Temporal and time-frequency correlation-based blind source separation methods. part i: Determined and underdetermined linear instantaneous mixtures

In this paper, we propose two versions of a correlation-based blind source separation (BSS) method. Whereas its basic version oper-ates in the time domain, its extended form is based on the time-frequency (TF) representations of the observed signals and thus applies to much more general conditions. The latter approach con-sists in identifying the columns of the (permuted scaled) mixing matrix in TF areas where this method detects that a single source occurs. Both the detection and identification stages of this ap-proach use local correlation parameters of the TF transforms of the observed signals. This BSS method, called TIFCORR (for TIme-Frequency CORRelation-based BSS), is shown to yield very ac-curate separation for linear instantaneous mixtures of real speech signals (output SNR’s are above 60 dB). 1