Personalized acoustic feedback management

Abstract

The invention relates to personalized acoustic feedback management. Acoustic feedback management systems, devices, and methods are described. In one aspect, an audio device may analyze a hearing curve of a user to incorporate the hearing curve into various feedback management techniques (e.g., decorrelation techniques, adaptive feedback cancellation techniques, etc.) to personalize management of acoustic feedback of the audio device.

Description

BACKGROUND

[0001] Related Patent Applications

[0002] This application claims the benefit of priority of U.S. Provisional Application No. 63 / 641,113, filed May 1, 2024, which is incorporated by reference herein. TECHNICAL FIELD

[0003] Aspects of the present disclosure relate herein to digital audio signal processing techniques for improving the environmental sound reproduction effect of an audio device, such as a headphone or earphone / earbud. Other aspects are also described.

[0004] BACKGROUND

[0005] Consumer electronic devices, such as headphones and mobile phone handsets, referred to as audio devices, are used in a variety of different settings. Such devices typically include a microphone that receives an acoustic signal of environmental sound and a speaker that reproduces that environmental sound into the user’s ear after some electronic processing of the microphone signal. SUMMARY

[0006] Acoustic feedback management systems, devices, and methods are described. In one aspect, an acoustic feedback management system receives a microphone signal, applies a gain to the microphone signal based on a user’s hearing curve (e.g., audiogram), and applies feedback management when a correlation between the applied gain and a feedback path attenuation signal exceeds a feedback threshold. In some instances, the applied feedback management includes a decorrelation technique. In other instances, the applied feedback management includes an adaptive feedback cancellation technique. In another aspect, such feedback management systems and methods can be executed on an audio device. BRIEF DESCRIPTION OF DRAWINGS

[0007] FIG. 1A An example audio device is shown in accordance with an aspect.

[0008] FIG. 1B is a schematic diagram of an example audio device in accordance with an aspect.

[0009] FIG. 2 is a graphical representation of an example hearing curve in accordance with an aspect.

[0010] FIG. 3 is a feedback loop diagram in accordance with an aspect.

[0011] FIG. 4 is a flowchart of a method for managing acoustic feedback based on a user’s hearing curve in accordance with an aspect. DETAILED DESCRIPTION

[0012] It has been observed that acoustic instability in an audio device can lead to acoustic feedback (e.g., howling). In some instances, acoustic instability can occur when the audio device is in a steady state. In other instances, acoustic instability can occur when the audio device is in a dynamic state, such as when an object gets closer to the speaker / microphone (e.g., manually adjusting the fit of the device), the seal / acoustic leak between the audio device and the user’s ear gets larger (e.g., when the device is inserted / removed), etc. In such instances, the speaker output and the microphone input can become highly correlated. Conventional approaches have utilized various techniques to address acoustic feedback (e.g., de-correlation, adaptive feedback cancellation, etc.). In one example, conventional de-correlation techniques de-correlate the speaker output and the microphone input signals to reduce the risk of acoustic feedback before it occurs, such as performing a frequency shift on the audio signal sent to the speaker, adding a delay to the audio signal to make it misaligned with the microphone signal, injecting noise into the speaker path (e.g., noise injection), etc. In another example, conventional adaptive feedback cancellation techniques cancel acoustic feedback that can have already occurred by estimating a filter to attenuate the feedback and then applying the filter to remove the feedback without removing the rest of the signal. However, it has been observed that such techniques can lead to degradation in audio quality and / or introduce audible artifacts. Specifically, with respect to noise injection, it has been observed that the degree of noise injection required to cause a de-correlation effect can also produce user-perceptible signal distortion.

