The present disclosure relates to a hearing device that comprises an in-canal microphone configured for pick-up of at least body conducted sound in a user's ear canal volume and a vibration sensor configured for pick-up of mechanical vibration generated by body-conducted sound of the user for example by vibration of ear canal tissue. A processing unit of the hearing device determines a first compensation signal for cancelling the at least body-conducted sound in the user's ear canal volume based on sound picked-up by the in-canal microphone. The processing unit determines a second compensation signal for cancelling the at least body-conducted sound in the user's ear canal volume based on a vibration signal supplied by the vibration sensor.

The technology described herein can be embodied in a computer implemented method that includes detecting, by one or more processing devices, onset of an unstable condition in an active noise control system. The method also includes obtaining, responsive to detecting the onset of the unstable condition, updated filter coefficients for a system-identification filter configured to represent a transfer function of a secondary path of the active noise control system. The updated filter coefficients are generated using a set of multiple subband adaptive filters, wherein filter coefficients of each subband adaptive filter in the set are configured to adapt to changes in a corresponding portion of a frequency range associated with potential unstable conditions in the active noise control system. The method also includes programming the system identification filter with the updated coefficients to affect operation of the active noise control system.

The technology described herein can be embodied in a computer implemented method that includes detecting, by one or more processing devices, onset of an unstable condition in an active noise control system. The method also includes obtaining, responsive to detecting the onset of the unstable condition, updated filter coefficients for a system-identification filter configured to represent a transfer function of a secondary path of the active noise control system. The updated filter coefficients are generated using a set of multiple subband adaptive filters, wherein filter coefficients of each subband adaptive filter in the set are configured to adapt to changes in a corresponding portion of a frequency range associated with potential unstable conditions in the active noise control system. The method also includes programming the system identification filter with the updated coefficients to affect operation of the active noise control system.

A noise controller includes a first control unit that outputs a control signal for outputting sound for reducing noise to a first speaker, a first characteristic circuit that generates a signal by performing convolution, using a transfer characteristic from the second speaker to a second sound collector, on a control signal output from the first control unit to a second speaker, a subtractor that subtracts the signal generated by the first characteristic circuit from an output signal of a second sound collector and outputs a resultant signal. The first control unit generates the control signal to be output to the first speaker while the output signal from the subtractor serves as a reference signal so that an output signal of the first sound collector is minimized, and outputs the control signal to the first speaker.

Techniques and apparatuses are described that perform respiration rate sensing. Provided according to one or more preferred embodiments is a hearable, such as an earbud, that is capable of performing a novel physiological monitoring process termed herein audioplethysmography, an active acoustic method capable of sensing subtle physiologically-related changes observable at a user's outer and middle ear. Instead of relying on other auxiliary sensors, such as optical or electrical sensors, audioplethysmography involves transmitting and receiving acoustic signals to monitor a user's respiration rate. In addition to being relatively unobtrusive, some hearables can be configured to support audioplethysmography without the need for additional hardware. As such, the size, cost, and power usage of the hearable can help make health monitoring accessible to a larger group of people and improve the user experience with hearables.

Embodiments of a diagnostic tool for an active noise cancelling system are presented. The diagnostic tool may generate an output from the active noise cancelling system and capture input to the active noise cancelling system that results from the output of the active noise cancelling system. The diagnostic tool may generate visual output to aid in evaluation of active noise cancelling systems.

An image capture device detects a wind whistle using two or more microphones. The image capture device includes a processor that obtains microphone signals from the two or more microphones and determines coherence values between the microphone signals across a frequency band. The processor determines a coherence value for each frequency bin of the frequency band. Based on a detection of an elevated coherence value in a frequency bin, the processor determines the presence of a whistle. The processor attenuates the frequency bin based on a determination that the elevated coherence value is above a threshold.

An active vibration noise control device includes: a speaker for outputting a cancellation sound for canceling a noise; an error microphone for generating an error signal from the noise and the cancellation sound; a control filter configured to generate the cancellation sound based on a plurality of reference signals corresponding to the noise; and a disturbance determination part configured to make a determination as to whether a disturbance is present using the error signal and the plurality of reference signals. The disturbance determination part is configured to: calculate an overall correlation by summing a correlation function between each of the plurality of reference signals and the error signal, and make the determination as to whether the disturbance is present based on the overall correlation.

An active aerodynamic noise control apparatus includes a SoundCam installed inside a vehicle, an aerodynamic noise data measurement unit configured to measure aerodynamic noise data, an ultrasonic data measurement unit configured to measure primary ultrasonic data, an acoustic data measurement unit configured to measure primary acoustic data, a correlation coefficient calculation unit configured to calculate a correlation coefficient, an ultrasonic sensor location confirmation unit configured to confirm a secondary ultrasonic sensor location, an ultrasonic data collection unit configured to collect secondary ultrasonic data, an acoustic data collection unit configured to collect secondary acoustic data, an aerodynamic noise region determination unit configured to determine an aerodynamic noise region, an active noise control sound generation unit configured to generate an active noise control sound, and an active noise control sound output unit configured to output the generated active noise control sound.

Embodiments of a diagnostic tool for an active noise cancelling system are presented. The diagnostic tool may generate an output from the active noise cancelling system and capture input to the active noise cancelling system that results from the output of the active noise cancelling system. The diagnostic tool may generate visual output to aid in evaluation of active noise cancelling systems.