CN116320867A - Wind noise detection method and device and earphone - Google Patents
Wind noise detection method and device and earphone Download PDFInfo
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- H04R1/00—Details of transducers, loudspeakers or microphones
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Abstract
The disclosure relates to a wind noise detection method, a wind noise detection device and an earphone, and relates to the technical field of audio signal processing and the technical field of earphones. The method is applied to the earphone, the earphone comprises a first signal collector and a second signal collector, and the method comprises the following steps: acquiring a first audio signal acquired by a first signal acquisition unit; determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal; under the condition that the environment where the earphone is located is determined to have a suspected wind noise signal, acquiring a second audio signal acquired by a second signal acquisition unit; and determining whether wind noise exists in the environment where the earphone is positioned according to the first audio signal and the second audio signal. The method combines the single-microphone detection scheme and the double-microphone detection scheme, can greatly reduce the consumption of computational resources and increase the duration of the earphone. In addition, the multi-level detection mode is adopted in the method, the accuracy of wind noise detection can be effectively guaranteed, and the possibility of false detection of wind noise is reduced to a certain extent.
Description
Technical Field
The disclosure relates to the technical field of audio signal processing and the technical field of headphones, and in particular relates to a wind noise detection method, a wind noise detection device and headphones.
Background
Headphones have become an integral part of work and life for some students, job staffs, and art creators. The earphone has the advantages of self-adaptive sound effect compensation, active noise reduction, spatial audio and other functions. Among them, the active noise reduction function becomes an important consideration for more and more people to choose headphones. In the use process of the earphone, the wind noise problem is difficult to avoid, and can bring great influence to the use experience of the earphone, such as conversation reduction, music quality and the like. Therefore, how to detect wind noise in the environment where the earphone is located is one of the important research directions in the art.
Disclosure of Invention
In order to overcome the problems in the related art, the present disclosure provides a wind noise detection method, a device and an earphone.
According to a first aspect of embodiments of the present disclosure, there is provided a wind noise detection method applied to an earphone, the earphone including a first signal collector and a second signal collector, the method including:
acquiring a first audio signal acquired by the first signal acquisition unit;
determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal;
acquiring a second audio signal acquired by the second signal acquisition unit under the condition that the environment where the earphone is positioned is determined to have a suspected wind noise signal;
and determining whether wind noise exists in the environment where the earphone is positioned according to the first audio signal and the second audio signal.
In some embodiments of the present disclosure, the determining, according to the first audio signal, whether a suspected wind noise signal exists in an environment where the earphone is located includes: performing filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal and the subband signal.
In some embodiments of the present disclosure, the determining, according to the first audio signal and the subband signal, whether a suspected wind noise signal exists in an environment where the earphone is located includes: determining a first energy of the first audio signal; determining a second energy of the subband signal; determining that a suspected wind noise signal exists in the environment where the earphone is located under the condition that the first energy meets a first condition and the second energy meets a second condition; or if the first energy does not meet the first condition and/or the second energy does not meet the second condition, determining that a suspected wind noise signal does not exist in the environment where the earphone is located.
In some embodiments of the present disclosure, the determining, according to the first audio signal and the second audio signal, whether wind noise exists in an environment where the earphone is located includes: determining a pearson correlation coefficient between the first audio signal and the second audio signal; under the condition that the pearson correlation coefficient is larger than or equal to a first threshold value, determining that wind noise does not exist in the environment where the earphone is located; or under the condition that the pearson correlation coefficient is smaller than or equal to the first threshold value, determining that wind noise exists in the environment where the earphone is located.
In some embodiments of the present disclosure, the method further comprises: and returning to the step of acquiring the first audio signal acquired by the first signal acquisition unit under the condition that the environment where the earphone is positioned is determined to not have a suspected wind noise signal.
