Fourier transform can be performed on the second audio signal to obtain a second time-frequency representation X2(λ,μ) of the second signal acquisition device. Here, λ represents the frame index, and μ represents the frequency point. Then, based on the first time-frequency representation X1(λ,μ) and the second time-frequency representation X2(λ,μ), the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal is determined. As an example, the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal can be determined with reference to formula (5).
[0093]
[0094] Where X2′(λ,μ) is the conjugate representation of the second time-frequency representation X2(λ,μ).
[0095] Based on the correlation coefficient This allows for the determination of the intensity of wind noise signals present in the environment where the headphones are located. In one implementation, the correlation coefficient can be used to determine the intensity of wind noise signals present in the environment where the headphones are located. In another implementation, the correlation characteristics between the first audio signal and the second audio signal can be calculated based on the correlation coefficient, and these correlation characteristics can be used to determine the intensity of wind noise signals present in the environment where the headphones are located. As an example, the correlation characteristics Γ(λ,μ) between the first audio signal and the second audio signal can be determined by referring to formula (6).
[0096]
[0097] Step 406: Determine the corresponding noise reduction coefficient based on the intensity of the wind noise signal. The noise reduction coefficient is used to assist the headphones in performing the corresponding noise reduction processing.
[0098] It should be noted that, in the embodiments of this disclosure, steps 401-404 can be implemented in any of the embodiments of this disclosure, and this disclosure does not limit them.
[0099] According to the wind noise detection method of this disclosure, a first audio signal is acquired by a first signal acquisition device to determine whether a suspected wind noise signal exists, i.e., a first-level wind noise judgment is performed. If a suspected wind noise signal is determined to exist, a second audio signal is acquired by a second signal acquisition device. Based on the first and second audio signals, it is determined whether wind noise exists in the environment where the headphones are located, i.e., a second-level wind noise judgment is performed. If wind noise is determined to exist in the environment where the headphones are located, the corresponding noise reduction coefficient is determined based on the intensity of the wind noise signal. In actual use, the noise reduction coefficient can be adaptively adjusted according to the wind noise intensity, thereby achieving a smooth change in the listening experience in wind noise scenarios and reducing subjective abruptness.
[0100] To achieve the above embodiments, this disclosure provides a wind noise detection device. Figure 5 This is a schematic diagram illustrating the structure of a wind noise detection device according to an exemplary embodiment. It should be noted that this wind noise detection device is applied to headphones, which include a first signal acquisition unit and a second signal acquisition unit. Figure 5 As shown, the wind noise detection device includes: a first acquisition module 501, a first determination module 502, a second acquisition module 503, and a second determination module 504. Among them,
[0101] The first acquisition module 501 is used to acquire the first audio signal collected by the first signal collector.
[0102] The first determining module 502 is used to determine, based on the first audio signal, whether there is a suspected wind noise signal in the environment where the headphones are located.
[0103] The second acquisition module 503 is used to acquire the second audio signal collected by the second signal collector when it is determined that there is a suspected wind noise signal in the environment where the headphones are located.
[0104] The second determining module 504 is used to determine whether there is wind noise in the environment where the headphones are located, based on the first audio signal and the second audio signal.
[0105] In some embodiments of this disclosure, the first determining module 501 is specifically used to: perform a filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determine whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal and the sub-band signal.
[0106] In some embodiments of this disclosure, the first determining module 501 is specifically used to: determine the first energy of the first audio signal; determine the second energy of the sub-band signal; determine that there is a suspected wind noise signal in the environment where the headphones are located when the first energy satisfies the first condition and the second energy satisfies the second condition; or, determine that there is no suspected wind noise signal in the environment where the headphones are located when the first energy does not satisfy the first condition and / or the second energy does not satisfy the second condition.
[0107] In some embodiments of this disclosure, the second determining module 504 is specifically used to: determine the Pearson correlation coefficient between the first audio signal and the second audio signal; if the Pearson correlation coefficient is greater than or equal to a first threshold, determine that there is no wind noise in the environment where the headphones are located; or, if the Pearson correlation coefficient is less than or equal to the first threshold, determine that there is wind noise in the environment where the headphones are located.
[0108] In some embodiments of this disclosure, the first signal collector is a feedforward microphone; the second signal collector is a call microphone.
[0109] In some embodiments of this disclosure, the first acquisition module 501 is further configured to: acquire the first audio signal collected by the first signal collector when it is determined that there is no suspected wind noise signal in the environment where the headphones are located.
