Headphone wind noise recognition method, device and headphone

Abstract

The present application discloses a headphone wind noise recognition method, device and headphone. The headphone includes a feedforward microphone located outside the ear and a feedback microphone located inside the ear. The method includes: obtaining a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone; performing Fourier transform on the feedforward microphone signal and the feedback microphone signal to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal; performing inverse feedback filtering on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result; performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse mixed filtering processing result; and obtaining a headphone wind noise recognition result based on the relationship between the inverse feedback filtering processing result and the inverse mixed filtering processing result. The present application utilizes the existing microphone of the headphone for wind noise recognition, and does not need to set up other microphones additionally, which reduces the hardware cost and has a good wind noise recognition effect.

Description

Technical Field

[0001] The present application relates to the technical field of earphone wind noise recognition, and in particular to an earphone wind noise recognition method, device and earphone. Background Art

[0002] In noisy scenarios, people often wear active noise-cancelling headphones to reduce the noise actually heard by the human ear and achieve a better auditory experience. General active noise-cancelling headphones contain a feedforward microphone outside the ear and a feedback microphone inside the ear. It uses the feedforward microphone outside the ear to detect the noise outside the ear, generates an electrical signal through feedforward noise reduction, and transmits it to the speaker to generate an acoustic signal with the same amplitude and opposite direction as the noise inside the ear, thereby achieving the purpose of reducing the noise inside the ear. Since the feedforward noise reduction effect is limited, the feedback microphone in the ear can also be used to further reduce the residual noise in the ear through feedback noise reduction to achieve a better noise reduction experience. In addition, the existing feedforward microphone and feedback microphone of the active noise-cancelling headphones can also be used for calls, that is, when the user is making a voice call, the noise influence in the uplink voice signal (that is, the voice signal sent to the other party) is suppressed through the processing algorithm.

[0003] It is inevitable to encounter wind noise during the use of headphones. The principle of wind noise is: when wind encounters an obstacle, it will generate turbulence (also known as spoiler). The turbulence causes the air pressure near the cavity of the microphone to fluctuate. By resonating with the air column in the cavity of the microphone, the noise generated by the turbulence is amplified. This amplified noise is picked up by the microphone, and wind noise is generated. Wind noise is not generated in the human ear, but only at the microphone end. Therefore, after turning on the feedforward noise reduction, the wind noise will be transmitted to the human ear, resulting in a poor experience when listening to music. At the same time, wind noise also affects calls, resulting in reduced call clarity. In order to reduce the impact of wind noise, you must first identify the wind noise, and then take some measures to reduce the impact of wind noise.

[0004] However, the inventors have found that the wind noise recognition method in the prior art needs to be further improved in terms of recognition accuracy or recognition cost. Summary of the invention

[0005] In view of this, the main purpose of the present application is to provide a headphone wind noise recognition method, device and headphone, which are used to solve the technical problems of poor recognition accuracy or high recognition cost of wind noise recognition methods in the prior art.

[0006] According to a first aspect of the present application, a method for identifying wind noise in an earphone is provided, wherein the earphone comprises a feedforward microphone located outside the ear and a feedback microphone located inside the ear, and the method comprises:

[0007] Acquire a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone;

[0008] Performing Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal;

[0009] Performing inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result;

[0010] Performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result;

[0011] Based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result, a headphone wind noise recognition result is obtained.

[0012] According to a second aspect of the present application, a headphone wind noise recognition device is provided, the headphone comprising a feedforward microphone located outside the ear and a feedback microphone located inside the ear, the device comprising:

[0013] A microphone signal acquisition unit, used to acquire a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone;

[0014] A Fourier transform unit, used to perform Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal;

[0015] An inverse feedback filtering processing unit, used to perform inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result;

[0016] An inverse feedforward filtering processing unit, used for performing inverse feedforward filtering processing on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result;

[0017] The wind noise recognition unit is used to obtain a headphone wind noise recognition result based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result.

[0018] According to a third aspect of the present application, there is provided an earphone, comprising: a feedforward microphone located outside the ear, a feedback microphone located inside the ear, a speaker, a processor, and a memory storing computer executable instructions.

[0019] When the executable instructions are executed by the processor, the aforementioned headphone wind noise recognition method is implemented.

