Abstract: A method, computer program product, and computer system for receiving, by a computing device, an input signal. A first power spectral density estimate may be generated for a linear reverberant component associated with the input signal. A second power spectral density estimate may be generated for a non-linear reverberant component associated with the input signal. A power spectral density estimate may be generated by combining the first power spectral density estimate for the linear reverberant component and the second power spectral density estimate for the non-linear reverberant component. One or more parameters for at least one of the linear reverberant component and the non-linear reverberant component may be updated. One or more undesired signal components in an output signal resulting from the input signal may be reduced via residual echo suppression based upon, at least in part, updating the one or more parameters.

Abstract: A system and associated method for estimating one or more reverberation parameters includes an adaptive, parametric, linear prediction filter having one or more power spectral density (PSD) estimates of signals of one or more channels as inputs. The prediction filter estimates at least one parameter related to reverberation time, such as T60, and can further estimate an additional parameter, such as Direct-to-Reverberant Ratio (DRR). The prediction filter may be adapted during a period of reverberation by minimizing a cost function. Adaptation can include using a gradient descent approach, which can operate according to a step size provided by an adaptation controller configured to determine the period of reverberation. One or more microphones can provide the signals. The reverberation parameters estimated can be applied to a reverberation suppressor, with an estimator that does not require a training phase and without relying on assumptions of the user's position relative to the microphones.

Abstract: A method, computer program product, and computer system for receiving, by a computing device, an input signal. A first power spectral density estimate may be generated for a linear reverberant component associated with the input signal. A second power spectral density estimate may be generated for a non-linear reverberant component associated with the input signal. A power spectral density estimate may be generated by combining the first power spectral density estimate for the linear reverberant component and the second power spectral density estimate for the non-linear reverberant component. One or more parameters for at least one of the linear reverberant component and the non-linear reverberant component may be updated. One or more undesired signal components in an output signal resulting from the input signal may be reduced via residual echo suppression based upon, at least in part, updating the one or more parameters.

Abstract: A system and associated method for estimating one or more reverberation parameters includes an adaptive, parametric, linear prediction filter having one or more power spectral density (PSD) estimates of signals of one or more channels as inputs. The prediction filter estimates at least one parameter related to reverberation time, such as T60, and can further estimate an additional parameter, such as Direct-to-Reverberant Ratio (DRR). The prediction filter may be adapted during a period of reverberation by minimizing a cost function. Adaptation can include using a gradient descent approach, which can operate according to a step size provided by an adaptation controller configured to determine the period of reverberation. One or more microphones can provide the signals. The reverberation parameters estimated can be applied to a reverberation suppressor, with an estimator that does not require a training phase and without relying on assumptions of the user's position relative to the microphones.

Abstract: Methods and apparatus for estimating the power spectral density (PSD) of a residual interference having first and second components after adaptive interference cancellation (AIC). The first component can be estimated using a real-valued FIR filter operating on a time series of PSD estimates of a reference signal, and the second component can be estimated using an exponential decay over time corresponding to a reverberation time using the PSD of the reference signal.

Abstract: Methods and apparatus for estimating the power spectral density (PSD) of a residual interference having first and second components after adaptive interference cancellation (AIC). The first component can be estimated using a real-valued FIR filter operating on a time series of PSD estimates of a reference signal, and the second component can be estimated using an exponential decay over time corresponding to a reverberation time using the PSD of the reference signal.