Provided is a signal processing device that performs noise canceling by combining a feedforward method and a feedback method. A signal processing device includes: a correlation calculation unit that calculates a correlation between a first sound pickup signal by a first microphone installed outside a predetermined region and a second sound pickup signal by a second microphone installed in the predetermined region; a determination unit that determines the correlation; and a control unit that performs control based on a result of the determination. The control unit controls execution of signal processing for generating a cancellation signal to be output within the predetermined region from the first sound pickup signal and the second sound pickup signal or output of the cancellation signal.

The present disclosure provides a method for determining an arrangement of reference sensors for active road noise control (ARNC) in a vehicle with an automatic calibration system. The method includes mounting a plurality of vibrational sensors on a plurality of structure elements of the vehicle to generate a plurality of vibrational input signals and mounting at least one microphone inside a cabin of the vehicle to capture at least one acoustic input signal. The method further includes determining an arrangement of reference sensors from the plurality of vibrational sensors by determining a subset of vibrational sensors which sense the main mechanical inputs of road noise contributing to the at least one acoustic input signal.

An acoustic echo canceller (AEC) uses a simulated echo from an adaptive filter to cancel an actual echo from a real environment. The echo cancellation is optimal when the adaptive filter response accurately matches the environment response. This can be achieved by changing coefficients of the filter in a step-wise fashion until the filter is converged on a configuration that provides optimal results. The convergence of the filter can be negatively affected by interference due to a double talk event or by an event in which the environment is changed. The disclosed AEC is configured to respond to these disruptive events by adjusting a step-size of the adaptive algorithm used to change the coefficients.

In one embodiment, a pickup system includes a wind detector and a wind suppressor. The wind detector has a plurality of analyzers each configured to analyze first and second input signals, and a combiner configured to combine outputs of the plurality of analyzers and issue, based on the combined outputs, a wind level indication signal indicative of wind activity. The analyzers can be selected from a group of analyzers including a spectral slope analyzer, a ratio analyzer, a coherence analyzer, a phase variance analyzer and the like. The wind suppressor has a ratio calculator configured to generate a ratio of the first and second input signals, and a mixer configured to select one of the first or second input signals and to apply to the selected input signal one of first or second panning coefficients based on the wind level indication signal and on the ratio.

An active noise reduction system includes a canceling sound output device configured to output a canceling sound for canceling a noise, a noise signal generator configured to generate noise signals based on the noise, and a controller configured to control the canceling sound output device based on the noise signals, wherein the controller is configured to acquire buffer data in which the noise signals are stored in a time series, generate a plurality of divided data by dividing the buffer data, calculate a correlation value of the buffer data based on the plurality of divided data, detect presence/absence of disturbance mixed in the buffer data based on the correlation value, and switch control over the canceling sound output device according to the presence/absence of the disturbance mixed in the buffer data.

A method for reducing the power of an acoustic primary noise signal (d.sub.m(n)) at one or more control positions in a vehicle passenger compartment using an adaptive filter. The method comprising to compare a mean correlation coefficient (γ.sub.m(n)) between an electrical error signal (e.sub.m(n) and a modelled secondary anti-noise signal ŷ.sub.m(n) with at least one predefined threshold (α, β).

An ambient sound processing method provided includes determining a time-frequency spectrum of an ambient sound in preset duration. A matching scenario is determined from at least one preset scenario according to the time-frequency spectrum of the ambient sound in the preset duration, where a time-frequency spectrum of the matching scenario matches the time-frequency spectrum of the ambient sound in the preset duration. Operation information corresponding to the matching scenario is determined as the operation information to be executed, and an operation is performed according to the operation information to be executed and a subsequently received ambient sound, and an operated signal is determined. The operated signal is mixed to obtain a mixed signal, and the mixed signal is transmitted to a headset, where the mixed signal includes at least an audio signal played by user equipment of a user.

A noise-cancellation system, including: a plurality of sensors, each sensor outputting a sensor signal; a controller configured to receive each sensor signal, and, for each sensor signal, to: determine a power of the sensor signal at a plurality of frequencies; determine a measure of association between the power of the sensor signal at the plurality of frequencies and frequency; and determine whether the measure of association exceeds a predetermined threshold, wherein the processor is further configured to compute a noise-cancellation signal using the sensor signals, wherein the noise-cancellation signal is computed excluding sensor signals that were determined to exceed the predetermined threshold; and at least one actuator receiving the noise-cancellation signal and producing a noise-cancellation audio signal.

A method for reducing the power of an acoustic primary noise signal (d.sub.m(n)) at one or more control positions in a vehicle passenger compartment using an adaptive filter. The method comprising to compare a mean correlation coefficient (.sub.m(n)) between an electrical error signal (e.sub.m(n) and a modelled secondary anti-noise signal .sub.m(n) with at least one predefined threshold (, ).

An ambient sound processing method provided includes determining a time-frequency spectrum of an ambient sound in preset duration. A matching scenario is determined from at least one preset scenario according to the time-frequency spectrum of the ambient sound in the preset duration, where a time-frequency spectrum of the matching scenario matches the time-frequency spectrum of the ambient sound in the preset duration. Operation information corresponding to the matching scenario is determined as the operation information to be executed, and an operation is performed according to the operation information to be executed and a subsequently received ambient sound, and an operated signal is determined. The operated signal is mixed to obtain a mixed signal, and the mixed signal is transmitted to a headset, where the mixed signal includes at least an audio signal played by user equipment of a user.