[0013] According to aspects, an acoustic feedback management ("AFM") system manages acoustic feedback by incorporating a user's hearing profile into various techniques for addressing acoustic feedback. For example, the AFM system can analyze a user's hearing profile (e.g., audiogram) to determine a detection threshold for each band in the hearing profile, where sounds above the detection threshold can be audible to the user, and sounds below the threshold can be inaudible to the user. Further, in an aspect where a de-correlation technique can be utilized to prevent acoustic feedback, the de-correlation technique (e.g., noise injection, etc.) can be "customized" to the detection threshold, such that the de-correlation technique is inaudible to the user. In aspects where an adaptive feedback cancellation technique is utilized to cancel acoustic feedback, the shape of the filter can be informed by the user's hearing profile, such that the AFM system can prioritize attenuation in areas where there is more gain in the hearing profile and where the user has more hearing loss, such that the adaptive feedback cancellation technique can be inaudible or less noticeable to the user. By personalizing the methods used to manage acoustic feedback (e.g., de-correlation techniques, adaptive feedback cancellation techniques, etc.), the AFM system not only avoids the drawbacks of conventional techniques (e.g., audio quality degradation, audible artifacts, etc.), but also allows for more aggressive feedback management techniques, and thus allows for more aggressive gain to be applied, which can result in an increased hearing coverage (e.g., an additional 5-10 dB of amplification).

[0014] In various aspects, reference is made to the accompanying drawings. However, certain aspects can be practiced without one or more of these specific details, or in combination with other known methods and configurations. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the aspects. In other instances, well-known process techniques have not been described in particular detail in order to not unnecessarily obscure aspects of the application. References made to "one aspect" in the description indicate that a particular feature, structure, configuration, or characteristic described in connection with that aspect is included in at least one aspect. Thus, the appearance of the phrase "in one aspect" in various places throughout the specification are not necessarily referring to the same aspect. Additionally, the particular features, structures, configurations, or characteristics can be combined in any suitable manner in one or more aspects.

[0015] Reference is now made to FIG. 1A FIG. 1 shows an example audio device 100. Such an audio device can include any type of headphone (e.g., over-ear, on-ear, around-ear, earphone, earbud (e.g., outer ear, in-ear, etc.), earpiece, hearing aid, etc., which can be implemented individually (e.g., one ear) or as a pair (e.g., two ears) as part of an AFM system. In the example of FIG. 1, the audio device 100 (herein "device") is an in-ear earbud in the user's left ear. FIG. 1A

[0016] ​Referring now to FIG. 1B , a schematic diagram of an example device is shown. The device 100 can include an AFM system 110, which can be implemented using hardware, firmware, and / or software. For example, the device 100 can include one or more processors (e.g., central processing units, etc.) coupled to a memory (e.g., read-only memory, random access memory, etc.), where the one or more processors can execute a set of instructions stored on the memory. In addition, the one or more processors can include networking technology to enable wireless communication (e.g., Bluetooth, etc.) between the device 100 and an external device or computer system (e.g., mobile device, tablet, etc.). In FIG. 1B an example, the device 100 includes a processor 102 that can execute a set of instructions stored on a memory 104, where the processor 102 can include networking technology to enable wireless communication with a processor 202 of a mobile device 200. In addition, the device 100 can include a microphone 106 configured to receive environmental sounds from an environment of a user, and a speaker 108 configured to produce sounds into an ear of the user. The device 100 can also include a power source 109 (e.g., lithium-ion battery, etc.) to provide power to components of the device 100, where such components can be housed in a housing 101.

[0017] The AFM system 110 can include a frequency band analyzer 120, an amplifier 130, a hearing curve analyzer 140, and a feedback manager 150. In some aspects, the AFM system 110 can be implemented in whole or in part on an external device (e.g., mobile device, tablet, etc.), such that operations of the hearing curve analyzer 140, for example, can be performed on the mobile device, and operations of the feedback manager 150 can be performed on the device 100. In other aspects, the AFM system 110 can be implemented in whole or in part on the device 100. In FIG. 1B an example, the AFM system 110 is implemented on the device 100, such that operations of the AFM system 110 can be performed on the earbud itself.

[0018] The frequency band analyzer 120 analyzes environmental sounds in the environment by resolving the microphone signal into frequency bands or sub-bands. For example, a frequency band analyzer (e.g., a spectral analyzer) can receive an input signal from a microphone, and perform a frequency analysis on the input signal, where the amplitude of the input signal can be measured across multiple frequency bands or sub-bands. In FIG. 1A an example, the processor 102 can execute a set of instructions stored on the memory 104 to cause the frequency band analyzer 120 to resolve the input signal from the microphone 106 to measure the amplitude of the input signal across multiple frequency bands, which can then be sent to the amplifier 130, as shown by the arrow from the frequency band analyzer 120 to the amplifier 130.

