Abstract: Methods and systems are provided for automatic noise control. Automatic noise control includes controlling a shadow noise control transfer function based on a shadow error signal and a filtered or unfiltered reference signal, generating the shadow error signal based on a filtered or unfiltered shadow anti-noise signal and an error signal, and substituting the noise control transfer function by the shadow noise control transfer function if the shadow error signal is smaller than the error signal.

Abstract: A noise suppression method includes transforming a time-domain input signal into an input spectrum that is the spectrum of the input signal, the input signal comprising speech components and noise components, and the input spectrum comprising a speech spectrum that is the spectrum of the speech components and a noise spectrum that is the spectrum of the noise components, smoothing magnitudes of the input spectrum to provide a smoothed-magnitude input spectrum, and estimating basic suppression filter coefficients from the input spectrum and the smoothed input spectrum. The method further includes determining noise suppression filter coefficients from the estimated basic suppression filter coefficients and a spectral correlation factor, the spectral correlation factor indicating whether speech is present in the input signal or not, filtering the input spectrum based on the noise suppression filter coefficients to generate an output spectrum; and transforming the output spectrum into a time-domain output signal.

Abstract: Methods and systems are provided for automatic noise control. Automatic noise control includes controlling a shadow noise control transfer function based on a shadow error signal and a filtered or unfiltered reference signal, generating the shadow error signal based on a filtered or unfiltered shadow anti-noise signal and an error signal, and substituting the noise control transfer function by the shadow noise control transfer function if the shadow error signal is smaller than the error signal.

Abstract: Detecting fricatives in a noisy speech signal having a clean speech signal and a noise signal, includes bandpass filtering of the noisy speech signal with a first transfer function having a first passband range to provide a first filtered noisy speech signal, and bandpass filtering of the noisy speech signal with a second transfer function having a second passband range, the second passband being different from the first passband to provide a second filtered noisy speech signal. Detecting fricatives further includes applying a maximum operation to the first filtered noisy speech signal and the second filtered noisy speech signal to provide a maximum spectrum that is representative of a frequency range of maximum fricative energy, and deciding, based on the maximum spectrum, whether a fricative is contained in the noisy speech signal. A decision signal is output that is representative of the decision.

Abstract: Systems and methods for noise reduction are provided including operations for noisy speech signals, such as speech signals that are subject to speech processing, speech recognition and speech transmission for voice communication purposes. In one embodiment, a system for noise suppression includes an input smoothing filter to smooth magnitudes of the input spectrum, a desired noise shape determination block configured to determine a desired noise shape of the noise spectrum dependent on the smoothed-magnitude input spectrum, and a suppression factors determination block configured to determine a set of suppression factors based on the desired noise shape and the smoothed-magnitude input spectrum. In one embodiment, a filter coefficient determination block is configured to determine noise suppression filter coefficients from the desired noise shape of the noise spectrum. Embodiments are also directed to systems and methods for noise reduction.

Abstract: Acoustic echo cancelling includes receiving a source signal and a sink signal; providing a first error signal representative of an echo-free residual signal based on a first set of coefficients based on the source signal and the sink signal, the first error signal forming an output signal of the controller; providing a second error signal based on a second set of coefficients based on the source signal and the sink signal; detecting a room change if the evaluated first second error signal is greater than a sum or product of the evaluated second first error signal and a first threshold; copying one of sets of reference coefficients stored in a memory to the second acoustic echo canceller; and copying the first set of coefficients from the first acoustic echo canceller as a set of reference coefficients into at least one of the second acoustic echo canceller and the memory.

Abstract: Detecting fricatives in a noisy speech signal having a clean speech signal and a noise signal, includes bandpass filtering of the noisy speech signal with a first transfer function having a first passband range to provide a first filtered noisy speech signal, and bandpass filtering of the noisy speech signal with a second transfer function having a second passband range, the second passband being different from the first passband to provide a second filtered noisy speech signal. Detecting fricatives further includes applying a maximum operation to the first filtered noisy speech signal and the second filtered noisy speech signal to provide a maximum spectrum that is representative of a frequency range of maximum fricative energy, and deciding, based on the maximum spectrum, whether a fricative is contained in the noisy speech signal. A decision signal is output that is representative of the decision.

Abstract: Acoustic echo cancelling includes receiving a source signal and a sink signal; providing a first error signal representative of an echo-free residual signal based on a first set of coefficients based on the source signal and the sink signal, the first error signal forming an output signal of the controller; providing a second error signal based on a second set of coefficients based on the source signal and the sink signal; detecting a room change if the evaluated first second error signal is greater than a sum or product of the evaluated second first error signal and a first threshold; copying one of sets of reference coefficients stored in a memory to the second acoustic echo canceller; and copying the first set of coefficients from the first acoustic echo canceller as a set of reference coefficients into at least one of the second acoustic echo canceller and the memory.

Abstract: Systems and methods for noise reduction are provided including operations for noisy speech signals, such as speech signals that are subject to speech processing, speech recognition and speech transmission for voice communication purposes. In one embodiment, a system for noise suppression includes an input smoothing filter to smooth magnitudes of the input spectrum, a desired noise shape determination block configured to determine a desired noise shape of the noise spectrum dependent on the smoothed-magnitude input spectrum, and a suppression factors determination block configured to determine a set of suppression factors based on the desired noise shape and the smoothed-magnitude input spectrum. In one embodiment, a filter coefficient determination block is configured to determine noise suppression filter coefficients from the desired noise shape of the noise spectrum. Embodiments are also directed to systems and methods for noise reduction.