An example active road noise control includes generating with a sensor arrangement a primary sense signal representative of at least one of accelerations, motions and vibrations that occur at a first position, and providing a noise reducing signal by processing the primary sense signal according to an adaptive mode of operation or a non-adaptive mode of operation. It further includes generating within the vehicle body noise reducing sound at the second position from the noise reducing signal, evaluating the primary sense signal and controlling the processing of the primary sense signal so that the primary sense signal is processed in the adaptive mode of operation when the magnitude of the primary sense signal undercuts a first threshold and in the non-adaptive mode of operation when the magnitude of the primary sense signal exceeds a second threshold, the first threshold being equal to or smaller than the second threshold.

Certain example embodiments relate to an acoustic wall assembly that uses active and/or passive sound reverberation to achieve noise-disruptive functionality, and/or a method of making and/or using the same. With the active approach, sound waves in a given frequency range are detected by a sound masking circuit. Responsive to detection of such sound waves, an air pump (e.g., speaker) is used to pump air in the wall assembly to actively mask the detected sound waves via reverberation and/or the like. The wall assembly may include one, two, or more walls, and the walls may be partial or full walls. With the passive approach, sound waves in a given frequency range are disrupted via features (e.g., holes, slits, etc.) formed in and/or on a wall itself. These techniques may be used together or separately, in different example embodiments.

The handling of disturbances to audio signals may be improved with an adaptive noise cancellation (ANC) system that performs frequency-domain adaption. The ANC systems may be configured to determine if a disturbance is present at a first frequency in the second input signal received from the reference microphone. The ANC systems may update an algorithm of an adaptive filter based, at least in part, on the first input signal, the second input signal, and a feedback signal that is based on an output of the adaptive filter by changing parameters of the algorithm such that the adaptive filter adapts around the first frequency differently than other frequencies when the disturbance is present.

Noises that are to be emitted by an aerial vehicle during operations may be predicted using one or more machine learning systems, algorithms or techniques. Anti-noises having equal or similar intensities and equal but out-of-phase frequencies may be identified and generated based on the predicted noises, thereby reducing or eliminating the net effect of the noises. The machine learning systems, algorithms or techniques used to predict such noises may be trained using emitted sound pressure levels observed during prior operations of aerial vehicles, as well as environmental conditions, operational characteristics of the aerial vehicles or locations of the aerial vehicles during such prior operations. Anti-noises may be identified and generated based on an overall sound profile of the aerial vehicle, or on individual sounds emitted by the aerial vehicle by discrete sources.

An example active road noise control includes generating with a sensor arrangement a primary sense signal representative of at least one of accelerations, motions and vibrations that occur at a first position, and providing a noise reducing signal by processing the primary sense signal according to an adaptive mode of operation or a non-adaptive mode of operation. It further includes generating within the vehicle body noise reducing sound at the second position from the noise reducing signal, evaluating the primary sense signal and controlling the processing of the primary sense signal so that the primary sense signal is processed in the adaptive mode of operation when the magnitude of the primary sense signal undercuts a first threshold and in the non-adaptive mode of operation when the magnitude of the primary sense signal exceeds a second threshold, the first threshold being equal to or smaller than the second threshold.

A wireless earpiece includes a wireless earpiece housing, a processor disposed within the wireless earpiece housing, at least one microphone operatively connected to the processor, and at least one speaker operatively connected to the processor. The processor is configured to receive audio from the at least one microphone, perform processing of the audio to provide processed audio, and output the processed audio to the at least one speaker. The processing of the audio involves identifying body generated sounds generated by a body of a user of the wireless earpiece and removing the body generated sounds.

An active noise reduction system and method to cancel fan or blower noise. The system utilizes 2 microphones: one to pick up the subject noise and the noisy signal at far field. The proposed system utilizes a portable loudspeaker that is placed near the subject. The loudspeaker broadcasts omni-directional or directional anti-phase signals to reduce the noise at far field. The system includes a real-time processor (DSP or FPGA) with fast adaptive filter to process the 2 microphone signals and generate the anti-phase signal. The adaptive filter uses the second microphone as a reference to generate an out-of-phase signal, which can then suppress the far field noise. The system is simple to set up and portable. The system utilizes frequency-domain adaptive filter and proven algorithms to quickly compute the anti-phase signals for cancelling detected noise.

A wind noise throb reduction system includes a controller configured to reduce wind noise throb, an active noise cancellation subsystem responsive to the controller and a dynamic airflow control subsystem responsive to the controller. A related method of reducing wind noise throb in a passenger compartment of a motor vehicle is also provided.

An audio processing system includes at least one first microphone, at least one adaptive filter, and a processor. The at least one first microphone acquires a first audio signal and outputs a first signal based on the first audio signal. The first audio signal includes at least one of a first audio component generated at a first position and a second audio component generated at a second position different from the first position. The first signal is input to the at least one adaptive filter. The at least one adaptive filter outputs a passing signal based on the first signal. The processor, when executing a program stored in a memory, performs: making a determination of which of the first audio component and the second audio component the first audio signal includes more; and controlling a filter coefficient of the adaptive filter based on a result of the determination.

In a directionality control system, a camera device captures a video of image capture area (SA). A microphone array device collects a sound in image capture area (SA). A signal processing section detects a sound source of the sound in image capture area (SA) which is collected by the microphone array device. In a case where the detected sound source is within a range of privacy area (PRA), an output control section controls the sound in image capture area (SA) which is collected by the microphone array device and is output from speaker device (37).