[0019] Amplifier 130 can determine the amount of gain or amplification that can be needed to boost each frequency band of the microphone signal. In one aspect, the amount of gain is related to the degree of hearing loss of the user. For example, more gain can be applied in the case where the user has a high degree of hearing loss. In another aspect, the amount of gain is related to the amount of noise in the environment. For example, as the environmental noise rises, less gain can be applied even in the case where the user has a high degree of hearing loss. This can be due to the non-linear nature of hearing loss, where the user can have difficulty hearing quiet sounds in a noisy environment, but can still hear louder sounds in the same noisy environment. As such, amplifier 130 can analyze the environmental noise in the environment based on the data provided by frequency band analyzer 120 (as described above). Further, amplifier 130 can analyze the degree of hearing loss of the user based at least in part on the hearing loss data provided by hearing curve analyzer 140.

[0020] Hearing curve analyzer 140 can analyze a hearing curve specific to the user. The hearing curve can include the results of a hearing test performed by the user and displayed in a graph or chart (e.g., an audiogram) or any other suitable format (e.g., a table, a list, etc.). In some aspects, the hearing curve can be stored on a memory (e.g., memory 104) of device 100, where a processor (e.g., processor 102) can execute instructions stored on the memory to send the hearing curve to hearing curve analyzer 140. In other aspects, the hearing curve can be stored on an external device or system (e.g., a mobile device, a tablet, etc.) and then sent to device 100 periodically or in response to a request from a processor of device 100. In some aspects, the hearing curve can be analyzed by hearing curve analyzer 140 to determine a detection threshold of the user. FIG. 1B In an example, hearing curve 142 is stored on memory 204 of mobile device 200. Further, mobile device 200 can include processor 202, where processor 202 includes networking technology to enable wireless communication (e.g., Bluetooth, etc.) between mobile device 200 and device 100. For example, processor 102 of device 100 can communicate with processor 202 of mobile device 200 to retrieve or otherwise receive hearing curve 142 from memory 204 of mobile device 200. In such an example, hearing curve 142 can then be stored on memory 104 of device 100, where updated hearing curves can subsequently be provided to device 100 as they become available. Further, hearing curve analyzer 140 can determine a detection threshold of the user based on the hearing curve of the user.

[0021] Referring now to FIG. 2 , an example graphical representation of hearing curve 142 is shown. The graphical representation of hearing curve 142 (e.g., an audiogram) plots the relationship of frequency / pitch (x-axis) to the hearing level of the user (y-axis). As shown, the hearing curve 142 can include a series of points 144 that represent the degree of hearing loss of the user at different frequencies / pitches. For example, the points 144 can represent the degree of hearing loss of the user at 125 Hz, 250 Hz, 500 Hz, 1000 Hz, 2000 Hz, 3000 Hz, 4000 Hz, and 6000 Hz. In some aspects, the points 144 can represent the degree of hearing loss of the user at other frequencies / pitches, such as 8000 Hz, 10000 Hz, etc. Further, the points 144 can represent the degree of hearing loss of the user at other frequencies / pitches, such as 125 Hz, 250 Hz, 500 Hz, 1000 Hz, 2000 Hz, 3000 Hz, 4000 Hz, and 6000 Hz. In some aspects, the points 144 can represent the degree of hearing loss of the user at other frequencies / pitches, such as 8000 Hz, 10000 Hz, etc. FIG. 2As shown, the hearing curve 142 includes data related to both the user's right and left ears. For clarity and simplicity, only the data related to the left ear will be discussed. However, it should be noted that the AFM system 110 operates on both the right and left ears in the same personalized manner based on their respective datasets, such that the technique used for the right ear can differ from the technique used for the left ear in response to the same ambient noise environment. FIG. 2 As shown, each data point includes a frequency band and a corresponding hearing threshold. For example, hearing curve 142 includes data point 1 (DP1) at frequency F1 and hearing level L1, data point 2 (DP2) at frequency F2 and hearing level L2, data point 3 (DP3) at frequency F3 and hearing level L3, and data point 4 (DP4) at frequency F4 and hearing level L4. Furthermore, the shape of the curve in the graphical representation of hearing curve 142 shows that the user has greater hearing loss at higher frequency ranges compared to lower frequency ranges. In this way, the hearing curve analyzer 140 can determine the user's detection threshold at each frequency band, where sounds below the detection threshold for a particular frequency band may be inaudible, while sounds above the detection threshold may be audible.