In some embodiments of the present disclosure, the method further comprises: under the condition that the environment where the earphone is located is determined to have wind noise, determining the strength of the wind noise signal existing in the environment where the earphone is located according to the first audio signal and the second audio signal; and determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
In some embodiments of the present disclosure, the determining, according to the first audio signal and the second audio signal, the strength of a wind noise signal existing in an environment where the earphone is located includes: performing short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal collector; performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal collector; determining a correlation coefficient of an amplitude spectrum between the first audio signal and the second audio signal according to the first time-frequency representation and the second time-frequency representation; and determining the strength of wind noise signals existing in the environment where the earphone is positioned according to the correlation coefficient.
In some embodiments of the present disclosure, the first signal collector is a feed-forward microphone; the second signal collector is a call microphone.
According to a second aspect of embodiments of the present disclosure, there is provided a wind noise detection apparatus configured to an earphone, the earphone including a first signal collector and a second signal collector, the apparatus including:
the first acquisition module is used for acquiring the first audio signal acquired by the first signal acquisition unit;
the first determining module is used for determining whether a suspected wind noise signal exists in the environment where the earphone is located according to the first audio signal;
the second acquisition module is used for acquiring a second audio signal acquired by the second signal acquisition unit under the condition that the environment where the earphone is located is determined to have a suspected wind noise signal;
and the second determining module is used for determining whether wind noise exists in the environment where the earphone is positioned according to the first audio signal and the second audio signal.
In some embodiments of the disclosure, the first determining module is specifically configured to: performing filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal and the subband signal.
In some embodiments of the disclosure, the first determining module is specifically configured to: determining a first energy of the first audio signal; determining a second energy of the subband signal; determining that a suspected wind noise signal exists in the environment where the earphone is located under the condition that the first energy meets a first condition and the second energy meets a second condition; or if the first energy does not meet the first condition and/or the second energy does not meet the second condition, determining that a suspected wind noise signal does not exist in the environment where the earphone is located.
In some embodiments of the disclosure, the second determining module is specifically configured to: determining a pearson correlation coefficient between the first audio signal and the second audio signal; under the condition that the pearson correlation coefficient is larger than or equal to a first threshold value, determining that wind noise does not exist in the environment where the earphone is located; or under the condition that the pearson correlation coefficient is smaller than or equal to the first threshold value, determining that wind noise exists in the environment where the earphone is located.
In some embodiments of the disclosure, the first acquisition module is further configured to: and under the condition that the environment where the earphone is located is determined to not have a suspected wind noise signal, acquiring a first audio signal acquired by the first signal acquisition unit.
In some embodiments of the present disclosure, the apparatus further comprises a third determination module; wherein the third determining module is configured to: under the condition that the environment where the earphone is located is determined to have wind noise, determining the strength of the wind noise signal existing in the environment where the earphone is located according to the first audio signal and the second audio signal; and determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
In some embodiments of the disclosure, the third determining module is specifically configured to: performing short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal collector; performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal collector; determining a correlation coefficient of an amplitude spectrum between the first audio signal and the second audio signal according to the first time-frequency representation and the second time-frequency representation; and determining the strength of wind noise signals existing in the environment where the earphone is positioned according to the correlation coefficient.
In some embodiments of the present disclosure, the first signal collector is a feed-forward microphone; the second signal collector is a call microphone.
According to a third aspect of embodiments of the present disclosure, there is provided an earphone comprising:
a first signal collector and a second signal collector;
a processor;
a memory for storing processor-executable instructions; wherein the instructions are executable by the processor to enable the processor to perform the method of the first aspect.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program, characterized in that the computer program, when executed by a processor, implements the method of the preceding first aspect.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects: and acquiring a first audio signal through a first signal acquisition device, and determining whether a suspected wind noise signal exists or not, namely, performing primary wind noise judgment. Under the condition that the suspected wind noise signal is determined to exist, a second audio signal is acquired based on a second signal acquisition unit, and whether wind noise exists in the environment where the earphone is located or not is determined according to the first audio signal and the second audio signal, namely, secondary wind noise judgment is performed. The method combines the single-microphone detection scheme and the double-microphone detection scheme, does not need to continuously perform double-microphone detection, can greatly reduce the consumption of computing power resources, and increases the duration of the earphone. In addition, the multi-level detection mode is adopted in the method, the accuracy of wind noise detection can be effectively guaranteed, and the possibility of false detection of wind noise is reduced to a certain extent.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flowchart illustrating a wind noise detection method according to an exemplary embodiment.
