An image capture device includes a processor for wind noise processing. The processor receives signals from a first microphone, a first plurality of microphones, and a second plurality of microphones. The processor may segment the signals into low frequency bins and high frequency bins. The processor may select a minimum level signal bin for the low frequency bins. For the high frequency bins, the processor may select a minimum level signal bin for a first group of microphones or a second group of microphones. The processor may generate a composite signal by combining the selected minimum level signal bins for the low frequency bins and the selected minimum level signal bins for the high frequency bins.

Methods, systems, computer-readable media, devices, and apparatuses for synchronized mode transitions are presented. A first device configured to be worn at an ear includes a processor configured to, in a first contextual mode, produce an audio signal based on audio data. The processor is also configured to, in the first contextual mode, exchange a time indication of a first time with a second device. The processor is further configured to, at the first time, transition from the first contextual mode to a second contextual mode based on the time indication.

There is described a switchable microphone device which may be switched between a digital output mode and an analog output mode. There is further described a system for use of such a device, which allows for the switching between analog and digital computing modes.

An image capture device with dynamic wind noise compression tuning techniques is described. A technique includes detecting of the presence of wind noise by measuring coherence between at least two microphones. For a compressor, adjusting a default compression threshold and default compression parameters based on the coherence measurements. For each microphone, applying by the compressor the adjusted compression parameters when an audio signal is above the adjusted compression threshold and applying the default compression parameters when the audio signal is below the adjusted compression threshold.

Examples of the disclosure relate to an apparatus that provides a decimator for audio signals. The apparatus comprises means for: receiving one or more audio input signals and applying a multi-stage decimation process to the one or more audio input signals wherein the multi-stage decimation process comprises at least a first branch and a second branch. The apparatus also comprises means for applying audio signal analysis to the one or more audio input signals. The audio signal analysis extracts at least one audio signal parameter from the one or more audio input signals and is performed on the output of the first branch of the multi-stage decimation process. Use of the second branch of the multi-stage decimation process is dependent upon the outcome of the audio signal analysis.

An earphone includes a feedforward microphone located outside ear and a feedback microphone located inside ear. A method for recognizing wind noise of the earphone includes: feedforward microphone signal collected by feedforward microphone and feedback microphone signal collected by feedback microphone are acquired; Fourier transform is performed on feedforward and feedback microphone signals to obtain a feedforward microphone frequency domain signal and a feedback microphone frequency domain signal; inverse feedback filtering processing is performed on the feedback microphone frequency domain signal to obtain an inverse feedback filtering processing result; inverse feedforward filtering processing is performed on the feedforward microphone frequency domain signal and the inverse feedback filtering processing result to obtain an inverse hybrid filtering processing result; and a wind noise recognition result of the earphone is obtained based on an interrelationship between the inverse feedback filtering processing result and the inverse hybrid filtering processing result.

An earphone includes a first microphone located outside an ear and a second microphone located inside the ear. A method for recognizing wind noise of the earphone includes: a first microphone signal collected by the first microphone and a second microphone signal collected by the second microphone are acquired; a first frequency domain filtered signal is obtained based on the first microphone signal and the second microphone signal; and obtaining a wind noise recognition result of the earphone based on coherence between the first microphone signal and the first frequency domain filtered signal.

A hearing device may include a housing, a microphone, and an acoustic element. The housing may include a shell and a microphone port disposed between an outer surface of the shell and an inner surface of the shell that defines a cavity within the shell. The microphone may be disposed within the cavity of the shell and acoustically connected to the microphone port. The acoustic element may be disposed on the outer surface of the shell or at least partially within the microphone port. The acoustic element may include a substrate and fibers extending from the substrate. At least a portion of acoustic energy incident upon the acoustic element may be received by the microphone.

A device includes one or more processors configured to obtain audio signals representing sound captured by at least three microphones and determine spatial audio data based on the audio signals. The one or more processors are further configured to determine a metric indicative of wind noise in the audio signals. The metric is based on a comparison of a first value and a second value. The first value corresponds to an aggregate signal based on the spatial audio data, and the second value corresponds to a differential signal based on the spatial audio data.

A system includes a microphone unit coupled to a roof of an autonomous vehicle. The microphone unit includes a microphone board having a first opening. The microphone unit also includes a first microphone positioned over the first opening and coupled to the microphone board. The microphone unit further includes an accelerometer. The system also includes a processor coupled to the microphone unit.