[0022] Return to reference FIG. 1B The hearing curve analyzer 140 can process hearing curve 142, which may include extracting and analyzing the user's hearing loss data across multiple frequency bands or subbands. Furthermore, the hearing curve analyzer 140 can send such hearing loss data to the amplifier 130 (and in parallel to the feedback manager 150), as indicated by the arrow connecting the hearing curve analyzer 140 and the amplifier 130. The amplifier 130 can then compare the hearing loss data associated with hearing curve 142 sent from the hearing curve analyzer 140 with microphone signal data sent from the frequency band analyzer 120. Based on this comparison, the amplifier 130 can determine the different amounts of gain required for each frequency band in the user's hearing curve. In one example, when the user has similar... FIG. 2 In the case of the hearing curve 142 shown, due to the greater amount of hearing loss in the higher frequency range, amplifier 130 can provide more gain in the higher frequency range. Amplifier 130 can then apply the determined gain to the microphone signal to generate a tunable microphone signal for each frequency band, wherein such gain may be limited or capped by a maximum possible gain (e.g., maximum stable gain, maximum no-feedback gain, etc.) that could cause device instability. Furthermore, processor 102 can make such data from amplifier 130 (e.g., determined gain, applied gain, etc.) shared with feedback manager 150.

[0023] The feedback manager 150 can analyze data from the amplifier 130 and the hearing curve analyzer 140 (both subsystems have incorporated the user's hearing curve in their respective analysis) to perform feedback management operations related to the device 100. As used herein, feedback management can include feedback mitigation, cancellation, decorrelation, or any other suitable method for managing the effects of acoustic feedback (e.g., decorrelation techniques, feedback cancellation techniques, etc.). Acoustic feedback can be observed to occur in either a steady state or a dynamic state. In a steady state, acoustic feedback can occur due to a hearing aid or user characteristic, e.g., an applied gain that exceeds the maximum stable gain of the device. In a dynamic state, the device can experience acoustic instability due to a sudden change in the acoustic environment, where, for example, the user adjusts the device and sound leaks from the speaker to the microphone (e.g., acoustic leakage). In such aspects, whether acoustic instability rises to the level of acoustic feedback (e.g., howling) is based at least in part on the feedback path between the microphone and the speaker.

[0024] Reference is now made to FIG. 3 , which shows a diagram of an example feedback path (or feedback loop) from the speaker 108 to the microphone 106. In an aspect, the risk of acoustic feedback involves a correlation between the applied gain and the attenuation of the signal between the speaker and the microphone along the feedback path. For example, in FIG. 3 , if the attenuation F(z) of the amplified sound from the speaker 108 to the microphone 106 is greater than the applied gain G(z) from the microphone 106 to the speaker 108, then acoustic feedback can not occur. Conversely, if the applied gain G(z) from the microphone 106 to the speaker 108 is greater than the attenuation F(z) of the amplified sound from the speaker 108 to the microphone 106, then the residual signal from the feedback path can be amplified exponentially with each pass through the feedback path / loop to produce an audible oscillation typically associated with acoustic feedback. The correlation between these signals in the feedback path / loop can be summarized in an equation, such as Equation (1), where the condition for acoustic stability can be met:

[0025] (1) |F(z) G(z)| < 1

[0026] For example, if F(z) is -35 dB, then G(z) must be less than 35 dB to avoid acoustic feedback. In aspects, the threshold at which the correlation between F(z) and G(z) causes acoustic feedback can be referred to as a feedback threshold.