FIG. 2 is a flow chart illustrating another wind noise detection method according to an exemplary embodiment.
Fig. 3 is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment.
Fig. 4 is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment.
Fig. 5 is a schematic structural view of a wind noise detection apparatus according to an exemplary embodiment.
Fig. 6 is a schematic structural view of another wind noise detection apparatus according to an exemplary embodiment.
Fig. 7 is a block diagram of an earphone according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
In the active noise reduction technology, the wind noise detection algorithm is a ring which is important. In the related art, a single-microphone detection scheme and a double-microphone detection scheme exist to judge whether wind noise exists or not. Wherein, single wheat detection performance is relatively poor, easily causes erroneous judgement. The double-microphone detection scheme detects wind noise in the environment where the earphone is located by adopting the double-microphone signal correlation. However, the dual-microphone detection scheme needs two paths of data streams, which can cause larger power consumption, and the wind noise scene is less than the non-wind noise scene, so that the continuous dual-microphone detection can cause unnecessary calculation power resource loss, and the dual-microphone detection scheme is also a huge test for the duration of part of wireless headphones.
The disclosure provides a wind noise detection method, a wind noise detection device and an earphone, so as to reduce the consumption of computational power resources caused when wind noise is detected, and simultaneously ensure the accuracy of wind noise detection.
Fig. 1 is a flowchart illustrating a wind noise detection method according to an exemplary embodiment. It should be noted that the wind noise detection method is applied to the earphone. The earphone comprises a first signal collector and a second signal collector. As shown in fig. 1, the wind noise detection method may include the following steps.
It should be noted that, the earphone according to the embodiment of the present disclosure is an earphone configured with dual microphones. Alternatively, in some embodiments of the present disclosure, the first signal collector may be a feed-forward microphone that collects noise audio of the out-of-ear environment. As one example, the headphones may be a TWS true wireless headphone, a wired headphone, or the like.
It should be noted that the first signal collector may collect noise in the environment outside the ear, i.e. the first audio signal. That is, the first-level wind noise judgment is performed on the wind noise signal in the environment based on the first audio signal acquired by the first signal acquirer. As a possible implementation manner, whether a suspected wind noise signal exists in the environment where the earphone is located or not can be judged according to whether the first audio signal meets a preset condition or not.
In some embodiments of the present disclosure, the second signal collector may be a talk microphone collecting talk audio. Under the condition that the suspected wind noise signal is determined to exist, the second audio signal is acquired based on the second signal acquisition unit, and the secondary wind noise judgment is carried out, namely, double-microphone detection is not required to be continuously carried out, so that the consumption of computational resources can be greatly reduced.
As a possible implementation, the correlation between the first audio signal and the second audio signal may be used to determine whether wind noise is present in the environment in which the earphone is located.
Optionally, in some embodiments of the present disclosure, when it is determined that the environment in which the earphone is located does not have a suspected wind noise signal, the step of acquiring the first audio signal acquired by the first signal acquirer may be performed back, and the audio signal is continuously acquired, and wind noise in the environment in which the earphone is located is detected.
According to the wind noise detection method disclosed by the embodiment of the disclosure, the first audio signal is collected through the first signal collector, and whether a suspected wind noise signal exists or not is determined, namely, primary wind noise judgment is performed. Under the condition that the suspected wind noise signal is determined to exist, a second audio signal is acquired based on a second signal acquisition unit, and whether wind noise exists in the environment where the earphone is located or not is determined according to the first audio signal and the second audio signal, namely, secondary wind noise judgment is performed. The method combines the single-microphone detection scheme and the double-microphone detection scheme, does not need to continuously perform double-microphone detection, can greatly reduce the consumption of computing power resources, and increases the duration of the earphone. In addition, the multi-level detection mode is adopted in the method, the accuracy of wind noise detection can be effectively guaranteed, and the possibility of false detection of wind noise is reduced to a certain extent.
