A method for reducing noise within a vehicle cabin comprising at least one error sensor and at least one sound transducer, the method comprising: the at least one error sensor measuring at least one first noise at a first location; selecting at least one sound zone from a plurality of sound zones within the cabin for reducing noise in said at least one sound zone, based on a presence of a driver and passenger(s) within the cabin; estimating at least one second noise that would have been measured at a second location within the selected at least one sound zone, based on a primary transfer function describing a primary acoustic path from the first location to the second location; the at least one sound transducer generating at least one secondary noise for reducing the at least one second noise that would have been measured at the second location.

An apparatus for providing active noise control, includes: one or more microphones configured to detect sound entering through an aperture of a building structure; a set of speakers configured to provide sound output for cancelling or reducing at least some of the sound; and a processing unit communicatively coupled to the set of speakers, wherein the processing unit is configured to provide control signals to operate the speakers, wherein the control signals are independent of an error-microphone output.

Systems and methods for communicating information related to a wearable device are disclosed. Exemplary information includes audio information.

A vibration cancellation method is a vibration cancellation method for canceling vibration arriving at a seat from outside of the seat, the vibration being transmitted to a user seated in the seat. The method includes canceling, by a vibration cancellation unit (4), a vibration by outputting a cancellation signal from a position close to a position where user's head is placed when a user is seated, the cancellation signal being obtained based on a reference signal and an error signal. The reference signal is obtained by a vibration sensor (2) disposed in a position close to a vibration source outside the seat in the seat, and the error signal is obtained by an error vibration sensor (3) disposed in the position close to the position where user's head is placed when the user is seated in the seat.

Methods and systems are provided for an automatic noise control system. Automatic noise control includes evaluating an amplitude of an acceleration acting on an acceleration sensor and generating a reference signal representative of the amplitude of the acceleration, the acceleration being representative of unwanted noise sound generated by a noise source, filtering the reference signal with a noise control transfer function to generate an anti-noise signal, and converting with a loudspeaker the anti-noise signal into anti-noise sound.

Example techniques involve noise-robust acoustic echo cancellation. An example implementation may involve causing one or more speakers of the playback device to play back audio content and while the audio content is playing back, capturing, via the one or more microphones, audio within an acoustic environment that includes the audio playback. The example implementation may involve determining measured and reference signals in the STFT domain. During each n.sup.th iteration of an acoustic echo canceller (AEC): the implementation may involve determining a frame of an output signal by generating a frame of a model signal by passing a frame of the reference signal through an instance of an adaptive filter and then redacting the n.sup.th frame of the model signal from an n.sup.th frame of the measured signal. The implementation may further involve determining an instance of the adaptive filter for a next iteration of the AEC.

The present disclosure presents a feedback active noise control system and strategy with online secondary-path modeling, and belongs to the technical field of active noise control. The linear prediction subsystem takes the residual noise as its input and separates the remaining sinusoidal noise from the broadband noise. The remaining sinusoidal noise is used effectively not only to update the controller but also to scale the auxiliary noise, while the broadband noise serves as a desired input of online secondary-path modeling subsystem. In this way, the coupling between the controller and the online secondary-path modeling subsystem is significantly mitigated, leading to both faster convergence and improved noise reduction performance. A practical scheme for refreshing the entire system is also developed to enhance its robustness against even abrupt changes with the secondary path or the primary noise. The present disclosure enhances the applicability of feedback active noise control in practical applications.

An active noise control (ANC) system includes a speaker and one or more processors programmed to implement a delayless subband filtered-x least mean square control algorithm. The algorithm includes a variable bandwidth discrete Fourier transform filter bank having a number of subbands such that the system, in response to a broadband white noise reference signal indicative of road noise in the vehicle, exhibits a uniform gain spectrum across a frequency range defined by the subbands and partially cancels the road noise via output of the speaker.

A personal audio device, such as a wireless telephone, includes noise canceling that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone is provided proximate the speaker to measure the output of the transducer in order to control the adaptation of the anti-noise signal and to estimate an electro-acoustical path from the noise canceling circuit through the transducer. The anti-noise signal is adaptively generated to minimize the ambient audio sounds at the error microphone. A processing circuit that performs the adaptive noise canceling (ANC) function also filters one or both of the reference and/or error microphone signals, to bias the adaptation of the adaptive filter in one or more frequency regions to alter a degree of the minimization of the ambient audio sounds at the error microphone.

The disclosure is related to a method and a system for self-tuning active noise canceller (STANC) and a headset apparatus. The headset apparatus is placed on a measurement device to emulate user scenario where the user receives audio signal from the headset. The STANC system receives environmental noise signal from a microphone inside the headset. The output of the STANC system acts as reverse noise signal to suppress the environmental noise signal via a speaker unit. The corresponding mixture signal is defined as an error signal. In a calibration mode, the error signal received from the measurement device can be used to update the STANC parameters. The process will be done when the error signal is lower than a predefined threshold. The final parameters can be saved as default settings for the headset apparatus in a user mode.