[0020] According to a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the aforementioned headphone wind noise recognition method is implemented.

[0021] The beneficial effects of the present application are as follows: the earphones used in the earphone wind noise recognition method of the embodiment of the present application include structures such as a feedforward microphone and a feedback microphone. When performing wind noise recognition, the feedforward microphone signal collected by the feedforward microphone and the feedback microphone signal collected by the feedback microphone can be first obtained; in order to facilitate subsequent signal processing and calculation, the feedforward microphone signal and the feedback microphone signal can be converted into the frequency domain by Fourier transform, and then the feedforward microphone frequency domain signal and the feedback microphone frequency domain signal are obtained respectively; then the feedback microphone frequency domain signal is subjected to inverse feedback filtering processing to obtain the frequency domain signal picked up by the feedback microphone when feedback noise reduction is not turned on, as the inverse feedback filtering processing result; the inverse feedback filtering processing result obtained above is combined with the feedforward microphone frequency domain signal to perform inverse feedforward filtering processing to obtain the frequency domain signal picked up by the feedback microphone when hybrid noise reduction is not turned on, as the inverse hybrid filtering processing result; finally, based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result, the earphone wind noise recognition result can be obtained. The headphone wind noise recognition method of the embodiment of the present application utilizes the existing feedforward microphone and feedback microphone of the headphone to recognize wind noise, without the need to set up other additional microphones, thereby reducing hardware costs and achieving better wind noise recognition effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0023] Figure 1 This is a flow chart of a headphone wind noise recognition method according to an embodiment of the present application;

[0024] Figure 2 This is a schematic diagram of the structure of an earphone in one embodiment of the present application;

[0025] Figure 3 A schematic diagram of a flow chart of a headphone wind noise recognition method according to an embodiment of the present application;

[0026] Figure 4 This is a block diagram of a headphone wind noise recognition device according to an embodiment of the present application;

[0027] Figure 5 This is a schematic diagram of the structure of headphones in another embodiment of the present application. DETAILED DESCRIPTION

[0028] The exemplary embodiments of the present application will be described in more detail below with reference to the accompanying drawings. These embodiments are provided to enable a more thorough understanding of the present application and to fully convey the scope of the present application to those skilled in the art. Although exemplary embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0029] In the prior art, there is a solution that uses a microphone outside the ear (feedforward microphone) to identify wind noise. This solution requires the establishment of a database of wind noise signals with different wind forces and directions in advance in order to extract wind noise features and perform comparative identification. This solution is not only highly complex but also has a large computational workload. Once wind noise that is not in the database is encountered, the recognition accuracy will be greatly reduced.

[0030] Another solution is to use dual microphones outside the ear to identify wind noise. It uses information such as the correlation of signals obtained by the dual microphones outside the ear to identify wind noise (the correlation between the noise signals generated by the two microphones outside the ear is very low, while the correlation between other external sounds is higher). It has high accuracy, but requires adding another microphone outside the ear on the basis of the active noise reduction headphones, which will increase hardware costs and processing overhead.

[0031] In addition, when the headset turns on feedforward noise reduction or hybrid noise reduction (i.e., feedforward noise reduction and feedback noise reduction are turned on at the same time), the wind noise outside the ear will be transmitted into the ear after the feedforward noise reduction, making the coherence of the microphone signals inside and outside the ear high. At this time, the coherence information cannot be used to identify the presence of wind noise. Based on this, an embodiment of the present application provides a method for identifying wind noise when the headset turns on feedforward noise reduction or hybrid noise reduction.

[0032] Specifically, Figure 1 A schematic diagram of a flow chart of a method for identifying wind noise in headphones according to an embodiment of the present application is shown. Figure 2 A schematic diagram of the structure of an earphone provided according to an embodiment of the present application is shown, the earphone includes an external ear microphone (feedforward microphone) 21, located at the position of the earphone housing close to the outside of the ear, for picking up external ear environmental noise signals, and also includes an internal ear microphone (feedback microphone) 22, located at the front end of the speaker, for picking up internal ear noise signals, and also includes a speaker 23 for playing sound sources. The feedforward microphone 21 is used for feedforward noise reduction of the earphone, and the feedback microphone 22 is used for feedback noise reduction of the earphone. When the two noise reductions are turned on at the same time, it is called hybrid noise reduction. Feedforward noise reduction, feedback noise reduction and hybrid noise reduction can all be regarded as a type of active noise reduction.