[0027] The feedback manager 150 can determine whether the device 100 exceeds a feedback threshold in a stable state (e.g., more than a maximum stable gain), a dynamic state (e.g., an applied gain exceeds a feedback path attenuation), or any combination thereof, where such a feedback threshold can be frequency dependent, such that each frequency band can have a particular feedback threshold. In instances where the device 100 does not exceed the feedback threshold for a particular frequency band, the user can be at low risk for acoustic feedback in that particular frequency band. In instances where the device 100 exceeds the feedback threshold for a particular frequency band, the user can be at high risk for acoustic feedback (e.g., howling, etc.) in that particular frequency band. Referring back to FIG. 2 In the hearing profile 142 of FIG. 1 B, for data point 3, the feedback manager 150 can determine that the device 100 does not exceed the feedback threshold at frequency F3 because the hearing level L3 at frequency F3 is close to the normal hearing range and can only require a minimal gain, where such a minimal gain can not exceed the maximum stable gain in a stable state or can not be greater than the feedback path attenuation in a dynamic state. In such instances, the user can be at low risk for acoustic feedback. Conversely, for data point 4, the feedback manager 150 can determine that the device 100 exceeds the feedback threshold at frequency F4 because the hearing level L4 at frequency F4 is far from the normal hearing range and can require a significant gain, where such a significant gain can exceed the maximum stable gain in a stable state or can be greater than the feedback path attenuation in a dynamic state. In such instances, the user can be at high risk for acoustic feedback. As noted above, in such instances, the feedback manager 150 can perform any suitable operation for managing the effects of acoustic feedback, where such operations can be in conjunction with or informed by the hearing profile of the particular user. In some aspects, the feedback manager 150 can temporarily reduce the gain applied by the amplifier 130 in a particular frequency band based on the hearing profile of the user. In other aspects, the feedback manager 150 can employ a decorrelation technique to prevent acoustic feedback from occurring, where the decorrelation technique can be employed below a detection threshold, for example, based on the hearing profile of the user. In other aspects, the feedback manager 150 can employ an acoustic feedback cancellation technique to cancel or neutralize acoustic feedback that has already occurred, where the shape of the filter can be tailored according to the hearing profile of the user, for example. It should be noted that the above feedback management methods are not exhaustive, and other feedback management methods can be contemplated. One such feedback management method, decorrelation, is described in more detail below.

[0028] The feedback manager 150 can employ the decorrelation technique based on the detection threshold of the user determined by the hearing curve analyzer 140 and / or supplemental audio signals (e.g., environmental noise masking, etc.) that can obscure the audibility of artifacts produced by the decorrelation technique. It has been observed that conventional approaches employ the decorrelation technique without incorporating the hearing curve of the user. For example, in cases where noise injection is used as the decorrelation technique, conventional approaches utilize a wideband white noise that can span multiple frequency bands and introduce artifacts into the speaker path that are audible to the user. In the described aspects, the hearing curve of the user can be used to“customize” or“personalize” the decorrelation technique applied by the AFM system 110. Specifically, the hearing curve analyzer 140 can analyze the hearing curve of the user to determine the detection threshold (e.g., hearing level, decibel level, etc.) for each frequency band, such that the decorrelation technique can be employed below the detection threshold. For example, in cases where the decibel level of the decorrelation technique to be applied (e.g., noise injection, etc.) is below the detection threshold for a particular frequency band, the decorrelation technique can be inaudible to the user. Conversely, in cases where the decibel level of the decorrelation technique to be applied exceeds the detection threshold for a particular frequency band, the decorrelation technique can be audible to the user.

[0029] Further, based on the detection threshold determined by the hearing curve analyzer 140, the feedback manager 150 can determine whether to employ the decorrelation technique for each frequency band. For example, in FIG. 2 In one example, the feedback manager 150 can determine that the detection threshold at frequency F4 can be set to hearing level L4, and thus a noise signal, for example, can be injected into the path of the speaker 108 where the decibel level of the noise signal does not exceed the detection threshold at frequency F4. In such an example, the noise signal would be inaudible to the user. In another example, the feedback manager 150 can determine that the detection threshold at frequency F3 can be set to hearing level L3, and thus a noise signal can be injected into the path of the speaker 108 where the decibel level of the noise signal does not exceed the detection threshold at frequency F3. Further, the respective noise signal can be a narrowband noise signal, where the characteristics of the narrowband noise signal can be customized or limited to a particular frequency band (e.g., frequency band F4, frequency band F3, etc.) and a particular decibel level (e.g., hearing level L4, hearing level L3, etc.) based on the hearing curve of the user. In this way, the decorrelation technique can be personalized or customized to the hearing curve of the user, such that such decorrelation techniques can be undetectable to the user.

