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.

In order to achieve the above-mentioned object or another objective, a portable acoustic device according to one aspect of the present invention comprises: a man body housing having an opening at a first surface thereof; an acoustic output unit provided inside the main body housing; an ear housing having a first end portion connected to the opening at the first surface of the main body housing, and having an acoustic hole formed at a second end portion; and a rotating module for rotating the ear housing relative to the main body housing, wherein the portable acoustic device can be carried by being inserted into the ear of a user, can be worn in either the left ear or the right, and increases wearing sensation by being wearable since the angle thereof is changed to be suitable for the ears of the user.

In a signal processing device, a signal processing method, a recording medium, and a rangehood apparatus, a filter coefficient is set in a sound cancelling filter, and the sound cancelling filter outputs a cancellation signal. A coefficient calculator calculates a first filter coefficient. An oscillation suppressor calculates a second filter coefficient by applying a window function to the first filter coefficient to set the second filter coefficient as the filter coefficient.

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 ear interface mode of headphones may be determined by measuring an acoustic response of the headphones. For example, the headphones may be determined to be in a leaky or sealed configuration. An adaptive noise cancellation (ANC) system may be controlled based on the determined ear interface mode of the headphones. For example, a set of configuration parameters may be loaded for the ANC system corresponding to the known ear interface mode. An anti-noise signal may be generated according to the selected configuration parameters, and that anti-noise signal added during playback of media, such as voice recordings, music, videos, or telephone call speech.

A microphone system may include a measuring device that includes a plurality of sound elements and a semiconductor chip connected to the sound elements and receives a vibration signal and a noise signal from the outside to cancel the vibration signal and changes a phase of the noise signal to output a reverse phase noise signal; and a driver that is connected to the semiconductor chip and is included in a front glass of a vehicle and vibrates in response to the reverse phase noise signal to cancel a noise signal inputted from the outside.

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 exemplary engine noise control includes directly picking up engine noise from an engine of a vehicle at a pick-up position to generate a sense signal representative of the engine noise, and active noise control filtering to generate a filtered sense signal from the sense signal. The control further includes converting the filtered sense signal from the active noise control filtering into anti-noise and radiating the anti-noise to a listening position in an interior of the vehicle. The filtered sense signal is configured so that the anti-noise reduces the engine noise at the listening position.

A method of controlling an audio system comprises: receiving an audio signal, and applying a first gain to the audio signal and outputting an amplified audio signal. On receiving a user input to increase the first gain applied to the audio signal, if the first gain is at a first threshold value, the method comprises: receiving an ambient noise signal, processing the ambient noise signal with a second gain value and outputting a noise cancellation signal, and changing the second gain value in response to the user input.

A system for self-organized acoustic signal cancellation over a network is disclosed. The system may transmit an acoustic sounding signal to an interfering device so that a channel measurement may be performed for a channel between the interfering device and an interferee device. The system may receive the channel measurement for the channel from the interfering device and also receive a digitized version of an audio interference signal associated with the interfering device. Based on the channel measurement and the digital version of the interference signal, the system may calculate a cancellation signal prior to the arrival of the original over-the-air audio interference signal that corresponds to the digital version of audio interference signal. The system may then apply the cancellation signal to an audio signal associated with the interferee device to remove the interference signal from the audio signal.