Blind source separation in mobile environments using a priori knowledge
Erik Visser, Te-Won Lee · 2004
A speech enhancement scheme including blind source separation and background denoising based on minimum statistics is studied in mobile environments. To accommodate the dependence of the separated output signals on the spatial properties of the recorded source signals, these blind signal processing steps are complemented by an adaptive separated output channel selection stage using prior knowledge about the desired speaker speech content. The resulting scheme performance is illustrated by speech recognition experiments on real recordings corrupted by various noise sources and shown to outperform conventional beamforming and single channel denoising techniques as well as an equivalent scheme with fixed output channel selection.