FIG. 2 is a flow chart illustrating another wind noise detection method according to an exemplary embodiment. As shown in fig. 1, the wind noise detection method may include the following steps.
As an example, the first audio signal may be subjected to a filtering operation with reference to formula (1) to obtain a sub-band signal after the filtering operation.
Where x (t) is the first audio signal, y (t) is the subband signal after the filtering operation,
for bandpass filtering operation, l is the lower frequency of the passband and h is the upper frequency of the passband. Alternatively, in some embodiments of the present disclosure, l=100 Hz and h=500 Hz may be set.
In some embodiments of the present disclosure, whether a suspected wind noise signal exists in an environment where the earphone is located may be determined according to whether the energy of the first audio signal and the energy of the subband signal meet a preset condition. As a possible implementation, the first energy E of the first audio signal may be determined with reference to equation (2) 1 Determining a second energy E of the subband signal with reference to equation (3) 2 。
Wherein N is the number of sampling points, x (i) is the first audio signal of the ith sampling point, y (i) is the subband signal of the ith sampling point
At a first energy E 1 Meets the first condition and the second energy E 2 And under the condition that the second condition is met, determining that a suspected wind noise signal exists in the environment where the earphone is positioned. At a first energy E 1 Does not satisfy the first condition, or the second energy E 2 Does not satisfy the second condition, or the first energy E 1 The first condition is not satisfied and the second energy E 2 And under the condition that the second condition is not met, determining that a suspected wind noise signal does not exist in the environment where the earphone is located. Wherein the first condition is a first energy E 1 Greater than or equal to a first threshold T 1 The second condition is the second energy E 2 Greater than or equal to the second threshold E 2 ，T 1 、T 2 And the judgment threshold value is set according to actual conditions.
It should be noted that, in the embodiments of the present disclosure, the steps 204 to 205 may be implemented in any of the embodiments of the present disclosure, which is not limited by the present disclosure.
According to the wind noise detection method, the first audio signal is collected through the first signal collector, filtering operation is conducted on the first audio signal, whether a suspected wind noise signal exists or not is determined according to the first audio signal and the subband signals after the filtering operation, namely primary wind noise judgment is conducted, and detection accuracy of the suspected wind noise signal is improved. Under the condition that the suspected wind noise signal is determined to exist, a second audio signal is acquired based on a second signal acquisition unit, and whether wind noise exists in the environment where the earphone is located or not is determined according to the first audio signal and the second audio signal, namely, secondary wind noise judgment is performed. The method combines the single-microphone detection scheme and the double-microphone detection scheme, does not need to continuously perform double-microphone detection, can greatly reduce the consumption of computing power resources, and increases the duration of the earphone. In addition, the detection mode of multilevel is adopted in the present disclosure, the accuracy of wind noise detection can be improved, and the wind noise false detection possibility is reduced to a certain extent.
Fig. 3 is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment. As shown in fig. 3, the wind noise detection method may include the following steps.
Step 304 determines a pearson correlation coefficient between the first audio signal and the second audio signal.
As an example, the pearson correlation coefficient C between the first audio signal and the second audio signal may be determined with reference to equation (4).
Where x (i) is the first audio signal of the ith sample point,
z (i) is the second audio signal of the ith sample point, which is the average value of the first audio signal x (t), is +.>
The average value of the second audio signal z (t), and N is the number of sampling points.
Optionally, in other embodiments of the present disclosure, it may further be determined that wind noise does not exist in the environment where the earphone is located if the pearson correlation coefficient is greater than or equal to the first threshold, and that wind noise exists in the environment where the earphone is located if the pearson correlation coefficient is less than the first threshold.
It should be noted that, in the embodiment of the present disclosure, the steps 301 to 303 may be implemented in any manner of embodiments of the present disclosure, which is not limited by the present disclosure.
