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This paper presents a contrast function and associated algorithm for blind separation of audio signals. The contrast function is based on second-order statistics to minimize the ratio between the product of the diagonal entries and the determinant of the covariance matrix. The contrast function can be minimized by a batch and adaptive gradient descent method to formulate a blind source separation algorithm. Experimental results on realistic audio signals show that the proposed algorithm yielded comparable separation performance with benchmark algorithms for speech signals, and outperformed benchmark algorithms for music signals.