Blind extraction of a dominant source signal from mixtures of many sources [audio source separation applications]

This paper presents a method for enhancing a dominant target source that is close to sensors, and suppressing other interferences. The enhancement is performed blindly, i.e. without knowing the number of total sources or information about each source, such as position and active time. We consider a general case where the number of sources is larger than the number of sensors. We employ a two-stage processing technique where a spatial filter is first employed in each frequency bin and time-frequency masking is then used to improve the performance further. To obtain the spatial filter we employ independent component analysis and then select the component of the target source. Time-frequency masks in the second stage are obtained by calculating the angle between the basis vector corresponding to the target source and a sample vector. The experimental results for a simulated cocktail party situation were very encouraging.