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In this paper we present a novel hybrid algorithm for blind source separation of three speech signals in a real room environment. The algorithm in addition to using second-order statistics also exploits an information-theoretic approach, based on higher order statistics, to achieve source separation and is well suited for real-time implementation due to its fast adaptive methodology. It does not require any prior information or parameter estimation. The algorithm also uses a novel post-separation speech harmonic alignment that results in an improved performance. Experimental results in simulated and real environments verify the effectiveness of the proposed method, and analysis demonstrates that the algorithm is computationally efficient.

Abstract-In this paper a novel algorithm is presented for frequency estimation of a complex exponential by interpolating Fourier coefficients in a non-iterative way by shifting the minimum variance and using a non-linear function. The estimator presented is unbiased and normally distributed with asymptotic variance that is ≈ . of the Cramer RaoBound and is optimally uniform over the entire range while requiring calculation of the fewest Fourier coefficients.