Method and apparatus to determine a speaker activity detection measure from energy-based characteristics of signals from a plurality of speaker-dedicated microphones, detect acoustic events using power spectra for the microphone signals, and determine a robust speaker activity detection measure from the speaker activity measure and the detected acoustic events.

Hybrid audio beamforming systems and methods with narrower beams and improved directivity are provided. The hybrid audio beamforming system includes a time domain beamformer for processing upper frequency band signals of an audio signal using a time domain beamforming technique, and a frequency domain beamformer for processing groups of lower frequency band signals of the audio signal using frequency domain beamforming techniques.

An exemplary system includes a memory storing instructions and a processor communicatively coupled to the memory. The processor may be configured to execute the instructions to present a spectro-temporally modulated audio signal to a user. The spectro-temporally modulated audio signal may be modulated within both a frequency domain and a time domain. The processor may be further configured to execute the instructions to adjust a modulation depth of the spectro-temporally modulated audio signal while the spectro-temporally modulated audio signal is being presented to the user, determine, during the adjusting of the modulation depth, a modulation detection threshold that corresponds to a minimum modulation depth at which the user is able to perceive modulation of the spectro-temporally modulated audio signal, and determine, based on the modulation detection threshold, a hearing capability of the user.

In at least one embodiment, an audio amplifier system is provided. The system includes a loudspeaker and an audio amplifier. The loudspeaker transmits an audio output into a listening environment. The audio amplifier is programmed to receive an audio input signal and to generate an excursion signal corresponding to a first excursion level of the voice coil based on the audio input signal. The audio amplifier is further programmed to limit the excursion signal to reach a maximum excursion level and to determine a target pressure for an enclosure of the loudspeaker based on the maximum excursion level. The audio amplifier is further programmed to generate a target current signal based at least on the target pressure and to convert the target current signal into a target voltage signal to a target driving signal to drive the voice coil to reach the maximum excursion level.

An example process includes receiving a voltage input and a current input associated with one or more audio signals, bandpass filtering the voltage input and the current input, determining a root means square of the bandpass filtered portion, dividing the determined root means square of the voltage by the root means square of the current to identify an impedance value, and determining whether a fault has occurred based on the impedance value.

A hearing device, e.g. a hearing aid or a headset, configured to be worn by a comprises an input unit for providing at least one electric input signal in a time-frequency representation; and a signal processor comprising a target signal estimator for providing an estimate of the target signal; a noise estimator for providing an estimate of the noise; and a gain estimator for providing respective gain values in dependence of said target signal estimate and said noise estimate. The gain estimator comprises a trained neural network, wherein the outputs of the neural network comprise real or complex valued gains, or separate real valued gains and real valued phases. The signal processor is configured—at a given time instance t—to calculate changes Δx(i,t)=x(i,t)−{circumflex over (x)}(i,t−1), and Δh(j,t−1)=h(j,t−1)−ĥ(j,t−2) to an input vector x(t) and to the hidden state vector h(t−1), respectively, from one time instance, t-1, to the next, t, and where {circumflex over (x)}(i,t−1) and ĥ(j,t−2) are estimated values of x(i,t−1) and h(j,t−2), respectively, where indices i, j refers to the i.sup.th input neuron and the j.sup.th neuron of the hidden state, respectively, where 1≤i≤N.sub.ch,x and 1≤j≤N.sub.ch,oh, wherein N.sub.ch,x and N.sub.ch,oh is the number of processing channels of the input vector x and the hidden state vector h, respectively, and wherein the signal processor is further configured to provide that the number of updated channels among said N.sub.ch,x and said N.sub.ch,oh processing channels of the modified gated recurrent unit for said input vector x(t) and said hidden state vector h(t−1), respectively, at said given time instance t is limited to a number of peak values N.sub.p,x, and N.sub.p,oh, respectively, where N.sub.p,x is smaller than N.sub.ch,x, and N.sub.p,oh, is smaller than N.sub.ch,oh.

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.

A method for processing audio signals includes extracting a fundamental frequency (F0) component from a first audio signal; processing the first audio signal with Dominant Melody Enhancement (DoME) based on a hearing profile and output a second audio signal; and providing the second audio signal to the user. The DoME enhances the F0 component. The enhancement weight of the DoME is corresponding to the hearing profile.

Processes, methods, systems, and devices are disclosed for synchronizing multiple wireless data streams captured in action by various sensors, with lost data recovery. For example, a source device may have multiple sensors acquiring data and sending the data streams (e.g., via Bluetooth connections) to a target device. Timing information may be appended for each of the data streams. Data packets of the multiple data streams may be formed with the timing information. The data packets may be transmitted to a target device that is configured to synchronize the multiple data streams using the timing information. The target device, applying the example processes or techniques of this disclosure, may accurately synchronize the multiple data streams. In some cases, the target device may capture additional data streams and the processor synchronizes all data streams of both the source and the target devices.

The present disclosure relates to an acoustic output apparatus. The acoustic output apparatus may include an earphone core including at least one acoustic driver for outputting sound though one or more sound guiding holes set on the acoustic output apparatus, a controller configured to cause the at least one acoustic driver to output sound, a power source assembly configured to provide electrical power to the earphone core, the one or more sensors, and the controller, and an interactive control component configured to allow an interaction between a user and the acoustic output apparatus.