Real-time Tf-gsc in Nonstationary Noise Environments

Adaptive beamforming techniques are inefficient for eliminating transient noise components that randomly arrive from unpredictable directions. In this paper, we present a real-time transfer function generalized sidelobe canceller (TF-GSC) for such nonstationary noise environments. Hypothesis testing in the spectral domain indicates either absence of transients, presence of an interfering transient, or presence of desired source components. The noise canceller branch of the TF-GSC is updated only during absence of transients, while the identification of the acoustical transfer function is carried out only when desired source components are present. Following the beamforming and the hypothesis testing, estimates for the signal presence probability, the noise power spectral density, and the desired speech log-spectral amplitude are derived. Experimental results demonstrate the usefulness of the proposed approach under nonstationary noise conditions.