Variable step size adaptive decorrelation filtering for competing speech separation

Two variable step size (VSS) techniques are proposed for adaptive decorrelation filtering (ADF) to improve the performance of competing speech separation. The first VSS method applies gradient adaptive step-size (GAS) to increase ADF convergence rate. Under some simplifying assumptions, the GAS technique is generalized to allow the combination with additional VSS techniques for ADF algorithm. The second VSS method is based on error analysis of ADF estimates under a simplified signal model to decrease steady state filter error. An integration of both techniques into ADF was tested with TIMIT speech data convolutively mixed by reverberant room impulse responses. Experimental results showed that the proposed algorithm significantly increased ADF convergence rate and improved gain in both target-tointerference ratio (TIR) and phone recognition accuracy of the target speech.