[0033] like Figure 1As shown, the headphone wind noise recognition method of the embodiment of the present application specifically includes the following steps S110 to S150:

[0034] Step S110 , obtaining a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone.

[0035] As mentioned above, the feedforward microphone is set at the position of the earphone shell close to the outside of the ear, which can pick up the ambient noise signal outside the ear, and the feedback microphone is set at the front end of the speaker, which can pick up the noise signal inside the ear. Therefore, the embodiment of the present application can first obtain the feedforward microphone signal collected by the feedforward microphone and the feedback microphone signal collected by the feedback microphone as the basic signal for wind noise recognition.

[0036] Step S120 , performing Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal.

[0037] After obtaining the feedforward microphone signal collected by the feedforward microphone and the feedback microphone signal collected by the feedback microphone, in order to facilitate subsequent calculation and processing of the signals, the feedforward microphone signal and the feedback microphone signal can be converted into the frequency domain through Fourier transform, thereby obtaining the feedforward microphone frequency domain signal (FFmic) and the feedback microphone frequency domain signal (FBmic), respectively.

[0038] Step S130, performing inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result.

[0039] The above-obtained feedback microphone frequency domain signal (FBmic) is subjected to inverse feedback filtering to obtain an inverse feedback filtering result (FB invfb ), the inverse feedback filtering process here can be understood as restoring the frequency domain signal picked up by the feedback microphone to the state when the headset does not turn on feedback noise reduction.

[0040] Step S140 , performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result.

[0041] After obtaining the above inverse feedback filtering result (FB invfb ), it is necessary to further combine the frequency domain signal of the feedforward microphone to perform inverse feedforward filtering on the inverse feedback filtering result to obtain the inverse hybrid filtering result (FB inv). Since the inverse feedforward filtering process is further performed on the basis of the inverse feedback processing, the inverse feedforward filtering process here can be understood as restoring the frequency domain signal picked up by the feedback microphone to the state when the headset does not turn on hybrid noise reduction (including feedforward noise reduction and feedback noise reduction). It should be noted that this step does not perform inverse feedforward filtering on the feedforward microphone frequency domain signal itself, because the feedforward microphone frequency domain signal is generated outside the ear and is not affected by active noise reduction. Therefore, it is only necessary to consider the impact of the feedforward microphone frequency domain signal in the ear on the feedback microphone frequency domain signal.

[0042] Step S150: obtaining a headphone wind noise recognition result based on the relationship between the inverse feedback filtering result and the inverse hybrid filtering result.

[0043] After obtaining the inverse feedback filtering result (FB invfb ) and the inverse hybrid filtering result (FB inv ), the recognition result of the headphone wind noise can be determined based on the relationship between the two, such as a proportional relationship, etc., including the recognition results with wind noise and without wind noise.

[0044] The headphone wind noise recognition method of the embodiment of the present application utilizes the existing feedforward microphone and feedback microphone of the headphone to recognize wind noise, without the need to set up other additional microphones, thereby reducing hardware costs and achieving better wind noise recognition effect.

[0045] In one embodiment of the present application, the inverse feedback filtering process is implemented by the following formula:

[0046] FB invfb =FBmic×(1-H fb ×G), (1)

[0047] Among them, FB invfb is the result of inverse feedback filtering, FBmic is the frequency domain signal of the feedback microphone, and H fb is the frequency response of the feedback filter used when the headset currently turns on feedback noise reduction, and G is the transfer function from the speaker to the feedback microphone;

[0048] The inverse feedforward filtering process is implemented by the following formula:

[0049] FB inv =FB invfb -FFmic×H ff ×G, (2)

[0050] Among them, FB inv is the inverse hybrid filtering result, FFmic is the frequency domain signal of the feedforward microphone, and H ffis the frequency response of the feedforward filter used when the headset currently turns on feedforward noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone.