According to the wind noise detection method disclosed by the embodiment of the disclosure, the first audio signal is collected through the first signal collector, and whether a suspected wind noise signal exists or not is determined, namely, primary wind noise judgment is performed. Under the condition that the suspected wind noise signal is determined to exist, a second audio signal is acquired based on a second signal acquisition unit, whether wind noise exists in the environment where the earphone is located or not is determined according to the pearson correlation coefficient between the first audio signal and the second audio signal, namely, secondary wind noise judgment is performed, and accuracy of wind noise detection is improved. The method combines the single-microphone detection scheme and the double-microphone detection scheme, does not need to continuously perform double-microphone detection, can greatly reduce the consumption of computing power resources, and increases the duration of the earphone. In addition, the method adopts a multi-level detection mode, so that the possibility of wind noise false detection is further reduced.
It should be noted that, in order to optimize the use experience of the earphone, in some embodiments of the present disclosure, under the condition that it is determined that the environment where the earphone is located has wind noise, the method may further perform targeted adaptation according to the detected wind noise signal, and assist the earphone to perform corresponding noise reduction processing, so as to avoid causing abrupt change in hearing. Fig. 4 is a flowchart illustrating yet another wind noise detection method according to an exemplary embodiment. As shown in fig. 4, the wind noise detection method may include the following steps.
In step 405, in the case that it is determined that wind noise exists in the environment where the earphone is located, the strength of the wind noise signal existing in the environment where the earphone is located is determined according to the first audio signal and the second audio signal.
Optionally, in some embodiments of the present disclosure, the first audio signal may be subjected to a short-time fourier transform, resulting in a first time-frequency representation X1 (λ, μ) of the first signal collector. And performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation X2 (lambda, mu) of the second signal collector. Where λ represents the frame index and μ represents the frequency bin. Then, a correlation coefficient of the amplitude spectrum between the first audio signal and the second audio signal is determined from the first time-frequency representation X1 (λ, μ) and the second time-frequency representation X2 (λ, μ). As an example, a correlation coefficient of the magnitude spectrum between the first audio signal and the second audio signal may be determined with reference to formula (5)
Wherein X2' (λ, μ) is a conjugated representation of the second time-frequency representation X2 (λ, μ).
According to the correlation coefficient
And further determining the intensity of wind noise signals existing in the environment where the earphone is located. In one implementation, the correlation coefficient may be determined as the strength of a wind noise signal present in the environment in which the headset is located. In another implementation, a correlation characteristic between the first audio signal and the second audio signal may also be calculated according to the correlation coefficient, and the correlation characteristic may be determined as the strength of a wind noise signal present in the environment in which the earphone is located. As an example, the correlation characteristic Γ (λ, μ) between the first audio signal and the second audio signal may be determined with reference to equation (6).
And step 406, determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
It should be noted that, in the embodiments of the present disclosure, the steps 401 to 404 may be implemented in any one of the embodiments of the present disclosure, which is not limited by the present disclosure.
According to the wind noise detection method disclosed by the embodiment of the disclosure, the first audio signal is collected through the first signal collector, and whether a suspected wind noise signal exists or not is determined, namely, primary wind noise judgment is performed. Under the condition that the suspected wind noise signal is determined to exist, a second audio signal is acquired based on a second signal acquisition unit, and whether wind noise exists in the environment where the earphone is located or not is determined according to the first audio signal and the second audio signal, namely, secondary wind noise judgment is performed. And under the condition that the environment where the earphone is positioned is determined to have wind noise, determining the corresponding noise reduction coefficient through the strength of the wind noise signal. The noise reduction coefficient can be adaptively adjusted according to the wind noise intensity in the actual use process, so that smooth change of hearing in a wind noise scene is realized, and subjective abrupt feeling is reduced.
In order to achieve the above embodiments, the present disclosure provides a wind noise detection apparatus. Fig. 5 is a schematic structural view of a wind noise detection apparatus according to an exemplary embodiment. It should be noted that, this wind noise detection device is applied to earphone, and this earphone includes first signal collector and second signal collector. As shown in fig. 5, 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. Wherein, the liquid crystal display device comprises a liquid crystal display device,
the first obtaining module 501 is configured to obtain a first audio signal collected by the first signal collector.
