A DNN beamformer trained with an augmented Lagrangian-inspired adaptive loss using target RTF and interference subspace estimates outperforms classical LCMV beamformers in multi-speaker enhancement with better sidelobe control and noise attenuation.
Derivative constraints for broad- band element space antenna array processors,
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Linearly Constrained Deep Beamformer for Multi-Speaker Scenarios
A DNN beamformer trained with an augmented Lagrangian-inspired adaptive loss using target RTF and interference subspace estimates outperforms classical LCMV beamformers in multi-speaker enhancement with better sidelobe control and noise attenuation.