[0051] As mentioned above, the purpose of the inverse feedback filtering process is to restore the frequency domain signal picked up by the feedback microphone to the state when the feedback noise reduction is not turned on in the headphones, and the purpose of the inverse feedforward filtering process is to restore the frequency domain signal picked up by the feedback microphone to the state when the hybrid noise reduction is not turned on in the headphones. Therefore, the embodiment of the present application can obtain the inverse feedback filtering process result before turning on the feedback noise reduction through the above formula (1), and can obtain the inverse hybrid filtering process result before turning on the hybrid noise reduction through the above formula (2), thereby providing an accurate frequency domain signal basis for subsequent wind noise recognition.

[0052] The transfer function G from the speaker to the feedback microphone in the above formulas (1) and (2) can be determined by collecting the speaker sound source signal and the feedback microphone signal picked up by the feedback microphone, and calculating the corresponding relationship between the two. There are two ways of calculation here: one is to calculate it offline in advance (that is, to determine it by measurement in the laboratory), and the transfer function G calculated offline in advance can be directly called when it is used, which takes less time. Considering that different people wear different earphones, there are also some differences in the structure inside the ear, and the coupling degree between the earphone and the human ear of different people is different, resulting in differences in the collected signals. Therefore, the signal data of multiple people can be collected in advance and then determined by statistical methods to improve the calculation accuracy. Another calculation method is to calculate it in real time, which can calculate a more accurate transfer function G according to the coupling degree between the human ear and the earphone of different people, and the accuracy is relatively higher. The specific method of calculating the transfer function G can be flexibly selected by technicians in this field according to the actual situation, and no specific limitation is made here.

[0053] Specifically, the transfer function G obtained by real-time measurement can be calculated based on the following formula (3):

[0054]

[0055] Where E[] is the expected operation, Ref(f,t) is the frequency domain signal of the sound source played by the speaker at time t, FBmic(f,t) is the frequency domain signal of the in-ear microphone at time t, and Ref * is the conjugate signal of the Ref signal.

[0056] In one embodiment of the present application, after obtaining the inverse feedback filtering processing result and the inverse mixing filtering processing result, the method also includes: obtaining a speaker sound source frequency domain signal played by the speaker in the earphone; and performing echo cancellation processing on the inverse feedback filtering processing result and the inverse mixing filtering processing result according to the speaker sound source frequency domain signal to obtain a more ideal processing result.

[0057] When the headset of the embodiment of the present application is in use, the speaker will play the sound source and generate a speaker sound source signal (Ref), such as a music signal and a downlink signal during a call. After the speaker sound source signal is emitted through the speaker, it will cause an echo when it is transmitted to the microphone, resulting in poor audio effect heard by the user on the other side of the call, and will also affect the accuracy of subsequent wind noise recognition. Therefore, echo cancellation processing can be performed here. When performing echo cancellation processing, the embodiment of the present application first obtains the sound source signal played by the speaker, and then converts the speaker sound source signal to the frequency domain through Fourier transform to facilitate subsequent calculations.

[0058] Since the echo signal and the loudspeaker sound source signal (Ref) in the signal received by the microphone are related, that is, there is a transfer function (H) from the loudspeaker sound source signal to the microphone echo signal. This related information can be used to estimate the echo information in the signal received by the microphone through the loudspeaker sound source signal, thereby removing the echo signal part of the microphone signal.

[0059] Specifically, the inverse hybrid filtering processing result and the inverse feedback filtering processing result obtained above can be used as the target signal (des), and the loudspeaker sound source signal can be used as the reference signal (Ref). The Normalized Least Mean Square (NLMS) adaptive algorithm can be used to obtain the best filter weights. This filter is the impulse response of the transfer function (H) mentioned above. The echo signal part in the target signal is estimated based on the convolution result of the filter weights and the reference signal. By subtracting this echo signal part from the target signal, the target signal after echo elimination can be obtained. It should be noted that the above echo elimination processing step is only an optional step. If the speaker of the headset does not play the sound source, that is, no loudspeaker sound source signal is generated, there is no echo problem at this time, so the echo elimination step can be omitted.

[0060] In one embodiment of the present application, based on the relationship between the inverse feedback filtering result and the inverse hybrid filtering result, obtaining the headphone wind noise recognition result includes: calculating the energy ratio of the inverse hybrid filtering result to the inverse feedback filtering result; if the ratio is greater than a first preset threshold, determining the headphone wind noise recognition result as no wind noise; if the ratio is less than a second preset threshold, determining the headphone wind noise recognition result as wind noise. The first preset threshold is greater than the second preset threshold; if the ratio is between the second preset threshold and the first preset threshold, the last headphone wind noise recognition result is used as the current headphone wind noise recognition result.