A first determining module 502, configured to determine, according to the first audio signal, whether a suspected wind noise signal exists in an environment where the earphone is located.
A second obtaining module 503, configured to obtain a second audio signal collected by the second signal collector when it is determined that the environment where the earphone is located has a suspected wind noise signal.
A second determining module 504, configured to determine whether wind noise exists in the environment where the earphone is located according to the first audio signal and the second audio signal.
In some embodiments of the present disclosure, the first determining module 501 is specifically configured to: performing filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation; and determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal and the subband signal.
In some embodiments of the present disclosure, the first determining module 501 is specifically configured to: determining a first energy of the first audio signal; determining a second energy of the subband signal; determining that a suspected wind noise signal exists in the environment where the earphone is located under the condition that the first energy meets a first condition and the second energy meets a second condition; or if the first energy does not meet the first condition and/or the second energy does not meet the second condition, determining that a suspected wind noise signal does not exist in the environment where the earphone is located.
In some embodiments of the present disclosure, the second determining module 504 is specifically configured to: determining a pearson correlation coefficient between the first audio signal and the second audio signal; under the condition that the pearson correlation coefficient is larger than or equal to a first threshold value, determining that wind noise does not exist in the environment where the earphone is located; or under the condition that the pearson correlation coefficient is smaller than or equal to the first threshold value, determining that wind noise exists in the environment where the earphone is located.
In some embodiments of the present disclosure, the first signal collector is a feed-forward microphone; the second signal collector is a call microphone.
In some embodiments of the present disclosure, the first acquisition module 501 is further configured to: and under the condition that the environment where the earphone is located is determined to not have a suspected wind noise signal, acquiring a first audio signal acquired by the first signal acquisition unit.
Optionally, in some embodiments of the present disclosure, as shown in fig. 6, the wind noise detection device further includes: and a third determination module. Wherein the third determining module 605 is configured to: under the condition that the environment where the earphone is located is determined to have wind noise, determining the strength of the wind noise signal existing in the environment where the earphone is located according to the first audio signal and the second audio signal; and determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
In some embodiments of the present disclosure, the third determining module 605 is specifically configured to: performing short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal collector; performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal collector; determining a correlation coefficient of an amplitude spectrum between the first audio signal and the second audio signal according to the first time-frequency representation and the second time-frequency representation; and determining the strength of wind noise signals existing in the environment where the earphone is positioned according to the correlation coefficient. Wherein 601-604 of fig. 6 have the same function and structure as 501-504 of fig. 5.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 7 is a block diagram of an earphone according to an exemplary embodiment.
Referring to fig. 7, headphones 700 may include one or more of the following components: a first signal collector 701, a second signal collector 702, a processing component 703, a memory 704, a power component 706, an audio component 710, an input/output (I/O) interface 712, and a communication component 716.
The first signal collector 701 is configured to collect a first audio signal. In an exemplary embodiment, the first signal collector 818 may be a feed forward microphone.
The second signal collector 802 is configured to collect a second audio signal. In an exemplary embodiment, the second signal collector 820 may be a talk microphone.
The processing component 703 generally controls overall operation of the headset 700, such as operations associated with telephone calls, data communications, camera operations, and recording operations. The processing component 703 may include one or more processors 720 to execute instructions to perform all or part of the steps of the methods described above. Further, the processing component 703 may include one or more modules that facilitate interactions between the processing component 703 and other components. For example, the processing component 703 may include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 703.
The memory 704 is configured to store various types of data to support operation at the headset 700. Examples of such data include instructions for any application or method operating on headset 700, contact data, phonebook data, messages, pictures, video, and the like. The memory 704 may be implemented by any type or combination of volatile or nonvolatile memory devices 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 memory, flash memory, magnetic or optical disk.
The power component 706 provides power to the various components of the headset 700. Power component 706 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for headset 700.