[0110] Optionally, in some embodiments of this disclosure, such as Figure 6 As shown, the wind noise detection device further includes a third determining module. The third determining module 605 is used to: determine the intensity of the wind noise signal in the environment where the headphones are located, based on the first audio signal and the second audio signal, when it is determined that wind noise exists in the environment where the headphones are located; and determine a corresponding noise reduction coefficient based on the intensity of the wind noise signal, wherein the noise reduction coefficient is used to assist the headphones in performing corresponding noise reduction processing.
[0111] In some embodiments of this disclosure, the third determining module 605 is specifically configured to: perform a short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal acquisition device; perform a short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal acquisition device; determine the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal based on the first time-frequency representation and the second time-frequency representation; and determine the intensity of the wind noise signal present in the environment where the headphones are located based on the correlation coefficient. Figure 6 601-604 and Figure 5 The 501-504 series have the same function and structure.
[0112] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.
[0113] Figure 7 This is a block diagram illustrating an earphone according to an exemplary embodiment.
[0114] Reference Figure 7 The headset 700 may include one or more of the following components: a first signal acquisition unit 701, a second signal acquisition unit 702, a processing unit 703, a memory 704, a power component 706, an audio component 710, an input / output (I / O) interface 712, and a communication component 716.
[0115] The first signal acquisition unit 701 is used to acquire a first audio signal. In an exemplary embodiment, the first signal acquisition unit 818 may be a feedforward microphone.
[0116] The second signal collector 802 is used to collect a second audio signal. In an exemplary embodiment, the second signal collector 820 may be a microphone for communication.
[0117] Processing component 703 typically controls the overall operation of headset 700, such as operations associated with telephone calls, data communication, camera operation, and recording. Processing component 703 may include one or more processors 720 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 703 may include one or more modules to facilitate interaction between processing component 703 and other components. For example, processing component 703 may include a multimedia module to facilitate interaction between multimedia component 808 and processing component 703.
[0118] Memory 704 is configured to store various types of data to support operation of the headset 700. Examples of this data include instructions for any application or method operating on the headset 700, contact data, phonebook data, messages, pictures, videos, etc. Memory 704 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.
[0119] The power supply component 706 provides power to the various components of the headset 700. The power supply component 706 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the headset 700.
[0120] Audio component 710 is configured to output and / or input audio signals. For example, audio component 710 includes a microphone (MIC) configured to receive external audio signals when headset 700 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 704 or transmitted via communication component 716. In some embodiments, audio component 710 also includes a speaker for outputting audio signals.
[0121] I / O interface 712 provides an interface between processing component 703 and peripheral interface modules, such as buttons. These buttons may include, but are not limited to, home buttons, volume buttons, start buttons, and lock buttons.
[0122] Communication component 716 is configured to facilitate wired or wireless communication between headset 700 and other devices. Headset 700 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 716 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 716 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
[0123] In an exemplary embodiment, the earphone 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.
[0124] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 704 including instructions, which can be executed by the processor 720 of the headset 700 to perform the above-described method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.
[0125] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.
[0126] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.
Claims
1. A method for detecting wind noise, characterized in that, Applied to headphones, the headphones including a first signal collector and a second signal collector, the method includes: The first audio signal is acquired based on the first signal acquisition device; Based on the first audio signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located; If it is determined that there is a suspected wind noise signal in the environment where the headphones are located, a second audio signal is collected based on the second signal collector; Based on the first audio signal and the second audio signal, determine whether there is wind noise in the environment where the headphones are located.
2. The method as described in claim 1, characterized in that, The step of determining whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal includes: The first audio signal is filtered to obtain the filtered sub-band signal; Based on the first audio signal and the sub-band signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
3. The method as described in claim 2, characterized in that, The step of determining whether there is a suspected wind noise signal in the environment where the headphones are located based on the first audio signal and the sub-band signal includes: Determine the first energy of the first audio signal; Determine the second energy of the sub-band signal; If the first energy satisfies the first condition and the second energy satisfies the second condition, it is determined that there is a suspected wind noise signal in the environment where the headphones are located; or, If the first energy does not meet the first condition, and / or the second energy does not meet the second condition, it is determined that there is no suspected wind noise signal in the environment where the headphones are located.
4. The method as described in claim 1, characterized in that, The step of determining whether there is wind noise in the environment where the headphones are located based on the first audio signal and the second audio signal includes: Determine the Pearson correlation coefficient between the first audio signal and the second audio signal; If the Pearson correlation coefficient is greater than or equal to the first threshold, it is determined that there is no wind noise in the environment where the headphones are located; or, If the Pearson correlation coefficient is less than or equal to the first threshold, it is determined that there is wind noise in the environment where the headphones are located.
