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We present a new multi-stage iterative technique for enhancing noisy speech under low signal-to-interference-ratio (SNR) environments. In the present paper, the speech is enhanced in two stages, in the first stage the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the desired speech component. In both the stages, the coefficient adaptation is performed using the multi-channel spatio-temporal correlation sequences of the observed data. The technique is mathematically equivalent and is computationally simpler than the existing generalized eigenvalue decomposition (GEVD) or the generalized singular value decomposition (GSVD) based techniques. Simulation results under low SNR diffuse noise scenarios indicate significant gains in SNR without introducing musical noise artifacts.
Date of Conference: 18-21 Oct. 2009