The audio component 710 is configured to output and/or input audio signals. For example, the audio component 710 includes a Microphone (MIC) configured to receive external audio signals when the headset 700 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may be further stored in the memory 704 or transmitted via the communication component 716. In some embodiments, the audio component 710 further includes a speaker for outputting audio signals.
The I/O interface 712 provides an interface between the processing component 703 and a peripheral interface module, which may be a button or the like. These buttons may include, but are not limited to: homepage button, volume button, start button, and lock button.
The communication component 716 is configured to facilitate communication between the headset 700 and other devices, either wired or wireless. Headset 700 may access a wireless network based on a communication standard, such as WiFi,2G, or 3G, or a combination thereof. In one exemplary embodiment, the communication component 716 receives broadcast signals or broadcast related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 716 further includes a Near Field Communication (NFC) module to facilitate short range communications. 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.
In an exemplary embodiment, the headset 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 elements for executing the methods described above.
In an exemplary embodiment, a non-transitory computer readable storage medium is also provided, such as memory 704, including instructions executable by processor 720 of headset 700 to perform the above-described method. For example, the non-transitory computer readable storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
Other embodiments of the invention will be apparent to those skilled in the art from 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 following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It is to be understood that the invention is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (18)
1. A wind noise detection method, characterized in that it is applied to an earphone, the earphone includes a first signal collector and a second signal collector, the method includes:
acquiring a first audio signal acquired by the first signal acquisition unit;
determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal;
acquiring a second audio signal acquired by the second signal acquisition unit under the condition that the environment where the earphone is positioned is determined to have a suspected wind noise signal;
and determining whether wind noise exists in the environment where the earphone is positioned according to the first audio signal and the second audio signal.
2. The method of claim 1, wherein determining whether a suspected wind noise signal is present in the environment of the headset based on the first audio signal comprises:
performing filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation;
and determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal and the subband signal.
3. The method of claim 2, wherein determining whether a suspected wind noise signal exists in the environment of the earphone according to the first audio signal and the subband signal comprises:
determining a first energy of the first audio signal;
determining a second energy of the subband signal;
determining that a suspected wind noise signal exists in the environment where the earphone is located under the condition that the first energy meets a first condition and the second energy meets a second condition; or alternatively, the process may be performed,
and under the condition that the first energy does not meet the first condition and/or the second energy does not meet the second condition, determining that a suspected wind noise signal does not exist in the environment where the earphone is located.
4. The method of claim 1, wherein determining whether wind noise is present in the environment of the headset based on the first audio signal and the second audio signal comprises:
determining a pearson correlation coefficient between the first audio signal and the second audio signal;
under the condition that the pearson correlation coefficient is larger than or equal to a first threshold value, determining that wind noise does not exist in the environment where the earphone is located; or alternatively, the process may be performed,
and under the condition that the pearson correlation coefficient is smaller than or equal to the first threshold value, determining that wind noise exists in the environment where the earphone is located.
5. The method of claim 1, wherein the method further comprises:
and returning to the step of acquiring the first audio signal acquired by the first signal acquisition unit under the condition that the environment where the earphone is positioned is determined to not have a suspected wind noise signal.
6. The method of any one of claims 1 to 5, wherein the method further comprises:
under the condition that the environment where the earphone is located is determined to have wind noise, determining the strength of the wind noise signal existing in the environment where the earphone is located according to the first audio signal and the second audio signal;
and determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
7. The method of claim 6, wherein determining the strength of the wind noise signal present in the environment of the headset based on the first audio signal and the second audio signal comprises:
performing short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal collector;
performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal collector;
determining a correlation coefficient of an amplitude spectrum between the first audio signal and the second audio signal according to the first time-frequency representation and the second time-frequency representation;
and determining the strength of wind noise signals existing in the environment where the earphone is positioned according to the correlation coefficient.
8. The method of claim 1, wherein the first signal collector is a feed forward microphone; the second signal collector is a call microphone.
