Described herein is a technique by which a hearing may automatically switch between a directional microphone mode and an omnidirectional microphone mode base upon an estimate of the noise floor as derived from the input signal. A minimum statistics estimator may be used to estimate the noise floor.

One example may include a method that includes receiving, at a presentation server, an audio data signal from a mobile device located in a presentation space, identifying a mobile device identification characteristic of the mobile device based on the received audio data signal, determining a mobile device location via a location determination procedure, and playing the audio signal via a loudspeaker.

An example method of operation may include designating sub-regions which collectively provide a defined reception space, receiving audio signals at a controller from the microphone arrays in the defined reception space, configuring the controller with known locations of each of the microphone arrays, assigning each of the sub-regions to at least one of the microphone arrays based on the known locations, and creating beamform tracking configurations for each of the microphone arrays based on their assigned sub-regions.

An original noisy signal of each of at least two microphones is acquired by acquiring, using the at least two microphones, an audio signal emitted by each sound source. For each frame in time domain, an estimated frequency-domain signal of each sound source is acquired according to the original noisy signal of each of the at least two microphones. A frequency collection containing a plurality of predetermined static frequencies and dynamic frequencies is determined in a predetermined frequency band range. A weighting coefficient of each frequency contained in the frequency collection is determined according to the estimated frequency-domain signal of the each frequency in the frequency collection. A separation matrix of the each frequency is determined according to the weighting coefficient. The audio signal emitted by each of the at least two sound sources is acquired based on the separation matrix and the original noisy signal.

In a method for direction-dependent noise rejection for a hearing system, first and second input transducers are used to generate an interference signal and a target signal from a sound from the surroundings. The interference signal and/or the target signal are referenced to a useful signal source arranged in a target direction. The target signal is generated with a target directivity pattern. For each of a first plurality of frequency bands, an acoustic characteristic of the target signal is compared with a corresponding acoustic characteristic of the interference signal, and the comparison is used to ascertain a provisional weighting factor. The provisional weighting factor is used to form for the frequency band a weighting factor for the respective frequency bands. An input signal to be processed is weighted on a frequency-band-by-frequency-band basis using the respective weighting factor, and the weighted input signal is used to generate an output signal.

An image capture device includes a housing having a lens snout protruding from a front housing surface. A front microphone is mounted below the lens snout. A top microphone is mounted under a top housing surface. The top microphone is positioned to receive direct freestream air flow at a first pitched forward angle. The front microphone is positioned to receive turbulent air flow at a second pitched forward angle. The second pitched forward angle is greater than or equal to the first pitched forward angle. An audio processor receives a first audio signal and a second audio signal from the top microphone and front microphone, respectively. The audio processor generates frequency sub-bands from the first and second audio signals. The audio processor selects the frequency sub-bands with the lowest noise metric and combines them to generate an output audio signal.

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.

A system and method for selecting audio capture sensors of wearable devices in obtaining voice data. The method provides obtaining signals associated with the user's voice at first and second wearable devices, comparing energy levels of the first and second signals, and selecting one or more audio capture sensors based on the energy levels of each signal. Due to the symmetry of the acoustic energy produced by the user's voice to a first and second wearable device, any difference in energy level between the total energy obtained by the first wearable device and the total energy obtained by the second wearable device can be attributed solely to ambient noise. Thus, the device with the higher total energy has a lower signal-to-noise ratio and selection of an audio capture sensor of the other wearable device with a higher signal-to-noise ratio is provided to obtain voice data moving forward.

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.

An example system for playing media content with a media playback device in a vehicle can be programmed to obtain a sound measurement indicative of a sound level associated with playback of the media content by the media playback device in the vehicle. The example system also can determine a deviation in an expected sound level based upon the sound measurement. Finally, the system can modify playback of the media content by the media playback device (110) based upon the deviation.