5. The method as described in claim 1, characterized in that, The method further includes: If it is determined that there is no suspected wind noise signal in the environment where the headphones are located, return to the step of collecting the first audio signal based on the first signal collector.
6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: If it is determined that there is wind noise in the environment where the headphones are located, the intensity of the wind noise signal in the environment where the headphones are located is determined based on the first audio signal and the second audio signal; Based on the intensity of the wind noise signal, a corresponding noise reduction coefficient is determined, wherein the noise reduction coefficient is used to assist the headphones in performing corresponding noise reduction processing.
7. The method as described in claim 6, characterized in that, The step of determining the intensity of wind noise signals present in the environment where the headphones are located based on the first audio signal and the second audio signal includes: Perform a short-time Fourier transform on the first audio signal to obtain the first time-frequency representation of the first signal acquisition device; Perform a short-time Fourier transform on the second audio signal to obtain the second time-frequency representation of the second signal acquisition device; Based on the first time-frequency representation and the second time-frequency representation, determine the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal; Based on the correlation coefficient, the intensity of the wind noise signal present in the environment where the headphones are located is determined.
8. The method as described in claim 1, characterized in that, The first signal acquisition device is a feedforward microphone; the second signal acquisition device is a call microphone.
9. A wind noise detection device, characterized in that, Configured in an earphone, the earphone includes a first signal collector and a second signal collector, the device comprising: The first acquisition module is used to acquire a first audio signal based on the first signal acquisition device; The first determining module is used to determine, based on the first audio signal, whether there is a suspected wind noise signal in the environment where the headphones are located; The second acquisition module is used to acquire a second audio signal based on the second signal acquisition device when it is determined that there is a suspected wind noise signal in the environment where the headphones are located. The second determining module is used to determine whether there is wind noise in the environment where the headphones are located, based on the first audio signal and the second audio signal.
10. The apparatus as claimed in claim 9, characterized in that, The first determining module is specifically used for: The first audio signal is filtered to obtain the filtered sub-band signal; Based on the first audio signal and the sub-band signal, determine whether there is a suspected wind noise signal in the environment where the headphones are located.
11. The apparatus as claimed in claim 10, characterized in that, The first determining module is specifically used for: Determine the first energy of the first audio signal; Determine the second energy of the sub-band signal; If the first energy satisfies the first condition and the second energy satisfies the second condition, it is determined that there is a suspected wind noise signal in the environment where the headphones are located; or, If the first energy does not meet the first condition, and / or the second energy does not meet the second condition, it is determined that there is no suspected wind noise signal in the environment where the headphones are located.
12. The apparatus as claimed in claim 9, characterized in that, The second determining module is specifically used for: Determine the Pearson correlation coefficient between the first audio signal and the second audio signal; If the Pearson correlation coefficient is greater than or equal to the first threshold, it is determined that there is no wind noise in the environment where the headphones are located; or, If the Pearson correlation coefficient is less than or equal to the first threshold, it is determined that there is wind noise in the environment where the headphones are located.
13. The apparatus as claimed in claim 9, characterized in that, The first acquisition module is also used for: If it is determined that there is no suspected wind noise signal in the environment where the headphones are located, the first audio signal is collected based on the first signal collector.
14. The apparatus according to any one of claims 9 to 13, characterized in that, The device further includes a third determining module; wherein the third determining module is used for: If it is determined that there is wind noise in the environment where the headphones are located, the intensity of the wind noise signal in the environment where the headphones are located is determined based on the first audio signal and the second audio signal; Based on the intensity of the wind noise signal, a corresponding noise reduction coefficient is determined, wherein the noise reduction coefficient is used to assist the headphones in performing corresponding noise reduction processing.
15. The apparatus as claimed in claim 14, characterized in that, The third determining module is specifically used for: Perform a short-time Fourier transform on the first audio signal to obtain the first time-frequency representation of the first signal acquisition device; Perform a short-time Fourier transform on the second audio signal to obtain the second time-frequency representation of the second signal acquisition device; Based on the first time-frequency representation and the second time-frequency representation, determine the correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal; Based on the correlation coefficient, the intensity of the wind noise signal present in the environment where the headphones are located is determined.
16. The apparatus as claimed in claim 9, characterized in that, The first signal acquisition device is a feedforward microphone; the second signal acquisition device is a call microphone.
17. An earphone, characterized in that, include: First signal acquisition unit and second signal acquisition unit; processor; A memory for storing processor-executable instructions; wherein the instructions are executed by the processor to enable the processor to perform the method of any one of claims 1-8.
18. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-8.