9. Wind noise detection device, its characterized in that disposes in the earphone, the earphone includes first signal collector and second signal collector, the device includes:
the first acquisition module is used for acquiring the first audio signal acquired by the first signal acquisition unit;
the first determining module is used for determining whether a suspected wind noise signal exists in the environment where the earphone is located according to the first audio signal;
the second acquisition module is used for acquiring a second audio signal acquired by the second signal acquisition unit under the condition that the environment where the earphone is located is determined to have a suspected wind noise signal;
and the second determining module is used for determining whether wind noise exists in the environment where the earphone is positioned according to the first audio signal and the second audio signal.
10. The apparatus of claim 9, wherein the first determination module is specifically configured to:
performing filtering operation on the first audio signal to obtain a sub-band signal after the filtering operation;
and determining whether a suspected wind noise signal exists in the environment where the earphone is positioned according to the first audio signal and the subband signal.
11. The apparatus of claim 10, wherein the first determination module is specifically configured to:
determining a first energy of the first audio signal;
determining a second energy of the subband signal;
determining that a suspected wind noise signal exists in the environment where the earphone is located under the condition that the first energy meets a first condition and the second energy meets a second condition; or alternatively, the process may be performed,
and under the condition that the first energy does not meet the first condition and/or the second energy does not meet the second condition, determining that a suspected wind noise signal does not exist in the environment where the earphone is located.
12. The apparatus of claim 9, wherein the second determination module is specifically configured to:
determining a pearson correlation coefficient between the first audio signal and the second audio signal;
under the condition that the pearson correlation coefficient is larger than or equal to a first threshold value, determining that wind noise does not exist in the environment where the earphone is located; or alternatively, the process may be performed,
and under the condition that the pearson correlation coefficient is smaller than or equal to the first threshold value, determining that wind noise exists in the environment where the earphone is located.
13. The apparatus of claim 9, wherein the first acquisition module is further to:
and under the condition that the environment where the earphone is located is determined to not have a suspected wind noise signal, acquiring a first audio signal acquired by the first signal acquisition unit.
14. The apparatus of any one of claims 9 to 13, wherein the apparatus further comprises a third determination module; wherein the third determining module is configured to:
under the condition that the environment where the earphone is located is determined to have wind noise, determining the strength of the wind noise signal existing in the environment where the earphone is located according to the first audio signal and the second audio signal;
and determining a corresponding noise reduction coefficient according to the intensity of the wind noise signal, wherein the noise reduction coefficient is used for assisting the earphone in carrying out corresponding noise reduction processing.
15. The apparatus of claim 14, wherein the third determination module is specifically configured to:
performing short-time Fourier transform on the first audio signal to obtain a first time-frequency representation of the first signal collector;
performing short-time Fourier transform on the second audio signal to obtain a second time-frequency representation of the second signal collector;
determining a correlation coefficient of an amplitude spectrum between the first audio signal and the second audio signal according to the first time-frequency representation and the second time-frequency representation;
and determining the strength of wind noise signals existing in the environment where the earphone is positioned according to the correlation coefficient.
16. The apparatus of claim 9, wherein the first signal collector is a feed forward microphone; the second signal collector is a call microphone.
17. An earphone, comprising:
a first signal collector and a second signal collector;
a processor;
a memory for storing processor-executable instructions; wherein the instructions are executable by the processor to enable the processor to perform the method of any one of claims 1-8.
18. A computer readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the method according to any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310161983.6A CN116320867A (en) | 2023-02-23 | 2023-02-23 | Wind noise detection method and device and earphone |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310161983.6A CN116320867A (en) | 2023-02-23 | 2023-02-23 | Wind noise detection method and device and earphone |
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| Publication Number | Publication Date |
|---|---|
| CN116320867A true CN116320867A (en) | 2023-06-23 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310161983.6A Pending CN116320867A (en) | 2023-02-23 | 2023-02-23 | Wind noise detection method and device and earphone |
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| Country | Link |
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| CN (1) | CN116320867A (en) |
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2023
- 2023-02-23 CN CN202310161983.6A patent/CN116320867A/en active Pending
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