FIELD OF THE DISCLOSURE

The present disclosure is directed generally to audio processing for wind noise reduction on wearable audio devices.

BACKGROUND

One important aspect of a wearable audio device is the ability to capture voice audio from the wearer. Whether the captured speech is in the context of a voice call with another person, or entering a voice audio command in an electronic system, the clarity of the voice audio is important to the use of the device. Most wearable audio devices utilize one or more embedded microphones to capture the voice audio. However, devices such as audio eyeglasses or open ear headsets contain microphones which are exposed to the external environment. These microphones are particularly vulnerable to wind noise drowning out captured voice audio.

The wind noise issue may be exacerbated by wearable audio devices utilizing minimum variance distortionless response (MVDR) beamforming. Beamforming allows the audio sensors of the device to focus audio capture on particular spatial regions, such as the regions around the user's mouth. MVDR beamforming is often preferred due to its high performance in terms of clarity and naturalness, particularly in areas with some degree of diffused noise, such as a cafeteria setting. However, the characteristics of MVDR beamforming can cause significant amplification of wind noise, sometimes to the point of overwhelming any captured voice audio.

Accordingly, there is a need for an audio processing system capable of reducing wind noise on wearable audio devices.

SUMMARY

This disclosure generally relates to audio processing for wind noise reduction on wearable audio devices.

Generally, in one aspect, a wind noise reduction system is provided. The wind noise reduction system may include a first beamformer. The first beamformer may be configured to generate a first voice signal. The first voice signal may be generated based on a first frequency domain microphone signal and a second frequency domain microphone signal. The first beamformer may be a delay and sum (DAS) beamformer.

The wind noise reduction system may further include a second beamformer. The second beamformer may be configured to generate a second voice signal. The second voice signal may be based on the first frequency domain microphone signal and the second frequency domain microphone signal. The second beamformer may be a minimum variance distortionless response (MVDR) beamformer.

The wind noise reduction system may further include a wind detector. The wind detector may be configured to generate a wind detection signal. The wind detection signal may be generated based on the first voice signal and the second voice signal.

The wind noise reduction system may further include a third beamformer. The third beamformer may be configured to generate a wind array voice signal. The wind array voice signal may be generated based on the first frequency domain microphone signal, the second frequency domain microphone signal, and a frequency domain accelerometer signal. According to an example, the third beamformer may be a generalized eigenvalue (GEV) beamformer.

The wind noise reduction system may further include a fixed voice mixer. The fixed voice mixer may be configured to generate an output voice signal. The output voice signal may be generated based on a microphone array voice signal, the wind array voice signal, and the wind detection signal. According to an example, the microphone array voice signal may correspond to the second voice signal.

According to an example, the wind noise reduction system may further include a dynamic voice mixer configured to generate the microphone array voice signal. The microphone array voice signal may be based on the first voice signal and the second voice signal. According to a further example, the microphone array voice signal may be further based on a first energy level of the first voice signal and a second energy level of the second voice signal.

According to an example, the wind noise reduction system may further include a filter bank. The filter bank may be configured to generate the first frequency domain microphone signal. The first frequency domain microphone signal may be generated based on a first time domain microphone signal.

The filter bank may be further configured to generate the second frequency domain microphone signal. The second frequency domain microphone signal may be generated based on a second time domain microphone signal.

The filter bank may be further configured to generate the frequency domain accelerometer signal. The frequency domain accelerometer signal may be generated based on a time domain accelerometer signal.

According to an example, the wind noise reduction system may further include a first microphone. The first microphone may be further configured to generate the first time domain microphone signal. The wind noise reduction system may further include a second microphone. The second microphone may be further configured to generate the second time domain microphone signal. The wind noise reduction system may further include an accelerometer. The accelerometer may be further configured to generate the time domain accelerometer signal.

According to an example, the wind detection signal may be a no wind detected signal or a low wind detected signal. The output voice signal may correspond to the microphone array voice signal.

According to an example, the wind detection signal may be a high wind detected signal. The output voice signal may correspond to a blended voice signal. The blended voice signal may be based on the microphone array voice signal and the wind array voice signal.

According to an example, the wind detection signal may be a no wind detected signal or a low wind detected signal. The output voice signal may correspond to the first frequency domain microphone signal and/or the second frequency domain microphone signal.