[0030] FIG. 4is a flowchart of a method for managing acoustic feedback of an audio device based on a user's hearing profile. In aspects, the method can be performed by a processor coupled to a memory, such as the processor 102 and the memory 104, or alternatively by a combination of a processor coupled to a memory and other electronic circuitry. At operation 4010, a microphone of the device 100 (e.g., the microphone 106) can receive an acoustic signal from an environment of a user, where the microphone can convert the acoustic signal into an electrical signal to be sent to the band analyzer 120. The band analyzer 120 can resolve the received microphone signal by determining the amplitude of the microphone signal across a plurality of frequency bands or sub-bands. The band analyzer 120 can then send the resolved microphone signal to the amplifier 130. At operation 4020, the amplifier 130 can determine a gain to be applied to the microphone signal based on a user's hearing profile. The user's hearing profile (e.g., audiogram) can be retrieved from a memory of the device 100 (e.g., the memory 104) or from an external device (e.g., the mobile device 200, etc.). The hearing profile can be processed by the hearing profile analyzer 140, which can extract and analyze the user's hearing loss data across a plurality of frequency bands or sub-bands in order to determine the user's detection threshold at each frequency band. The hearing profile analyzer 140 can then send such data to the amplifier 130. The amplifier 130 can compare the hearing loss data from the hearing profile sent by the hearing profile analyzer 140 to the ambient noise data from the microphone 106 sent by the band analyzer 120. Based on the comparison, the amplifier 130 can determine different gains required for different frequency bands in the user's hearing profile. Further, the amplifier 130 can then apply the determined gains to the microphone signal to generate an adjusted microphone signal for each frequency band, where the processor 102 can cause such data to be shared with the feedback manager 150.

[0031] Further reference is made to FIG. 4 At operation 4030, the feedback manager 150 can determine whether to apply a feedback management technique based on the user's hearing profile. In some aspects, such as when acoustic feedback occurs in a static state, the feedback manager 150 can reduce the applied gain such that the applied gain is below a maximum gain threshold of the device 100. In other aspects, such as when acoustic feedback occurs in a dynamic state, the feedback manager 150 can determine that the applied gain is above a maximum gain threshold of the device 100 and that the feedback path attenuation (e.g., the gain applied to the microphone signal) is below a minimum gain threshold of the device 100. In such aspects, the feedback manager 150 can apply a feedback management technique to the adjusted microphone signal to reduce the occurrence of acoustic feedback. In some aspects, the feedback management technique can include reducing the gain applied to the adjusted microphone signal, such as by the amplifier 130. In other aspects, the feedback management technique can include reducing the gain applied to the adjusted microphone signal, such as by the amplifier 130, and increasing the feedback path attenuation, such as by the feedback manager 150. In yet other aspects, the feedback management technique can include reducing the gain applied to the adjusted microphone signal, such as by the amplifier 130, and increasing the feedback path attenuation, such as by the feedback manager 150, and reducing the feedback path attenuation, such as by the feedback manager 150. FIG. 3whether the correlation between the signals exceeds a feedback threshold. In instances where the correlation between the signals does not exceed the feedback threshold, the feedback manager 150 can not apply the feedback management approach to the audio signal driving the loudspeaker. In instances where the correlation between the signals exceeds the feedback threshold, the feedback manager 150 (at operation 4040) can apply the feedback management approach to the audio signal driving the loudspeaker, where the audio signal driving the loudspeaker includes the adjusted microphone signal. In some aspects, the feedback manager 150 can employ a decorrelation technique based on the user’s hearing profile. For example, where a noise signal is employed as the decorrelation technique, the frequency bands and decibel levels of the noise signal can be limited to or tailored to particular frequency bands and particular decibel levels, such that the noise signal is inaudible to the user. In other aspects, the feedback manager 150 can apply an adaptive feedback cancellation technique based on the user’s hearing profile. For example, where an adaptive filter is utilized to attenuate acoustic feedback, such an adaptive filter can be informed or shaped by the user’s hearing profile to be inaudible or less noticeable to the user.

[0032] In utilizing various aspects of the aspects, it will be apparent to those skilled in the art that combinations or variations of the above aspects are possible for managing acoustic feedback based on a user’s hearing profile. While aspects are described in terms of specific structural features and / or method acts, it should be understood that the appended claims are not necessarily limited to the specific features or acts described. The specific features and acts are disclosed as exemplary forms of implementing the claims.

