SPEAKER RECOGNITION IMPROVEMENT USING BLIND INVERSION OF DISTORTIONS (FriAmSS2)

Author(s) : Marcos Faundez-Zanuy (EUP Mataro, SPAIN) Jordi Sole-Casals (Universitat de Vic, SPAIN)

Abstract : In this paper we propose the inversion of nonlinear distortions in order to improve the recognition rates of a speaker recognizer system. We study the effect of saturations on the test signals, trying to take into account real situations where the training material has been recorded in a controlled situation but the testing signals present some mismatch with the input signal level (saturations). The experimental results shows that a combination of several strategies can improve the recognition rates with saturated test sentences from 80% to 89.39%, while the results with clean speech (without saturation) is 87.76% for one microphone.

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