Methods and apparatuses for convolutive blind source separation

An apparatus for performing convolutive blind source separation, comprising:

• a first transformer, at least implemented in part in hardware, which transforms each of a plurality of input signals into frequency domain;
• a calculator, at least implemented in part in hardware, which calculates values of coefficients of unmixing filters corresponding to frequency bins by performing a gradient descent process on a cost function at least dependent on the coefficients of the unmixing filters, wherein in each iteration of the gradient descent process, gradient terms for calculating the values of the same coefficient of the unmixing filter are adjusted to improve smoothness of the gradient terms across the frequency bins;
• wherein the calculator is configured to, with respect to each of the coefficients, transform the gradient terms over the frequency bins for calculating the coefficient into a time domain filter of length T, de-emphasize coefficients of the time domain filter at time indices exceeding a first threshold smaller than the length T, and transform coefficients of the time domain filter from time domain into frequency domain through a length-T transformation;
• an estimator, at least implemented in part in hardware, which, with respect to each of the frequency bins, estimates source signals by filtering the transformed input signals through the respective unmixing filter configured with the calculated values of the coefficients;
• and
• a second transformer, at least implemented in part in hardware, which transforms the estimated source signals on the respective frequency bins into time domain,
• wherein the cost function is adapted to evaluate decorrelation between the estimated source signals.

A non-transitory computer-readable storage medium having computer program instructions recorded thereon, when being executed by a processor, the instructions enabling the processor to perform a method of convolutive blind source separation based on second order statistics comprising:

• transforming each of a plurality of input signals into frequency domain;
• calculating values of coefficients of unmixing filters corresponding to frequency bins by performing a gradient descent process on a cost function at least dependent on the coefficients of the unmixing filters, wherein in each iteration of the gradient descent process, gradient terms for calculating the values of the same coefficient of the unmixing filters are adjusted to improve smoothness of the gradient terms across the frequency bins;
• wherein the adjusting comprises:
• with respect to each of the coefficients, transforming the terms over the frequency bins for calculating the coefficient into a time domain filter of length T;
• de-emphasizing coefficients of the time domain filter at time indices exceeding a first threshold smaller than the length T;
• and
• transforming coefficients of the time domain filter from time domain into frequency domain through a length-T transformation;
• with respect to each of the frequency bins, estimating source signals by filtering the transformed input signals through the respective unmixing filter configured with the calculated values of the coefficients;
• and
• transforming the estimated source signals on the respective frequency bins into time domain,
• wherein the cost function is adapted to evaluate decorrelation between the estimated source signals.