[0061] When hybrid noise reduction is turned on in the headset, the inventor found that when the outside of the ear is a normal noise scene (non-wind noise scene), the noise in the ear will be reduced after hybrid noise reduction is turned on compared to before hybrid noise reduction is turned on. When the outside of the ear is a wind noise scene, after hybrid noise reduction is turned on, wind noise is transmitted into the ear through the feedforward microphone, and the noise in the ear will become higher than before hybrid noise reduction is turned on. As mentioned above, the purpose of the inverse feedback filtering process is to restore the frequency domain signal picked up by the feedback microphone to the state when the headset does not turn on feedback noise reduction, and the purpose of the inverse feedforward filtering process is to restore the frequency domain signal picked up by the feedback microphone to the state when the headset does not turn on hybrid noise reduction. Therefore, the embodiment of the present application can obtain the inverse feedback filtering process result before turning on feedback noise reduction through the above formula (1), and the inverse hybrid filtering process result before turning on hybrid noise reduction can be obtained through the above formula (2), which can provide an accurate frequency domain signal basis for subsequent wind noise recognition.

[0062] To this end, the signal energy before hybrid noise reduction is turned on and the signal energy after hybrid noise reduction is turned on can be compared to determine whether it is a wind noise scene. Preferably, the frequency band where feedforward noise reduction has an obvious effect can be selected for energy calculation and comparison. That is, the frequency band where feedforward noise reduction has an obvious effect can be determined first, and then the determined frequency band where feedforward noise reduction has an obvious effect can be selected to calculate the energy ratio of the inverse hybrid filtering processing result and the inverse feedback filtering processing result, and then the energy ratio can be compared.

[0063] Based on this, the embodiment of the present application can pre-set a first preset threshold value T1 and a second preset threshold value T2 for wind noise recognition, where T1>T2. Among them, FB inv _A represents the energy value of the inverse hybrid filtering result in the frequency band {freq1, freq2}, FB invfb _A represents the energy value of the inverse feedback filtering result in the frequency band {freq1, freq2}. When R is greater than the threshold value T1, it means that the energy before the hybrid noise reduction is turned on is larger, and it is considered that the scene outside the ear is not wind noise at this time; when R is less than the threshold value T2, it means that the energy before the hybrid noise reduction is turned on is smaller and the energy after it is turned on is larger, then it is considered that wind is entering the ear through the feedforward microphone, causing the noise in the ear to become higher, and therefore it is judged that there is wind noise outside the ear.

[0064] In another embodiment, if the value of R is between the thresholds T1 and T2, the last wind noise determination result is used as the current determination result.

[0065] In one embodiment of the present application, when only the feedforward noise reduction is turned on, the feedback microphone frequency domain signal is directly used as the inverse feedback filtering result.

[0066] When the headphones only turn on the feedforward noise reduction, it can be considered that the frequency response H of the feedback filter used when the headphones turn on the feedback noise reduction at the current moment fb If FBmic is equal to 0, it can be seen from formula (1) in the above embodiment that the result of the inverse feedback filtering processing is the feedback microphone frequency domain signal FBmic. Therefore, when the earphone only turns on feedforward noise reduction, wind noise recognition can still be performed through the above embodiment.

[0067] In one embodiment of the present application, the method also includes: after obtaining the headphone wind noise recognition result, suppressing the wind noise by any one or more of the following methods: reducing the gain of the feedforward microphone, turning off the feedforward microphone, or attenuating the low-frequency band signal in the feedforward microphone signal collected by the feedforward microphone.

[0068] After identifying that the current scene is a scene with wind noise, corresponding follow-up measures can be taken to reduce the adverse effects of wind noise. For example, the gain of the feedforward microphone can be reduced to reduce the wind noise entering the ear due to the feedforward noise reduction being turned on; or the feedforward microphone can be turned off to avoid the wind noise entering the ear when the feedforward noise reduction is turned on when there is wind noise; or only the low-frequency signal of the feedforward microphone is attenuated, because the wind noise is mainly concentrated in the low frequency. This can reduce the wind noise entering the ear in the low frequency band due to the feedforward noise reduction being turned on, and retain a certain noise reduction effect in other frequency bands.

