A device for reducing crosstalk in an audio system that has first and second pairs of loudspeakers and first and second audio sources. The device is connected to each audio source and to at least the first pair of loudspeakers. The device includes a module for acquiring first audio signals from the first source and second audio signals from the second source, a module for determining crosstalk reduction filters resulting from a loudspeaker of the second pair, a module for calculating corrective signals, by applying the reduction filters to the second audio signals, and a module for generating corrected audio signals for the first pair, obtained from the first audio signals and corrective signals. Each reduction filter is obtained from transfer functions, each representing an acoustic path between a loudspeaker and a user's ear.

Embodiments and methods perform ear cavity frequency response (EFCR) adaptive noise cancelation (ANC) with path-compensation over an entire main path to the eardrum (MPED) of a user. A number of ANC filter models are pre-trained to include respective anti-noise path (ANP) filter models and respective MPED filter models representing ANC filter configurations. As a user wears a headphone earpiece, characteristics of the wearer and the position/orientation of wearing manifest a wearer/wearing condition. Techniques described herein can continuously or periodically and efficiently determine which of the pre-trained ANC filter models most closely described the present MPED of the present wearer/wearing condition, and can continuously or periodically update the ANC filter configuration based on the pre-trained models to maintain high-performance ANC that includes EFCR path-compensation.

In some implementations, an output of a first channel of an echo cancellation variable filter having an output of a first microphone output from a second speaker as an input is added to an output of a second microphone. An echo cancellation coefficient updating unit updates the filter coefficient of the first channel so that the error that is the output of a second adder is minimized. Using the output of the second channel that uses the output of a sound source device output from the first speaker as an input and shares the filter coefficient with the first channel as a reference signal, and the output of the second microphone as an error, the noise cancellation coefficient updating unit updates the filter coefficient of the noise cancellation variable filter that generates a noise-canceling sound to be output from the output of the sound source device to the second speaker.

A noise cancelling system for a vehicle includes a microphone, at least one first sensor configured to collect first data related to an element that generates a noise sound, at least one second sensor configured to collect second data related to an element that changes a secondary path of the noise sound, a controller configured to select a secondary path model corresponding to the second data from among a plurality of pre-stored secondary path models, input the first data to a secondary path filter corresponding to the selected secondary path model, and generate an anti-noise signal based on output data of the secondary path filter and error data received from the microphone, and a speaker configured to output an anti-noise sound based on the anti-noise signal.

A computer-implemented method for generating anti-noise using an anti-noise generator to suppress noise from a noise source in an environment comprises processing a sound signal, which is representative of ambient sound including noise, anti-noise and propagation noise from the environment, using a deep learning algorithm configured to generate an anti-noise signal to form anti-noise. The deep learning algorithm comprises a convolution layer; after the convolution layer, a series of atrous scaled convolution modules, wherein each of the atrous scaled convolution modules comprises an atrous convolution, a nonlinear activation function after the atrous convolution, and a pointwise convolution after the nonlinear activation function; after the series of atrous scaled convolution modules, a recurrent neural network; and after the recurrent neural network, a plurality of fully connected layers.

A system and method for integrating a home media system and other home systems. As a non-limiting example, various aspects of this disclosure provide a system and method that flexibly and efficiently provide communication and/or resource sharing between a home media system and various other home systems.

In the method according to the invention for active noise suppression, a transfer function for a secondary path between a loudspeaker and an error microphone is measured (20). Based on the measured transfer function for the secondary path, a transfer function for a primary path between a reference microphone and the error microphone is estimated (21). Based on the estimated transfer function for the primary path, filter coefficients for filtering to generate the cancellation signal are then determined (22).

Adaptive operations of a first noise control system and a second noise control system may include a speaker that outputs noise cancellation sound, a microphone that detects an error signal, an auxiliary filter that generates, from a noise signal, a correction signal that corrects the error signal so that a difference in a position between the microphone and a noise cancellation position is compensated, and an adaptive filter that performs an adaptive operation using the corrected error signal to generate the noise cancellation sound from the noise signal are alternately performed. A transfer function learned in a state in which the second noise control system is stopped is set in the auxiliary filter of the first noise control system, and a transfer function learned in a state in which the adaptive operation of the first noise control system is stopped is set in the auxiliary filter of the second noise control system.

An active control method for filtered reference affine projection sign algorithm based on variable step size includes: S1, acquiring impulse noise signals and transmitting the signals to control filters; S2, transmitting the impulse noise signals by the control filters to post filters; S3, generating cancellation signals of the impulse noise signals by the post filters according to the impulse noise signals and internal active control algorithms, and transmitting the cancellation signals to a speaker; S4, sending out the cancellation signal by the speaker to superimpose with the impulse noise signals to cancel the impulse noise signal. A convex combination structure and a variable step size strategy are adopted, and by adjusting step size coefficients in the control filter structure, convergence speed of algorithm is controlled, contradiction between convergence speed and steady-state error is coordinated, convergence performance of control algorithm to impulse noises is improved, and impulse noises are effectively controlled.

An active noise control device includes a secondary path filter coefficient updating unit. The secondary path filter coefficient updating unit is configured to update a coefficient of a secondary path filter by using a coefficient of the secondary path filter after previous updating as a previous value, when a phase characteristic of the secondary path filter that sets an initial value as the coefficient and a phase characteristic of the secondary path filter that uses the previous value as the coefficient are not approximate to each other.