Sector-Based Detection for Hands-Free Speech Enhancement in Cars

Adaptation control of beamforming interference cancellation techniques is investigated for in-car speech acquisition. Two efficient adaptation control methods are proposed that avoid target cancellation. The implicit'' method varies the step-size continuously, based on the filtered output signal. The explicit'' method decides in a binary manner whether to adapt or not, based on a novel estimate of target and interference energies. It estimates the average delay-sum power within a volume of space, for the same cost as the classical delay-sum. Experiments on real in-car data validate both methods, including a case with 100 km/h background road noise.