[0069] like Figure 3 As shown in the figure, a schematic diagram of the headphone wind noise recognition process is provided. First, the feedforward microphone signal collected by the feedforward microphone and the feedback microphone signal collected by the feedback microphone are obtained, and Fourier transform processing is performed to obtain the feedforward microphone frequency domain signal FFmic and the feedback microphone frequency domain signal FBmic. Then, the inverse feedback filtering processing is performed on FBmic to obtain the inverse feedback filtering result FB invfb Combined with the feedforward microphone frequency domain signal FFmic, the inverse feedback filtering result FB invfb Then perform inverse feedforward filtering to obtain the inverse hybrid filtering result FB inv Then, according to the speaker sound source signal Ref played by the speaker, the inverse feedback filtering result FB is respectively invfb And the inverse mixed filter result FB inv Perform echo cancellation processing. Finally, according to the inverse feedback filtering result FB after echo cancellation processing invfb And the inverse mixed filter result FB inv Wind noise recognition is performed to perform subsequent processing such as wind noise suppression based on the wind noise recognition results.

[0070] The embodiment of the present application also provides a headphone wind noise recognition device, which belongs to the same technical concept as the aforementioned headphone wind noise recognition method. The headphone includes a feedforward microphone located outside the ear and a feedback microphone located inside the ear. Figure 4 A block diagram of a headphone wind noise recognition device according to an embodiment of the present application is shown. Figure 4 The headphone wind noise recognition device 400 includes: a microphone signal acquisition unit 410, a Fourier transform unit 420, an inverse feedback filter processing unit 430, an inverse feedforward filter processing unit 440 and a wind noise recognition unit 450.

[0071] A microphone signal acquisition unit 410 is used to acquire a feedforward microphone signal collected by a feedforward microphone and a feedback microphone signal collected by a feedback microphone;

[0072] A Fourier transform unit 420, configured to perform Fourier transform on the feedforward microphone signal and the feedback microphone signal to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal;

[0073] The inverse feedback filter processing unit 430 is used to perform inverse feedback filter processing on the feedback microphone frequency domain signal to obtain an inverse feedback filter processing result;

[0074] An inverse feedforward filtering processing unit 440 is used to perform inverse feedforward filtering processing on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result;

[0075] The wind noise recognition unit 450 is used to obtain the headphone wind noise recognition result based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result.

[0076] In one embodiment of the present application, the inverse feedback filtering process is implemented by the following formula:

[0077] FB invfb =FBmic×(1-H fb ×G), (1)

[0078] Among them, FBinvfb is the result of the inverse feedback filtering process, FBmic is the frequency domain signal of the feedback microphone, Hfb is the frequency response of the feedback filter used when the headset currently turns on feedback noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone;

[0079] The inverse feedforward filtering process is implemented by the following formula:

[0080] FB inv =FB invfb -FFmic×H ff ×G, (2)

[0081] Among them, FBinv is the inverse hybrid filtering result, FFmic is the frequency domain signal of the feedforward microphone, Hff is the frequency response of the feedforward filter used when the headset currently turns on the feedforward noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone.

[0082] In one embodiment of the present application, the device also includes: a speaker sound source signal acquisition unit, which is used to obtain a speaker sound source frequency domain signal played by the speaker in the earphone after obtaining the inverse feedback filtering processing result and the inverse mixing filtering processing result; an echo cancellation processing unit, which is used to perform echo cancellation processing on the inverse feedback filtering processing result and the inverse mixing filtering processing result according to the speaker sound source frequency domain signal.

[0083] In one embodiment of the present application, the wind noise recognition unit 450 is specifically used to: calculate the energy ratio of the inverse hybrid filtering processing result and the inverse feedback filtering processing result; if the ratio is greater than a first preset threshold, the headphone wind noise recognition result is determined to be without wind noise; if the ratio is less than a second preset threshold, the headphone wind noise recognition result is determined to be with wind noise, wherein the first preset threshold is greater than the second preset threshold; if the ratio is between the second preset threshold and the first preset threshold, the last headphone wind noise recognition result is used as the current headphone wind noise recognition result.

