A soft-decision adaptation mode controller for an efficient frequency-domain generalized sidelobe canceller

In this paper, we propose a new soft-decision adaptation mode controller (SD-AMC) for frequency domain generalized sidelobe canceller (GSC) as a speech enhancement system. Contrarily to conventional systems that update filter coefficients in a hard-decision manner using voice activity detection (VAD), the proposed method flexibly controls the step-sizes of adaptive filters depending on the probability of speech presence in each frequency bin. Therefore, it further improves the system performance for various environments without much consideration on noise type and signal to noise ratio (SNR) of input signal. It also improves the robustness of GSC system by avoiding the miss-classification error by the hard-decision logic. Experimental results with speech recognition systems verify that the SD-AMC shows higher performance than ideally designed hard-decision approaches.