Claims

1. An audio device, the audio device comprising: microphone; speaker; At least one processor, said at least one processor being coupled to the microphone and the speaker; and A memory coupled to the at least one processor, the memory storing instructions that, when executed by the at least one processor, cause the device to perform operations including: Receive microphone signals from the microphone; Based on the user's hearing profile, gain is applied to the microphone signal to generate an conditioned microphone signal. Determine whether the correlation between the applied gain and the attenuation signal in the feedback path exceeds the feedback threshold; as well as When the feedback threshold is exceeded, feedback management is applied to the audio signal driving the speaker based on the user's hearing curve, wherein the audio signal driving the speaker includes the regulated microphone signal.

2. The device of claim 1, wherein the audio device is a headset, and the hearing curve includes an audiogram.

3. The device according to claim 1, wherein the feedback threshold is frequency-dependent.

4. The device of claim 1, wherein application feedback management includes employing decorrelation techniques, the decorrelation techniques including injecting noise signals into the audio signal driving the speaker.

5. The device of claim 4, wherein the frequency band of the noise signal is limited to the frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold.

6. The device of claim 5, wherein the noise signal has a decibel level below a detection threshold such that the noise signal is inaudible to the user, the detection threshold being based on the user's hearing curve.

7. The device of claim 1, wherein application feedback management includes applying adaptive feedback cancellation technology, the adaptive feedback cancellation technology including applying a filter to the audio signal based on the user's hearing curve.

8. An acoustic feedback management system for an audio device, the acoustic feedback management system comprising: The memory is used to store instructions; and At least one processor, the at least one processor being configured to execute the instructions to perform the following operations: Receive microphone signals from the microphone; Based on the user's hearing curve, gain is applied to the microphone signal to generate an conditioned microphone signal; Determine whether the correlation between the applied gain and the attenuation signal in the feedback path exceeds the feedback threshold; as well as When the feedback threshold is exceeded, feedback management is applied to the audio signal driving the speaker based on the user's hearing curve, wherein the audio signal driving the speaker includes the regulated microphone signal.

9. The system of claim 8, wherein the audio device is a headset, and the hearing curve includes an audiogram.

10. The system of claim 8, wherein the feedback threshold is frequency-dependent.

11. The system of claim 8, wherein the at least one processor executes the instructions to apply feedback management by employing a decorrelation technique, the decorrelation technique comprising injecting a noise signal into the audio signal driving the speaker.

12. The system of claim 11, wherein the frequency band of the noise signal is limited to the frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold.

13. The system of claim 12, wherein the noise signal has a decibel level below a detection threshold such that the noise signal is inaudible to the user, the detection threshold being based on the user's hearing curve.

14. The system of claim 8, wherein the at least one processor executes the instructions to apply feedback management by applying an adaptive feedback cancellation technique, the adaptive feedback cancellation technique comprising applying a filter to the audio signal based on the user's hearing curve.

15. A method for managing acoustic feedback of an audio device, the method comprising: Receive microphone signals from the microphone; Based on the user's hearing curve, the device's processing circuitry applies gain to the microphone signal to generate an regulated microphone signal; The processing circuitry of the device determines whether the correlation between the applied gain and the feedback path attenuation signal exceeds a feedback threshold. as well as When the feedback threshold is exceeded, the processing circuitry of the device applies feedback management to the audio signal driving the speaker based on the user's hearing curve, wherein the audio signal driving the speaker includes the regulated microphone signal.

16. The method of claim 15, wherein the audio device is a headset, and the hearing curve includes an audiogram.

17. The method of claim 15, wherein the feedback threshold is frequency-dependent.

18. The method of claim 15, wherein application feedback management includes employing decorrelation techniques, the decorrelation techniques including injecting noise signals into the audio signal driving the speaker.

19. The method of claim 18, wherein the frequency band of the noise signal is limited to the frequency band where the correlation between the applied gain and the feedback path attenuation signal exceeds the feedback threshold.

20. The method of claim 19, wherein the noise signal has a decibel level below a detection threshold such that the noise signal is inaudible to the user, the detection threshold being based on the user's hearing profile.

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