[0084] In one embodiment of the present application, when calculating the energy ratio of the inverse hybrid filtering result to the inverse feedback filtering result, the wind noise identification unit 450 selects a frequency band where the feedforward noise reduction has an obvious effect for energy calculation and comparison.

[0085] In one embodiment of the present application, the inverse feedback filter processing unit 430 is further configured to: when only the feedforward noise reduction is turned on, directly use the feedback microphone frequency domain signal as the inverse feedback filter processing result.

[0086] In one embodiment of the present application, the device also includes: a wind noise suppression unit, which is used to suppress wind noise after obtaining the headphone wind noise recognition result by any one or more of the following methods: reducing the gain of the feedforward microphone, turning off the feedforward microphone, or attenuating the low-frequency band signal in the feedforward microphone signal collected by the feedforward microphone.

[0087] It should be noted that:

[0088] Figure 5 The schematic diagram of the headset is shown in Figure 1. Figure 5At the hardware level, the headset includes a feedforward microphone located outside the ear, a feedback microphone located inside the ear, a speaker, a memory and a processor, and optionally also includes an interface module, a communication module, etc. The memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage, etc. Of course, the headset may also include hardware required for other services.

[0089] The processor, interface module, communication module and memory can be interconnected through an internal bus, which can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0090] The memory is used to store computer executable instructions. The memory provides computer executable instructions to the processor through an internal bus.

[0091] The processor executes the computer executable instructions stored in the memory and is specifically used to implement the following operations:

[0092] Acquire a feedforward microphone signal collected by a feedforward microphone and a feedback microphone signal collected by a feedback microphone;

[0093] Performing Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal;

[0094] Performing inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result;

[0095] Performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result;

[0096] Based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result, the headphone wind noise recognition result is obtained.

[0097] The above application Figure 4The functions performed by the headphone wind noise recognition device disclosed in the illustrated embodiment can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor or an instruction in software form. The above processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0098] The headset can also perform Figure 1 The steps of the headphone wind noise recognition method are implemented in Figure 1 The functions of the illustrated embodiment will not be described in detail in the embodiments of the present application.

[0099] The embodiment of the present application further proposes a computer-readable storage medium, which stores one or more programs. When the one or more programs are executed by a processor, the aforementioned headphone wind noise recognition method is implemented, and is specifically used to execute:

[0100] Acquire a feedforward microphone signal collected by a feedforward microphone and a feedback microphone signal collected by a feedback microphone;

[0101] Performing Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal;

[0102] Performing inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result;

[0103] Performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result;

[0104] Based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result, the headphone wind noise recognition result is obtained.

[0105] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program codes.

[0106] The present application is described by flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0110] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0111] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0112] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0113] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) characterized in that it contains computer-usable program code.

[0114] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for identifying wind noise in headphones, wherein the headphones include a feedforward microphone located outside the ear and a feedback microphone located inside the ear, characterized in that: The method comprises: Acquire a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone; Performing Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal; Performing inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result; Performing inverse feedforward filtering on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result; Based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result, obtaining a headphone wind noise recognition result; The obtaining of the headphone wind noise recognition result based on the relationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result includes: Calculating the energy ratio of the inverse hybrid filtering result to the inverse feedback filtering result; If the ratio is greater than a first preset threshold, determining that the headphone wind noise recognition result is no wind noise; If the ratio is less than a second preset threshold, the headphone wind noise recognition result is determined to be wind noise, wherein the first preset threshold is greater than the second preset threshold.

2. The method according to claim 1, characterized in that: The inverse feedback filtering process is implemented by the following formula: FB invfb =FBmic×(1-H fb ×G) Among them, FB invfb is the result of inverse feedback filtering, FBmic is the frequency domain signal of the feedback microphone, and H fb is the frequency response of the feedback filter used when the headset currently turns on feedback noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone; The inverse feedforward filtering process is implemented by the following formula: Facebook inv =FB invfb -FFmic×H ff ×G Among them, FB inv is the inverse hybrid filtering result, FFmic is the frequency domain signal of the feedforward microphone, and H ff is the frequency response of the feedforward filter used when the headset currently turns on feedforward noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone.

