Geometrically Constrained Source Extraction and Dereverberation Based on Joint Optimization

Source extraction, which aims at extracting the target source signalsfrom the observed reverberant mixtures, plays an important rolein voice communication and human-machine interfaces. Amongthe numerous source extraction methods that have been developed,the geometrically constrained (GC) one, which incorporates thedirection-of-arrival (DOA) information of the target signals, hasdemonstrated great potential. However, this method generallysuffers from significant performance degradation in strong reverberantenvironments since it is challenging to obtain in such environmentsaccurate DOA estimates that are needed by the algorithm. Toaddress this problem, we present in this work an iterative algorithm,which integrates the source-wise weighted prediction error (WPE)-based dereverberation principle with the geometrically constrainedsource extraction method. We show that this algorithm is able toimprove the DOA estimation accuracy as well as the source extractionperformance.