According to an example, the output voice signal may correspond to the first frequency domain microphone signal if the first frequency domain microphone signal has a first signal-to-noise ratio (SNR) greater than a second SNR of the second frequency domain microphone signal. The output voice signal may correspond to the second frequency domain microphone signal if the first SNR is less than the second SNR. The output voice signal may correspond to a blended microphone signal if the SNR is substantially equal to the second SNR. The blended microphone signal may be based on the first frequency domain microphone signal and the second frequency domain microphone signal.

Generally, in another aspect, a wearable audio device is provided. The wearable audio device may be a pair of audio eyeglasses or an open ear headset.

The wearable audio device may include a first microphone. The first microphone may be configured to generate a first time domain microphone signal.

The wearable audio device may include a second microphone. The second microphone may be configured to generate a second time domain microphone signal.

The wearable audio device may include an accelerometer. The accelerometer may be configured to generate a time domain accelerometer signal.

The wearable audio device may include a filter bank. The filter bank may be configured to generate a first frequency domain microphone signal based on the first time domain microphone signal. The filter bank may be further configured to generate a second frequency domain microphone signal based on the second time domain microphone signal. The filter bank may be further configured to generate a frequency domain accelerometer signal based on the time domain accelerometer signal.

The wearable audio device may include a first beamformer. A first beamformer may be configured to generate a first voice signal. The first voice signal may be based on the first frequency domain microphone signal and the second frequency domain microphone signal. The first beamformer may be a DAS beamformer.

The wearable audio device may include a second beamformer. The second beamformer may be configured to generate a second voice signal. The second voice signal may be based on the first frequency domain microphone signal and the second frequency domain microphone signal. The second beamformer may be a MVDR beamformer.

The wearable audio device may include a third beamformer. The third beamformer may be configured to generate a wind array voice signal. The wind array voice signal may be based on the first frequency domain microphone signal, the second frequency domain microphone signal, and a frequency domain accelerometer signal. The third beamformer may be a GEV beamformer.

The wearable audio device may include a wind detector. The wind detector may be configured to generate a wind detection signal. The wind detection signal may be based on the first voice signal and the second voice signal.

The wearable audio device may include a fixed voice mixer. The fixed voice mixer may be configured to generate an output voice signal. The output voice signal may be based on a microphone array voice signal, the wind array voice signal, and the wind detection signal. According to an example, the microphone array voice signal is the second voice signal.

According to an example, the wearable audio device may include a dynamic voice mixer. The dynamic voice mixer may be configured to generate the microphone array voice signal. The microphone array voice signal may be based on the first voice signal and the second voice signal.

Generally, in another aspect, a method for reducing wind noise is provided. The method may include generating, via a first beamformer, a first voice signal based on a first frequency domain microphone signal and a second frequency domain microphone signal. The method may further include generating, via a second beamformer, an second voice signal based on the first frequency domain microphone signal and the second frequency domain microphone signal. The method may further include generating, via a wind detector, a wind detection signal based on the first voice signal and the second voice signal. The method may further include generating, via a third beamformer, a wind array voice signal based on the first frequency domain microphone signal, the second frequency domain microphone signal, and a frequency domain accelerometer signal. The method may further include generating, via a fixed voice mixer, an output voice signal based on a microphone array voice signal, the wind array voice signal, and the wind detection signal.

According to an example, the method may further include generating, via a first microphone, the first time domain microphone signal. The method may further include generating, via a second microphone, the second time domain microphone signal. The method may further include generating, via an accelerometer, the time domain accelerometer signal. The method may further include generating, via a filter bank, the first frequency domain microphone signal based on a first time domain microphone signal. The method may further include generating, via the filter bank, the second frequency domain microphone signal based on a second time domain microphone signal. The method may further include generating, via the filter bank, the frequency domain accelerometer signal based on a time domain accelerometer signal.

According to an example, the method may further include, generating, via a dynamic voice mixer, the microphone array voice signal based on the first voice signal and the second voice signal.

According to an example, the first beamformer may be a DAS beamformer, the second beamformer may be an MVDR beamformer, and the third beamformer may be a GEV beamformer.

Other features and advantages will be apparent from the description and the claims.