3. The method according to claim 1, characterized in that After obtaining the inverse feedback filtering processing result and the inverse hybrid filtering processing result, the method further includes: Obtaining a frequency domain signal of a speaker sound source played by a speaker in the earphone; According to the loudspeaker sound source frequency domain signal, echo cancellation processing is performed on the inverse feedback filtering processing result and the inverse mixing filtering processing result.

4. The method according to claim 1, characterized in that: The calculation step selects a frequency band where feedforward noise reduction has an obvious effect to perform energy calculation and comparison.

5. The method according to claim 1, characterized in that When only the feedforward noise reduction is turned on, the feedback microphone frequency domain signal is directly used as the inverse feedback filtering processing result.

6. The method according to claim 1, characterized in that The method further comprises: After obtaining the headphone wind noise recognition result, the wind noise is suppressed by any one or more of the following methods: reducing the gain of the feedforward microphone, turning off the feedforward microphone, or attenuating the low-frequency band signal in the feedforward microphone signal collected by the feedforward microphone.

7. An earphone wind noise recognition device, the earphone comprising a feedforward microphone located outside the ear and a feedback microphone located inside the ear, characterized in that: The device comprises: A microphone signal acquisition unit, used to acquire a feedforward microphone signal collected by the feedforward microphone and a feedback microphone signal collected by the feedback microphone; A Fourier transform unit, used to perform Fourier transform on the feedforward microphone signal and the feedback microphone signal respectively to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal; An inverse feedback filtering processing unit, used to perform inverse feedback filtering processing on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result; An inverse feedforward filtering processing unit, used for performing inverse feedforward filtering processing on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result; A wind noise recognition unit, configured to obtain a headphone wind noise recognition result based on the relationship between the inverse feedback filtering result and the inverse hybrid filtering result; The wind noise recognition unit is specifically used for: Calculating the energy ratio of the inverse hybrid filtering result to the inverse feedback filtering result; If the ratio is greater than a first preset threshold, determining that the headphone wind noise recognition result is no wind noise; If the ratio is less than a second preset threshold, the headphone wind noise recognition result is determined to be wind noise, wherein the first preset threshold is greater than the second preset threshold.

8. The device according to claim 7, characterized in that The inverse feedback filtering process is implemented by the following formula: FB invfb =FBmic×(1-H fb ×G) Among them, FB invfb is the result of inverse feedback filtering, FBmic is the frequency domain signal of the feedback microphone, and H fb is the frequency response of the feedback filter used when the headset currently turns on feedback noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone; The inverse feedforward filtering process is implemented by the following formula: Facebook inv =FB invfb -FFmic×H ff ×G Among them, FB inv is the inverse hybrid filtering result, FFmic is the frequency domain signal of the feedforward microphone, and H ff is the frequency response of the feedforward filter used when the headset currently turns on feedforward noise reduction, and G is the transfer function from the speaker in the headset to the feedback microphone.

9. The device according to claim 7, characterized in that The device also includes: A loudspeaker sound source frequency domain signal acquisition unit, used to acquire a loudspeaker sound source frequency domain signal played by a loudspeaker in the earphone; The echo cancellation unit is used to perform echo cancellation processing on the inverse feedback filtering processing result and the inverse mixing filtering processing result according to the loudspeaker sound source frequency domain signal.

10. The device according to claim 7, characterized in that When the wind noise identification unit is used to calculate the energy ratio of the inverse hybrid filtering result and the inverse feedback filtering result, the wind noise identification unit selects a frequency band where the feedforward noise reduction has an obvious effect for energy calculation and comparison.

11. The device according to claim 7, characterized in that The inverse feedback filter processing unit is further used to: when only the feedforward noise reduction is turned on, directly use the feedback microphone frequency domain signal as the inverse feedback filter processing result.

12. The device according to claim 7, characterized in that The device also includes: a wind noise suppression unit, which is used to suppress wind noise after obtaining the headphone wind noise recognition result by any one or more of the following methods: reducing the gain of the feedforward microphone, turning off the feedforward microphone, or attenuating the low-frequency band signal in the feedforward microphone signal collected by the feedforward microphone.

13. A headset, characterized in that: include: A feedforward microphone located outside the ear, a feedback microphone located inside the ear, a speaker, a processor, and a memory storing computer executable instructions, wherein when the executable instructions are executed by the processor, the headphone wind noise recognition method of any one of claims 1 to 6 is implemented.

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