Aspects relate to systems and methods for dynamic active noise reduction including at least a sensor configured to sense a physiological characteristic of a user and transmit a physiological signal correlated to the sensed physiological characteristic, at least an environmental microphone configured to transduce an environmental noise to an environmental noise signal, a processor configured to receive the environmental noise signal, generate a noise-reducing sound signal as a function of the environmental noise signal, and, modify the noise-reducing sound signal as a function of the physiological signal, and a speaker configured to transduce a noise-reducing sound from the modified noise-reducing sound signal.

Sound reduction includes producing an error signal representative of sound present in a target space, producing a reference signal corresponding to undesired sound present in the target space, and producing, based on the reference signal and the error signal a cancelling output signal representative of the undesired sound present in the target space. The method further includes producing, based on the cancelling output signal, sound to destructively interfere with the undesired sound present in the target space, and limiting the amplitude or power of at least one of the reference signal, the error signal and the cancelling output signal if a first condition is met, the at least one signal under examination is at least one of the reference signal, the error signal and the cancelling output signal, and fully or partially suspending the active noise controller update mechanism if a second condition is met.

A noise cancellation system for cancelling sounds within a vehicle. The noise cancellation system includes microphones, a camera, a controller, and speakers. The microphones are disposed adjacent to occupant locations, and configured to generate microphone signals representative of noise sounds and cancellation audio sounds. The camera is configured to generate a video signal that captures head configurations of the occupants. The controller is configured to receive rotor control signals, calculate hearing locations based on tracking data of the head configurations of the occupants, and generate a speaker signals based on the hearing locations, the microphone signals, and the rotor control signals. The speakers are configured to generate the cancellation audio sounds. The cancellation audio sounds attenuate the noise sounds.

A method for tuning filter parameters of a noise cancellation enabled audio system with an ear-mountable playback device comprising a speaker and a feedback noise microphone located in proximity to the speaker comprises provision of acoustic transfer functions between the speaker and the feedback noise microphone, between the speaker and an eardrum, between an ambient sound source and the eardrum and between the ambient sound source and the feedback noise microphone. The parameters of a feedback filter function, which is designed to process a feedback noise signal, are tuned. A noise cancellation performance of the audio system at the eardrum is determined based on each of the acoustic transfer functions and on the feedback filter function.

Embodiments of active noise control (ANC) headphones and operating methods thereof are disclosed herein. In one example, a headphone includes a speaker, an internal microphone, and a processor. The speaker is configured to play an audio of interest based on an audio source signal. The internal microphone is configured to obtain a mixed audio signal including a noise signal and the audio of interest played by the speaker. The processor is configured to determine a first current system parameter of the headphone based on the mixed audio signal at a first time point, and determine if the first current system parameter of the headphone is higher than a predetermined threshold to determine if the headphone is worn by a user.

An earbud system for reducing noise is disclosed. The earbud system comprises an analog to digital converter to convert analog audio signals of a sound captured by one or more sound sensors into digital audio signals, and one or more processors to filter one or more raw bits with a specific frequency band from the digital audio signals to obtain filtered digital audio signals and extract human audible frequency bands from the filtered digital audio signals. The processors predict and/or classify, using an artificial intelligence based mechanism, the extracted human audible frequency bands into ambient noise corresponding to a first set of frequencies and desired sound, to be heard by the user, corresponding to a second set of frequencies. The processors further generate anti-phase signals for a first set of frequencies to reduce noise, and audible phase signals for the second set of frequencies.

A system for adjusting volume and ambient sounds in an earphone device with Active Noise Cancelling (ANC) functionality, implemented using a microphone and a signal processor, wherein a signal mixer is configured to, in response to detecting a rotation of a first dial connected to the earphone device, adjust the proportions between a group of signals in a mixed signal generated for the speaker of the earphone device, and thereby enabling precise and intuitive control of both playback volume and ambient sound processing.

A hybrid ANC system that can allow a feedback microphone to receive the same external noise as a feedforward microphone. A processor can generate an anti-noise signal based on what both microphones received to cancel a broader range of frequencies of the external noise.

The invention relates to an adaptive active noise cancellation apparatus and an audio playback system using the same. The adaptive active noise cancellation apparatus shapes an error signal and a noise signal according to a shape of an ideal noise. After that, the shaped noise signal and the shaped error signal are sent into a parameter adjusting unit to perform an adaptive parameter adjustment. Thus, the adaptive noise filter unit is not only can adaptively suppress noise and minimize the error signal, but also can suppress specific frequencies that are sensitive to the human ear.

Various implementations include systems for processing audio signals to remove artifacts introduced by a machine learning system in challenging environments. In particular implementations, a method includes generating a processed audio signal for a hearing assistance device in which the processed audio signal is intended to perceptually dominate a user auditory experience, including: processing an unprocessed audio signal received by the hearing assistance device, wherein the processing includes utilizing a machine learning (ML) system to generate an ML enhanced audio signal; determining a mixing coefficient from an environmental noise assessment; mixing the ML enhanced audio signal with the unprocessed audio signal using the mixing coefficient to generate the processed audio signal; and outputting the processed audio signal.