Abstract To improve the recognition accuracy rate of a text-independent speaker recognition system, a total least square-nuisance attribute projection (TLS-NAP) algorithm is proposed. The perturbation of the projection matrix is considered and its negative effect is minimized when hidden variables are estimated by the total least square algorithm. A better performance is obtained by the nuisance attribute projection space based on these variables. The effectiveness of the proposed method is demonstrated by the experimental results on NIST SRE 08 data corpus.
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2012, Vol. 25 
